基于模糊混合进化算法的多个FACTS元件协调控制

针对多个FACTS装置的控制器之间存在的负交互影响,通过将模糊理论、协同进化算法和免疫算法相结合,提出一种模糊混合多目标进化算法求解FACTS元件的协调控制问题。在求解过程中,利用模糊集理论建立模糊多目标优化模型,确定整体的优化目标。采用协同进化算法对各FACTS元件控制器的参数进行种群划分,以克服常规进化算法在问题规模扩大时易于出现的早收敛现象。在优化过程中,结合多种群合作策略和免疫算法保持解的多样性,最终得到控制参数的Pareto最优解集。对静止同步串联补偿器与静止同步补偿器2种FACTS装置的控制器进行了协调设计,仿真结果表明,与常规进化算法相比,所提方法能同时实现影响分析与参数优化功能,且收敛快速,稳定性好。     

基于多FACTS的网侧阻尼协调控制量化指标研究

研究多变量系统等效开环过程(effective open-loop process,EOP)理论在电力系统多柔性交流输电装置(flexible AC transmission system,FACTS)协调控制量化分析中的应用,并提出基于EOP的多FCATS阻尼控制器交互作用分析方法及量化指标。推导电力系统阻尼控制框架下的 EOP,在此基础上建立用于多FACTS阻尼控制器分析的阻尼控制等效开环过程(damping control effective open-loop process,DCEOP)。提出基于 DCEOP 谱半径和多变量 Nyquist 推广定理的多FACTS阻尼控制器交互影响分析方法,可以判断系统中是否存在多FACTS阻尼控制器的负交互作用。进一步推导并提出基于DCEOP的多FACTS交互风险因子和交互作用因子,实现了多FACTS阻尼控制器协调控制及交互作用的量化分析。最后,通过算例分析验证了所提方法的正确性以及在实际电网中应用的可行性。     

基于合作协同进化和IMPSO算法的多阶段多目标电网规划

提出一种模型,其任务是在满足安全约束的条件下,确定何时、何地,新建多少线路以满足各阶段电网负荷增长的需要,同时使建设费用、运行费用和网损费用最小。尝试将合作协同进化算法与IMPSO算法结合,应用于多阶段多目标的电力系统规划问题,在各阶段中采用IMPSO算法多目标优化,各阶段之间通过合作协同算法根据各约束条件进行协调。与常规算法比较,在算例分析与实际应用中取得了较好的效果。     

基于合作协同进化和IMPSO算法的多阶段多目标电网规划

提出一种模型,其任务是在满足安全约束的条件下,确定何时、何地,新建多少线路以满足各阶段电网负荷增长的需要,同时使建设费用、运行费用和网损费用最小.尝试将合作协同进化算法与IMPSO算法结合,应用于多阶段多目标的电力系统规划问题,在各阶段中采用IMPSO算法多目标优化,各阶段之间通过合作协同算法根据各约束条件进行协调.与常规算法比较,在算例分析与实际应用中取得了较好的效果.     

基于非支配遗传算法及协同进化算法的多目标多区域电网规划

基于快速分类的非支配遗传算法(NSGA-II)是一种新型的多目标遗传算法,文中首次将其应用于电网优化规划。多个算例分析表明NSGA-II算法在电网规划中具有良好的优化效果,为各目标之间的权衡分析提供了有效的工具;协同进化算法采用分解-协调的思想处理复杂系统的演化,可以克服当优化问题规模扩大时,常规进化算法易于出现过早收敛的现象。据此提出将协同进化算法和NSAG-II算法相结合,以用于处理大规模多区域的电力系统规划问题,在各子网采用NSAG-II算法优化的过程中进行多区域协调。与常规遗传算法相比,算例分析取得了更好的规划结果。     

基于多目标进化算法的TCSC非线性控制器设计

提出了一种利用多目标进化算法设计可控串联补偿(TCSC)非线性稳定控制器的方案，设计目标是选取合适的控制器参数，达到提高电力系统暂态稳定性的效果。将非线性控制器反馈增益的选择归结为参数优化问题，并且在优化过程中同时考虑电力系统响应的多项性能指标。采用该方法优化的非线性控制器参数可以较有效地阻尼电力系统振荡。     

多目标配电网故障定位的Pareto进化算法

提出一种用于配电网故障定位的多目标优化模型,采用带精英策略的快速非支配排序遗传算法(NSGA-Ⅱ)进行求解.传统多目标优化问题通过加权方式转换为单目标问题,对权值比较敏感,且每次只能得到一种权值下的最优解.NSGA-Ⅱ则避免了传统加权求解时权值的选择和解的偏好性.该算法采用快速非支配排序机制,计算复杂性低;同时考虑个体拥挤距离,从而保证种群的多样性;最后,提出适用于故障定位的最优解集处理方法,便于从多目标最优解集中筛选出唯一符合故障情况的解.算例测试分别模拟单点、多点故障,以及信息完备和部分信息畸变的情况,测试结果表明,所提方法均能准确地定位故障区段.     

