We propose two market designs for the optimal day-ahead scheduling of energy exchanges within renewable energy communities. The first one implements a cooperative demand side management scheme inside a community where members objectives are coupled through grid tariffs, whereas the second allows in addition the valuation of excess generation in the community and on the retail market. Both designs are formulated as centralized optimization problems first, and as non cooperative games then. In the latter case, the existence and efficiency of the corresponding (Generalized) Nash Equilibria are rigorously studied and proven, and distributed implementations of iterative solution algorithms for finding these equilibria are proposed, with proofs of convergence. The models are tested on a use-case made by 55 members with PV generation, storage and flexible appliances, and compared with a benchmark situation where members act individually (situation without community). We compute the global REC costs and individual bills, inefficiencies of the decentralized models compared to the centralized optima, as well as technical indices such as self-consumption ratio, self-sufficiency ratio, and peak-to-average ratio.

翻译：本文提出了两种面向可再生能源社区内日前能量交换优化的市场设计。第一种方案在社区内实施合作需求侧管理机制，其中成员目标通过电网电价耦合；第二种方案则额外允许评估社区内部及零售市场中的过剩发电价值。两种设计首先被表述为集中式优化问题，随后被建模为非合作博弈。针对后者，本文严谨研究并证明了相应（广义）纳什均衡的存在性与有效性，提出了用于求解这些均衡的迭代算法分布式实现方案，并给出了收敛性证明。模型基于包含55个拥有光伏发电、储能及灵活负荷成员的实际案例进行测试，并与成员独立行动（无社区情境）的基准情形进行对比。我们计算了全球可再生能源社区总成本、个体电费、分散式模型相较于集中式最优方案的低效性，以及自消费比、自足比和峰均比等技术指标。