Autonomous Energy Trading for Community-Based Local Energy Market

Auteurs

Cao J., Ma A., Cortes P.R.

Référence

Proceedings - 2024 4th Power System and Green Energy Conference, PSGEC 2024, pp. 1083-1087, 2024

Description

Energy Communities (ECs) will play a crucial role in increasing the adoption of renewable energy. To enable efficient and cost-effective energy trading within the energy community framework, this paper proposes an autonomous energy trading platform for ECs to engage in the local energy market. The proposed two-layer market coordination mechanism consists of: 1) a local market coordinator, which will manage energy trading between energy communities and the wholesale electricity market to minimize costs and battery degradation; and 2) an energy community coordinator, which will facilitate autonomous energy trading within the local market by self-learning from historical data using Deep Reinforcement Learning (DRL). The effectiveness of this framework is validated using real-world data from the UK energy market.

Lien

doi:10.1109/PSGEC62376.2024.10721062