Discrimination-Based Double Auction for Maximizing Social Welfare in the Electricity and Heating Market Considering Privacy Preservation
Lu Wang, Wei Gu, Shuai Lu, Haifeng Qiu, and Zhi Wu

TL;DR
This paper introduces a privacy-preserving, discrimination-based double auction mechanism for electricity and heating markets that maximizes social welfare through Nash equilibrium analysis and distributed algorithms.
Contribution
It presents a novel auction mechanism with privacy preservation, proves Nash equilibrium properties, and develops a distributed algorithm for practical implementation.
Findings
Social welfare increased by 4-15% compared to other mechanisms.
The proposed distributed algorithm effectively reaches demand-supply balance.
Theoretical proof of Nash equilibrium existence and uniqueness.
Abstract
This paper proposes a doubled-sided auction mechanism with price discrimination for social welfare (SW) maximization in the electricity and heating market. In this mechanism, energy service providers (ESPs) submit offers and load aggregators (LAs) submit bids to an energy trading center (ETC) to maximize their utility; in turn, the selfless ETC as an auctioneer leverages dis-criminatory price weights to regulate the behaviors of ESPs and LAs, which combines the individual benefits of each stakeholder with the overall social welfare to achieve the global optimum. Nash games are employed to describe the interactions between players with the same market role. Theoretically, we first prove the existence and uniqueness of the Nash equilibrium; then, considering the requirement of game players to preserve privacy, a distributed algorithm based on the alternating direction method of…
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Taxonomy
TopicsSmart Grid Energy Management · Auction Theory and Applications · Electric Power System Optimization