基于协同进化算法的西北电网无功优化

西北电网全网无功分布具有典型的结构性特征。而常规遗传算法忽略了无功优化问题的结构性特征,计算时间过长,甚至找不到最优可行解。就此,采用协同进化算法对西北电网的无功优化问题进行研究,将西北全网划分成了甘青、陕西、宁夏3个子区,建立了每个子区自身的目标函数,采用常规遗传算法对子区内的控制变量先行优化,并将运算结果作为下一步协同进化计算的初始值,从而预先对参与运算的初始点进行了有效地筛选,以提高运算效率。实际运行算例表明,在收敛速度和迭代精度上,此协同进化算法均优于常规遗传算法。     

基于多目标进化算法的TCSC非线性控制器设计

提出了一种利用多目标进化算法设计可控串联补偿（TCSC）非线性稳定控制器的方案，设计目标是选取合适的控制器参数，达到提高电力系统暂态稳定性的效果。将非线性控制器反馈增益的选择归结为参数优化问题，并且在优化过程中同时考虑电力系统响应的多项性能指标。采用该方法优化的非线性控制器参数可以较有效地阻尼电力系统振荡。     

基于协同进化的电力系统多目标优化*

随着社会的发展与科技的进步,电力系统在不断的发展,人们所追求的也不仅仅是经济效益,电力系统所造成的能源浪费及其安全性等问题也受到人们的广泛关注。文中选取电力系统燃料成本、有功网损、电压质量三个目标作为优化目标,基于粒子群、遗传与差分进化算法提出一种基于协同进化的多目标优化算法。分别在标准测试函数与IEEE-30节点进行实验,结果显示文中提出的算法有更好的收敛性与稳定性,更易获得完整的Pareto前沿。     

Comparison of performances of several FACTS devices using Cuckoo search algorithm optimized 2DOF controllers in multi-area AGC

This paper presents automatic generation control (AGC) of three unequal area thermal systems with single reheat turbine and appropriate generation rate constraints (GRC) in each area. A two degree of freedom (2DOF) controller called 2DOF-integral plus double derivative (2DOF-IDD) is proposed for the first time in AGC as secondary controller. Secondary controller gains and other parameters are optimized simultaneously using a more recent evolutionary computational technique called Cuckoo Search algorithm (CS). The system dynamic responses for various 2DOF controllers such as 2DOF-PI, 2DOF-PID, and 2DOF-DD are compared. Investigations reveal that responses with 2DOF-IDD are better than others. Performance of several FACTS devices such as Static synchronous series compensator (SSSC), Thyristor controlled series capacitor (TCSC), Thyristor controlled phase shifter (TCPS), and Interline power flow controller (IPFC) in presence of 2DOF-IDD controller are compared and found that the dynamic responses with IPFC are better than others. For the first time in AGC, a case study is performed with placement of IPFC and observed that IPFC present in all three areas of the system performs better. Sensitivity analysis reveals that the CS optimized 2DOF-IDD controller parameters obtained in presence of IPFC in all three areas at nominal condition of loading and size of step load perturbation (SLP) are robust and need not be reset with wide changes in system loading and SLP. Also, the comparison of convergence curve of various algorithms reveals that CS algorithm converges much faster than others.     

基于改进协同演化算法的综合能源系统经济性与可靠性优化规划

随着多能流耦合程度的加深以及能源利用需求的多样化,综合能源系统(IES)对规划方案的经济性与可靠性提出了更高的要求.然而,经济性与可靠性之间存在相互制约的复杂关系,导致二者难以实现协调优化.为此,提出了一种基于改进协同演化算法的IES经济性与可靠性优化规划方法.在多场景经济性评估模型和基于马尔科夫链蒙特卡洛法的供能可靠...     

Grasshopper optimization algorithm optimized multistage controller for automatic generation control of a power system with FACTS devices

This paper uses a Grasshopper Optimization Algorithm (GOA) optimized PDF plus (1+ PI) controller for Automatic generation control (AGC) of a power system with Flexible AC Transmission system (FACTS) devices. Three differently rated reheat turbine operated thermal units with appropriate generation rate constraint (GRC) are considered along with different FACTS devices. A new multistage controller design structure of a PDF plus (1 + PI) is introduced in the FACTS empowered power system for AGC while the controller gains are tuned by the GOA. The superiority of the proposed algorithm over the Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) algorithms is demonstrated. The dynamic responses of GOA optimized PDF plus (1+ PI) are compared with PIDF, PID and PI controllers on the same system. It is demonstrated that GOA optimized PDF plus (1+ PI) controller provides optimum responses in terms of settling time and peak deviations compared to other controllers. In addition, a GOA-tuned PDF plus (1 + PI) controller with Interline Power Flow Controller (IPFC) exhibits optimal results compared to other FACTS devices. The sturdiness of the projected controller is validated using sensitivity analysis with numerous load patterns and a wide variation of parameterization. To further validate the real-time feasibility of the proposed method, experiments using OPAL-RT OP5700 RCP/HIL and FPGA based real-time simulations are carried out.     

