Abstract

The increasing penetration of small- or medium-sized distributed energy resources, such as PV panels, wind turbines, and batteries, is facilitating the emergence of a more consumer-centric electricity market. Meanwhile, with the increase of such distributed energy resources, traditional market design suffers more and more from the security and low-efficiency issues. Thus, toward the consumer-centric electricity market, it is important to design more flexible energy transaction mechanisms to meet the demand of the more consumer-centric energy distribution. In this paper, we design such an electricity market framework to enable all peers of the energy network to carry out energy transactions directly with others in a decentralized manner. Firstly, for the energy prosumer side, the ensemble learning algorithm is applied to forecast future energy production and consumption. Based on the forecasting result, a power flow optimization is designed to determine the optimal power scheduling of the power system including the P2P trading strategy. For the energy transaction, we apply the discrete double auction adapting McAfee's mechanism to achieve its peer-to-peer manner. We simulate a number of test cases with various renewable resources penetration levels to validate its viability using real-world data and compare our P2P market with the traditional centralized market.

@inproceedings{hang2020auction,
  title={Auction-based Peer-to-peer Energy Transaction Model with Prosumer-side Energy Scheduling},
  author={Hang, Gai and Gan, Xiaoying and Draz, Mahmoud},
  booktitle={2020 IEEE 11th International Symposium on Power Electronics for Distributed Generation Systems (PEDG)},
  pages={505--510},
  organization={IEEE}
}