上都电厂串补输电系统附加励磁阻尼控制抑制次同步谐振的现场试验

在上都电厂串补输电系统上进行附加励磁阻尼控制(supplementary excitation damping control,SEDC)抑制次同步谐振(subsynchronous resonance,SSR)的现场试验,介绍试验的运行环境、操作内容和主要结果。试验表明:上都电厂串补输电系统存在SSR风险,尤其是模态2在3/4台机并网运行、上承1回线方式下会出现发散现象,危及机网安全;而SEDC能显著提高扭振模态阻尼,加快SSR收敛速度,有效抑制SSR发散;试验涵盖了各种运行方式和操作,表明SEDC具有良好的适应性;现场实测和仿真结果的比较分析表明他们之间是吻合的。这是国内第1次以现场试验方式验证串补输电系统的SSR发散风险和SEDC的抑制效果,为SEDC抑制次同步谐振的进一步工程应用奠定基础。     

上都电厂SEDC提高次同步扭振阻尼的现场试验

在上都电厂4号机上进行了附加励磁阻尼控制(SEDC)提高次同步扭振阻尼的现场试验,介绍了试验的基本原理、运行环境、主要内容和试验数据分析。试验结果表明:采用励磁注入法可安全、可靠地激发轴系次同步扭振并精确测定其特征频率,SEDC能有效改善各扭振模态的阻尼且不会对励磁系统常规调节功能(自动电压调节器/电力系统稳定器)造成不利影响。作为中国第1次以现场试验方式实证SEDC提高次同步扭振模态阻尼的效果,为自主研发和应用SEDC抑制次同步振荡/谐振奠定了基础。     

采用STATCOM与SEDC的多机系统次同步谐振抑制措施

并列同型的多台汽轮机组通过带串补线路送出时可能发生次同步谐振(subsynchronous resonance,SSR)。出力不均衡时,各机组轴系扭振行为不一致,在幅值和相位上均有差别。以双机系统为例,对并列多机系统发生SSR时各机组轴系扭振行为的差异进行了研究。时域仿真结果表明,将各机组发电机转速均取作输入信号时,仅采用静止同步补偿器(static var compensator,STATCOM)便可抑制所有机组的轴系扭振,但是抑制速度缓慢;以网侧STATCOM为主、机侧附加励磁阻尼控制(supplementary excitation damping,SEDC)为辅的联合SSR抑制措施可以结合SEDC和STATCOM各自作为SSR抑制措施的优点,快速有效地抑制多机系统SSR。     

采用遗传-模拟退火算法优化设计SVC次同步阻尼控制器

针对锦界电厂串补输电工程的多模态次同步谐振(SSR)问题,在基波电纳次同步调制机理基础上,优化设计静止无功补偿器(SVC)次同步阻尼控制器(SSDC).首先建立适应SSR分析与控制设计、包含SVC的多机系统线性化模型,其次提出了基于独立模态控制思路的控制器结构,然后将控制参数设计问题规范为一个约束型非线性规划问题,进而采用遗传-模拟退火(GASA)算法求解得到控制参数,最后采用特征值分析和时域仿真验证了控制系统的有效性.结果表明:SVC-SSDC能大幅提高机组扭振的模态阻尼,有效抑制SSR,从而保证了机组和电网的安全稳定运行.     

发电机励磁与SVC的改进自适应反步无源协调控制

考虑了阻尼系数的不确定性,提出了一种改进自适应反步无源协调控制策略,设计了发电机励磁与静止无功补偿器(SVC)的非线性协调控制器。采用浸入与不变(I & I)自适应控制设计了阻尼系数的自适应估计律,提高了控制器的自适应能力。基于反步法逐步递推,设计了SVC的控制律,并结合无源性理论,得到了发电机励磁的控制律。在反步法设计过程中,为了减小“微分爆炸”,将虚拟控制量的导数看作不确定项,并引入非线性阻尼算法对其进行处理。仿真结果表明,所设计的协调控制器明显地改善了电力系统的稳定性,并且具备较强的自适应性和鲁棒性。     

发电机的浸入与不变自适应反步鲁棒励磁控制器

针对含有不确定参数的发电机励磁控制系统,设计了一种新型的自适应反步鲁棒励磁控制器。在设计过程中,基于反步法逐步进行控制器的设计,并引入非线性阻尼算法来减小反步法的"计算膨胀"问题,有效地增强了控制器的鲁棒性。接着介绍了应用浸入与不变自适应控制设计阻尼系数的自适应估计律。通过MATLAB软件进行仿真研究,验证了该算法的有效性和优越性。     

基于模拟退火算法的模糊控制器优化设计

提出了一种解析规则模糊控制器的改进结构，引入了能够动态调整模糊控制规则的修正函数，并给出了模糊控制器输出控制量在稳态附近的局部连续化算法；同时，通过模拟退火算法，实现了模糊控制器控制参数的组合优化设计。结果表明，使用该方法设计的模糊控制器具有响应快、超调小、稳态精度高等优点，改善了模糊控制系统的性能。     

