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热电联产中电锅炉调峰问题 被引量:2

Peak regulation of electric boiler in cogeneration
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摘要 为充分利用风能进行发电,减少化石燃料的燃烧量,需要解决将风电并入电网带来的弃风问题。采用在二级热网设置调峰电锅炉的方法来消纳过剩的风电,通过合理分配各机组的出力来降低整个电力系统的运行成本,建立了考虑风电的热电联产电力系统优化调度模型,以机组的煤耗量作为目标函数。考虑到风电的消纳问题,设置了反映煤耗量和弃风量的适应度函数。采用改进的遗传算法对模型进行求解,设计智能交叉、变异算子保证算法的搜索能力和收敛性。通过算例验证了模型的合理性,并通过不同容量比的煤耗特性验证了电锅炉调峰的灵活性。算法可为各机组制定较为经济的负荷分配策略。 In order to make full use of wind energy for power generation and reduce the amount of fossil fuel combustion,it is necessary to solve the problem of wind abandonment caused by the integration of wind power into the power network.This paper adopted the method of setting peak-shaving electric boilers in the secondary heating network to absorb excess wind power,and reduced the operating costs of the entire power system by rational distributing the output of each unit.It established a co-generation power system optimization scheduling model considering wind power,which set the amount of coal consumption as the objective function.Considering the consumption of wind power,a fitness function was set to reflect the coal consumption and abandoned wind volume.In this paper,the improved genetic algorithm was used to solve the model,in which the intelligent crossover and mutation operators were designed to ensure the search ability and convergence of the algorithm.The rationality of the model was verified by a use case where the flexibility of peak shaving of electric boilers was verified by the coal consumption characteristics with different capacity ratios.The proposed algorithm can formulate a more economical load distribution strategy for each unit.
作者 杨世豪 孙小平 田丰 吴昊天 YANG Shi-hao;SUN Xiao-ping;TIAN Feng;WU Hao-tian(School of Automation,Shenyang Aerospace University,Shenyang 110136,China;Vehicle Processing Department,Shanghai ABB Engineering Co.LTD,Shanghai 201319,China)
出处 《沈阳航空航天大学学报》 2021年第1期63-69,共7页 Journal of Shenyang Aerospace University
关键词 电锅炉调峰 风电消纳 热电联产 遗传算法 机组负荷分配 electric boiler peak shaving wind power accommodation combined heat and power generation genetic algorithm unit load distribution
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