부산대학교 도서관

As China is gradually building a clean, low-carbon, safe and efficient energy system with renewable energy (RE) as the leading force, and accelerating the realization of the “ $30\cdot 60$ “ dual carbon goal. To give further play to the key role of the market in optimal resources, this paper proposes an optimization model of day-ahead electricity market-clearing optimization model considering medium and long-term contract electricity decomposition (MLCED) and RE. The MLCED result is introduced into the clearing model of day-ahead market as a constraint to ensure the fairness of bidding units dispatching and reduce risk. The paper analyzes the system uncertainty and adds wind power penetration into the spot electricity price simulation as an influencing factor. The fuzzy optimization method is used to convert multi-objective to balance the interests of different priorities, and a particle swarm optimization (PSO) algorithm based on genetic algorithm (GA) optimization is designed to expand the search ability. Finally, based on a specific example, the model and results are analyzed to verify the feasibility of the multi-objective clearing optimization model of medium and long-term electricity market (MLEM) and day-ahead market connection considering wind power participation.