| import gradio as gr |
| import numpy as np |
| import pandas as pd |
| import matplotlib.pyplot as plt |
| import google.generativeai as genai |
|
|
| |
| |
| |
|
|
| def solar_power(capacity_kw): |
| irradiance = np.sin(np.linspace(0, np.pi, 24)) |
| irradiance[irradiance < 0] = 0 |
| return capacity_kw * irradiance |
|
|
|
|
| def wind_power(capacity_kw): |
| wind_speed = np.random.uniform(3, 10, 24) |
| power = capacity_kw * (wind_speed / 12) ** 3 |
| return power |
|
|
|
|
| def load_profile(homes): |
| night_load = homes * 0.3 |
| day_load = homes * 0.1 |
| load = [] |
|
|
| for h in range(24): |
| if 18 <= h or h <= 6: |
| load.append(night_load) |
| else: |
| load.append(day_load) |
|
|
| return np.array(load) |
|
|
|
|
| |
| |
| |
|
|
| def generate_microgrid(desc, api_key): |
|
|
| homes = 50 |
| solar_kw = 60 |
| wind_kw = 20 |
|
|
| solar = solar_power(solar_kw) |
| wind = wind_power(wind_kw) |
| load = load_profile(homes) |
|
|
| total_generation = solar + wind |
|
|
| df = pd.DataFrame({ |
| "Hour": range(24), |
| "Solar": solar, |
| "Wind": wind, |
| "Load": load, |
| "Generation": total_generation |
| }) |
|
|
| |
| plt.figure() |
| plt.plot(df["Hour"], df["Solar"]) |
| plt.plot(df["Hour"], df["Wind"]) |
| plt.plot(df["Hour"], df["Load"]) |
| plt.plot(df["Hour"], df["Generation"]) |
| plt.xlabel("Hour") |
| plt.ylabel("Power (kW)") |
| plt.title("24 Hour Microgrid Simulation") |
|
|
| chart_path = "simulation.png" |
| plt.savefig(chart_path) |
|
|
| |
| ai_text = "Demo Mode" |
|
|
| if api_key: |
| genai.configure(api_key=api_key) |
| model = genai.GenerativeModel("gemini-pro") |
|
|
| prompt = f""" |
| Analyze this rural energy system and give professional |
| engineering recommendations: |
| |
| {desc} |
| |
| Include optimization suggestions. |
| """ |
|
|
| response = model.generate_content(prompt) |
| ai_text = response.text |
|
|
| report = f""" |
| ✅ AI Microgrid Design Completed |
| |
| Solar Capacity: {solar_kw} kW |
| Wind Capacity: {wind_kw} kW |
| Battery Recommendation: 150 kWh |
| |
| Total Daily Energy Generated: |
| {round(total_generation.sum(),2)} kWh |
| |
| AI Engineering Insight: |
| {ai_text} |
| """ |
|
|
| return report, chart_path |
|
|
|
|
| |
| |
| |
|
|
| with gr.Blocks(theme=gr.themes.Soft()) as demo: |
|
|
| gr.Markdown(""" |
| # 🌱 GreenSolar AI Microgrid Designer |
| ### AI-Powered Solar + Wind Hybrid System for Rural Pakistan |
| """) |
|
|
| description = gr.Textbox( |
| label="Village Energy Description", |
| lines=6 |
| ) |
|
|
| api = gr.Textbox( |
| label="Google Gemini API Key", |
| type="password" |
| ) |
|
|
| output = gr.Textbox(label="Engineering Report", lines=12) |
| chart = gr.Image(label="24 Hour Simulation Dashboard") |
|
|
| btn = gr.Button("Generate AI Microgrid") |
|
|
| btn.click( |
| generate_microgrid, |
| inputs=[description, api], |
| outputs=[output, chart] |
| ) |
|
|
| demo.launch() |