Optimization and coordination of wide-area damping controls for enhancing the transfer capability of interconnected power systems

This paper proposes systematic procedures to design wide-area damping controls (WADCs) in large interconnected power systems. An efficient model reduction method is first introduced, based on the pseudo-random binary signal (PRBS) probing technique and the prediction error identification algorithm (PEM). Then, the comprehensive controllability concept, as well as its calculating method, is proposed for properly locating the supplementary damping controllers. Further, an improved modal performance index is adopted as the measure of the stabilizing effect. With various constraints taken into account to meet practical engineering requirements, finally, the optimized and coordinated tuning of WADC parameters under various operation scenarios is achieved by a constrained nonlinear programming algorithm. The proposed approach has been tested on a practical 437-machine, 2791-node interconnected power system and the simulation results have demonstrated its high effectiveness in damping inter-area oscillations and enhancing across-region transfer capabilities.     

基于改进遗传模拟退火算法的电网无功优化

电网无功优化问题是一个多变量、多约束的混合非线性规划问题,其操作变量既有连续变量又有离散变量,优化过程复杂繁琐.遗传算法是模拟生物在自然环境中的遗传和进化过程而形成的一种自适应的全局优化搜索算法,可用于解决含有离散变量的复杂优化问题.针对传统遗传算法的收敛速度慢,易陷入局部最优解等缺陷,提出一种基于遗传模拟退火思想求解电力系统无功优化的新算法,并引入灵敏度分析,对基本遗传算法的编码、初始种群、适应度函数和交叉、变异策略等进行改进.使用本文算法对IEEE14节点进行优化计算,仿真结果证明了本文模型和算法的实用性、可靠性和优越性.     

基于MA的水电站机组组合优化问题的研究

在日负荷任务下,建立了以耗水量最小为目标的水电站机组组合优化数学模型。设计了文化基因算法（Memetic Algorithm,MA）的工程实现方法,包括编码设计、适应度函数设计等。提出了二进制与浮点数的混和编码以及交叉和变异的双重遗传操作方式,设计了个体合法化的流程,采用模拟退火算法作为局部搜索策略。绘制了算法对问题的求解流程,并编制了基于MATLAB语言的优化计算程序。仿真结果表明：MA具有比GA更优的收敛性能,更有效降低机组切换频率。     

混合型无线传感器网络覆盖空洞修复算法

针对无线传感器执行器网络运行过程中节点必要的移动或者失效导致的感知空洞,提出了一种基于混合粒子群优化算法的空洞修复方案,该方案首先提出一种基于网格的网络覆盖率,并以此为优化目标将空洞修复问题转化为无约束优化问题,然后使用融合了模拟退火思想的粒子群优化算法对优化问题进行求解,最后仿真证明模拟退火算法的概率突跳特性弥补了粒子群优化算法容易陷入早熟收敛的缺陷,该混合算法可以对空洞修复问题进行有效地求解。     

An optimal design method for efficiency of permanent magnet motors

In optimal design of a permanent magnet (PM) motor, many design variables are required to consider some device properties. These variables are, for example, the shape of core and magnet, the tooth length, the number of turns, and the winding radius. Moreover, many restrictions must be considered in practical PM motor design. These restrictions are, for example, the slot space factor and the cogging torque. However, the optimization problem, which has many design variables by the finite element method (FEM), has not been reported. In this paper, the efficiency of PM motor under the considerations given above is optimized by using FEM and optimization algorithm. In this problem, an objective function has many local minima and it is difficult to calculate its gradient. For these reasons, the genetic algorithm (GA) and simulated annealing method (SA), which are stochastic methods, are used for optimization method, because of the possibility of global range search and because gradient calculation is not required. Adding to both optimization methods, in this paper, SA combined with GA is used for one of the optimization methods. It is found that the solutions optimized by these methods are reasonable from an engineering point of view. © 2001 Scripta Technica, Electr Eng Jpn, 138(3): 72–79, 2002     

基于凝聚率和网络重构效率评价的骨架网架优化

黑启动恢复问题是大停电后系统安全防御的重要课题,确定合理的骨架网络对于快速建立输电网架和负荷的全面恢复,具有重要意义。首先,提出一种基于电气凝聚率和网络重构效率表征骨架网络优劣的方法。该方法采用节点凝聚率、线路凝聚率定量表征电网电气特性,以网络重构效率表征电网拓扑结构联系的紧密程度,并考虑电网安全运行约束,以此建立骨架网络的优化模型;在此基础上,提出基于模拟退火改进离散粒子群算法的方法以实现骨架网络重构过程的优化,获取能涵盖主要枢纽节点和关键线路的综合性能最优和次优的骨架网络。最后以新英格兰10机39节点系统为算例,验证了骨架网络优化模型的合理性与求解算法的正确性。     

