Cost-Optimization for Win-Win P2P Energy Systems.

Attracted by a cheaper bill, more and more energy customers invest in local electricity generation and storage. Recent research advocates Peer-to-Peer (P2P) energy sharing as a way to make the most of the local energy resources, further reducing the bill of each participating end-user. However, optimizing the usage of the distributed resources is either directed to reduce costs for the customers (such as consumers and prosumers) or the grid company, and it is challenging to make them both win. We develop and analyze in this work a realistic model to implement P2P energy sharing systems that are attractive both to customers and to the grid companies. Considering that all actors are only benefits-driven, we provide mechanisms for achieving win-win P2P energy communities by developing adapted optimization procedures. Through an experimental study, we show that win-win configurations are reachable under a variety of possible scenarios in terms of distribution of energy resources. Our findings include precise figures following the current energy landscape and advocate that all actors can profit from more distributed renewable resources, making them a key driving force of tomorrow's energy systems.