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：针对可再生能源社区内的最优日前能量交换调度，我们提出了两种市场设计。第一种方案在社区内实施合作型需求侧管理机制，其中成员的目标通过电网电价进行耦合；第二种方案则允许在社区内部及零售市场上对过剩发电量进行估值。两种设计首先被构建为集中式优化问题，随后转化为非合作博弈。在后一种情况下，我们严格研究并证明了相应（广义）纳什均衡的存在性与效率，提出了用于求解这些均衡的分布式迭代算法实现，并给出了收敛性证明。模型在包含55个成员（具有光伏发电、储能及柔性负荷）的用例场景中进行了测试，并与成员独立行动（无社区情境）的基准情形进行了比较。我们计算了全球可再生能源社区总成本及个体账单、分散式模型相较于集中式最优解的低效性，以及自消费比、自给率和峰均比等技术指标。