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Utilizing distributed renewable and energy storage resources via peer-to-peer (P2P) energy trading has long been touted as a solution to improve energy system’s resilience and sustainability. Consumers and prosumers (those who have energy generation resources), however, do not have expertise to engage in repeated P2P trading, and the zero-marginal costs of renewables present challenges in determining fair market prices. To address these issues, we propose a multi-agent reinforcement learning (MARL) framework to help automate consumers’ bidding and management of their solar PV and energy storage resources, under a specific P2P clearing mechanism that utilizes the so-called supply-demand ratio. In addition, we show how the MARL framework can integrate physical network constraints to realize decentralized voltage control, hence ensuring physical feasibility of the P2P energy trading and paving ways for real-world implementations. 

We study the market structure for emerging distribution-level energy markets with high renewable energy penetration. Renewable generation is known to be uncertain and has a close-to-zero marginal cost. In this paper, we use solar energy as an example of such zero-marginal-cost resources for our focused study. We first show that, under high penetration of solar generation, the classical real-time market mechanism can either exhibit significant price-volatility (when each firm is not allowed to vary the supply quantity), or induce price-fixing (when each firm is allowed to vary the supply quantity), the latter of which leads to extreme unfairness of surplus division. To overcome these issues, we propose a new rental-market mechanism that trades the usage-right of solar panels instead of real-time solar energy. We show that the rental market produces a stable and unique price (therefore eliminating price-volatility), maintains positive surplus for both consumers and firms (therefore eliminating price-fixing), and achieves the same social welfare as the traditional real-time market. A key insight is that rental markets turn uncertainty of renewable generation from a detrimental factor (that leads to price-volatility in real-time markets) to a beneficial factor (that increases demand elasticity and contributes to the desirable rental-market outcomes).