优化电压质量、控制无功平衡的方法和措施

通过对监控所辖站电压、无功运行情况及采用的优化电压质量、控制无功平衡方法分析,指出了当前电压控制和无功平衡方面存在的问题,对提高电压管理水平、优化电网运行提出了解决策略     

电力系统无功优化方案比较

电力系统无功优化是保证系统安全、经济运行的一项有效手段,是降低网损、提高电压质量的重要措施。传统的静态无功优化不能满足实际运行需要,考虑系统负荷变化以及控制设备动作次数限制的无功优化更有实际应用价值。本文尽可能的细述电力系统无功优化的各种方案,并一一进行了分析讨论,提出应寻求多种算法最佳配合的混和优化策略,以弥补相互的不足。     

基于模糊理论的变电站无功综合控制策略的研究

针对传统九区图法由于未考虑电压调节与无功调节间的相互影响,造成对边界处的控制结果震荡,从而导致装置频繁动作的缺陷,提出了基于模糊理论的变电站无功综合控制策略。仿真结果表明,模糊边界九区法以及模糊控制的采用,可在保持无功调节效果不变,且不增加无功调节次数的情况下,明显减少装置动作次数并减小电压波动,该策略有效。     

含分布式电源配电网的无功优化

提出了基于改进遗传算法的含分布式发电的配电网无功优化方法。构建了包含分布式发电系统的配电网无功优化数学模型,采用改进遗传算法对分布式发电的无功功率给定进行了优化。通过算例仿真结果,说明所设计的改进优化算法在减少功率损耗和提高电压质量上的有效性和正确性。     

配网无功电压实时优化集中控制策略研究

电网运行的安全、经济、稳定是电力企业研究的重点内容,电压质量的稳定对于用电设备的质量稳定有着重要的作用,电力系统实现无功电压集中化控制是目前的研究热点,实现无功电压的优化控制,是保障电网运行水平稳定安全的前提。本文从无功电压的控制现状进行分析,探讨集中控制技术方案,并对无功电压的优化集中控制策略进行优化。     

基于变电站综合自动化的电压、无功调节策略

目前新建的66kV及以下变电所基本上都要求采用变电站综合自动化系统,在变电站综合自动化系统的基础上,通过增加电压无功控制软件模块,以在传统九域图基础上扩充的十七域图为基本控制策略,通过对系统电压（高压侧电压）正常和越限情况的分析,实现电压无功优化控制,避免了九域图控制的跳区现象,减少了控制次数,延长了变压器以及无功设备的寿命,同时又兼顾了系统电压。并以负荷大小确定电压无功限值,使VQC（电压无功综合控制系统）调节更实用化。     

基于组合的电力系统无功优化及组合权重的确定

电力系统无功优化是提高电力系统电压质量的重要措施之一,我们有必要采取措施使电力系统的无功规划达到最优,但是由于电力系统无功规划的非线性和复杂性,所以很难找到一种方法使其达到最优解,本文基于此点,将多种无功优化方法求得的解进行组合,从而得到一组最优解,减小了一种方法所带来的误差,本文还根据每种解的误差确定每种解在组合中的权重。     

风电场集群集中控制策略仿真

本文提出了一种风电场SVC综合优化控制策略及实现方法,在理论上,这一控制策略将无功补偿装置合理控制可以优化电网的无功潮流,提高安全稳定极限和输送能力,然后结合仿真分析了SVC在相关风电场电压控制中的作用并总结出风电场稳定运行的一些建议。     

变电站电压、无功综合控制的原理

对变电站电压无功综合控制系统提出了越来越高的要求。本文从变电站无功优化控制和提高变电站综合自动化水平着眼,对变电站电压无功控制应用方面问题进行了分析。     

电网无功电压优化控制

无功电压控制对于电力系统的安全、经济运行有着重要的意义,随着计算机和自动化技术的发展,自动电压控制(AVC)的实现成为可能.但在实际情况中存在诸多问题.本文就电网无功电压控制策略进行探讨,在分析电网无功电压控制目的和意义的基础上,提出电网无功优化策略及相关的优化算法.     

