基于改进微分进化算法的电力系统无功优化

提出了一种改进的微分进化算法求解电力系统无功优化问题。在进化过程中，该算法根据进化情况采用动态参数调整机制提高算法的搜索效率，并且对种群重叠状况进行实时监视，对重叠个体利用混沌搜索策略来进一步提高算法的全局寻优能力。通过对IEEE 6、IEEE 30、IEEE 118标准测试系统及某地区实际系统的无功优化问题计算及结果分析表明，文中提出的改进微分进化算法高效、且全局寻优能力强。     

基于改进类电磁机制的水火电力系统短期优化调度

针对水火电力系统短期优化调度模型的大规模、强非线性特点,采用类电磁机制对其进行求解。通过对搜索策略和寻优机制分析,揭示算法效率高的根本原因在于其融合了常规优化算法的高效搜索优势。经计算分析表明,个体受力计算及局部搜索是影响算法优化效率的主要因素。通过对算法的电荷量计算、受力计算、算法全局与局部搜索策略改进,首次提出适合于大规模非线性优化问题求解的单方向受力类电磁机制,并从理论上证明其全局收敛性。为进一步提高算法优化性能,将改进算法与遗传算法的交叉算子和变异算子融合应用于优化调度模型求解,通过广西水火电力系统进行仿真分析,结果表明该算法在求解大规模强非线性优化问题方面的有效性和显著优越性。     

改进遗传蚁群算法及其在电机结构优化中的研究

针对电机的优化设计问题,采用一种改进的二进制遗传蚁群算法,对一台4极7.5k W的自起动永磁同步电动机的结构参数进行优化,该算法结合遗传算法和蚁群算法各自的优点,并且能解决连续空间优化问题。介绍了改进二进制遗传蚁群算法的基本思想及其特点,重点论述该算法在电机优化设计中的具体实现方法。采用编程语言实现该算法,通过大量的仿真计算验证算法的全局收敛能力。利用有限元方法对优化后的电磁设计方案进行仿真,结果表明该算法可以使自起动永磁同步电动机得到较好的优化,有可能提高电机的起动性能和运行性能。     

基于改进粒子群算法的继电保护定值优化

对传统的粒子群算法进行了改进，得出一种适用于继电保护整定计算全局优化的改进粒子群算法，为继电保护定值优化的后续研究工作提供了一定的基础。同时，与基于遗传算法优化的继电保护整定计算进行了比较，结果表明改进粒子群算法可成功应用于继电保护全局优化整定。     

基于类电磁机制算法的综合能源系统多目标优化调度

针对综合能源系统低碳经济调度的优化问题,引入P2G设备提升系统的弃风消纳空间与低碳经济性,以运行成本与碳排放量为优化目标,建立含多种供能设备的综合能源系统多目标优化调度模型。模型的求解采用改进的类电磁机制算法,针对综合能源系统调度问题约束较为复杂,算法易陷入局部最优的问题,引入立方混沌初始化、差分进化策略和自适应权重因子,增强了算法的全局搜索能力与收敛性。结果表明,提出的IELM算法在全局最优解方面、收敛效率方面和操作适应性具有明显优势,P2G装置能有效提升系统的弃风消纳率与低碳经济成本。     

一种电力系统无功优化的新型混合优化算法

提出了一种适合于求解电力系统无功优化问题的新型混合优化算法,该算法结合基于邻域搜索的群搜索优化算法和改进灾变遗传算法。综合考虑两种算法的特点,将无功优化问题分步进行交替求解,第一步采用改进灾变遗传算法迭代两次更新解群体,第二步在此基础上采用基于邻域搜索的群搜索优化算法使群体中各解向当前最优解靠拢,交替进行,最终达到全局最优解。在IEEE118节点系统试验计算结果表明,与其他算法相比,该混合算法具有较好的全局收敛性且不容易陷入局部最优,在优化效果以及算法稳定度上都具有明显的优势。在某实际290节点电网计算结果表明,该混合算法能够适应实际电力系统无功优化问题的求解。     

自适应变异粒子群优化算法在水轮发电机优化设计中的应用

本文介绍了一种应用于水轮发电机优化设计的新的全局优化算法--粒子群优化算法(PSO算法),并对其进行了改进.改进后的PSO算法(称之为AMPSO)的优化结果与未改进的粒子群优化算法(PSO)和遗传算法(GA)优化结果相比,具有很好的全局收敛性,能有效地避免早熟收敛问题,适用于电机的优化设计.     

