diff --git a/.DS_Store b/.DS_Store new file mode 100644 index 0000000000000000000000000000000000000000..7571bf19c7445cd4abc6ae7e6249836144c5a735 Binary files /dev/null and b/.DS_Store differ diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 0000000000000000000000000000000000000000..1ef325f1b111266a6b26e0196871bd78baa8c2f3 --- /dev/null +++ b/.gitattributes @@ -0,0 +1,59 @@ +*.7z filter=lfs diff=lfs merge=lfs -text +*.arrow filter=lfs diff=lfs merge=lfs -text +*.bin filter=lfs diff=lfs merge=lfs -text +*.bz2 filter=lfs diff=lfs merge=lfs -text +*.ckpt filter=lfs diff=lfs merge=lfs -text +*.ftz filter=lfs diff=lfs merge=lfs -text +*.gz filter=lfs diff=lfs merge=lfs -text +*.h5 filter=lfs diff=lfs merge=lfs -text +*.joblib filter=lfs diff=lfs merge=lfs -text +*.lfs.* filter=lfs diff=lfs merge=lfs -text +*.lz4 filter=lfs diff=lfs merge=lfs -text +*.mds filter=lfs diff=lfs merge=lfs -text +*.mlmodel filter=lfs diff=lfs merge=lfs -text +*.model filter=lfs diff=lfs merge=lfs -text +*.msgpack filter=lfs diff=lfs merge=lfs -text +*.npy filter=lfs diff=lfs merge=lfs -text +*.npz filter=lfs diff=lfs merge=lfs -text +*.onnx filter=lfs diff=lfs merge=lfs -text +*.ot filter=lfs diff=lfs merge=lfs -text +*.parquet filter=lfs diff=lfs merge=lfs -text +*.pb filter=lfs diff=lfs merge=lfs -text +*.pickle filter=lfs diff=lfs merge=lfs -text +*.pkl filter=lfs diff=lfs merge=lfs -text +*.pt filter=lfs diff=lfs merge=lfs -text +*.pth filter=lfs diff=lfs merge=lfs -text +*.rar filter=lfs diff=lfs merge=lfs -text +*.safetensors filter=lfs diff=lfs merge=lfs -text +saved_model/**/* filter=lfs diff=lfs merge=lfs -text +*.tar.* filter=lfs diff=lfs merge=lfs -text +*.tar filter=lfs diff=lfs merge=lfs -text +*.tflite filter=lfs diff=lfs merge=lfs -text +*.tgz filter=lfs diff=lfs merge=lfs -text +*.wasm filter=lfs diff=lfs merge=lfs -text +*.xz filter=lfs diff=lfs merge=lfs -text +*.zip filter=lfs diff=lfs merge=lfs -text +*.zst filter=lfs diff=lfs merge=lfs -text +*tfevents* filter=lfs diff=lfs merge=lfs -text +# Audio files - uncompressed +*.pcm filter=lfs diff=lfs merge=lfs -text +*.sam filter=lfs diff=lfs merge=lfs -text +*.raw filter=lfs diff=lfs merge=lfs -text +# Audio files - compressed +*.aac filter=lfs diff=lfs merge=lfs -text +*.flac filter=lfs diff=lfs merge=lfs -text +*.mp3 filter=lfs diff=lfs merge=lfs -text +*.ogg filter=lfs diff=lfs merge=lfs -text +*.wav filter=lfs diff=lfs merge=lfs -text +# Image files - uncompressed +*.bmp filter=lfs diff=lfs merge=lfs -text +*.gif filter=lfs diff=lfs merge=lfs -text +*.png filter=lfs diff=lfs merge=lfs -text +*.tiff filter=lfs diff=lfs merge=lfs -text +# Image files - compressed +*.jpg filter=lfs diff=lfs merge=lfs -text +*.jpeg filter=lfs diff=lfs merge=lfs -text +*.webp filter=lfs diff=lfs merge=lfs -text +# Video files - compressed +*.mp4 filter=lfs diff=lfs merge=lfs -text +*.webm filter=lfs diff=lfs merge=lfs -text diff --git a/LICENSE b/LICENSE new file mode 100644 index 0000000000000000000000000000000000000000..0e6c0924bc1e6baf841dbcc3a889138ffffbddc5 --- /dev/null +++ b/LICENSE @@ -0,0 +1,21 @@ +MIT License + +Copyright (c) 2025 Zuzanna Osika + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in +all copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN +THE SOFTWARE. diff --git a/README.md b/README.md new file mode 100644 index 0000000000000000000000000000000000000000..ace576db96d0b2437a0106063e8c23e9535362ad --- /dev/null +++ b/README.md @@ -0,0 +1,102 @@ +# MORL4Water + +
+🥐 Dataset Metadata + +This repository includes a Croissant metadata file [`croissant.json`](./croissant.json), making MORL4Water compatible with Hugging Face standards for dataset discoverability and interoperability. +Learn more about [Croissant metadata](https://huggingface.co/docs/croissant/index). + +
+ +--- + +Welcome to **MORL4Water**, a flexible Gym environment designed for simulating **water management** in river systems. +With MORL4Water, you can build detailed water simulations and **train or test multi-objective reinforcement learning (MORL)** agents. + +Currently, we have **three river basins** implemented as Gym environments: +- **Nile River Basin** +- **Susquehanna River Basin** +- **Omo River Basin** + +The toolkit is **modular**, allowing users to extend or build their own water systems. +For an overview of available system components, please refer to the [System Elements](#). + +--- + +## 🚀 Installation and Running + +### Installation + +Ensure you are using **Python ≥ 3.11**. Install via pip: + +```bash +pip install morl4water +``` + +### Running an Example Simulation + +```python +import mo_gymnasium +import morl4water.examples + +# Create the environment +water_management_system = mo_gymnasium.make('nile-v0') + +def run_nile(): + obs, info = water_management_system.reset() + print(f'Initial Obs: {obs}') + final_truncated = False + final_terminated = False + for t in range(10): + if not final_terminated and not final_truncated: + action = water_management_system.action_space.sample() + print(f'Action for month {t}: {action}') + ( + final_observation, + final_reward, + final_terminated, + final_truncated, + final_info + ) = water_management_system.step(action) + print(f'Observation: {final_observation}') + print(f'Reward: {final_reward}') + else: + break + return final_observation + +run_nile() +``` + +--- + +## 📚 Documentation + +For detailed documentation, visit the [MORL4Water Website](https://osikazuzanna.github.io/morl4water/). + +--- + +## 📜 License + +This project is licensed under the [MIT License](https://opensource.org/licenses/MIT). + +--- + +## ✨ Citation + +If you use MORL4Water in your work, please consider citing it (BibTeX coming soon). + +--- + + + +# 🛠️ Contributing + +Contributions are welcome! Feel free to open an issue or pull request. + +--- + +# 🛡️ About + +Developed by **Zuzanna Osika**, 2025. + +--- \ No newline at end of file diff --git a/croissant.json b/croissant.json new file mode 100644 index 0000000000000000000000000000000000000000..575950bf0b6f9844dde8a14c578253ae3c7a6b6a --- /dev/null +++ b/croissant.json @@ -0,0 +1,29 @@ +{ + "@context": "https://w3id.org/croissant/context.jsonld", + "@type": "Dataset", + "name": "MORL4Water", + "description": "MORL4Water is a flexible modular Gym environment for simulating water management in river systems, designed to train and test multi-objective reinforcement learning (MORL) agents. Includes Nile River Basin, Susquehanna River Basin, and Omo River Basin environments.", + "license": "https://opensource.org/licenses/MIT", + "distribution": [ + { + "@type": "DataDownload", + "encodingFormat": "application/zip", + "contentUrl": "https://huggingface.co/osikazuzanna/morl4water/resolve/main/morl4water.zip" + } + ], + "creator": { + "@type": "Person", + "name": "Zuzanna Osika" + }, + "keywords": [ + "multi-objective reinforcement learning", + "MORL", + "Gymnasium", + "water management", + "simulation", + "river systems", + "environment modeling" + ], + "datePublished": "2025-04-26" + } + \ No newline at end of file diff --git a/morl4water/__init__.py b/morl4water/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..36c1447390fffde79029418db9197828268e8c8b --- /dev/null +++ b/morl4water/__init__.py @@ -0,0 +1,4 @@ +from . import core +from . import examples + +__all__ = ["core", "examples"] \ No newline at end of file diff --git a/morl4water/core/.DS_Store b/morl4water/core/.DS_Store new file mode 100644 index 0000000000000000000000000000000000000000..9510ac2abb231547e54b2d45d2c0dd460369c787 Binary files /dev/null and b/morl4water/core/.DS_Store differ diff --git a/morl4water/core/__init__.py b/morl4water/core/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..139597f9cb07c5d48bed18984ec4747f4b4f3438 --- /dev/null +++ b/morl4water/core/__init__.py @@ -0,0 +1,2 @@ + + diff --git a/morl4water/core/envs/__init__.py b/morl4water/core/envs/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/morl4water/core/envs/water_management_system.py b/morl4water/core/envs/water_management_system.py new file mode 100644 index 0000000000000000000000000000000000000000..53addb02371f87af2b8bcafc795fa6caf13844f8 --- /dev/null +++ b/morl4water/core/envs/water_management_system.py @@ -0,0 +1,247 @@ +import gymnasium as gym +import numpy as np +from datetime import datetime +from dateutil.relativedelta import relativedelta +from gymnasium.spaces import Box, Dict, Space +from gymnasium.core import ObsType, RenderFrame +from typing import Any, Union, Optional +from morl4water.core.models.flow import Flow +from morl4water.core.models.facility import Facility, ControlledFacility +import time +from gymnasium.spaces import flatten_space + +class WaterManagementSystem(gym.Env): + def __init__( + self, + water_systems: list[Union[Facility, ControlledFacility, Flow]], + rewards: dict, + start_date: datetime, + timestep_size: relativedelta, + seed: int = 42, + add_timestamp = None, + custom_obj = None + ) -> None: + self.water_systems: list[Union[Facility, ControlledFacility, Flow]] = water_systems + self.rewards: dict = rewards + + self.start_date: datetime = start_date + self.current_date: datetime = start_date + self.timestep_size: relativedelta = timestep_size + self.timestep: int = 0 + + self.seed: int = seed + self.add_timestamp = add_timestamp + self.custom_obj = custom_obj + + self.observation_space: Space = self._determine_observation_space() + self.observation_space = flatten_space(self.observation_space) + self.action_space: Space = self._determine_action_space() + self.action_space = flatten_space(self.action_space) + + self.max_capacities = self._determine_capacities() + + if self.custom_obj: + self.reward_space: Space = Box(-1.0, 1.0, shape=(len(self.custom_obj),)) + else: + self.reward_space: Space = Box(-1.0, 1.0, shape=(len(rewards.keys()),)) + + + self.observation: np.array = self._determine_observation() + + + + + + for water_system in self.water_systems: + water_system.current_date = self.current_date + water_system.timestep_size = self.timestep_size + + def _determine_observation(self) -> np.array: + result = [] + for water_system in self.water_systems: + if isinstance(water_system, ControlledFacility): + result.append(water_system.determine_observation()) + result_normalized = list(np.divide(result, self.max_capacities)) + if self.add_timestamp: + result.append(0) + result_normalized.append(0) + + return np.array(result), np.array(result_normalized) + + def _determine_observation_space(self) -> Dict: + if self.add_timestamp is not None: + return Dict( + { + **{ + water_system.name: Box(low=0, high=1) + for water_system in self.water_systems + if isinstance(water_system, ControlledFacility) + }, + "timestamp": Box(low=0, high=1) + } + ) + + else: + return Dict( + { + water_system.name: Box(low=0, high=1) + for water_system in self.water_systems + if isinstance(water_system, ControlledFacility) + } + ) + + + def _determine_action_space(self) -> Dict: + return Dict( + { + water_system.name: water_system.action_space + for water_system in self.water_systems + if isinstance(water_system, ControlledFacility) + } + ) + + def _determine_capacities(self): + capacities = [water_system.max_capacity for water_system in self.water_systems if isinstance(water_system, ControlledFacility)] + return capacities + + def _is_truncated(self) -> bool: + return False + + def _determine_info(self) -> dict[str, Any]: + # TODO: decide on what we wnat to output in the info. + return {"water_systems": self.water_systems} + + def reset(self, seed: Optional[int] = None, options: Optional[dict] = None) -> tuple[ObsType, dict[str, Any]]: + # We need the following line to seed self.np_random. + super().reset(seed=seed) + self.current_date = self.start_date + self.timestep = 0 + + self.observation, observation_normalized = self._determine_observation() + # Reset rewards + for key in self.rewards.keys(): + self.rewards[key] = 0 + + for water_system in self.water_systems: + water_system.current_date = self.start_date + water_system.reset() + return observation_normalized, self._determine_info() + + def step(self, action: np.array) -> tuple[np.array, np.array, bool, bool, dict]: + """ + Execute a single step in the water management simulation. + + This method processes the provided action for each water system in the + environment, updating the states of each facility and returning the + observations, rewards, termination status, truncation status, and + additional information. + + Args: + action (np.array): An array of actions to be taken for each + controlled facility in the simulation. The action should + correspond to the facilities' names. + + Returns: + tuple[np.array, np.array, bool, bool, dict]: + A tuple containing: + + - np.array: A flattened array of normalized observations for + each water system, representing their current states as + percentages of their maximum capacities. + - np.array: A flattened array of final rewards collected from + the facilities based on the executed actions. + - bool: A flag indicating whether the simulation has + terminated. + - bool: A flag indicating whether the simulation has been + truncated. + - dict: A dictionary containing additional information, such + as the current date and other relevant data from the + water systems. + + Notes: + - The method resets rewards for each facility at the beginning + of the step. + - If `custom_obj` is specified, only the relevant rewards are + returned based on the keys in `custom_obj`. + - Observations are normalized by dividing by their maximum + capacities. + - The method increments the timestep and updates the current + date based on the `timestep_size` attribute. + + """ + + final_reward = {} + + + # Reset rewards + for key in self.rewards.keys(): + final_reward[key] = 0 + + final_observation = {} + final_terminated = False + final_truncated = False + final_info = {"date": self.current_date} + + for water_system in self.water_systems: + water_system.current_date = self.current_date + + if isinstance(water_system, ControlledFacility): + observation, reward, terminated, truncated, info = water_system.step(action[water_system.name]) + + elif isinstance(water_system, Facility) or isinstance(water_system, Flow): + observation, reward, terminated, truncated, info = water_system.step() + else: + raise ValueError() + + # Set observation for a Controlled Facility. + if isinstance(water_system, ControlledFacility): + final_observation[water_system.name] = observation + + # Add reward to the objective assigned to this Facility (unless it is a Flow or the facility has no objectives). + if isinstance(water_system, Facility) or isinstance(water_system, ControlledFacility): + if water_system.objective_name: + final_reward[water_system.objective_name] += reward + + # Store additional information + final_info[water_system.name] = info + + + # Determine