Day-Ahead Programming of Energy Communities Participating in Pay-as-Bid Service Markets (2311.12203v1)

Abstract: This paper proposes an optimal strategy for a Renewable Energy Community participating in the Italian pay-as-bid ancillary service market. The community is composed by a group of residential customers sharing a common facility equipped with a PV power plant and a battery energy storage system. This battery is employed to maximize the community cash flow obtained by the participation in the service market. A scenario-based optimization problem is defined to size the bids to be submitted to the market and to define the corresponding optimal battery energy exchange profile for the day ahead. The proposed optimization scheme is able to take in to account the probability of acceptance of the service market bids and the uncertainties on the forecasts of PV generation and energy demands. Results prove the effectiveness of the approach and the economic advantages on participating in the service market.