基于协同进化算法的配电网络重构方案

提出了一种基于协同进化算法的配电网络重构方案,将配电网络重构分解为各个回路优化的子问题,采用分开进化、定期协同的思想来处理各个子问题,即生成与回路数目相等的种群,在确保全局最优解为优化方向的前提下,各种群独立进化对应各回路的优化过程.特殊的基因操作减少了不可行解的数量,提高了优化效率;使用“确定树”方法进行不可行解的修复,降低了陷入局部最优解的概率.算例结果表明所提算法具有较好的计算结果和较高的计算效率.     

Quantitative evaluation of generator power control effect of FACTS controllers for power system stabilization

The advancement of power electronics technologies has significantly developed the power system stabilizing controllers. Quantitative as well as qualitative evaluation of their effectiveness in power systems is a matter of great importance for the feasibility investigation of these apparatus. In this paper, the possible control region of FACTS controllers with series and/or shunt configuration in a single machine to infinite bus system is formulated in the powerangle curve with a set of algebraic equations. The effectiveness of TCPST (Thyristor‐Controlled Phase Shifting Transformer), SSSC (Static Synchronous Series Compensator), and TCSC (Thyristor‐Controlled Series Compensator) for the improvement of the transient stability is evaluated quantitatively as a numerical example. The correctness of the proposed method has been confirmed by analysis based on the electromagnetic transients simulation with a detailed system model. © 2001 Scripta Technica, Electr Eng Jpn, 138(3): 43–51, 2002     

基于RGA的FACTS控制器之间的交互影响研究

多台FACTS控制器之间的交互影响与协调是FACTS技术应用中亟待解决的问题,介绍了采用相对增益矩阵(RGA)方法,分析了多机电力系统中多台柔性交流输电系统(FACTS)控制器之间的交互影响。通过对4机两区域系统以及新英格兰系统两个实例的分析研究,分别采用频域分析、特征值分析以及时域仿真三种方法来验证RGA所得的结论,证明了RGA方法可以用来分析FACTS间的交互现象。     

Load frequency control using Bat inspired algorithm based dual mode gain scheduling of PI controllers for interconnected power system

This paper highlights the load frequency control using dual mode Bat algorithm based scheduling of PI controllers for interconnected power systems. The bat inspired algorithm based on the echolocation of bats has been developed in 2010. In this study, the bat inspired algorithm based dual mode PI controller is applied to the multi-area interconnected thermal power system in order to tune the parameter PI controllers. The proposed controller is simple in structure and easy for implementation. The proposed controller was compared with those from conventional the PI controllers and Fuzzy gain scheduling of PI controllers. The simulation results show the point that the proposed bat inspired algorithm, based dual mode gain scheduling of PI controllers (BIDPI), provides better transient as well as steady state of response. It is also found that the proposed controller is less sensitive to the changes in system parameters.     

基于电力系统稳定分析与控制的FACTS技术评述

对FACTS控制器的数学模型、稳定控制及策略等方面进行了评述,总结了当前国内外FACTS研究在稳定方面的最新动态和关键问题。指出需要在电力系统的动态分析及FACTS的控制方案设计中考虑FACTS的内部动态特性,并认为动态相量模型极具优势。     

基于滑窗DFT算法的并网逆变器多目标协调控制方法

由于传统并网逆变器协调控制方法中没有检测畸变电流,导致控制过程中计算时间增加,控制效果不理想。针对这些问题,提出一种基于滑窗离散傅里叶变换(Discrete Fourier Transformation, DFT)算法的并网逆变器多目标协调控制方法。利用自适应抽样算法自动调整采样时间,引入滑窗DFT思想构建有源滤波器,通过滤波器对并网逆变器中的畸变电流进行检测。对并网逆变器中功率和坐标两者之间的关系进行分析,采用比例积分(Proportional Integral,PI)并联重复的复合型控制器对输出电流进行实时跟踪控制。同时根据线性叠加原理,获取并网逆变器的等效被控对象模型,简化补偿控制器设计,最终实现并网逆变器多目标协调控制。经实验测试证明,所提方法能够将计算效率提升14.6%,控制后的波畸变率下降幅度达到15.8%,功率因数增长幅度达到14.9%。