Energy Efficient Community: A Two-Stage Market Optimization Framework Incorporating P2p Trading, Market Dynamics and Uncertainties

This study integrates local market clearing-based P2P energy trading with day-ahead markets and real-time operations, creating a two-stage market optimization framework for a local energy community. The model aims to manage uncertainties arising from photovoltaic (PV) generation and load demand while optimizing community-wide energy procurement and trading decisions to lower costs. In Stage 1 (day-ahead optimization), the retailer procures power for the day ahead and makes spot market purchases, considering various scenarios of PV generation and load demand. Stage 2 (real-time optimization) enables P2P energy exchanges within the energy community and allows for power export to the wholesale market through the community manager. The results are analyzed to determine their effects on grid imports, battery charging and discharging, peak demand, and overall community costs. Findings indicate that P2P trading and coordinated market participation can lead to significant cost savings, particularly for prosumers with battery storage and PV facilities. This approach offers a robust solution for enhancing decentralized energy management and local energy trading within energy communities.