Bi-level optimization algorithm for trading quantity and surplus maximization in P2P electricity market
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Abstract
The increasing adoption of renewable energy and the evolution of energy markets have led to the need for innovative trading mechanisms, particularly in peer-to-peer (P2P) energy markets. This paper proposes a bi-level optimization algorithm for trading quantity and surplus maximization (BLO-TQSM) in P2P energy trading, incorporating a double-side carbon taxation scheme (DCTS). The BLO-TQSM algorithm is designed to optimize both the trading quantity and surplus by finding the best matching of participants in the market, while the DCTS mechanism integrates carbon tax considerations into the pricing of fossil and renewable energy sources. The shift factor, obtained by particle swarm optimization (PSO), is introduced to find the proposed bi-level maximization algorithm. The proposed method was tested in two scenarios: one without DCTS and one with DCTS. The results show that the algorithm significantly improves trading quantity and surplus in the P2P market compared to traditional power pool models. Moreover, the inclusion of DCTS further enhances the market's environmental sustainability by promoting the use of renewable energy and moving towards a carbon-neutral market.
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