Tagungsbeiträge

Auction-based Peer-to-peer Energy Transaction Model with Prosumer-side Energy Scheduling

AutorGai Hang, Mahmoud Draz, Gan Xiaoying
QuelleInternational Confernce on Smart Grid and Smart Cities (ICSGC) 
LinksUni-Bibliothek 

The increasing penetration of small-scale distributed energy resources, such as rooftop solar and behind-the-meter batteries, is opening the door for a more consumer-centric electricity market. At the same time, with the increase of 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 ensure the safe and efficient operation of energy distribution. In this paper, we design such an electricity market framework to support all agents of the energy sector to directly engage in energy transactions with others in a decentralized manner. Firstly, for the energy prosumer side, the ensemble learning algorithm is applied to forecast future energy demand and generation. Based on the energy forecast, 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.