基于改进鲸鱼算法的混合直流输电系统控制参数优化方法

混合直流输电系统结合了传统电网换相换流器和电压源换流器的优点，具有广泛的应用前景。为解决混合直流输电系统控制参数优化问题，引入一种新型的元启发式算法--鲸鱼算法。针对算法全局搜索能力较差的问题，引入混合优化理论，利用模拟退火和联赛选择机制对其进行了改进，改进算法有效平衡了全局搜索与局部开发能力，降低了对参数选择的依赖性。以双极型两端混合直流输电测试系统为研究对象，采用改进鲸鱼算法优化整流侧定电流控制中的比例积分（proportional integra，PI）参数和逆变侧dq轴双环控制器的PI参数，并通过MATLAB和PSCAD软件联合仿真实现该算法。算例结果表明，相比于原始鲸鱼算法和粒子群算法，所提算法具有更高收敛精度，有效优化了控制系统的参数，提升了混合直流输电系统的指令跟踪能力。     

An adaptive chaotic artificial bee colony algorithm for short-term hydrothermal generation scheduling

Short-term hydrothermal scheduling (SHS) is a complicated nonlinear optimization problem with a set of constraints, which plays an important role in power system operations. In this paper, we propose to use an adaptive chaotic artificial bee colony (ACABC) algorithm to solve the SHS problem. In the proposed method, chaotic search is applied to help the artificial bee colony (ABC) algorithm to escape from a local optimum effectively. Furthermore, an adaptive coordinating mechanism of modification rate in employed bee phase is introduced to increase the ability of the algorithm to avoid premature convergence. Moreover, a new constraint handling method is combined with the ABC algorithm in order to solve the equality coupling constraints. We used a hydrothermal test system to demonstrate the effectiveness of the proposed method. The numerical results obtained by ACABC are compared with those obtained by the adaptive ABC algorithm (AABC), the chaotic ABC algorithm (CABC) and other methods mentioned in literature. The simulation results indicate that the proposed method outperforms those established optimization algorithms.     

基于改进遗传退火算法的输配电网协调规划方法

针对目前对输配电网协调性考虑不足的问题,考虑机组间负荷优化分配因素,引入耗量成本,构建了包含输配电网协调性指标的电网评价指标体系。结合电网经济性指标和可靠性指标,通过优化算法选出综合性能最优的输配电网规划方案。在解决遗传算法\"早熟\"、易陷于局部最优等问题的基础上,提出了一种优化算法并将其应用于考虑输配网协调性的电网规划问题中。仿真计算结果表明,所提出的方法是可行、高效的。     

基于最小二乘支持向量机和自适应模拟退火算法的电磁场逆问题全局优化方法

分析了目前电磁场逆问题全局优化算法存在的收敛速度慢以及搜索时间长等问题的主要原因,并针对以上问题提出了基于最小二乘支持向量机和自适应模拟退火电磁场逆问题优化新算法,充分利用了自适应模拟退火算法中丢失的已搜索过点的信息,动态地建立和改进待求问题的数值模型,指导最优解的搜索过程,大大减少了求解电磁场正问题的求解次数,缩短了搜索到最优解的时间,通过仿真实验以及实际应用的对比,效果显著,提高了电磁场优化设计的实际应用能力。     

An application of reactive tabu search for service restoration in distribution systems and its comparison with the genetic algorithm and parallel simulated annealing

Service restoration in distribution systems can be formulated as a combinatorial optimization problem. It is the problem to determine power sources for each load considering various operational constraints in distribution systems. Up to now, the problem has been dealt with using conventional methods such as the branch and bound method, expert systems, neural networks, and fuzzy reasoning. Recently, modern heuristic methods such as genetic algorithms (GA), simulated annealing (SA), and tabu search (TS) have been attracting notice as efficient methods for solving large combinatorial optimization problems. Moreover, reactive tabu search (RTS) can solve the parameter tuning problem, which is recognized as the essential problem of the TS. Therefore, RTS, GA, and SA can be efficient search methods for service restoration in distribution systems. This paper develops an RTS for service restoration and compares RTS, GA, and PSA (parallel SA) for the problem. The feasibility of the proposed methods is shown and compared on a typical distribution system model with promising results. © 2000 Scripta Technica, Electr Eng Jpn, 133(3): 71–82, 2000     

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.     

基于混沌模拟退火粒子群优化算法的电动汽车充电站选址与定容

针对城市电动汽车充电站的选址与定容问题,建立了考虑充电站运营商、电动汽车用户以及电网企业综合利益的充电站选址定容规划模型。采用Voronoi图思想和需求点栅格化理论,结合Floyd最短路径算法划分充电站的服务范围。提出采用一种混沌模拟退火粒子群优化算法对问题进行求解,通过引入混沌理论使粒子更高效地遍历搜寻空间,并结合模拟退火算法的概率突跳特性使算法在迭代后期仍具有较高的全局寻优能力。通过算例分析表明,采用所提算法对城市电动汽车充电站选址定容进行优化规划的可行性和有效性。