Demand response is one of the important adjustable load resources,which plays an important role in promoting carbon reduction and new energy consumption in new power systems.This article integrated carbon flow theory,intelligent optimization algorithm,and multi-attribute evaluation methods into adjustable load operation strategy decision-making for demand response.It constructed a demand response strategy optimization model with the objective function of minimizing user electricity costs and constraints covering power supply and demand balance and unit output limitations.A genetic algorithm was used to determine the various chromosomes of the advantageous population that are conducive to achieving optimization goals.By combining the economic benefits of each chromosome,the consumption of new energy,and the calculation results of user carbon emission intensity,the improved entropy weight method and weight sum method were combined to comprehensively evaluate and rank all chromosomes.As a result,the demand response strategy that ensures the global best economic benefits,consumption of new energy,and carbon reduction effects of the system was obtained,which maximized the value of adjustable load resources.The feasibility and effectiveness of the method were finally verified through examples.
维普
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