An Agent Based Model to Simulate Local Electricity Markets, LEM, and their Interaction with the Wholesale Market, WSM

Abstract

Local Electricity Markets (LEM) associated with Energy Communities and more specifically with Renewable Energy Communities, REC, are fostering new optimization models to enable the development of strategies regarding the increase of community energy savings and profits. In this scope, this paper presents an Agent-Based Model (ABM) as a decision tool to support energy transactions between the LEM and the Wholesale Market (WSM) on an hourly basis. The developed market environment was modelled as a Markov Decision Process (MDP). In this scope, an Agent Based Model using the Q-Learning mechanism was used to implement it and to simulate the local market model and its interaction with the WSM. The developed model was tested using an energy community that integrates a collective building with 15 apartments and PV generation. The paper describes and discusses the obtained market strategy and the profits that can be obtained by the Energy Community.