Real-Time Bidding in a Walrasian Local Energy Market

Résumé fourni par la source

This paper presents a Local Energy Market (LEM) model based on Walrasian Auctions for near real-time energy trading among peers in an Energy Community. The market operates with minimal information exchange, where peers only indicate trade decisions and quantities. The auctioneer updates prices iteratively to balance supply and demand. Two core algorithms support the LEM: (1) the Auctioneer Price Decision Algorithm, which adjusts prices based on past imbalances, and (2) a real-time bidding optimization algorithm, which optimizes peers‘ energy dispatch and local energy trading decisions based on expected demand, generation, storage, and opportunity costs of external trading. This work details the design and implementation of the bidding optimization algorithm and evaluates its performance through simulations. The results compare the LEM to a centralized pool-based market and individual optimizations, assessing its efficiency and imbalance control. The findings support the development of innovative and decentralized energy markets and smart grid applications.

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