whether program should stop + final_terminated = final_terminated or terminated + final_truncated = final_truncated or truncated or self._is_truncated() + + + self.timestep += 1 + self.current_date += self.timestep_size + + #check if only a subset of rewards to return + if self.custom_obj is not None: + final_reward = [final_reward[key] for key in self.custom_obj] + else: + final_reward = list(final_reward.values()) + + final_observations = list(final_observation.values()) + #normalize the observation to be percentage of max capacity + final_observations = list(np.divide(final_observations, self.max_capacities)) + if self.add_timestamp=='m': + final_observations.append(final_info['date'].month/12) + elif self.add_timestamp=='h': + final_observations.append(final_info['date'].hour/24) + + + + return ( + np.array(final_observations).flatten(), + np.array(final_reward).flatten(), + final_terminated, + final_truncated, + final_info + ) + + def close(self) -> None: + # TODO: implement if needed, e.g. for closing opened rendering frames. + pass + + def render(self) -> Union[RenderFrame, list[RenderFrame], None]: + # TODO: implement if needed, for rendering simulation. + pass diff --git a/morl4water/core/models/__init__.py b/morl4water/core/models/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..4a11341b7f9abd5599f6dde5c99a89ab46e34921 --- /dev/null +++ b/morl4water/core/models/__init__.py @@ -0,0 +1,12 @@ +# models/__init__.py +from .catchment import Catchment +from .flow import Flow, Inflow, Outflow +from .irrigation_district import IrrigationDistrict +from .objective import Objective +from .power_plant import PowerPlant +from .reservoir_with_pump import ReservoirWithPump +from .reservoir import Reservoir +from .weir import Weir +from .facility import Facility, ControlledFacility + +__all__ = ["Catchment", "Flow","Facility","ControlledFacility", "Inflow", "Outflow", "IrrigationDistrict", "Objective", "PowerPlant", "ReservoirWithPump", "Reservoir", "Weir"] diff --git a/morl4water/core/models/catchment.py b/morl4water/core/models/catchment.py new file mode 100644 index 0000000000000000000000000000000000000000..7b580547c2fe824ce4a9972427d02701f82693bb --- /dev/null +++ b/morl4water/core/models/catchment.py @@ -0,0 +1,22 @@ +from morl4water.core.models.facility import Facility + + +class Catchment(Facility): + def __init__(self, name: str, all_water_accumulated: list[float]) -> None: + super().__init__(name) + self.all_water_accumulated: list[float] = all_water_accumulated + + def determine_reward(self) -> float: + return 0 + + def get_inflow(self, timestep: int) -> float: + return self.all_water_accumulated[timestep % len(self.all_water_accumulated)] + + def determine_consumption(self) -> float: + return 0 + + def is_truncated(self) -> bool: + return self.timestep >= len(self.all_water_accumulated) + + def determine_info(self) -> dict: + return {"water_consumption": self.determine_consumption()} diff --git a/morl4water/core/models/facility.py b/morl4water/core/models/facility.py new file mode 100644 index 0000000000000000000000000000000000000000..310be6bcdde3afd0742cc29de0ac81d76c296723 --- /dev/null +++ b/morl4water/core/models/facility.py @@ -0,0 +1,339 @@ +import numpy as np +from abc import ABC, abstractmethod +from datetime import datetime +from dateutil.relativedelta import relativedelta +from gymnasium.spaces import Space, Box +from gymnasium.core import ObsType, ActType +from typing import SupportsFloat, Optional +from morl4water.core.models.objective import Objective + + +class Facility(ABC): + """ + Abstract base class representing a facility with inflow and outflow management, along with reward determination. + + Attributes + ---------- + name : str + Identifier for the facility. + all_inflow : list[float] + Historical inflow values recorded over time. + all_outflow : list[float] + Historical outflow values recorded over time. + objective_function : Callable + Function to evaluate the facility’s performance based on defined objectives. + objective_name : str + Name of the objective function used. + current_date : Optional[datetime] + Date associated with the current timestep of the facility. + timestep_size : Optional[relativedelta] + Size of the timestep for simulation. Usually 1 month. + timestep : int + Current timestep index for the facility simulation. + split_release : Optional + Placeholder for managing release strategies (usage to be defined). + normalize_objective : float + Normalization factor for the objective reward. + """ + def __init__(self, name: str, objective_function=Objective.no_objective, objective_name: str = "", normalize_objective=0.0) -> None: + """ + Initializes a Facility instance. + + Args: + name (str): Identifier for the facility. + objective_function (Callable): Function to evaluate the facility’s performance. + objective_name (str): Name of the objective function. + normalize_objective (float): Maximum value for normalizing the reward; defaults to 0.0. + """ + self.name: str = name + self.all_inflow: list[float] = [] + self.all_outflow: list[float] = [] + + self.objective_function = objective_function + self.objective_name = objective_name + + self.current_date: Optional[datetime] = None + self.timestep_size: Optional[relativedelta] = None + self.timestep: int = 0 + + self.split_release = None + self.normalize_objective = normalize_objective + + @abstractmethod + def determine_reward(self) -> float: + """ + Abstract method to compute the reward based on the facility's performance. + + Returns: + float: The computed reward for the current timestep. + + Raises: + NotImplementedError: If this method is not implemented in a subclass. + """ + raise NotImplementedError() + + @abstractmethod + def determine_consumption(self) -> float: + """ + Abstract method to calculate the facility's water consumption. + + Returns: + float: The calculated water consumption for the current timestep. + + Raises: + NotImplementedError: If this method is not implemented in a subclass. + """ + raise NotImplementedError() + + def is_terminated(self) -> bool: + """ + Checks if the facility simulation has reached a terminating condition. + + Returns: + bool: Always returns False for the base Facility class; override in subclasses as needed. + """ + return False + + def is_truncated(self) -> bool: + """ + Checks if the facility simulation has been truncated. + + Returns: + bool: Always returns False for the base Facility class; override in subclasses as needed. + """ + return False + + def get_inflow(self, timestep: int) -> float: + """ + Retrieves the inflow value for a specific timestep. + + Args: + timestep (int): The timestep index for which to retrieve the inflow. + + Returns: + float: The inflow value for the specified timestep. + + Raises: + IndexError: If the timestep is out of bounds. + """ + return self.all_inflow[timestep] + + def set_inflow(self, timestep: int, inflow: float) -> None: + """ + Sets the inflow value for a specific timestep, adjusting if necessary. + + Args: + timestep (int): The timestep index at which to set the inflow. + inflow (float): The inflow value to set. + + Raises: + IndexError: If the timestep index is invalid. + """ + if len(self.all_inflow) == timestep: + self.all_inflow.append(inflow) + elif len(self.all_inflow) > timestep: + self.all_inflow[timestep] += inflow + else: + raise IndexError + + def determine_outflow(self) -> float: + """ + Calculates the outflow based on the current inflow and consumption. + + Returns: + float: The calculated outflow for the current timestep. + """ + return self.get_inflow(self.timestep) - self.determine_consumption() + + def get_outflow(self, timestep: int) -> float: + """ + Retrieves the outflow value for a specific timestep. + + Args: + timestep (int): The timestep index for which to retrieve the outflow. + + Returns: + float: The outflow value for the specified timestep. + + Raises: + IndexError: If the timestep is out of bounds. + """ + return self.all_outflow[timestep] + + def step(self) -> tuple[ObsType, float, bool, bool, dict]: + """ + Advances the simulation by one timestep, calculating outflows and rewards. + + Returns: + tuple[ObsType, float, bool, bool, dict]: A tuple containing: + - ObsType: Placeholder for observation type (to be defined). + - float: The reward for the current timestep. + - bool: Indicates if the simulation has terminated. + - bool: Indicates if the simulation has been truncated. + - dict: Additional information about the facility's state. + """ + self.all_outflow.append(self.determine_outflow()) + # TODO: Determine if we need to satisy any terminating codnitions for facility. + reward = self.determine_reward() + if self.normalize_objective>0.0: + reward = reward/self.normalize_objective + terminated = self.is_terminated() + truncated = self.is_truncated() + info = self.determine_info() + + self.timestep += 1 + + return None, reward, terminated, truncated, info + + def reset(self) -> None: + """ + Resets the facility to its initial state for a new simulation run. + + Returns: + None + """ + self.timestep: int = 0 + self.all_inflow: list[float] = [] + self.all_outflow: list[float] = [] + + def determine_info(self) -> dict: + """ + Method to gather information about the facility's state. + + Returns: + dict: A dictionary containing information about the facility. + + Raises: + NotImplementedError: If this method is not implemented in a subclass. + """ + raise NotImplementedError() + + def __eq__(self, other): + """ + Checks equality between two Facility instances based on their names. + + Args: + other (Facility): The other facility to compare against. + + Returns: + bool: True if both facilities are of the same class and have the same name, False otherwise. + """ + return isinstance(other, self.__class__) and self.name == other.name + + def __hash__(self): + """ + Returns a hash of the facility based on its name. + + Returns: + int: The hash value of the facility. + """ + return hash(self.name) + + +class ControlledFacility(ABC): + def __init__( + self, + name: str, + observation_space: Space, + action_space: ActType, + max_capacity: float, + max_action: float, + + objective_function=Objective.no_objective, + objective_name: str = "", + ) -> None: + self.name: str = name + self.all_inflow: list[float] = [] + self.all_outflow: list[float] = [] + self.max_capacity: float = max_capacity + self.max_action: float = max_action + + + self.observation_space: Space = observation_space + #check if there is more than one outflow from a reservoir + if len(self.max_action)>1: + self.action_space: Space = Box(low=0, high=1, shape=(len(self.max_action),)) + else: + self.action_space: Space = action_space + + self.objective_function = objective_function + self.objective_name = objective_name + + + self.current_date: Optional[datetime] = None + self.timestep_size: Optional[relativedelta] = None + self.timestep: int = 0 + + self.should_split_release = np.prod(self.action_space.shape) > 1 + self.split_release = None + + @abstractmethod + def determine_reward(self) -> float: + raise NotImplementedError() + + @abstractmethod + def determine_outflow(action: ActType) -> float: + raise NotImplementedError() + + @abstractmethod + def determine_observation(self) -> ObsType: + raise NotImplementedError() + + @abstractmethod + def is_terminated(self) -> bool: + raise NotImplementedError() + + def is_truncated(self) -> bool: + return False + + def get_inflow(self, timestep: int) -> float: + return self.all_inflow[timestep] + + def set_inflow(self, timestep: int, inflow: float) -> None: + if len(self.all_inflow) == timestep: + self.all_inflow.append(inflow) + elif len(self.all_inflow) > timestep: + self.all_inflow[timestep] += inflow + else: + raise IndexError + + def get_outflow(self, timestep: int) -> float: + return self.all_outflow[timestep] + + def step(self, action: ActType) -> tuple[ObsType, SupportsFloat, bool, bool, dict]: + self.all_outflow.append(self.determine_outflow(action)) + # TODO: Change stored_water to multiple outflows. + + observation = self.determine_observation() + reward = self.determine_reward() + terminated = self.is_terminated() + truncated = self.is_truncated() + info = self.determine_info() + + self.timestep += 1 + + return ( + observation, + reward, + terminated, + truncated, + info, + ) + + def reset(self) -> None: + self.timestep: int = 0 + self.all_inflow: list[float] = [] + self.all_outflow: list[float] = [] + + def determine_info(self) -> dict: + """ + Returns information about the reservoir. + + """ + raise {} + + def __eq__(self, other): + return isinstance(other, self.__class__) and self.name == other.name + + def __hash__(self): + return hash(self.name) diff --git a/morl4water/core/models/flow.py b/morl4water/core/models/flow.py new file mode 100644 index 0000000000000000000000000000000000000000..f11f3d6ee51bde152a5767a14319f71718702581 --- /dev/null +++ b/morl4water/core/models/flow.py @@ -0,0 +1,138 @@ +from datetime import datetime +from dateutil.relativedelta import relativedelta +from typing import Union, Optional +from morl4water.core.models.facility import Facility, ControlledFacility +from gymnasium.core import ObsType + + +class Flow: + def __init__( + self, + name: str, + sources: list[Union[Facility, ControlledFacility]], + destinations: Facility | ControlledFacility | dict[Facility | ControlledFacility, float], + max_capacity: float, + evaporation_rate: float = 0.0, + delay: int = 0, + default_outflow: Optional[float] = None, + ) -> None: + self.name: str = name + self.sources: list[Union[Facility, ControlledFacility]] = sources + + if isinstance(destinations, Facility) or isinstance(destinations, ControlledFacility): + self.destinations = {destinations: 1.0} + else: + self.destinations: dict[Union[Facility, ControlledFacility], float] = destinations + + self.max_capacity: float = max_capacity + self.evaporation_rate: float = evaporation_rate + + self.delay: int = delay + self.default_outflow: Optional[float] = default_outflow + + self.current_date: Optional[datetime] = None + self.timestep_size: Optional[relativedelta] = None + self.timestep: int = 0 + + def determine_source_outflow(self) -> float: + if self.timestep - self.delay < 0 and self.default_outflow: + return self.default_outflow + else: + timestep_after_delay_clipped = max(0, self.timestep - self.delay) + + return sum(source.get_outflow(timestep_after_delay_clipped) for source in self.sources) + + def determine_source_outflow_by_destination(self, destination_index: int, destination_inflow_ratio: float) -> float: + if self.timestep - self.delay < 0 and self.default_outflow: + return self.default_outflow + else: + timestep_after_delay_clipped = max(0, self.timestep - self.delay) + total_source_outflow = 0 + + # Calculate each source contribution to the destination + for source in self.sources: + source_outflow = source.get_outflow(timestep_after_delay_clipped) + + # Determine if source has custom split policy + if source.split_release: + total_source_outflow += source_outflow * source.split_release[destination_index] + else: + total_source_outflow += source_outflow * destination_inflow_ratio + + return total_source_outflow + + def set_destination_inflow(self) -> None: + for destination_index, (destination, destination_inflow_ratio) in enumerate(self.destinations.items()): + destination_inflow = self.determine_source_outflow_by_destination( + destination_index, destination_inflow_ratio + ) + + destination.set_inflow(self.timestep, destination_inflow * (1.0 - self.evaporation_rate)) + + def is_truncated(self) -> bool: + return False + + def determine_info(self) -> dict: + return {"name": self.name, "flow": self.determine_source_outflow()} + + def step(self) -> tuple[Optional[ObsType], float, bool, bool, dict]: + self.set_destination_inflow() + + terminated = self.determine_source_outflow() > self.max_capacity + truncated = self.is_truncated() + reward = float("-inf") if terminated else 0.0 + info = self.determine_info() + + self.timestep += 1 + + return None, reward, terminated, truncated, info + + def reset(self) -> None: + self.timestep = 0 + + +class Inflow(Flow): + def __init__( + self, + name: str, + destinations: Facility | ControlledFacility | dict[Facility | ControlledFacility, float], + max_capacity: float, + all_inflow: list[float], + evaporation_rate: float = 0.0, + delay: int = 0, + default_outflow: Optional[float] = None, + ) -> None: + super().