一种电力系统无功优化的新型混合优化算法

提出了一种适合于求解电力系统无功优化问题的新型混合优化算法,该算法结合基于邻域搜索的群搜索优化算法和改进灾变遗传算法.综合考虑两种算法的特点,将无功优化问题分步进行交替求解,第一步采用改进灾变遗传算法迭代两次更新解群体,第二步在此基础上采用基于邻域搜索的群搜索优化算法使群体中各解向当前最优解靠拢,交替进行,最终达到全局最优解.在IEEE118节点系统试验计算结果表明,与其他算法相比,该混合算法具有较好的全局收敛性且不容易陷入局部最优,在优化效果以及算法稳定度上都具有明显的优势.在某实际290节点电网计算结果表明,该混合算法能够适应实际电力系统无功优化问题的求解.     

基于改进免疫算法的电力系统无功优化

在克隆选择原理的基础上提出了一种改进的免疫算法用于求解电力系统无功优化问题。该算法在上一代最优抗体的基础上，构造了一个较小的细胞克隆半径和一个较大的高频变异半径，即通过一个较小邻域范围和一个较大邻域范围的并行搜索，使该方法在加强对问题局部搜索的同时兼顾了全局搜索，有效地提高了算法的收敛速度和精度。通过对马尔可夫链的分析，证明了该算法的全局收敛性。对无功优化问题中离散变量的处理，提出了一种简单的“切割”技术，仅在适应值评估时对优化的离散变量进行“切割”。最后，对标准IEEE 30节点系统和一个实际的118节点系统进行仿真，结果表明，该算法具有最优解质量高、收敛特性好的优点，有较强的实用意义。     

基于差分进化的波浪能转换装置阵列优化

针对如何有效利用波浪辐射和散射以提升波浪发电系统效率的问题,提出采用差分进化算法对波浪能转换装置阵列进行优化排布。差分进化算法全局搜索能力强并且计算时间少;同时,差分进化算法在精度和收敛速度上没法两全且可能会陷入局部解,为了使优化结果更准确,引入了自适应变异算子的概念对差分进化算法进行改进,改进后的算法收敛速度相对较快而且结果准确度高。结合改进算法,分别针对不同浮子数目的阵列进行优化与对比分析。仿真结果表明,阵列规模越大,浮子之间的互补作用越大,波浪能转换装置的效率越高,这验证了所提阵列优化方案的有效性。     

基于推理模型和模糊评估算法的锅炉智能设计

结合规则推理和实例推理推理模型,提出针对锅炉设计的模糊评估算法,经过模型与算法的结合,可有效实现锅炉的智能化设计。通过对设计过程的详细描述,给出了锅炉参数化设计中相关参数定义及要求,理论上论证了该模糊评估算法与推理模型结合的设计方案的可行性。该设计方案的提出和应用,为锅炉的智能化设计研究提供了一种较为合理可行的思路。结合现场锅炉设计案例,成功实现了锅炉的智能设计,证明了该方案在实际应用中的有效性和正确性。同时,结合实例还给出了每个设计过程中的一些必要的设计前提。结论揭示了该研究对于锅炉CAD智能化设计具有较大的参考价值。     

Pole placement technique for PSS and TCSC-based stabilizer design using simulated annealing

A pole placement technique for power system stabilizer (PSS) and thyristor controlled series capacitor (TCSC) based stabilizer using simulated annealing (SA) algorithm is presented in this paper. The proposed approach employs SA optimization technique to PSS (SAPSS) and TCSC-based stabilizer (SACSC) design. The design problem is formulated as an optimization problem where SA is applied to search for the optimal setting of the proposed SAPSS and SACSC parameters. A pole placement-based objective function to shift the dominant eigenvalues to the left in the s-plane is considered. The proposed SAPSS and SACSC have been examined on a weakly connected power system with different disturbances, loading conditions, and system parameter variations. Eigenvalue analysis and nonlinear simulation results show the effectiveness and the robustness of the proposed stabilizers and their ability to provide efficient damping of low frequency oscillations. In addition, the performance of the proposed stabilizers outperforms that of the conventional power system stabilizer (CPSS). It is also observed that the proposed SACSC improves greatly the voltage profile of the system under severe disturbances.     

A Design Approach for Direct-Drive Permanent-Magnet Motors

This paper presents a design approach of a direct-drive permanent-magnet (PM) motor for a medium-sized injection-molding application. In the proposed approach, genetic-algorithm (GA) loop works to optimize the lamination design in order to meet the requirements for the target application. To achieve the design optimization within a realistic time scale, the repeated calculation required to obtain fitness evaluation does not use finite-element analysis (FEA) but consists of a geometric flux-tube-based nonlinear magnetic analysis developed specifically for this class of motors. The validity of the proposed design approach is verified through several comparative studies on the design results with FEA using a 942- 88.8-kW three-phase multipole interior PM motor, which is designed by the proposed optimizing GA approach.     

