Optimal Combination Control Technology of Demand Side Resources of Distributed Renewable Energy Power Generation
The paper proposes a new unit commitment model that can promote carbon emission reduction in distributed renewable energy power systems. The model first comprehensively considers the optimal combination of low-carbon demand-side resources such as supply-side resources and demand response, electric vehicles, and distributed renewable energy power generation. Secondly, the model unit scheduling rules fully consider the carbon emission target and the economic target and propose a fuzzy dual-objective optimization method that can consider the relative priority of the target. When solving the optimization model, we improved the particle swarm optimization algorithm. We introduced the “cross” and “mutation” operators in the genetic algorithm to improve the particle swarm algorithm’s global optimization capability. The paper verifies the effectiveness of the model and algorithm through the analysis of a ten computer system.
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