__init__(name, None, destinations, max_capacity, evaporation_rate, delay, default_outflow) + self.all_inflow: list[float] = all_inflow + + def determine_source_outflow(self) -> float: + if self.timestep - self.delay < 0 and self.default_outflow: + return self.default_outflow + else: + timestep_after_delay_clipped = max(0, self.timestep - self.delay) % len(self.all_inflow) + + return self.all_inflow[timestep_after_delay_clipped] + + def determine_source_outflow_by_destination(self, destination_index: int, destination_inflow_ratio: float) -> float: + if self.timestep - self.delay < 0 and self.default_outflow: + return self.default_outflow + else: + timestep_after_delay_clipped = max(0, self.timestep - self.delay) % len(self.all_inflow) + + return self.all_inflow[timestep_after_delay_clipped] * destination_inflow_ratio + + def is_truncated(self) -> bool: + return self.timestep >= len(self.all_inflow) + + +class Outflow(Flow): + def __init__( + self, + name: str, + sources: list[Union[Facility, ControlledFacility]], + max_capacity: float, + ) -> None: + super().__init__(name, sources, None, max_capacity) + + def set_destination_inflow(self) -> None: + pass diff --git a/morl4water/core/models/irrigation_district.py b/morl4water/core/models/irrigation_district.py new file mode 100644 index 0000000000000000000000000000000000000000..c00b965b9c39793128d6bc7313b2cdb5527d0c58 --- /dev/null +++ b/morl4water/core/models/irrigation_district.py @@ -0,0 +1,130 @@ +from morl4water.core.models.facility import Facility + + +class IrrigationDistrict(Facility): + """ + Represents an irrigation district with specific water demand, consumption, and deficit tracking. + + Attributes + ---------- + name : str + Identifier for the irrigation district. + all_demand : list[float] + Monthly water demand values for the irrigation district. + total_deficit : float + Cumulative water deficit experienced by the district over time. + all_deficit : list[float] + Monthly record of deficits, calculated as demand minus consumption. + normalize_objective : float + Normalization factor for the objective function reward. It should be the highest monthly value in a year. Default is 0.0 + + """ + def __init__(self, name: str, all_demand: list[float], objective_function, objective_name: str, normalize_objective:float = 0.0) -> None: + """ + Initializes an Irrigation District instance. + + Parameters: + name : str + Identifier for the irrigation district. + all_demand : list[float] + Monthly water demand values for the irrigation district. + objective_function : callable + Function to evaluate the district’s performance. + objective_name : str + Name of the objective. + normalize_objective : float, optional + Maximum value for normalizing the objective, it should be the highest monthly demand in the whole year. By default 0.0. + + """ + super().__init__(name, objective_function, objective_name, normalize_objective) + self.all_demand: list[float] = all_demand + self.total_deficit: float = 0 + self.all_deficit: list[float] = [] + + def get_current_demand(self) -> float: + """ + Returns the demand value for the current timestep. + + Returns + ------- + float + Demand for the current timestep. + + """ + return self.all_demand[self.timestep % len(self.all_demand)] + + def determine_deficit(self) -> float: + """ + Calculates the reward (irrigation deficit) given the values of its attributes + + Returns + ------- + float + Water deficit of the irrigation district + """ + consumption = self.determine_consumption() + deficit = self.get_current_demand() - consumption + self.total_deficit += deficit + self.all_deficit.append(deficit) + return deficit + + def determine_reward(self) -> float: + """ + Calculates the reward for the irrigation district based on the objective function. + + Returns + ------- + float + Reward as calculated by the objective function. + """ + return self.objective_function(self.get_current_demand(), float(self.get_inflow(self.timestep))) + + def determine_consumption(self) -> float: + """ + Calculates the water consumption for the irrigation district based on current demand and inflow. + + Returns + ------- + float + Water consumption for the current timestep. + """ + return min(self.get_current_demand(), self.get_inflow(self.timestep)) + + def is_truncated(self) -> bool: + """ + Checks if the simulation has reached the end of the demand data. + + Returns: + bool: + True if the simulation has no more demand data to process, False otherwise. + """ + return self.timestep >= len(self.all_demand) + + def determine_info(self) -> dict: + """ + Returns information about the irrigation district. + + Returns: + dict: + A dictionary containing key metrics for the district. + """ + return { + "name": self.name, + "inflow": self.get_inflow(self.timestep), + "outflow": self.get_outflow(self.timestep), + "demand": self.get_current_demand(), + "total_deficit": self.total_deficit, + "list_deficits": self.all_deficit, + } + + def reset(self) -> None: + """ + Resets the irrigation district's deficit attributes and inherited attributes. + + Returns: + None + + """ + super().reset() + self.total_deficit = 0 + self.all_deficit = [] diff --git a/morl4water/core/models/objective.py b/morl4water/core/models/objective.py new file mode 100644 index 0000000000000000000000000000000000000000..b6b102ccf06a9b37009341389aacbf0a6954d461 --- /dev/null +++ b/morl4water/core/models/objective.py @@ -0,0 +1,37 @@ +class Objective: + + @staticmethod + def no_objective(*args): + return 0.0 + + @staticmethod + def identity(value: float) -> float: + return value + + @staticmethod + def is_greater_than_minimum(minimum_value: float) -> float: + return lambda value: 1.0 if value >= minimum_value else 0.0 + + @staticmethod + def is_greater_than_minimum_with_condition(minimum_value: float) -> float: + return lambda condition, value: 1.0 if condition and value >= minimum_value else 0.0 + + @staticmethod + def deficit_minimised(demand: float, received: float) -> float: + return -max(0.0, demand - received) + + @staticmethod + def deficit_squared_ratio_minimised(demand: float, received: float) -> float: + return -((max(0.0, demand - received) / demand) ** 2) + + @staticmethod + def supply_ratio_maximised(demand: float, received: float) -> float: + return received / demand if received / demand < 1.0 else 1.0 + + @staticmethod + def scalar_identity(scalar: float) -> float: + return lambda value: value * scalar + + @staticmethod + def sequential_scalar(scalar: list[float]) -> float: + return lambda index, value: value * scalar[index] diff --git a/morl4water/core/models/power_plant.py b/morl4water/core/models/power_plant.py new file mode 100644 index 0000000000000000000000000000000000000000..898f4490720a0769e4392364aefe57f98b326ed3 --- /dev/null +++ b/morl4water/core/models/power_plant.py @@ -0,0 +1,217 @@ +from morl4water.core.models.facility import Facility +from morl4water.core.models.reservoir import Reservoir +from morl4water.core.utils import utils +from scipy.constants import g +import numpy as np + + +class PowerPlant(Facility): + """ + Class to represent Hydro-energy Powerplant + + Attributes: + ----------- + name : str + identifier + efficiency : float + Efficiency coefficient (mu) used in hydropower formula + max_turbine_flow : float + Maximum possible flow that can be passed through the turbines for the + purpose of hydroenergy production + head_start_level : float + Minimum elevation of water level that is used to calculate hydraulic + head for hydropower production + max_capacity : float + Total design capacity (mW) of the plant + water_level_coeff : float + Coefficient that determines the water level based on the volume of outflow + Used to calculate at what level the head of the power plant operates + water_usage : float + Amount of water that is used by plant, decimal coefficient + + Methods: + ---------- + determine_reward(): + Calculates the reward (power generation) given the values of its attributes + determine_consumption(): + Determines how much water is consumed by the power plant + determine_info(): + Returns info about the hydro-energy powerplant + """ + + def __init__( + self, + name: str, + objective_function, + objective_name: str, + efficiency: float, + min_turbine_flow: float = 0.0, + normalize_objective: float = 0.0, + max_turbine_flow: float = 0.0, + head_start_level: float = 0.0, + max_capacity: float = 0.0, + reservoir: Reservoir = None, + water_usage: float = 0.0, + tailwater: np.array = None, + turbines: np.array = None, + n_turbines: int = 0, + energy_prices: np.array = None + ) -> None: + super().__init__(name, objective_function, objective_name, normalize_objective) + self.efficiency: float = efficiency + self.max_turbine_flow: float = max_turbine_flow + self.head_start_level: float = head_start_level + self.min_turbine_flow: float = min_turbine_flow + self.max_capacity: float = max_capacity + self.reservoir: Reservoir = reservoir + self.water_usage: float = water_usage + self.production_vector: np.ndarray = np.empty(0, dtype=np.float64) + self.tailwater = tailwater + self.turbines = turbines + self.n_turbines = n_turbines + self.energy_prices = energy_prices + + def determine_turbine_flow(self) -> float: + return max(self.min_turbine_flow, min(self.max_turbine_flow, self.get_inflow(self.timestep))) + + # Constants are configured as parameters with default values + def determine_production(self) -> float: + """ + Calculates power production in MWh , when tailwater and turbine data is not available + + Returns: + ---------- + float + Plant's power production in MWh + """ + m3_to_kg_factor: int = 1000 + w_Mw_conversion: float = 1e-6 + # Turbine flow is equal to outflow, as long as it does not exceed maximum turbine flow + turbine_flow = self.determine_turbine_flow() + + # Uses water level from reservoir to determine water level + water_level = self.reservoir.level_vector[-1] if self.reservoir.level_vector else 0 + # Calculate at what level the head will generate power, using water_level of the outflow and head_start_level + head = max(0.0, water_level - self.head_start_level) + + # Calculate power in mW, has to be lower than or equal to capacity + power_in_mw = min( + self.max_capacity, + turbine_flow * head * m3_to_kg_factor * g * self.efficiency * w_Mw_conversion, + ) + + # Calculate the numbe rof hours the power plant has been running. + final_date = self.current_date + self.timestep_size + timestep_hours = (final_date - self.current_date).total_seconds() / 3600 + + # Hydro-energy power production in mWh + production = power_in_mw * timestep_hours + self.production_vector = np.append(self.production_vector, production) + + return production + + + + + def determine_production_detailed(self) -> float: + """Calculates power production when tailwater information and information regarding turbines is known. + Assumes metric system""" + + cubicFeetToCubicMeters = 0.0283 # 1 cf = 0.0283 m3 + feetToMeters = 0.3048 # 1 ft = 0.3048 m + m3_to_kg_factor = 1000 + p = 0.0 + water_level = self.reservoir.level_vector[-1] if self.reservoir.level_vector else 0 + turbine_flow = self.determine_turbine_flow() + + deltaH = water_level - utils.interpolate_tailwater_level( + self.tailwater[0], self.tailwater[1], turbine_flow + ) + + q_split = turbine_flow + + for j in range(0, self.n_turbines): + if q_split < self.turbines[1][j]: + qturb = 0.0 + elif q_split > self.turbines[0][j]: + qturb = self.turbines[0][j] + else: + qturb = q_split + q_split = q_split - qturb + p = p + ( + self.efficiency + * g + * m3_to_kg_factor + * (cubicFeetToCubicMeters * qturb) + * (feetToMeters * deltaH) + * 3600 + / (3600 * 1000) + ) + + + # Calculate the numbe rof hours the power plant has been running. + final_date = self.current_date + self.timestep_size + timestep_hours = (final_date - self.current_date).total_seconds() / 3600 + + production = p * timestep_hours + self.production_vector = np.append(self.production_vector, production) + + return production + + + + def determine_reward(self) -> float: + """ + Determines reward for the power plant using the power production. + + Parameters: + ----------- + objective_function : (float) -> float + Function calculating the objective given the power production. + + Returns: + ---------- + float + Reward. + """ + + if self.turbines is not None and self.tailwater is not None: + return self.objective_function(self.determine_production_detailed()) + else: + return self.objective_function(self.determine_production()) + + def determine_consumption(self) -> float: + """ + Determines water consumption. + + Returns: + ---------- + float + How much water is consumed + """ + return self.determine_turbine_flow() * self.water_usage + + def determine_info(self) -> dict: + """ + Determines info of hydro-energy power plant + + Returns: + ---------- + dict + Info about power plant (name, inflow, outflow, water usage, timestep, total production) + """ + return { + "name": self.name, + "inflow": self.get_inflow(self.timestep), + "outflow": self.get_outflow(self.timestep), + "monthly_production": self.production_vector[-1], + "water_usage": self.water_usage, + "total production (MWh)": sum(self.production_vector), + } + + def determine_month(self) -> int: + return