考虑风电谐波影响与出力随机性的电力系统无功优化方法  

Reactive Power Optimization Considering the Harmonic Effects and Output Uncertainty of Wind Generation

作　　者：陈远扬[1] 谭益[1] 李勇[1] 曹一家[1] CHEN Yuanyang;TAN Yi;LI Yong;CAO Yijia(College of Electrical and Information Engineering,Hunan University,Changsha 410082,China)

机构地区：[1]湖南大学电气与信息工程学院,湖南长沙410082

出　　处：《湖南大学学报（自然科学版）》2024年第6期137-147,共11页Journal of Hunan University:Natural Sciences

基　　金：国家自然科学基金资助项目(U22B200134)。

摘　　要：电容器组等无功补偿装置的优化调整不仅可以减小电力系统网损,还会对电力系统的谐波潮流与谐波网损产生影响.风电不仅存在出力不确定性,而且会产生谐波污染,影响谐波潮流与谐波网损.然而,传统无功优化方法没有同时考虑风电的谐波特性与出力不确定性对谐波潮流和谐波网损的影响,可能导致谐波超标问题,不利于电力系统降低网损.因此,本文首先构建计及风电谐波影响的电力系统无功随机优化模型.该模型通过场景法对风电出力随机性进行建模,目标函数同时考虑基波和谐波网损,约束条件包括基波和谐波潮流约束、电压谐波总畸变率约束等.然后,针对该谐波约束的无功随机优化模型,本文提出了融合驱动力可调粒子群算法和全连接型深度神经网络的高效求解方法 .最后,通过三个修改后的IEEE测试系统对所提模型与方法的有效性进行了验证.The optimal adjustment of reactive power compensation device such as capacitors can not only reduce the network losses,but also present influences on harmonic power flow and harmonic power losses.Wind generators can produce harmonic pollution and present impacts on harmonic power flow and harmonic power losses.However,the effects of the harmonic characteristic and output uncertainty of wind power on harmonic power flow and harmonic power losses are not considered simultaneously in the traditional reactive power optimization methods,which may result in the violation of harmonic standard and is adverse to network losses reduction.In this regard,this paper proposes the reactive power stochastic optimization model for power systems considering the impact of the wind power harmonics.In this model,the uncertainty of wind power is modeled by the scenario method,and the base-frequency network losses and the harmonic losses are considered in the objective function.Also,the constraints such as base-frequency power flow equations,the harmonic power flow equations and the total harmonic voltage distortion constraint are incorporated into the proposed model.After that,focusing on the proposed reactive power stochastic optimization model,the highly efficient method combining the adjustable driving force-based particle swarm optimization and a fully-connected deep neural network is proposed in this paper.Finally,the effectiveness of the proposed model and method is validated by three modified IEEE test systems.

关 键 词：无功功率 电力系统潮流 谐波分析 风电 

分 类 号：TM714.3[电气工程—电力系统及自动化]