Grid-friendly pricing mechanism for peer-to-peer energy sharing market diffusion in communities

Abstract

As a novel trading mode, the peer-to-peer (P2P) energy market cannot be accepted by the end-users immediately. There is an adoption process before all the energy prosumers participate in the P2P trading market. Therefore, we first employ a generalized Bass model to depict the P2P energy market diffusion process in the communities. Since the P2P market is still in the diffusion stage, we develop a hybrid P2P energy market consisting of traditional pool-based and P2P trading modes. Then, we establish the cost minimization models of energy prosumers, community managers, and system operators to analyze the market equilibrium in such a hybrid P2P energy market. The dynamic network usage costs are included in the system operator’s model to guarantee the market operation considering the heterogeneous prosumers. Finally, we propose a hybrid market-clearing method consisting of deep reinforcement learning and optimization algorithms. We model the generalized Bass model as an equivalent Markov process. The community manager and system operator can learn the near-optimal prices in their Markov decision processes with prosumers’ partial information. Numerical simulations demonstrate that the Markovian Bass model describes the P2P market adoption process precisely. The trading and network usage prices with and without considering the P2P energy market diffusion are compared and analyzed.