self.timestep % 12 + + def reset(self) -> None: + super().reset() + self.production_vector = np.empty(0, dtype=np.float64) diff --git a/morl4water/core/models/reservoir.py b/morl4water/core/models/reservoir.py new file mode 100644 index 0000000000000000000000000000000000000000..0446de0384a36875143065f7cb4172f639f5b3ad --- /dev/null +++ b/morl4water/core/models/reservoir.py @@ -0,0 +1,233 @@ +from morl4water.core.models.facility import ControlledFacility +from gymnasium.spaces import Box, Space +import numpy as np +from dateutil.relativedelta import relativedelta +from datetime import datetime +from numpy.core.multiarray import interp as compiled_interp + + +class Reservoir(ControlledFacility): + """ + A class used to represent reservoirs of the problem + + Attributes + ---------- + name: str + Lowercase non-spaced name of the reservoir + storage_vector: np.array (1xH) + m3 + A vector that holds the volume of the water in the reservoir + throughout the simulation horizon + level_vector: np.array (1xH) + m + A vector that holds the elevation of the water in the reservoir + throughout the simulation horizon + release_vector: np.array (1xH) + m3/s + A vector that holds the actual average release per month + from the reservoir throughout the simulation horizon + evap_rates: np.array (1x12) + cm + Monthly evaporation rates of the reservoir + + Methods + ------- + determine_info() + Return dictionary with parameters of the reservoir. + storage_to_level(h=float) + Returns the level(height) based on volume. + level_to_storage(s=float) + Returns the volume based on level(height). + level_to_surface(h=float) + Returns the surface area based on level. + determine_outflow(action: float) + Returns average monthly water release. + """ + + def __init__( + self, + name: str, + max_capacity: float, + max_action: list[float], + objective_function, + integration_timestep_size: relativedelta, + evap_rates: list[float], + evap_rates_timestep_size: relativedelta, + storage_to_minmax_rel: list[list[float]], + storage_to_level_rel: list[list[float]], + storage_to_surface_rel: list[list[float]], + objective_name: str = "", + stored_water: float = 0, + spillage: float = 0, + observation_space = Box(low=0, high=1), + action_space = Box(low=0, high=1), + + ) -> None: + super().__init__(name, observation_space, action_space, max_capacity, max_action) + self.stored_water: float = stored_water + + self.evap_rates = evap_rates + self.evap_rates_timestep = evap_rates_timestep_size + self.storage_to_minmax_rel = storage_to_minmax_rel + self.storage_to_level_rel = storage_to_level_rel + self.storage_to_surface_rel = storage_to_surface_rel + + self.storage_vector = [] + self.level_vector = [] + self.release_vector = [] + + # Initialise storage vector + self.storage_vector.append(stored_water) + + self.objective_function = objective_function + self.objective_name = objective_name + + self.integration_timestep_size: relativedelta = integration_timestep_size + self.spillage = spillage + # self.water_level = self.storage_to_level(self.stored_water) + + def determine_reward(self) -> float: + # Pass water level to reward function + return self.objective_function(self.storage_to_level(self.stored_water)) + + def determine_outflow(self, actions: np.array) -> list[float]: + + current_storage = self.storage_vector[-1] + #check if we are releasing to one destination or more + if self.should_split_release == True: + #if it's more destinations, we have to create a list for sub-releases during the integration loop + sub_releases = [] + actions = np.multiply(actions, self.max_action) + else: + sub_releases = np.empty(0, dtype=np.float64) + actions = actions*self.max_action + + final_date = self.current_date + self.timestep_size + timestep_seconds = (final_date + self.evap_rates_timestep - final_date).total_seconds() + evaporatio_rate_per_second = self.evap_rates[self.determine_time_idx()] / (100 * timestep_seconds) + + while self.current_date < final_date: + next_date = min(final_date, self.current_date + self.integration_timestep_size) + integration_time_seconds = (next_date - self.current_date).total_seconds() + + #calculate the surface to get the evaporation + surface = self.storage_to_surface(current_storage) + #evaporation per integration timestep + evaporation = surface * (evaporatio_rate_per_second * integration_time_seconds) + #get min and max possible release based on the current storage + min_possible_release, max_possible_release = self.storage_to_minmax(current_storage) + #release per second is calculated based on the min-max releases which depend on the storage level and the predicted actions + release_per_second = min(max_possible_release, max(min_possible_release, np.sum(actions))) + + sub_releases = np.append(sub_releases, release_per_second) + + total_addition = self.get_inflow(self.timestep) * integration_time_seconds + + current_storage += total_addition - evaporation - (np.sum(release_per_second) - self.spillage) * integration_time_seconds + + self.current_date = next_date + + # Update the amount of water in the Reservoir + self.storage_vector.append(current_storage) + self.stored_water = current_storage + + # Record level based on storage for time t + self.level_vector.append(self.storage_to_level(current_storage)) + + # Calculate the ouflow of water + if self.should_split_release == True: + sub_releases = np.array(sub_releases) + average_release = np.mean(sub_releases, dtype=np.float64, axis = 0) + else: + average_release = np.mean(sub_releases, dtype=np.float64) + + self.release_vector.append(average_release) + + total_action = np.sum(average_release) + + # Split release for different destinations + if self.should_split_release and total_action != 0: + self.split_release = [(action / total_action) for action in average_release] + average_release = total_action + + return average_release + + def determine_info(self) -> dict: + info = { + "name": self.name, + "stored_water": self.stored_water, + "current_level": self.level_vector[-1] if self.level_vector else None, + "current_release": self.release_vector[-1] if self.release_vector else None, + "evaporation_rates": self.evap_rates.tolist(), + } + return info + + def determine_observation(self) -> float: + if self.stored_water > 0: + return self.stored_water + else: + return 0.0 + + def is_terminated(self) -> bool: + return self.stored_water > self.max_capacity or self.stored_water < 0 + + + + def determine_time_idx(self) -> int: + if self.evap_rates_timestep.months > 0: + return self.current_date.month - 1 + elif self.evap_rates_timestep.days > 0: + return self.current_date.timetuple().tm_yday - 1 + elif self.evap_rates_timestep.hours > 0: + return (self.current_date.timetuple().tm_yday - 1) * 24 + self.current_date.hour - 1 + else: + raise ValueError('The timestep is not supported, only time series with intervals of months, days, hours are supported') + + + def storage_to_level(self, s: float) -> float: + return self.modified_interp(s, self.storage_to_level_rel[0], self.storage_to_level_rel[1]) + + def storage_to_surface(self, s: float) -> float: + return self.modified_interp(s, self.storage_to_surface_rel[0], self.storage_to_surface_rel[1]) + + def level_to_minmax(self, h) -> tuple[np.ndarray, np.ndarray]: + return ( + np.interp(h, self.rating_curve[0], self.rating_curve[1]), + np.interp(h, self.rating_curve[0], self.rating_curve[2]), + ) + + def storage_to_minmax(self, s) -> tuple[np.ndarray, np.ndarray]: + return ( + np.interp(s, self.storage_to_minmax_rel[0], self.storage_to_minmax_rel[1]), + np.interp(s, self.storage_to_minmax_rel[0], self.storage_to_minmax_rel[2]), + ) + + @staticmethod + def modified_interp(x: float, xp: float, fp: float, left=None, right=None) -> float: + fp = np.asarray(fp) + + return compiled_interp(x, xp, fp, left, right) + + # def modified_interp(x: float, xp: float, fp: float, left=None, right=None) -> float: + # fp = np.asarray(fp) + # dim = len(xp) - 1 + # if x <= xp[0]: + # # if x is smaller than the smallest value on X, interpolate between the first two values + # y = (x - xp[0]) * (fp[1] - fp[0]) / (xp[1] - xp[0]) + fp[0] + # return y + # elif x >= xp[dim]: + # # if x is larger than the largest value, interpolate between the the last two values + # y = fp[dim] + (fp[dim] - fp[dim - 1]) / (xp[dim] - xp[dim - 1]) * ( + # x - xp[dim]) # y = Y[dim] + # return y + # else: + # return compiled_interp(x, xp, fp, left, right) + + + def reset(self) -> None: + super().reset() + stored_water = self.storage_vector[0] + self.storage_vector = [stored_water] + self.stored_water = stored_water + self.level_vector = [] + self.release_vector = [] diff --git a/morl4water/core/models/reservoir_with_pump.py b/morl4water/core/models/reservoir_with_pump.py new file mode 100644 index 0000000000000000000000000000000000000000..97d846ba25e67854010327ccf899cb577d549f2b --- /dev/null +++ b/morl4water/core/models/reservoir_with_pump.py @@ -0,0 +1,288 @@ +from morl4water.core.models.facility import ControlledFacility +from gymnasium.spaces import Box, Space +import numpy as np +from dateutil.relativedelta import relativedelta +from datetime import datetime +from numpy.core.multiarray import interp as compiled_interp +from typing import Callable +import inspect +from morl4water.core.utils import utils + +class ReservoirWithPump(ControlledFacility): + """ + A class used to represent reservoirs with a pump of the problem. + The pump can pump the water in and out of the reservoir as well as store the water + + Attributes + ---------- + name_reservoir: str + Lowercase non-spaced name of the reservoir + name_pump: str + Lowercase non-spaced name of the pumping station + storage_vector: np.array (1xH) + m3 + A vector that holds the volume of the water in the reservoir + throughout the simulation horizon + level_vector: np.array (1xH) + m + A vector that holds the elevation of the water in the reservoir + throughout the simulation horizon + release_vector: np.array (1xH) + m3/s + A vector that holds the actual average release per month + from the reservoir throughout the simulation horizon + evap_rates: np.array (1x12) + cm + Monthly evaporation rates of the reservoir + + Methods + ------- + determine_info() + Return dictionary with parameters of the reservoir. + storage_to_level(h=float) + Returns the level(height) based on volume. + level_to_storage(s=float) + Returns the volume based on level(height). + level_to_surface(h=float) + Returns the surface area based on level. + determine_outflow(action: float) + Returns average monthly water release. + """ + def __init__( + self, + name: str, + max_capacity: float, + max_action: float, + objective_function, + integration_timestep_size: relativedelta, + evap_rates: list[float], + evap_rates_pump: list[float], + evap_rates_timestep_size: relativedelta, + storage_to_minmax_rel: list[list[float]], + storage_to_level_rel: list[list[float]], + storage_to_surface_rel: list[list[float]], + storage_to_surface_rel_pump: list[list[float]], + storage_to_level_rel_pump: list[list[float]], + pumping_rules: Callable, + inflows_pump: list[float] = None, + objective_name: str = "", + stored_water_reservoir: float = 0, + stored_water_pump: float = 0, + observation_space = Box(low=0, high=1), + action_space = Box(low=0, high=1), + spillage: float = 0 + ) -> None: + super().__init__(name, observation_space, action_space, max_capacity, max_action) + self.stored_water: float = stored_water_reservoir + self.stored_pump: float = stored_water_pump + + self.evap_rates = evap_rates + self.evap_rates_pump = evap_rates_pump + self.evap_rates_timestep = evap_rates_timestep_size + self.storage_to_minmax_rel = storage_to_minmax_rel + self.storage_to_level_rel = storage_to_level_rel + self.storage_to_surface_rel = storage_to_surface_rel + self.storage_to_surface_rel_pump = storage_to_surface_rel_pump + self.storage_to_level_rel_pump = storage_to_level_rel_pump + self.spillage = spillage + self.required_params = ['day_of_the_week', 'hour', 'level_reservoir', 'level_pump', 'storage_reservoir', 'storage_pump'] + + self.inflows_pump = inflows_pump + + self.storage_vector = [] + self.storage_pump_vector = [] + self.level_vector = [] + self.release_vector = [] + + # Initialise storage vector + self.storage_vector.append(stored_water_reservoir) + self.storage_pump_vector.append(stored_water_pump) + + self.objective_function = objective_function + self.objective_name = objective_name + + self.integration_timestep_size: relativedelta = integration_timestep_size + + + if not callable(pumping_rules): + raise ValueError("The pumping rules should be defined as a function, which takes as argument storage_level of the reservoir and the pump.") + + # Get the signature of the method + sig = inspect.signature(pumping_rules) + + # Check if the method has the required parameters + for param in self.required_params: + if param not in sig.parameters: + raise ValueError(f"The method must have a parameter named '{param}'.") + + # Assign the provided method to the instance + self.pumping_rules = pumping_rules + + + def determine_reward(self) -> float: + # Pass water level to reward function + return self.objective_function(self.storage_to_level(self.stored_water)) + + def determine_outflow(self, actions: np.array) -> list[float]: + #determine current storage for the reservoir + current_storage = self.storage_vector[-1] + #determine current storage for the pump + current_storage_pump = self.storage_pump_vector[-1] + #check if we are releasing to one destination or more + if self.should_split_release == True: + #if it's more destinations, we have to create a list for sub-releases during the integration loop + sub_releases = [] + actions = np.multiply(actions, self.max_action) + else: + sub_releases = np.empty(0, dtype=np.float64) + actions = actions*self.max_action + + + final_date = self.current_date + self.timestep_size + timestep_seconds = (final_date + self.evap_rates_timestep - final_date).total_seconds() + evaporatio_rate_per_second = self.evap_rates[self.determine_time_idx()] / (100 * timestep_seconds) + evaporatio_rate_per_second_pump = self.evap_rates_pump[self.determine_time_idx()] / (100 * timestep_seconds) + + while self.current_date < final_date: + next_date = min(final_date, self.current_date + self.integration_timestep_size) + integration_time_seconds = (next_date - self.current_date).total_seconds() + + #pumping/release of the pump + + pumping, release_pump = self.pumping_rules(day = self.current_date.weekday(), + hour = self.current_date.hour, + level_reservoir = self.storage_to_level(current_storage), + level_pump = self.storage_to_level_pump(self.stored_pump), + storage_reservoir = current_storage, storage_pump = self.stored_pump) + + + surface = self.storage_to_surface(current_storage) + surface_pump = self.storage_to_surface_pump(current_storage_pump) + + evaporation = surface * (evaporatio_rate_per_second * integration_time_seconds) + evaporation_pump = surface_pump * (evaporatio_rate_per_second_pump * integration_time_seconds) + + current_storage_pump += (self.inflows_pump[self.timestep] + pumping - release_pump) * integration_time_seconds - evaporation_pump + + + min_possible_release, max_possible_release = self.storage_to_minmax(current_storage) + + release_per_second = min(max_possible_release, max(min_possible_release, np.sum(actions))) + + #depending if there are multiple outflows, append release decisions for every integration step + if self.should_split_release == True: + sub_releases.append(release_per_second) + else: + sub_releases = np.append(sub_releases, release_per_second) + + total_addition = (self.get_inflow(self.timestep) + release_pump) * integration_time_seconds + + current_storage += total_addition - evaporation - np.sum(release_per_second) * integration_time_seconds + + self.current_date = next_date + + # Update the amount of water in the Reservoir + self.storage_vector.append(current_storage) + self.stored_water = current_storage + + # Update water in the pump + self.storage_pump_vector.append(current_storage_pump) + self.stored_pump = current_storage_pump + + # Record level based on storage for time t + self.level_vector.append(self.storage_to_level(current_storage)) + + # Calculate the ouflow of water + if self.should_split_release == True: + sub_releases = np.array(sub_releases) + average_release = np.mean(sub_releases, dtype=np.float64, axis = 0) + else: + average_release = np.mean(sub_releases, dtype=np.float64) + + self.release_vector.append(average_release) + + total_action = np.sum(average_release) + # Split release for different destinations + if self.should_split_release and total_action != 0: + + self.split_release = [(action / total_action) for action in average_release] + average_release = total_action + + return average_release + + def determine_info(self) -> dict: + info = { + "name": self.name, + "stored_water": self.stored_water, + "current_level": self.level_vector[-1] if self.level_vector else None, + "current_release": self.release_vector[-1] if self.release_vector else None, + "evaporation_rates": self.evap_rates.tolist(), + "pump_level": self.stored_pump + } + return info + + def determine_observation(self) -> float: + return self.stored_water + + def is_terminated(self) -> bool: + return self.stored_water > self.max_capacity or self.stored_water < 0 + + def determine_time_idx(self) -> int: + if self.evap_rates_timestep.months > 0: + return self.current_date.month - 1 + elif self.evap_rates_timestep.days > 0: + return self.current_date.timetuple().tm_yday - 1 + elif self.evap_rates_timestep.hours > 0: + return (self.current_date.timetuple().tm_yday - 1) * 24 + self.current_date.hour - 1 + else: + raise ValueError('The timestep is not supported, only time series with intervals of months, days, hours are supported') + + def storage_to_level(self, s: float) -> float: + return self.modified_interp(s, self.storage_to_level_rel[0], self.storage_to_level_rel[1]) + + def storage_to_level_pump(self, s: float) -> float: + return self.modified_interp(s, self.storage_to_level_rel_pump[0], self.storage_to_level_rel_pump[1]) + + + def storage_to_surface(self, s: float) -> float: + return self.modified_interp(s, self.storage_to_surface_rel[0], self.storage_to_surface_rel[1]) + + def storage_to_surface_pump(self, s: float) -> float: + return self.modified_interp(s, self.storage_to_surface_rel_pump[0], self.storage_to_surface_rel_pump[1]) + + + def level_to_minmax(self, h) -> tuple[np.ndarray, np.ndarray]: + return ( + np.interp(h, self.rating_curve[0], self.rating_curve[1]), + np.interp(h, self.rating_curve[0], self.rating_curve[2]), + ) + + def storage_to_minmax(self, s) -> tuple[np.ndarray, np.ndarray]: + return ( + np.interp(s, self.storage_to_minmax_rel[0], self.storage_to_minmax_rel[1]), + np.interp(s, self.storage_to_minmax_rel[0], self.storage_to_minmax_rel[2]), + ) + + @staticmethod + def modified_interp(x: float, xp: float, fp: float, left=None, right=None) -> float: + fp = np.asarray(fp) + dim = len(xp) - 1 + if x <= xp[0]: + # if x is smaller than the smallest value on X, interpolate between the first two values + y = (x - xp[0]) * (fp[1] - fp[0]) / (xp[1] - xp[0]) + fp[0] + return y + elif x >= xp[dim]: + # if x is larger than the largest value, interpolate between the the last two values + y = fp[dim] + (fp[dim] - fp[dim - 1]) / (xp[dim] - xp[dim - 1]) * ( + x - xp[dim]) # y = Y[dim] + return y + else: + return compiled_interp(x, xp, fp, left, right) + + def reset(self) -> None: + super().reset() + stored_water = self.storage_vector[0] + self.storage_vector = [stored_water] + self.stored_water = stored_water + self.level_vector = [self.storage_to_level(stored_water)] + self.release_vector = [] diff --git a/morl4water/core/models/weir.py b/morl4water/core/models/weir.py new file mode 100644 index 0000000000000000000000000000000000000000..f6ef0d821df74f89d8fb17dc6f8b2fe7c9b90a4f --- /dev/null +++ b/morl4water/core/models/weir.py @@ -0,0 +1,142 @@ +from morl4water.core.models.facility import ControlledFacility +from gymnasium.spaces import Box, Space +import numpy as np +from dateutil.relativedelta import relativedelta +from datetime import datetime +from numpy.core.multiarray import interp as compiled_interp + + +class Weir(ControlledFacility): + """ + A class used to represent reservoirs of the problem + + Attributes + ---------- + name: str + Lowercase non-spaced name of the reservoir + storage_vector: np.array (1xH) + m3 + A vector that holds the volume of the water in the reservoir + throughout the simulation horizon + level_vector: np.array (1xH) + m + A vector that holds the elevation of the water in the reservoir + throughout the simulation horizon + release_vector: np.array (1xH) + m3/s + A vector that holds the actual average release per month + from the reservoir throughout the simulation horizon + evap_rates: np.array (1x12) + cm + Monthly evaporation rates of the reservoir + + Methods + ------- + determine_info() + Return dictionary with parameters of the reservoir. + storage_to_level(h=float) + Returns the level(height) based on volume. + level_to_storage(s=float) + Returns the volume based on level(height). + level_to_surface(h=float) + Returns the surface area based on level. + determine_outflow(action: float) + Returns average monthly water release. + """ + + def __init__( + self, + name: str, + max_capacity: float, + max_action: list[float], + objective_function, + integration_timestep_size: relativedelta, + objective_name: str = "", + stored_water: float = 0, + spillage: float = 0, + observation_space = Box(low=0, high=1), + action_space = Box(low=0, high=1), + + ) -> None: + super().__init__(name, observation_space, action_space, max_capacity, max_action) + self.stored_water: float = stored_water + + self.should_split_release = True + + + self.storage_vector = [] + self.level_vector = [] + self.release_vector = [] + + # Initialise storage vector + self.storage_vector.append(stored_water) + + self.objective_function = objective_function + self.objective_name = objective_name + + self.integration_timestep_size: relativedelta = integration_timestep_size + self.spillage = spillage + + + def determine_reward(self) -> float: + #Pass average inflow (which is stored_water ) to reward function + return self.objective_function(self.stored_water) + + def determine_outflow(self, actions: np.array) -> list[float]: + + destination_1_release = np.empty(0, dtype=np.float64) + weir_observation_lst = [] + + final_date = self.current_date + self.timestep_size + + while self.current_date < final_date: + next_date = min(final_date, self.current_date + self.integration_timestep_size) + + #See what is the current inflow to weir and scale up the action to the first destination ( the action is a percentage of water going to destination 1) + weir_observation = self.get_inflow(self.timestep) + max_action = weir_observation + actions_scaled_up = actions*max_action + + destination_1_release = np.append(destination_1_release, actions_scaled_up) + + weir_observation_lst = np.append(weir_observation_lst, weir_observation) + + self.current_date = next_date + + #Averaging inflow to weir over last step (usually month) as a potential observation space to be used + average_release = np.mean(weir_observation_lst, dtype=np.float64) + self.storage_vector.append(average_release) #TODO does it make sense to keep it? + self.stored_water = average_release # TODO used in determine_observation + + #potential storage (observation space understood as total inflow) is same as the total release + self.release_vector.append(average_release) + + # Split release for different destinations, action is expected to be in range [0,1] + self.split_release = [actions, (1-actions)] + + + return average_release + + def determine_info(self) -> dict: + info = { + "name": self.name, + "average_release": self.stored_water, + } + return info + + def determine_observation(self) -> float: + if self.stored_water > 0: + return self.stored_water + else: + return 0.0 + + def is_terminated(self) -> bool: + return self.stored_water > self.max_capacity or self.stored_water < 0 + + def reset(self) -> None: + super().reset() + stored_water = self.storage_vector[0] + self.storage_vector = [stored_water] + self.stored_water = stored_water + self.level_vector = [] + self.release_vector = [] diff --git a/morl4water/core/settings/settings_file_Nile_with_icons.xlsm b/morl4water/core/settings/settings_file_Nile_with_icons.xlsm new file mode 100644 index 0000000000000000000000000000000000000000..7ba9aeee0bc5a36d1469e1d8636595795a438c4f Binary files /dev/null and b/morl4water/core/settings/settings_file_Nile_with_icons.xlsm differ diff --git a/morl4water/core/utils/__init__.py b/morl4water/core/utils/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..a3466a53684df6a8c73e9db7632e75763357f57a --- /dev/null +++ b/morl4water/core/utils/__init__.py @@ -0,0 +1,26 @@ +# morl4water/core/utils/__init__.py +from .utils import ( + generate_random_actions, + convert_str_to_float_list, + gallonToCubicFeet, + inchesToFeet, + cubicFeetToCubicMeters, + feetToMeters, + acreToSquaredFeet, + acreFeetToCubicFeet, + cubicFeetToAcreFeet, + interpolate_tailwater_level, +) + +__all__ = [ + "generate_random_actions", + "convert_str_to_float_list", + "gallonToCubicFeet", + "inchesToFeet", + "cubicFeetToCubicMeters", + "feetToMeters", + "acreToSquaredFeet", + "acreFeetToCubicFeet", + "cubicFeetToAcreFeet", + "interpolate_tailwater_level", +] diff --git a/morl4water/core/utils/utils.py b/morl4water/core/utils/utils.py new file mode 100644 index 0000000000000000000000000000000000000000..2ca30cc37bca0229447464fdeecebd3a5ee92ea3 --- /dev/null +++ b/morl4water/core/utils/utils.py @@ -0,0 +1,71 @@ +import numpy as np +from numba import njit + +LIST_SPECIFIC_CHARACTERS = "[]," + + +def generate_random_actions(number_of_actions=4, seed=42) -> np.ndarray: + np.random.seed(seed) + return np.random.rand(4) * [10000, 10000, 10000, 4000] + + +def convert_str_to_float_list(string_list: str) -> list: + return list(map(float, string_list.translate(str.maketrans("", "", LIST_SPECIFIC_CHARACTERS)).split())) + +@njit +def gallonToCubicFeet(x): + conv = 0.13368 # 1 gallon = 0.13368 cf + return x * conv + + +@njit +def inchesToFeet(x): + conv = 0.08333 # 1 inch = 0.08333 ft + return x * conv + + +@njit +def cubicFeetToCubicMeters(x): + conv = 0.0283 # 1 cf = 0.0283 m3 + return x * conv + + +@njit +def feetToMeters(x): + conv = 0.3048 # 1 ft = 0.3048 m + return x * conv + + +@njit +def acreToSquaredFeet(x): + conv = 43560 # 1 acre = 43560 feet2 + return x * conv + + +@njit +def acreFeetToCubicFeet(x): + conv = 43560 # 1 acre-feet = 43560 feet3 + return x * conv + + +@njit +def cubicFeetToAcreFeet(x): + conv = 43560 # 1 acre = 43560 feet2 + return x / conv + + +@njit +def interpolate_tailwater_level(X, Y, x): + dim = len(X) - 1 + if x <= X[0]: + y = (x - X[0]) * (Y[1] - Y[0]) / (X[1] - X[0]) + Y[0] + return y + elif x >= X[dim]: + y = Y[dim] + (Y[dim] - Y[dim - 1]) / (X[dim] - X[dim - 1]) * ( + x - X[dim] + ) + return y + else: + y = np.interp(x, X, Y) + return y + diff --git a/morl4water/core/wrappers/__init__.py b/morl4water/core/wrappers/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/morl4water/core/wrappers/transform_action.py b/morl4water/core/wrappers/transform_action.py new file mode 100644 index 0000000000000000000000000000000000000000..b752551e3a020138cabc45bb222ca0e784c5a92c --- /dev/null +++ b/morl4water/core/wrappers/transform_action.py @@ -0,0 +1,34 @@ +import numpy as np +import gymnasium as gym +from gymnasium.spaces.dict import Dict +from morl4water.core.envs.water_management_system import WaterManagementSystem +from morl4water.core.models.facility import ControlledFacility + + +class ReshapeArrayAction(gym.ActionWrapper, gym.utils.RecordConstructorArgs): + def __init__(self, env: WaterManagementSystem): + # assert isinstance(env.action_space, Dict) + + self.ordered_shapes = {} + self.slices = {} + current_index = 0 + + for water_system in env.water_systems: + if isinstance(water_system, ControlledFacility): + number_of_actions = np.prod(water_system.action_space.shape) + + self.slices[water_system.name] = slice(current_index, current_index + number_of_actions) + self.ordered_shapes[water_system.name] = water_system.action_space.shape + + current_index += number_of_actions + + gym.utils.RecordConstructorArgs.__init__(self) + gym.ActionWrapper.