Dynamic Participation in Local Energy Markets: An Optimization-Based Peer-to-Peer Marketplace

Abstract

The increasing penetration of photovoltaic (PV) generation at the distribution level requires coordinated local energy transaction mechanisms to maintain system reliability. While peer-to-peer (P2P) trading frameworks can enhance local renewable utilization, fully decentralized designs face challenges in scalability and coordination. This paper proposes a centralized, tariff-driven P2P market for a local PV energy community in which a retail electricity provider acts as aggregator. The market is formulated as a social welfare optimization problem integrating PV generation, demand, and grid exchanges, guided by exogenous time-varying tariffs. To ensure computational scalability, the problem is decomposed using the Alternating Direction Method of Multipliers (ADMM), separating prosumer scheduling from portfolio-level balancing. A case study based on a low-voltage network data shows that local P2P matching can increase PV self-consumption and reduce tariff-based operating cost for the analyzed horizon.