Abstract
The paper proposes a new unit commitment model that can promote car-bon emission reduction in distributed renewable energy power systems. Themodel first comprehensively considers the optimal combination of low-carbon demand-side resources such as supply-side resources and demandresponse, electric vehicles, and distributed renewable energy power gener-ation. Secondly, the model unit scheduling rules fully consider the carbonemission target and the economic target and propose a fuzzy dual-objectiveoptimization method that can consider the relative priority of the target. Whensolving the optimization model, we improved the particle swarm optimizationalgorithm. We introduced the “cross” and “mutation” operators in the geneticalgorithm to improve the particle swarm algorithm’s global optimizationcapability. The paper verifies the effectiveness of the model and algorithmthrough the analysis of a ten computer system.
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