__init__(self, env) + + def action(self, action): + reshaped_actions = {} + + for name, sub_action_space_shape in self.ordered_shapes.items(): + reshaped_actions[name] = np.reshape(action[self.slices[name]], sub_action_space_shape) + + return reshaped_actions diff --git a/morl4water/examples/.DS_Store b/morl4water/examples/.DS_Store new file mode 100644 index 0000000000000000000000000000000000000000..2c84839d8183947756a03680d989d5a84f8d9c40 Binary files /dev/null and b/morl4water/examples/.DS_Store differ diff --git a/morl4water/examples/__init__.py b/morl4water/examples/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..31f3c8f5355bb000033a5231ac1ebf9a149e8ee1 --- /dev/null +++ b/morl4water/examples/__init__.py @@ -0,0 +1,23 @@ +from .nile_river_simulation import create_nile_river_env +from .omo_river_simulation import create_omo_river_env +from .susquehanna_river_simulation import create_susquehanna_river_env +from gymnasium.envs.registration import register + +__all__=['create_nile_river_env', 'create_omo_river_env', 'create_susquehanna_river_env'] + + +register( + id='nile-v0', + entry_point='morl4water.examples.nile_river_simulation:create_nile_river_env', +) + +register( + id='omo-v0', + entry_point='morl4water.examples.omo_river_simulation:create_omo_river_env', +) + + +register( + id='susquehanna-v0', + entry_point='morl4water.examples.susquehanna_river_simulation:create_susquehanna_river_env', +) \ No newline at end of file diff --git a/morl4water/examples/data/__init__.py b/morl4water/examples/data/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/morl4water/examples/data/nile_river/__init__.py b/morl4water/examples/data/nile_river/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/morl4water/examples/data/nile_river/catchments/InflowAtbara.txt b/morl4water/examples/data/nile_river/catchments/InflowAtbara.txt new file mode 100644 index 0000000000000000000000000000000000000000..2b1e49173fee158256aa5e5ea5e68575a207249f --- /dev/null +++ b/morl4water/examples/data/nile_river/catchments/InflowAtbara.txt @@ -0,0 +1,240 @@ +7.712786885245902 +3.004426229508197 +0.4216393442622951 +1.4672131147540983 +2.970983606557377 +28.256393442622947 +592.7859154929578 +1979.0281690140846 +1301.619718309859 +304.04647887323944 +63.12239436619718 +28.43633802816902 +7.712786885245902 +3.004426229508197 +0.4216393442622951 +1.4672131147540983 +2.970983606557377 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a/morl4water/examples/data/nile_river/reservoirs/store_level_rel_Roseires.txt b/morl4water/examples/data/nile_river/reservoirs/store_level_rel_Roseires.txt new file mode 100644 index 0000000000000000000000000000000000000000..c2c774b2dce0ccd331812e0bcfdaaa17fe295994 --- /dev/null +++ b/morl4water/examples/data/nile_river/reservoirs/store_level_rel_Roseires.txt @@ -0,0 +1,2 @@ +0 12000000 27000000 46000000 56000000 75000000 98000000 156000000 230000000 321000000 429000000 555000000 699000000 862000000 1044000000 1246000000 1354000000 1467000000 1585000000 1708000000 1836000000 1970000000 2290000000 2645000000 3035000000 3461000000 3922000000 4415000000 4941000000 5500000000 6095000000 +465 466 467 467.7 468 468.5 469 470 471 472 473 474 475 476 477 478 478.5 479 479.5 480 480.5 481 482 483 484 485 486 487 488 489 490 \ No newline at end of file diff --git a/morl4water/examples/data/nile_river/reservoirs/store_level_rel_Sennar.txt 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b/morl4water/examples/data/susquehanna_river/reservoirs/store_level_rel_Conowingo.txt new file mode 100644 index 0000000000000000000000000000000000000000..8dd404124cec6dfb26a7007f4d4b74c71093bf31 --- /dev/null +++ b/morl4water/examples/data/susquehanna_river/reservoirs/store_level_rel_Conowingo.txt @@ -0,0 +1,2 @@ + 0.0000000e+00 3.3493284e+08 7.0044480e+08 1.0579853e+09 1.4205352e+09 1.7873104e+09 2.1573961e+09 2.5297034e+09 2.9037096e+09 3.2795017e+09 + 1.0120000e+02 1.0220000e+02 1.0320000e+02 1.0420000e+02 1.0520000e+02 1.0620000e+02 1.0720000e+02 1.0820000e+02 1.0920000e+02 1.1020000e+02 \ No newline at end of file diff --git a/morl4water/examples/data/susquehanna_river/reservoirs/store_min_max_release_Conowingo.txt b/morl4water/examples/data/susquehanna_river/reservoirs/store_min_max_release_Conowingo.txt new file mode 100644 index 0000000000000000000000000000000000000000..36f8d047ad857d32e134a7c9163d48063fa0ac3a --- /dev/null +++ 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0000000000000000000000000000000000000000..98a61f5ab4b84f7552c99290dbfdbd080a10904e --- /dev/null +++ b/morl4water/examples/data/susquehanna_river/reservoirs/store_sur_rel_Conowingo.txt @@ -0,0 +1,2 @@ + 0.0000000e+00 3.3493284e+08 7.0044480e+08 1.0579853e+09 1.4205352e+09 1.7873104e+09 2.1573961e+09 2.5297034e+09 2.9037096e+09 3.2795017e+09 + 3.4586640e+08 3.5013528e+08 3.5475264e+08 3.6037188e+08 3.6477144e+08 3.6877896e+08 3.7139256e+08 3.7317852e+08 3.7483380e+08 3.7679400e+08 diff --git a/morl4water/examples/data/susquehanna_river/reservoirs/tailwater.txt b/morl4water/examples/data/susquehanna_river/reservoirs/tailwater.txt new file mode 100644 index 0000000000000000000000000000000000000000..eeca5e1622b2cc26aaa7239bb16b073e76c3a08c --- /dev/null +++ b/morl4water/examples/data/susquehanna_river/reservoirs/tailwater.txt @@ -0,0 +1,2 @@ + 0.0000000e+00 2.0000000e+03 5.0000000e+03 7.0000000e+03 1.0000000e+04 1.5000000e+04 2.0000000e+04 3.0000000e+04 4.0000000e+04 5.0000000e+04 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index 0000000000000000000000000000000000000000..3e90ed429c189c549274bd101bdafe703f466e64 --- /dev/null +++ b/morl4water/examples/data/susquehanna_river/reservoirs/wChester.txt @@ -0,0 +1,365 @@ + 5.2297813e+01 + 5.2297813e+01 + 5.2297813e+01 + 5.2297813e+01 + 5.2297813e+01 + 5.2297813e+01 + 5.2297813e+01 + 5.2297813e+01 + 5.2297813e+01 + 5.2297813e+01 + 5.2297813e+01 + 5.2297813e+01 + 5.2297813e+01 + 5.2297813e+01 + 5.2297813e+01 + 5.2297813e+01 + 5.2297813e+01 + 5.2297813e+01 + 5.2297813e+01 + 5.2297813e+01 + 5.2297813e+01 + 5.2297813e+01 + 5.2297813e+01 + 5.2297813e+01 + 5.2297813e+01 + 5.2297813e+01 + 5.2297813e+01 + 5.2297813e+01 + 5.2297813e+01 + 5.2297813e+01 + 5.2297813e+01 + 5.4748458e+01 + 5.4748458e+01 + 5.4748458e+01 + 5.4748458e+01 + 5.4748458e+01 + 5.4748458e+01 + 5.4748458e+01 + 5.4748458e+01 + 5.4748458e+01 + 5.4748458e+01 + 5.4748458e+01 + 5.4748458e+01 + 5.4748458e+01 + 5.4748458e+01 + 5.4748458e+01 + 5.4748458e+01 + 5.4748458e+01 + 5.4748458e+01 + 5.4748458e+01 + 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5.1515692e+01 + 5.1515692e+01 + 5.1515692e+01 + 5.1515692e+01 + 5.1515692e+01 diff --git a/morl4water/examples/nile_river_simulation.py b/morl4water/examples/nile_river_simulation.py new file mode 100644 index 0000000000000000000000000000000000000000..126ab53f351cb0daf56d98160c3796b0be281a2d --- /dev/null +++ b/morl4water/examples/nile_river_simulation.py @@ -0,0 +1,260 @@ +import numpy as np +from pathlib import Path +from gymnasium.spaces import Box +from gymnasium.wrappers import TimeLimit +from morl4water.core.envs.water_management_system import WaterManagementSystem +from morl4water.core.models import Reservoir +from morl4water.core.models import Flow, Inflow +from morl4water.core.models import Objective +from morl4water.core.models import PowerPlant +from morl4water.core.models import IrrigationDistrict +from morl4water.core.models import Catchment +from morl4water.core.wrappers.transform_action import ReshapeArrayAction +from datetime import datetime +from dateutil.relativedelta import relativedelta +from gymnasium.envs.registration import register +from importlib.resources import files + +data_directory = files("morl4water.examples.data.nile_river") + + + + +def create_nile_river_env(custom_obj = None, render_mode=None) -> WaterManagementSystem: + # Ethiopia + GERD_reservoir = Reservoir( + "GERD", + max_capacity=117500000000.0, + max_action=[10000], + integration_timestep_size=relativedelta(minutes=240), + objective_function=Objective.no_objective, + stored_water=15000000000.0, + evap_rates=np.loadtxt(data_directory / "reservoirs" / "evap_GERD.txt"), + evap_rates_timestep_size=relativedelta(months=1), + storage_to_minmax_rel=np.loadtxt(data_directory / "reservoirs" / "store_min_max_release_GERD.txt"), + storage_to_level_rel=np.loadtxt(data_directory / "reservoirs" / "store_level_rel_GERD.txt"), + storage_to_surface_rel=np.loadtxt(data_directory / "reservoirs" / "store_sur_rel_GERD.txt"), + ) + GERD_power_plant = PowerPlant( + "GERD_power_plant", + Objective.scalar_identity(1), + "ethiopia_power", + efficiency=0.93, + min_turbine_flow=0, + max_turbine_flow=4320, + head_start_level=507, + max_capacity=6000, + reservoir=GERD_reservoir, + normalize_objective=4464000.0 #the max amount of electricity produced possible in one month based on the max capacity + ) + # Sudan + DSSennar_irr_system = IrrigationDistrict( + "DSSennar_irr", + np.loadtxt(data_directory / "irrigation" / "irr_demand_DSSennar.txt"), + Objective.deficit_minimised, + "sudan_deficit_minimised", + normalize_objective=12.73148148 + ) + Gezira_irr_system = IrrigationDistrict( + "Gezira_irr", + np.loadtxt(data_directory / "irrigation" / "irr_demand_Gezira.txt"), + Objective.deficit_minimised, + "sudan_deficit_minimised", + normalize_objective=388.2915173 + ) + Hassanab_irr_system = IrrigationDistrict( + "Hassanab_irr", + np.loadtxt(data_directory / "irrigation" / "irr_demand_Hassanab.txt"), + Objective.deficit_minimised, + "sudan_deficit_minimised", + normalize_objective=38.96604938 + ) + Tamaniat_irr_system = IrrigationDistrict( + "Tamaniat_irr", + np.loadtxt(data_directory / "irrigation" / "irr_demand_Tamaniat.txt"), + Objective.deficit_minimised, + "sudan_deficit_minimised", + normalize_objective=25.84876543 + ) + USSennar_irr_system = IrrigationDistrict( + "USSennar_irr", + np.loadtxt(data_directory / "irrigation" / "irr_demand_USSennar.txt"), + Objective.deficit_minimised, + "sudan_deficit_minimised", + normalize_objective=148.2228196 + ) + Roseires_reservoir = Reservoir( + "Roseires", + max_capacity=6095000000.0, + max_action=[15000.0], + integration_timestep_size=relativedelta(minutes=240), + objective_function=Objective.no_objective, + stored_water=4571250000.0, + evap_rates=np.loadtxt(data_directory / "reservoirs" / "evap_Roseires.txt"), + evap_rates_timestep_size=relativedelta(months=1), + storage_to_minmax_rel=np.loadtxt(data_directory / "reservoirs" / "store_min_max_release_Roseires.txt"), + storage_to_level_rel=np.loadtxt(data_directory / "reservoirs" / "store_level_rel_Roseires.txt"), + storage_to_surface_rel=np.loadtxt(data_directory / "reservoirs" / "store_sur_rel_Roseires.txt"), + ) + Sennar_reservoir = Reservoir( + "Sennar", + max_capacity=579900000.0, + max_action = [7000.0], + integration_timestep_size=relativedelta(minutes=240), + objective_function=Objective.no_objective, + stored_water=434925000.0, + evap_rates=np.loadtxt(data_directory / "reservoirs" / "evap_Sennar.txt"), + evap_rates_timestep_size=relativedelta(months=1), + storage_to_minmax_rel=np.loadtxt(data_directory / "reservoirs" / "store_min_max_release_Sennar.txt"), + storage_to_level_rel=np.loadtxt(data_directory / "reservoirs" / "store_level_rel_Sennar.txt"), + storage_to_surface_rel=np.loadtxt(data_directory / "reservoirs" / "store_sur_rel_Sennar.txt"), + ) + # Egypt + Egypt_irr_system = IrrigationDistrict( + "Egypt_irr", + np.loadtxt(data_directory / "irrigation" / "irr_demand_Egypt.txt"), + Objective.deficit_minimised, + "egypt_deficit_minimised", + normalize_objective=2523.894863 + ) + HAD_reservoir = Reservoir( + "HAD", + max_capacity=182700000000.0, + max_action=[7000.0], + integration_timestep_size=relativedelta(minutes=240), + objective_function=Objective.is_greater_than_minimum(159), + objective_name="HAD_minimum_water_level", + stored_water=137025000000.0, + evap_rates=np.loadtxt(data_directory / "reservoirs" / "evap_HAD.txt"), + evap_rates_timestep_size=relativedelta(months=1), + storage_to_minmax_rel=np.loadtxt(data_directory / "reservoirs" / "store_min_max_release_HAD.txt"), + storage_to_level_rel=np.loadtxt(data_directory / "reservoirs" / "store_level_rel_HAD.txt"), + storage_to_surface_rel=np.loadtxt(data_directory / "reservoirs" / "store_sur_rel_HAD.txt"), + ) + # Create 'edges' between Facilities. + # TODO: determine max capacity for flows + GERD_inflow = Inflow( + "gerd_inflow", + GERD_reservoir, + float("inf"), + np.loadtxt(data_directory / "catchments" / "InflowBlueNile.txt"), + ) + + GerdToRoseires_catchment = Catchment( + "GerdToRoseires_catchment", np.loadtxt(data_directory / "catchments" / "InflowGERDToRoseires.txt") + ) + # TODO: add catchment 1 inflow to sources of Roseires (inflow with destination Roseires) + + Power_plant_flow = Flow("power_plant_flow", [GERD_reservoir], GERD_power_plant, float("inf")) + + Roseires_flow = Flow( + "roseires_flow", [GERD_power_plant, GerdToRoseires_catchment], Roseires_reservoir, float("inf") + ) + + RoseiresToAbuNaama_catchment = Catchment( + "RoseiresToAbuNaama_catchment", np.loadtxt(data_directory / "catchments" / "InflowRoseiresToAbuNaama.txt") + ) + + # TODO: add catchment 2 inflow to sources of USSennar (inflow with destination USSennar) + upstream_Sennar_received_flow = Flow( + "upstream_Sennar_received_flow", + [Roseires_reservoir, RoseiresToAbuNaama_catchment], + USSennar_irr_system, + float("inf"), + ) + + SukiToSennar_catchment = Catchment( + "SukiToSennar_catchment", np.loadtxt(data_directory / "catchments" / "InflowSukiToSennar.txt") + ) + + # TODO: add catchment 3 inflow to sources of Sennar (inflow with destination USSennar) + Sennar_flow = Flow("sennar_flow", [USSennar_irr_system, SukiToSennar_catchment], Sennar_reservoir, float("inf")) + + Gezira_received_flow = Flow("gezira_received_flow", [Sennar_reservoir], Gezira_irr_system, float("inf")) + + Dinder_catchment = Catchment("dinder_catchment", np.loadtxt(data_directory / "catchments" / "InflowDinder.txt")) + + Rahad_catchment = Catchment("rahad_catchment", np.loadtxt(data_directory / "catchments" / "InflowRahad.txt")) + + downstream_Sennar_received_flow = Flow( + "downstream_sennar_received_flow", + [Gezira_irr_system, Dinder_catchment, Rahad_catchment], + DSSennar_irr_system, + float("inf"), + ) + WhiteNile_catchment = Catchment( + "whitenile_catchment", + np.loadtxt(data_directory / "catchments" / "InflowWhiteNile.txt"), + ) + Taminiat_received_flow = Flow( + "taminiat_received_flow", + [DSSennar_irr_system, WhiteNile_catchment], + Tamaniat_irr_system, + float("inf"), + ) + + Atbara_catchment = Catchment("atbara_catchment", np.loadtxt(data_directory / "catchments" / "InflowAtbara.txt")) + + # TODO: change Hassanab received flow to depend on leftover flow from Taminiat in previous month (see A.2.8) + Hassanab_received_flow = Flow( + "hassanab_received_flow", + [Tamaniat_irr_system, Atbara_catchment], + Hassanab_irr_system, + float("inf"), + delay=1, + default_outflow=934.2, + ) + HAD_flow = Flow("had_flow", [Hassanab_irr_system], HAD_reservoir, float("inf")) + Egypt_flow = Flow("egypt_flow", [HAD_reservoir], Egypt_irr_system, float("inf")) + # Create water management system. Add Facilities in the topological order (in the list). + # Egypt deficit reward goes negative when there is a deficit. Otherwise is 0. + water_management_system = WaterManagementSystem( + water_systems=[ + GERD_inflow, + GERD_reservoir, + Power_plant_flow, + GERD_power_plant, + GerdToRoseires_catchment, + Roseires_flow, + Roseires_reservoir, + RoseiresToAbuNaama_catchment, + upstream_Sennar_received_flow, + USSennar_irr_system, + SukiToSennar_catchment, + Sennar_flow, + Sennar_reservoir, + Gezira_received_flow, + Gezira_irr_system, + Dinder_catchment, + Rahad_catchment, + downstream_Sennar_received_flow, + DSSennar_irr_system, + WhiteNile_catchment, + Taminiat_received_flow, + Tamaniat_irr_system, + Atbara_catchment, + Hassanab_received_flow, + Hassanab_irr_system, + HAD_flow, + HAD_reservoir, + Egypt_flow, + Egypt_irr_system, + ], + rewards={ + "ethiopia_power": 0, + "sudan_deficit_minimised": 0, + "egypt_deficit_minimised": 