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风力发电并风电能调度稳定性优化仿真 被引量:1

Wind Power Generation and Wind Power Dispatch Stability Optimization Simulation
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摘要 对风力发电并网电能调度稳定性优化,可以缓解风电出力的随机性和间歇性对电网安全稳定运行产生的影响,提升电力系统的风电消纳能力。进行风力发电并风电能调度时,应对储能系统的吸收和输出功率对电能调度进行约束,平滑风电的出力波动,但是传统方法通过组建含风电场的初始网络协同双层调度模型完成调度,不能利用储能系统的吸收和输出功率对电能波动进行平滑处理,存在调度稳定性差的弊端。提出一种交叉熵的风力发电并风电能调度稳定性优化方法,首先定义风度服从Weibull分布,计算出风电储能并网系统等效负荷平均方差,其次以系统参与风电发电调度利润最大为优化目标,计算出不同时段风电储能系统电能损耗成本,给出需求响应下风电机组储能协同调度模型的约束条件,组建风电储能协同调度优化模型。最后将交叉熵理论引入风电储能协同调度优化过程中,将风电场输出功率波动最小和发电效益最大为优化目标,以储能系统的吸收和输出功率为约束条件,求解风电储能调度稳定性优化模型。仿真结果表明,所提方法可以有效平抑风电场输出功率的波动,提高风力发电并风电能调度的稳定性。 An optimization method for scheduling stability of wind power generation connected wind power energy is proposed based on the cross entropy. Firstly,the wind degree obeyed Weibull distribution is defined and the average variance of equivalent load in grid - connected system of wind power stored energy is worked out. Then, the profit maximization of wind power generation scheduling with system participation is used as optimization objective to work out the cost of electric energy loss in wind power stored energy at different period. The constrain condition of collaborative scheduling model of wind power set energy storage under demand response is also given out to build the optimi- zation model of collaborative scheduling. Moreover, the cross entropy theory is introduced into the energy storage collaborative scheduling process of wind power. Finally, the optimization model for energy storage scheduling stability of wind power is solved by using the minimum output power fluctuation and maximum power generation benefit as optimization objective, the absorption and output power in energy storage system as the constraint condition. The simulation results show that the method can suppress the output power fluctuation of wind power field effectively and improve the scheduling stability.
作者 门艳 刘芳 闫富强 黄博 MEN Yan LIU Fang YAN Fu - qiang HUANG Bo(State Grid Xinjiang Electric Power Corporation Economy & Technology Research Institute ,Urumchi 830002, Chin)
出处 《计算机仿真》 北大核心 2017年第6期108-111,448,共5页 Computer Simulation
关键词 风电储能 协同调度 交叉熵 Wind power energy storage Collaborative scheduling Cross - entropy
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