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README.md

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 # SolarSys: Scalable Hierarchical Coordination for Distributed Solar Energy
+## Abstract
 
-SolarSys is a novel **Hierarchical Multi-Agent Reinforcement Learning (HRL)** system designed to manage energy storage and peer-to-peer (P2P) trading across large communities of solar-equipped residences. This repository contains the full source code for the SolarSys system, including the trained policies, the custom Gym environment, and the hierarchical diffusion model used for data generation.
+To address these limitations, we design SolarSys, a hierarchical coordination system for peer-to-peer energy trading in distributed
+solar and storage communities.
+SolarSys integrates local power sensing from smart meters and inverters with edge computation and distributed coordination to manage energy usage across large residential networks.
+
+The system is organized hierarchically to support decision making at both the household and cluster levels. 
+
+Each household node measures its generation, demand, and battery state, and makes local energy management decisions using a policy trained with Multi-Agent Proximal Policy Optimization to improve local solar usage and maintain cluster-level energy balance.
+
+Across clusters, SolarSys leverages a mean-field multi-agent reinforcement learning approach that updates high-level decisions using aggregated cluster conditions.
+
+This design allows clusters to adjust their decisions so the overall system remains consistent with practical grid constraints.
+
+In addition, we deploy SolarSys on a Raspberry Pi and find that the learned policies can run efficiently on low-power edge hardware.
+
+We evaluate SolarSys using real smart meter data from seven residential communities. 
+
+We find that SolarSys reduces the energy drawn from the grid by 27.48 ± 0.42\%, increases daytime solar utilization to 82.76 ± 5.11\%, and improves fairness to 0.773 (Jain’s Index).
+
+The results show that SolarSys enables efficient, fair, and scalable peer-to-peer energy trading in large-scale virtual power plant deployments.
 
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