0, + "HAD_minimum_water_level": 0, + }, + start_date=datetime(2025, 1, 1), + timestep_size=relativedelta(months=1), + seed=42 + ,add_timestamp='m', + custom_obj=custom_obj + + ) + + water_management_system = ReshapeArrayAction(water_management_system) + water_management_system = TimeLimit(water_management_system, max_episode_steps=240) + + return water_management_system diff --git a/morl4water/examples/omo_river_simulation.py b/morl4water/examples/omo_river_simulation.py new file mode 100644 index 0000000000000000000000000000000000000000..b464bfc0f46338b56b78abffb72af2899b2f1d75 --- /dev/null +++ b/morl4water/examples/omo_river_simulation.py @@ -0,0 +1,194 @@ +import numpy as np +from pathlib import Path +from gymnasium.spaces import Box +from gymnasium.wrappers import TimeLimit +from morl4water.core.envs.water_management_system import WaterManagementSystem +from morl4water.core.models import Reservoir +from morl4water.core.models import Weir +from morl4water.core.models import Flow, Inflow +from morl4water.core.models import Objective +from morl4water.core.models import PowerPlant +from morl4water.core.models import IrrigationDistrict +from morl4water.core.models import Catchment +from morl4water.core.wrappers.transform_action import ReshapeArrayAction +from datetime import datetime +from dateutil.relativedelta import relativedelta +from gymnasium.envs.registration import register + +from importlib.resources import files + +data_directory = files("morl4water.examples.data.omo_river") + + +#TODO translate all flows and nodes: + +#reservoirs: Gibe_III_reservoir, Koysha_reservoir +#Power plants: Gibe_III_power_plant, Koysha_power_plant +#weir: Kuraz Headworks +#Inflow: Flow A, Flow B, Flow C +#Flow: Gibe_III_reservoir_to_power_plant, Koysha_reservoir_to_power_plant, Gibe_III_Release, Koysha_Release, {Main_Channel, Canals_to_Kuraz}, +#Irrigation: Omorate, Canals to Kuraz Sugar Plantations + + + +def create_omo_river_env(custom_obj = None, render_mode=None) -> WaterManagementSystem: + + + #Gibe_III + GIBE_III_reservoir = Reservoir( + "GIBE_III", + max_capacity=11750000000.0, #m^3 11750000000.0 + max_action=[1064], #From Yugdeep it is equal to turbine_max_flow_rate (implemented in scaling actions back after rbf network) + integration_timestep_size=relativedelta(minutes=720), #integration timestep in Omo is 12 hours () + objective_function=Objective.no_objective, + stored_water=11750000000.0/2, #initial state 11750000000.0 + evap_rates=np.loadtxt(data_directory / "reservoirs" / "evap_GIBE_III.txt"), # cm/month + evap_rates_timestep_size=relativedelta(months=1), # TODO How does it work again? + storage_to_minmax_rel=np.loadtxt(data_directory / "reservoirs" / "store_min_max_release_GIBE_III.txt"),#m^3/s #Yugdeep does not change the max/min actions based on storage. The file shows contant min and max value + storage_to_level_rel=np.loadtxt(data_directory / "reservoirs" / "store_level_rel_GIBE_III.txt"), #data for interpolating from storage to height + storage_to_surface_rel=np.loadtxt(data_directory / "reservoirs" / "store_sur_rel_GIBE_III.txt"), #data for interpolating from storage to surface + ) + + GIBE_III_power_plant = PowerPlant( + "GIBE_power_plant", + Objective.scalar_identity(1), + "hydro_power_GIBE_and_Koysha", + efficiency=0.9, + min_turbine_flow=0, + max_turbine_flow=1064, + head_start_level=9, #level of the turbine needed for power calc + max_capacity=1870, # maximal capacity of power production + reservoir=GIBE_III_reservoir, + normalize_objective= 1391280 * 2 #TODO #the max amount of electricity produced possible in one month based on the max capacity + ) + #Koysha + KOYSHA_reservoir = Reservoir( + "KOYSHA", + max_capacity=6000000000.0, #m^3 + max_action=[1440], #From Yugdeep it is equal to turbine_max_flow_rate (implemented in scaling actions back) + integration_timestep_size=relativedelta(minutes=720), #integration timestep in Omo is 12 hours + objective_function=Objective.no_objective, + stored_water=6000000000.0/2, #initial state + evap_rates=np.loadtxt(data_directory / "reservoirs" / "evap_KOYSHA.txt"), # cm/month + evap_rates_timestep_size=relativedelta(months=1), + storage_to_minmax_rel=np.loadtxt(data_directory / "reservoirs" / "store_min_max_release_KOYSHA.txt"), + storage_to_level_rel=np.loadtxt(data_directory / "reservoirs" / "store_level_rel_KOYSHA.txt"), #data for interpolating from storage to height + storage_to_surface_rel=np.loadtxt(data_directory / "reservoirs" / "store_sur_rel_KOYSHA.txt") #data for interpolating from storage to surface + ) + + KOYSHA_power_plant = PowerPlant( + "KOYSHA_power_plant", + Objective.scalar_identity(1), + "hydro_power_GIBE_and_Koysha", + efficiency=0.9, + min_turbine_flow=0, + max_turbine_flow=1440.0, + head_start_level=8.5, #level of the turbine needed for power calc + max_capacity=2160.0, # maximal capacity of power production + reservoir=GIBE_III_reservoir, + normalize_objective= 1607040.0 * 2 #TODO #the max amount of electricity produced possible in one month based on the max capacity + ) + + #IRRIGATION DISTRICTS + Canals_to_Kuraz_Sugar_Plantations = IrrigationDistrict( + "Canals_to_Kuraz_Sugar_Plantations_irr", + np.loadtxt(data_directory / "irrigation" / "irr_demand_Kuraz.txt"), #TODO what is the unit here? + Objective.deficit_minimised, + "Kuraz_deficit_minimised", + normalize_objective=105.45 #simply the highest monthly demand in a year + ) + + Omorate = IrrigationDistrict( + "Omorate_irr", + np.loadtxt(data_directory / "irrigation" / "irr_demand_Omorate.txt"), + Objective.deficit_minimised, + "Omorate_deficit_minimised", + normalize_objective=522.68 #simply the highest monthly demand in a year + ) + + # -------------------------------- Testing ------------------------------------------------------- + + #KURAZ WEIR + KURAZ_Headworks_weir = Weir( + "KURAZ", + max_capacity= 1440, #m^3 used for termination so its fine / observation space is given [0, 1] by default/ TODO but max capacity is used for space normalisation / Thus, Use max rate of the incoming water, for example Koysha max release rate? + max_action=[1440], #As a max action this should be the release to one of the destinations + integration_timestep_size=relativedelta(minutes=720), #integration timestep in Omo is 12 hours + objective_function=Objective.no_objective, + stored_water=0.0 #initial state - should be default inflow to the weir + ) + + #INFLOWS + Flow_A_inflow = Inflow( + "Flow_A_inflow", + GIBE_III_reservoir, + float("inf"), + np.loadtxt(data_directory / "catchments" / "Flow_A_inflow.txt") # m^3/s + ) + + Flow_B_inflow = Inflow( + "Flow_B_inflow", + KOYSHA_reservoir, + float("inf"), + np.loadtxt(data_directory / "catchments" / "Flow_B_inflow.txt") + ) + + Flow_C_inflow = Inflow( + "Flow_C_inflow", + Omorate, + float("inf"), + np.loadtxt(data_directory / "catchments" / "Flow_C_inflow.txt") + ) + #FLOWS + + GIBE_III_to_plant_flow = Flow("GIBE_III_to_plant_flow", [GIBE_III_reservoir], GIBE_III_power_plant, float("inf")) + + GIBE_III_Release_flow = Flow("GIBE_III_Release_flow", [GIBE_III_power_plant], KOYSHA_reservoir, float("inf")) + + KOYSHA_to_plant_flow = Flow("KOYSHA_to_plant_flow", [KOYSHA_reservoir], KOYSHA_power_plant, float("inf")) + + KOYSHA_Release_flow = Flow("KOYSHA_Release_flow", [KOYSHA_power_plant], KURAZ_Headworks_weir, float("inf")) + + #WEIR object - the values to destinations an be anything because thery are overwritten in the class by the Agent's Action + KURAZ_Headworks_Weir_Release_flow = Flow("KURAZ_Headworks_Weir_Release_flow", [KURAZ_Headworks_weir], + destinations={Canals_to_Kuraz_Sugar_Plantations: "Agent's Action", Omorate: "Agent's Action"}, + max_capacity = float("inf")) + + + # Create water management system. Add Facilities in the topological order (in the list). + # deficit reward goes negative when there is a deficit. Otherwise is 0. + water_management_system = WaterManagementSystem( + water_systems=[ + Flow_A_inflow, + GIBE_III_reservoir, + GIBE_III_to_plant_flow, + GIBE_III_power_plant, + GIBE_III_Release_flow, + Flow_B_inflow, + KOYSHA_reservoir, + KOYSHA_to_plant_flow, + KOYSHA_power_plant, + KOYSHA_Release_flow, + KURAZ_Headworks_weir, + KURAZ_Headworks_Weir_Release_flow, + Flow_C_inflow, + Canals_to_Kuraz_Sugar_Plantations, + Omorate, + ], + rewards={ + "hydro_power_GIBE_and_Koysha": 0, + "Kuraz_deficit_minimised": 0, + "Omorate_deficit_minimised": 0, + }, + start_date=datetime(2029, 1, 1), + timestep_size=relativedelta(months=1), + seed=42 + ,add_timestamp='m', #adds month as a percentage (x/12) to observation space + custom_obj=custom_obj + + ) + + water_management_system = ReshapeArrayAction(water_management_system) + water_management_system = TimeLimit(water_management_system, max_episode_steps=144) #normally 144 for 12 years + + return water_management_system diff --git a/morl4water/examples/susquehanna_river_simulation.py b/morl4water/examples/susquehanna_river_simulation.py new file mode 100644 index 0000000000000000000000000000000000000000..c387f288435c74fd730f22bfc73f122fb6572ffc --- /dev/null +++ b/morl4water/examples/susquehanna_river_simulation.py @@ -0,0 +1,532 @@ +import numpy as np +from pathlib import Path +from gymnasium.spaces import Box +from gymnasium.wrappers.time_limit import TimeLimit +from datetime import datetime +from dateutil.relativedelta import relativedelta +from morl4water.core.envs.water_management_system import WaterManagementSystem +from morl4water.core.models import Reservoir +from morl4water.core.models import ReservoirWithPump +from morl4water.core.models import Flow, Inflow +from morl4water.core.models import Objective +from morl4water.core.models import PowerPlant +from morl4water.core.models import IrrigationDistrict +from morl4water.core.wrappers.transform_action import ReshapeArrayAction +from morl4water.core.models.facility import Facility, ControlledFacility +import time +from gymnasium.envs.registration import register +from typing import Any, Union, Optional +from gymnasium.core import ObsType, RenderFrame +from importlib.resources import files + +data_directory = files("morl4water.examples.data.susquehanna_river") + + + + +# Custom rules which define how the pump works, so how much water si pumped and released from the pump to the reservoir. +#Class reservoiwWithPump takes this function as a requred argument +def muddyrun_pumpturb_( + day_of_the_week, hour, level_reservoir = 0.0, + level_pump = 0.0, + storage_reservoir = 0.0, + storage_pump = 0.0): + # Determines the pumping and turbine release volumes in a day based + # on the hour and day of week for muddy run + QP = 24800 # cfs + QT = 32000 # cfs + + # active storage = sMR - deadStorage + qM = ( + storage_pump - 994779720.0 + ) / 3600 + qp = 0.0 + qt = 0.0 + if day_of_the_week == 6: # sunday + if hour < 5 or hour >= 22: + qp = QP + elif 0 <= day_of_the_week <= 3: # monday to thursday + if hour <= 6 or hour >= 21: + qp = QP + if (7 <= hour <= 11) or (17 <= hour <= 20): + qt = min(QT, qM) + elif day_of_the_week == 4: # friday + if (7 <= hour <= 11) or (17 <= hour <= 20): + qt = min(QT, qM) + elif day_of_the_week == 5: # saturday + if hour <= 6 or hour >= 22: + qp = QP + # water pumping stops to Muddy Run beyond this point. + # However, according to the conowingo authorities 800 cfs will be + # released as emergency credits in order to keep the facilities from + # running + # Q: The level in Conowingo impacts the pumping in Muddy Run. How? + if level_reservoir < 104.7: # if True cavitation problems in pumping + qp = 0.0 + + if level_pump < 470.0: + qt = 0.0 + return qp, qt # pumping, Turbine release + + +class WaterManagementSystemWithWaterLevels(WaterManagementSystem): + def __init__(self, *args, **kwargs): + # Call the parent class's __init__ method to inherit its initialization + super().__init__(*args, **kwargs) + + # Initialize the max_capacity_level attribute + self.max_capacity_level = self.water_systems[2].storage_to_level(self.water_systems[2].max_capacity) + + #we have to overwrite reset method as susquehanna simulation takes water levels and not storage volume as observation space + def reset(self, seed: Optional[int] = None, options: Optional[dict] = None) -> tuple[ObsType, dict[str, Any]]: + # We need the following line to seed self.np_random. + super().reset(seed=seed) + self.current_date = self.start_date + self.timestep = 0 + + self.observation, _ = self._determine_observation() + #We add this recalculation from storage to levels + observation = [self.water_systems[2].storage_to_level(self.observation[0])/self.max_capacity_level] + observation.append(0.0) + # Reset rewards + for key in self.rewards.keys(): + self.rewards[key] = 0 + + for water_system in self.water_systems: + water_system.current_date = self.start_date + water_system.reset() + return np.array(observation).flatten(), self._determine_info() + + #We overwrite the step method + def step(self, action: np.array) -> tuple[np.array, np.array, bool, bool, dict]: + final_reward = {} + + # Reset rewards + for key in self.rewards.keys(): + final_reward[key] = 0 + + final_observation = {} + final_terminated = False + final_truncated = False + final_info = {"date": self.current_date} + + for water_system in self.water_systems: + water_system.current_date = self.current_date + + if isinstance(water_system, ControlledFacility): + observation, reward, terminated, truncated, info = water_system.step(action[water_system.name]) + + elif isinstance(water_system, Facility) or isinstance(water_system, Flow): + observation, reward, terminated, truncated, info = water_system.step() + else: + raise ValueError() + + # Set observation for a Controlled Facility. + if isinstance(water_system, ControlledFacility): + final_observation[water_system.name] = observation + + # Add reward to the objective assigned to this Facility (unless it is a Flow). + if isinstance(water_system, Facility) or isinstance(water_system, ControlledFacility): + if water_system.objective_name: + final_reward[water_system.objective_name] += reward + + # Store additional information + final_info[water_system.name] = info + + + # Determine whether program should stop + final_terminated = final_terminated or terminated + final_truncated = final_truncated or truncated or self._is_truncated() + + + self.timestep += 1 + self.current_date += self.timestep_size + + #check if only a subset of rewards to return + if self.custom_obj is not None: + final_reward = [final_reward[key] for key in self.custom_obj] + else: + final_reward = list(final_reward.values()) + + #We change the final observation as we model the problem with water levels and not the storage volume as is by default + final_observations = [final_info['Conowingo']['current_level']/self.max_capacity_level] + if self.add_timestamp=='m': + final_observations.append(final_info['date'].month/12) + elif self.add_timestamp=='h': + final_observations.append(final_info['date'].hour/24) + + + + return ( + np.array(final_observations).flatten(), + np.array(final_reward).flatten(), + final_terminated, + final_truncated, + final_info + ) + + +def create_susquehanna_river_env(custom_obj = None, render_mode=None) -> WaterManagementSystemWithWaterLevels: + + + class ReservoirwithPumpDateDependendObjetive(ReservoirWithPump): + + + + def determine_reward(self) -> float: + is_weekend = self.current_date.weekday() < 5 + is_summer = 5 < self.current_date.month < 9 + summer_weekend = is_weekend and is_summer + return self.objective_function(summer_weekend, self.storage_to_level(self.stored_water)) + + + + def muddyrun_pumpturb(self, + day_of_the_week, hour, level_reservoir = 0.0, + level_pump = 0.0, + storage_reservoir = 0.0, + storage_pump = 0.0): + # Determines the pumping and turbine release volumes in a day based + # on the hour and day of week for muddy run + QP = 24800 # cfs + QT = 32000 # cfs + + # active storage = sMR - deadStorage + qM = ( + storage_pump - 994779720.0 + ) / 3600 + qp = 0.0 + qt = 0.0 + if day_of_the_week == 6: # sunday + if hour < 5 or hour >= 22: + qp = QP + elif 0 <= day_of_the_week <= 3: # monday to thursday + if hour <= 6 or hour >= 21: + qp = QP + if (7 <= hour <= 11) or (17 <= hour <= 20): + qt = min(QT, qM) + elif day_of_the_week == 4: # friday + if (7 <= hour <= 11) or (17 <= hour <= 20): + qt = min(QT, qM) + elif day_of_the_week == 5: # saturday + if hour <= 6 or hour >= 22: + qp = QP + # water pumping stops to Muddy Run beyond this point. + # However, according to the conowingo authorities 800 cfs will be + # released as emergency credits in order to keep the facilities from + # running + if level_reservoir < 104.7: # if True cavitation problems in pumping + qp = 0.0 + + if level_pump < 470.0: + qt = 0.0 + return qp, qt # pumping, Turbine release + + + #predifined release constraints, depending on the days of the year, different for each release as it affects differect capacities (baltimore, app, chester, downstream) + def actual_release(self, actions, level_Co, day_of_year): + # Check if it doesn't exceed the spillway capacity + Tcap = 85412 # total turbine capacity (cfs) + # maxSpill = 1242857.0 # total spillway combined (cfs) + w_atomic = np.loadtxt(data_directory / "reservoirs" / "wAtomic.txt") + w_baltimore = np.loadtxt(data_directory / "reservoirs" / "wBaltimore.txt") + w_chester = np.loadtxt(data_directory / "reservoirs" / "wChester.txt") + spillways = np.loadtxt(data_directory / "reservoirs" / "spillways_Conowingo.txt") + # minimum discharge values at APP, Balitomore, Chester and downstream + qm_A = 0.0 + qm_B = 0.0 + qm_C = 0.0 + qm_D = 0.0 + + # maximum discharge values. The max discharge can be as much as the + # demand in that area + qM_A = w_atomic[day_of_year] + qM_B = w_baltimore[day_of_year] + qM_C = w_chester[day_of_year] + qM_D = Tcap + + # reservoir release constraints (minimum level app) + if level_Co <= 98.5: + qM_A = 0.0 + else: + qM_A = w_atomic[day_of_year] + + if level_Co <= 90.8: #minumum level baltimore + qM_B = 0.0 + else: + qM_B = w_baltimore[day_of_year] + if level_Co <= 99.8: #minimum level chester (ft of water) + qM_C = 0.0 + else: + qM_C = w_chester[day_of_year] + + if level_Co > 110.2: # spillways activated + qM_D = ( + self.modified_interp(level_Co, spillways[0], spillways[1]) + + Tcap + ) # Turbine capacity + spillways + qm_D = ( + self.modified_interp(level_Co, spillways[0], spillways[1]) + + Tcap + ) + + # different from flood model + if level_Co < 105.5: + qM_D = 0.0 + elif level_Co < 103.5: + qM_A = 0.0 + elif level_Co < 100.5: + qM_C = 0.0 + elif level_Co < 91.5: + qM_B = 0.0 + + # actual release + rr = [] + rr.append(min(qM_A, max(qm_A, actions[0]))) + rr.append(min(qM_B, max(qm_B, actions[1]))) + rr.append(min(qM_C, max(qm_C, actions[2]))) + rr.append(min(qM_D, max(qm_D, actions[3]))) + return np.array(rr) + + + def determine_outflow(self, actions: np.array) -> list[float]: + + + current_storage = self.storage_vector[-1] + current_storage_pump = self.storage_pump_vector[-1] + + #check if we are releasing to one destination or more + if self.should_split_release == True: + #if it's more destinations, we have to create a list for sub-releases during the integration loop + sub_releases = [] + actions = np.multiply(actions, self.max_action) + else: + sub_releases = np.empty(0, dtype=np.float64) + actions = actions*self.max_action + + final_date = self.current_date + self.timestep_size + timestep_seconds = (final_date + self.evap_rates_timestep - final_date).total_seconds() + evaporatio_rate_per_second = self.evap_rates[self.determine_time_idx()] / (timestep_seconds) + evaporatio_rate_per_second_pump = self.evap_rates_pump[self.determine_time_idx()] / (timestep_seconds) + + while self.current_date < final_date: + next_date = min(final_date, self.current_date + self.integration_timestep_size) + integration_time_seconds = (next_date - self.current_date).total_seconds() + + #pumping/release of the pump + + pumping, release_pump = self.pumping_rules(day_of_the_week = self.current_date.weekday(), + hour = self.current_date.hour, + level_reservoir = self.storage_to_level(current_storage), + level_pump = self.storage_to_level_pump(current_storage_pump), + storage_reservoir = current_storage, + storage_pump = current_storage_pump) + + + surface = self.storage_to_surface(current_storage) + surface_pump = self.storage_to_surface_pump(current_storage_pump) + + evaporation = surface * evaporatio_rate_per_second + evaporation_pump = surface_pump * evaporatio_rate_per_second_pump + + current_storage_pump = current_storage_pump + (self.inflows_pump[self.timestep] + pumping - release_pump - evaporation_pump) * integration_time_seconds + day_of_year = self.current_date.timetuple().tm_yday - 1 #to read from a np array indexed at 1 + release_per_second = self.actual_release(actions, self.storage_to_level(current_storage), day_of_year) + + if self.should_split_release == True: + sub_releases.append(release_per_second) + else: + sub_releases = np.append(sub_releases, release_per_second) + + total_addition = (self.get_inflow(self.timestep) + release_pump) + + current_storage = current_storage + integration_time_seconds*(total_addition + -np.sum(release_per_second) + -evaporation + -pumping + -self.spillage) + + self.current_date = next_date + + + + # Update the amount of water in the Reservoir + self.storage_vector.append(current_storage) + self.stored_water = current_storage + + # Update water in the pump + self.storage_pump_vector.append(current_storage_pump) + self.stored_pump = current_storage_pump + + + # Record level based on storage for time t + self.level_vector.append(self.storage_to_level(current_storage)) + + # Calculate the ouflow of water depending if the releases are split (an array with lists of releases to different destinations from one reservoir or an array with scalar values) + if self.should_split_release == True: + sub_releases = np.array(sub_releases) + average_release = np.mean(sub_releases, dtype=np.float64, axis = 0) + else: + average_release = np.mean(sub_releases, dtype=np.float64) + + self.release_vector.append(average_release) + + total_action = np.sum(average_release) + # Split release for different destinations - calculate ratio of the releases to different destinations from the total action + if self.should_split_release and total_action != 0: + self.split_release = [(action / total_action) for action in average_release] + average_release = total_action + elif self.should_split_release and total_action == 0: + self.split_release = [(action) for action in average_release] + average_release = total_action + + + + return average_release + + + + class PowerPlantSequentialObjetive(PowerPlant): + def determine_reward(self) -> float: + return self.objective_function(self.timestep, self.determine_production_detailed()) + + Conowingo_reservoir = ReservoirwithPumpDateDependendObjetive( + name="Conowingo", + integration_timestep_size=relativedelta(hours=1), + objective_function=Objective.is_greater_than_minimum_with_condition(106.5), + objective_name="recreation", + stored_water_reservoir=2641905256.0, + evap_rates=np.loadtxt(data_directory / "reservoirs" / "evap_Conowingo.txt"), + evap_rates_timestep_size=relativedelta(days=1), + storage_to_minmax_rel=np.loadtxt(data_directory / "reservoirs" / "store_min_max_release_Conowingo.txt"), + storage_to_level_rel=np.loadtxt(data_directory / "reservoirs" / "store_level_rel_Conowingo.txt"), + storage_to_surface_rel=np.loadtxt(data_directory / "reservoirs" / "store_sur_rel_Conowingo.txt"), + pumping_rules=muddyrun_pumpturb_, + stored_water_pump = 1931101920.0, + evap_rates_pump = np.loadtxt(data_directory / "reservoirs" / "evap_Muddy.txt"), + storage_to_surface_rel_pump = np.loadtxt(data_directory / "reservoirs" / "storage_surface_rel_MR.txt"), + storage_to_level_rel_pump = np.loadtxt(data_directory / "reservoirs" / "storage_level_rel_MR.txt"), + inflows_pump = np.loadtxt(data_directory / "inflows" / "InflowMuddy.txt"), + spillage = 800, + max_capacity=6962264495.999999, + max_action=[41.302169, 464.16667, 54.748458, 85412] + ) + + Power_plant = PowerPlantSequentialObjetive( + name="Power_plant", + objective_function=Objective.sequential_scalar(np.loadtxt(data_directory / "reservoirs" / "avg_energy_prices.txt")), + objective_name="energy_revenue", + normalize_objective=198445191.2586579, + efficiency=0.79, + min_turbine_flow=210.0, #this assumes there is only one turbine! + max_turbine_flow=85412.0, #this assumes there is only one turbine! + head_start_level=0, + max_capacity=float("inf"), + reservoir=Conowingo_reservoir, + turbines = np.loadtxt(data_directory / "reservoirs" / "turbines_Conowingo2.txt"), + n_turbines = 13, + tailwater = np.loadtxt(data_directory / "reservoirs" / "tailwater.txt") + ) + + Atomic_system = IrrigationDistrict( + name="Atomic", + all_demand=np.loadtxt(data_directory / "demands" / "Atomic.txt"), + objective_function=Objective.supply_ratio_maximised, + objective_name="water_supply_Atomic", + ) + + Baltimore_system = IrrigationDistrict( + name="Baltimore", + all_demand=np.loadtxt(data_directory / "demands" / "Baltimore.txt"), + objective_function=Objective.supply_ratio_maximised, + objective_name="water_supply_Baltimore", + ) + + Chester_system = IrrigationDistrict( + name="Chester", + all_demand=np.loadtxt(data_directory / "demands" / "Chester.txt"), + objective_function=Objective.supply_ratio_maximised, + objective_name="water_supply_Chester", + ) + + Downstream_system = IrrigationDistrict( + name="Downstream", + all_demand=np.loadtxt(data_directory / "demands" / "Downstream.txt"), + objective_function=Objective.deficit_squared_ratio_minimised, + objective_name="enviromental_shortage", + ) + + Conowingo_inflow_main = Inflow( + name="conowingo_inflow_main", + destinations=Conowingo_reservoir, + max_capacity=float("inf"), + all_inflow=np.loadtxt(data_directory / "inflows" / "InflowConowingoMain.txt"), + ) + + Conowingo_inflow_lateral = Inflow( + name="conowingo_inflow_lateral", + destinations=Conowingo_reservoir, + max_capacity=float("inf"), + all_inflow=np.loadtxt(data_directory / "inflows" / "InflowConowingoLateral.txt"), + ) + + Conowingo_outflow = Flow( + name="conowingo_outflow", + sources=[Conowingo_reservoir], + destinations={Atomic_system: 0.25, Baltimore_system: 0.25, Chester_system: 0.25, Power_plant: 0.25}, + max_capacity=float("inf"), + ) + + Donwstream_inflow = Flow( + name="donwstream_inflow", + sources=[Power_plant], + destinations=Downstream_system, + max_capacity=float("inf"), + ) + + # Muddy_reservoir = Reservoir( + # name="Muddy", + # observation_space=Box(low=0, high=2471202360), + # action_space=Box(low=0, high=32000), + # integration_timestep_size=relativedelta(hours=1), + # objective_function=Objective.no_objective, + # objective_name="", + # stored_water=0, + # evap_rates=np.loadtxt(data_directory / "reservoirs" / "evap_Muddy.txt"), + # storage_to_minmax_rel=np.loadtxt(data_directory / "reservoirs" / "store_min_max_release_Muddy.txt"), + # storage_to_level_rel=np.loadtxt(data_directory / "reservoirs" / "store_level_rel_Muddy.txt"), + # storage_to_surface_rel=np.loadtxt(data_directory / "reservoirs" / "store_sur_rel_Muddy.txt"), + # ) + + water_management_system = WaterManagementSystemWithWaterLevels( + water_systems=[ + Conowingo_inflow_main, + Conowingo_inflow_lateral, + Conowingo_reservoir, + Conowingo_outflow, + Atomic_system, + Baltimore_system, + Chester_system, + Power_plant, + Donwstream_inflow, + Downstream_system, + ], + rewards={ + "recreation": 0, + "energy_revenue": 0, + "water_supply_Baltimore": 0, + "water_supply_Atomic": 0, + "water_supply_Chester": 0, + "enviromental_shortage": 0, + }, + start_date=datetime(2021, 1, 1), + timestep_size=relativedelta(hours=4), + seed=42, + add_timestamp='h', + custom_obj = custom_obj + ) + + water_management_system = ReshapeArrayAction(water_management_system) + water_management_system = TimeLimit(water_management_system, max_episode_steps=2190) + + return water_management_system diff --git a/pyproject.toml b/pyproject.toml new file mode 100644 index 0000000000000000000000000000000000000000..9ee20969beef45a4da0c12ecf2a278231a80eb84 --- /dev/null +++ b/pyproject.toml @@ -0,0 +1,58 @@ +[build-system] +requires = ["setuptools>=61.0", "wheel"] +build-backend = "setuptools.build_meta" + +[project] +name = "morl4water" +version = "0.1.3" +description = "Multi-Objective Reinforcement Learning environments of water management problems" +readme = "README.md" +requires-python = ">=3.11" +license = { text = "MIT" } + +authors = [ + { name = "Zuzanna Osika", email = "z.osika@tudelft.nl" } +] + +dependencies = [ + "mo-gymnasium==1.1.0", + "gymnasium", + "h5py", + "opencv-python==4.8.0.76", + "numpy==1.26.4", + "dill==0.3.5.1", + "pymoo==0.6.1.1", + "pytest==7.4.0", + "numba" +] + +classifiers = [ + "Programming Language :: Python :: 3", + "License :: OSI Approved :: MIT License" +] + +[project.urls] +Homepage = "https://osikazuzanna.github.io/morl4water" + + +# Auto-include all sub-packages +[tool.setuptools.packages.find] +where = ["."] +include = ["morl4water*"] + +# Ensure data files are included +[tool.setuptools] +include-package-data = true + +[tool.setuptools.package-data] +"morl4water.examples.data.nile_river.catchments" = ["*.txt"] +"morl4water.examples.data.nile_river.irrigation" = ["*.txt"] +"morl4water.examples.data.nile_river.reservoirs" = ["*.txt"] + +"morl4water.examples.data.omo_river.catchments" = ["*.txt"] +"morl4water.examples.data.omo_river.irrigation" = ["*.txt"] +"morl4water.examples.data.omo_river.reservoirs" = ["*.txt"] + +"morl4water.examples.data.susquehanna_river.demands" = ["*.txt"] +"morl4water.examples.data.susquehanna_river.inflows" = ["*.txt"] +"morl4water.examples.data.susquehanna_river.reservoirs" = ["*.txt"]