Chance-Constrained Peer-to-Peer Joint Energy and Reserve Market Considering Renewable Generation Uncertainty

• Published in: IEEE transactions on smart grid Vol. 12; no. 1; pp. 798 - 809
• Main Authors: Guo, Zhenwei, Pinson, Pierre, Chen, Shibo, Yang, Qinmin, Yang, Zaiyue
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01-01-2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: chance-constrained; consensus ADMM; Convex functions; Correlation; Distributed generation; Electricity consumption; Electricity supply industry; Energy management; Energy sources; Gaussian mixture model; Generators; Information management; joint energy and reserve market; Optimization; Peer to peer computing; Peer-to-peer market; Power system stability; Resource management; Uncertainty; uncertainty correlation; versatile distribution
• ISSN: 1949-3053; 1949-3061
• DOI: 10.1109/TSG.2020.3019603

Due to the fast development of distributed energy resources and demand-side response management, agents in electricity markets are becoming more proactive, which boosts the development of peer-to-peer (P2P) market mechanisms. However, to our knowledge, none of the existing works considers clearing both energy and reserve via a P2P market mechanism in order to compensate for the uncertainty originating from renewable generation and allocate the reserve cost induced by uncertainty fairly. In this article, a novel P2P joint energy and reserve market is proposed, where each agent can negotiate with neighboring agents to determine the quantities and prices of traded energy and reserve. We model the renewable generation uncertainty by versatile distribution and determine the required reserve based on a chance-constrained optimization approach. Then, a fully decentralized P2P market based on consensus alternating direction method of multipliers (ADMM) theory is proposed. In addition, to further lower the social cost, we exploit the correlation and complementarity among uncertainties and design a renewable community-based market, where all renewable agents share uncertainty information to community manager for calculating total required reserve. Finally, simulation results show the convergence performance, fairness and scalability of our market mechanism.