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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
