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计及需求侧管理的风电光伏互补电网调度方法

Wind Power Photovoltaic Complementary Grid Scheduling Method Taking Into Account Demand-Side Management
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摘要 由于传统方法未考虑需求侧管理因素,风电光伏互补电网调度效果不佳,电网消纳率较低,提出计及需求侧管理的风电光伏互补电网调度方法。根据风电光伏互补电网本身具有的特点,设定调度原则和假设条件,以电网运行总费用最小为目标建立运行优化调度目标函数。针对需求侧管理,给出电网功率平衡约束、风电光伏出力约束以及储能系统充放电功率约束条件,利用粒子群算法对函数求解,输出最优调度策略,实现计及需求侧管理的风电光伏互补电网调度。经实验证明,在设计方法的应用下,风电光伏互补电网的消纳率在86%左右,处于一个比较高的水平,设计方法在电网调度方面具有良好的应用前景。 Because traditional methods do not consider demand-side management factors,the scheduling effect of wind power photovoltaic complementary power grid is poor,and the digestion rate of the power grid is relatively low.Therefore,a wind power photovoltaic complementary grid scheduling method that takes into account demandside management is proposed.According to the characteristics of the wind power photovoltaic complementary power grid itself,scheduling principles and hypothetical conditions are set,and the operation optimization scheduling target function is established with the goal of the lowest total operating cost of the power grid.For demand-side management,the power balance constraint of the power of the power of the power grid,the wind power photovoltaic output constraint and the charging and discharge power constraint of the energy storage system,the particle swarm algorithm is used to solve the function and output the optimal scheduling strategy,so as to realize the scheduling of the wind photovoltaic complementary power grid that takes into account the demand-side management.Experiments show that under the application of the design method,the digestion rate of wind power photovoltaic complementary power grid is about 86%,which is at a relatively high level.The design method has a good application prospect in power grid scheduling.
作者 段树勋 张国栋 DUAN Shuxun;ZHANG Guodong(Shandong Zhongshi Yitong Group Co.,Ltd.,Jinan 250000,China)
出处 《通信电源技术》 2023年第13期85-87,共3页 Telecom Power Technology
关键词 需求侧管理 风电光伏互补电网 调度 目标函数 粒子群算法 demand-side management wind power photovoltaic complementary power grid scheduling target function particle swarm algorithm
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