Optimal Design of Coreless Axial Flux Permanent Magnet Synchronous Generator with Reduced Cost Considering Improved PM Leakage Flux Model

This paper presents an optimal design of coreless axial flux permanent magnet (AFPM) synchronous generator using particle swarm optimization method based on sizing equations of the machine. The design optimization is performed in order to reduce the active material cost of the generator. General practical and mechanical limitations are considered as optimization constraints. A magnetic circuit model based on quasi three-dimensional (3-D) model of the coreless AFPM machine is taken into account to calculate the permanent magnet leakage flux (PMLF) accuracy. A computer-aided program is evaluated according to the proposed optimized design procedure that is used to design a 2-kW, 16-pole AFPM generator with two rotors and one coreless stator. Finally, the 3-D finite-element model (FEM) of the machine is prepared to confirm the validity of the proposed PMLF model and proposed optimized design algorithm.     

Pre‐arrangement of solvability,complexity, stability and quality of GPC systems

A design problem of generalized predictive control (GPC) of plants characterized by discrete‐time models with a non‐zero transportation‐delay is considered. Conditions for the existence of the solution of the problem in terms of relevant design parameters (tuning knobs) are proposed and the system characteristics are discussed. Several design hints suitable for such plant models are proposed. Consequently, it is shown that by a suitable choice of the GPC tuning knobs a definite pre‐arrangement of the solvability, complexity, stability and quality (including robustness) of the resultant GPC control systems can be achieved. Some numerical examples are also given to illustrate the design problem and proposed methodology. Copyright © 2002 John Wiley & Sons, Ltd.     

基于开关电源的EMI滤波器设计与实现

通过对某型号开关电源的电磁兼容性进行分析和测试,提出了针对此开关电源的干扰抑制滤波器的有效设计方法,并利用PSpice软件进行了滤波器的设计与仿真。遵循设计方法,针对该开关电源的电磁干扰(EMI)滤波器已经实现,通过实际测试结果验证了设计方法的正确性。     

永磁机构的研究与发展

从机械设计、电子控制、数学方法、计算机辅助技术和材料科学的角度,对永磁机构的研究进展进行综述、分析和展望,并提出学科交叉、综合设计的发展理念,促进永磁机构的系统化研究和发展。     

Coordinated Design of Power System Stabilizers and Static Phase Shifters Using Genetic Algorithm

Coordinated design of a power system stabilizer (PSS) and a static phase shifter (SPS) using genetic algorithm (GA) is investigated in this paper. The design problem of PSS and SPS controller is formulated as an optimization problem. An eigenvalue-based objective function to increase the system damping is proposed. Then, GA is employed to search for optimal controller parameters. Different control schemes have been proposed and tested on a weakly connected power system with different disturbances, loading conditions, and parameter variations. It was observed that although the PSS enhances the power system stability, the SPS controller provides most of the damping and improves the voltage profile of the system. The nonlinear simulation results show the effectiveness and robustness of the proposed control schemes over a wide range of loading conditions and system parameter variations.     

Immersion and Invariance-based Non-linear Coordinated Control for Generator Excitation and Static Synchronous Compensator of Power Systems

In this article, a non-linear coordinated control of generator excitation and a static synchronous compensator is proposed to enhance the transient stability of an electrical power system. The coordinated controller proposed is designed via immersion and invariance methodology. In particular, a non-linear model of the power system and immersion and invariance design method are used to achieve not only power angle stability but also frequency and voltage regulations following a large disturbance (a symmetrical three-phase short-circuit fault) on one transmission line or a small perturbation to mechanical power input to synchronous generators in the system. The controller design is validated using a simulation study on a single-machine infinite bus. Simulation results show that the proposed controller can not only keep the system transiently stable but also simultaneously achieve power angle stability and frequency and voltage regulation.     

A new coordination strategy of SSSC and PSS controllers in power system using SOA algorithm based on Pareto method

Along with the development of power grids and increasing the use of Flexible AC Transmission System (FACTS) devices, complex and unexpected interactions will be increased in power system. With considering to the non-linearity of power system, operating point changes and reaction between power system and FACTS devices, using of linear methods are not suitable for controller design. Therefore, the nonlinear model to design of Power System Stabilizer (PSS) and Static Synchronous Series Compensator (SSSC) coordinated controllers is considered here. In this paper, a new multi-objective function as an optimization problem is proposed for this coordination process. Also a beneficial strategy to solve this optimization problem using Seeker Optimization Algorithm (SOA) based on Pareto optimum method with high convergence speed is presented. In order to evaluate the performance of the proposed method, coordination strategy is applied on a four-machine system under different contingencies. The results of the proposed multi-objective function are obtained and compared with others in this system and finally, superior ability of the proposed method is observed.