Automatic generation control of two-area electrical power systems via optimal fuzzy classical controller

The interconnected large-scale power systems are liable to performance degradation under the presence of sudden small load demands, parameter ambiguity and structural changes. Due to this, to supply reliable electric power with good quality, robust and intelligent control strategies are extremely requisite in automatic generation control (AGC) of power systems. Hence, this paper presents an output scaling factor (SF) based fuzzy classical controller to enrich AGC conduct of two-area electrical power systems. An implementation of imperialist competitive algorithm (ICA) is made to optimize the output SF of fuzzy proportional integral (FPI) controller employing integral of squared error criterion. Initially the study is conducted on a well accepted two-area non-reheat thermal system with and without considering the appropriate generation rate constraint (GRC). The advantage of the proposed controller is illustrated by comparing the results with fuzzy controller and bacterial foraging optimization algorithm (BFOA)/genetic algorithm (GA)/particle swarm optimization (PSO)/hybrid BFOA-PSO algorithm/firefly algorithm (FA)/hybrid FA-pattern search (hFA-PS) optimized PI/PID controller prevalent in the literature. The proposed approach is further extended to a newly emerged two-area reheat thermal-PV system. The superiority of the method is depicted by contrasting the results of GA/FA tuned PI controller. The proposed control approach is also implemented on a multi-unit multi-source hydrothermal power system and its advantage is established by Correlating its results with GA/hFA-PS tuned PI, hFA-PS/grey wolf optimization (GWO) tuned PID and BFOA tuned FPI controllers. Finally, a sensitivity analysis is performed to demonstrate the robustness of the proposed method to broad changes in the system parameters and size and/or location of step load perturbation.     

Analysis of integrated STATCOM-SMES based on three-phase three-level multi-pulse voltage source inverter for high power utility applications

This paper is aimed to investigate the operating characteristics of a static synchronous compensator (STATCOM) integrated with superconducting magnetic energy storage (SMES) for high power applications in the transmission network level. The STATCOM controller topology comprises multi-level multi-pulse neutral-point clamped-type (NPC) voltage source inverters (VSIs) using the harmonics cancellation technique, and incorporates a SMES coil. An innovative two-quadrant multi-level dc-dc converter is proposed to effectively interface the STATCOM with the superconducting coil using a buck-boost topology with neutral point voltage control capabilities; thus enabling to simultaneously control both active and reactive power exchange with the high voltage power system. A detailed analysis of major system variables is presented, including analytical results and digital simulations using the MATLAB/Simulink environment. Moreover, a three-level control scheme is designed, including a full decoupled current control strategy in the d-q reference frame with a novel controller to prevent the STATCOM dc bus capacitors voltage drift/imbalance and an enhanced power system frequency controller.     

一种快速有效的相似视频检索方法

提出了一种新的相似视频快速检索方法.根据视频的时空分布统计得到图像特征码和视频单元,通过统计视频单元数量度量视频相似性.为了适应可扩展计算的需要,提出了基于聚类索引表的检索方法.通过对大规模数据库的查询测试证明该相似性检索算法快速有效.     

基于人工神经网络的相位跟踪研究

本文介绍了一种基于人工神经网络的相位跟踪控制方法,当电网并网时,用于对控制电流与电网电压进行同相位跟踪,以实现对电网电压的同步跟踪。经MATLAB电力系统动态仿真,验证了该文提出的BP控制方法,跟踪性能良好,具有较强地自适应能力。     

和声模糊聚类在读者兴趣度建模中的应用

本文采取了3种必要的措施提高了聚类质量:考虑到各维数据特征属性对聚类效果影响不同,采用了基于统计方法的维度加权的方法进行特征选择;对于和声搜索算法的调音概率进行了改进,将改进的和声搜索算法和模糊聚类相结合用于快速寻找最优的聚类中心;循环测试各种中心数情况下的聚类质量以获得最佳的类中心数。接着,该算法被应用于图书馆读者兴趣度建模中,用于识别图书馆日常运行时各读者借阅图书的类型,实验表明该算法较其它算法更优。这样的读者兴趣度聚类分析可以进行图书推荐,从而提高图书馆的运行效率。     

Population extremal optimization-based extended distributed model predictive load frequency control of multi-area interconnected power systems

How to design a set of optimal distributed load frequency controllers for a multi-area interconnected power system is an important but still challenging issue in the field of modern electric power systems. This paper presents an adaptive population extremal optimization-based extended distributed model predictive load frequency control method called PEO-EDMPC for a multi-area interconnected power system. The key idea behind the proposed method is formulating the dynamic load frequency control issue of each area power system as an extended distributed discrete-time state-space model based on an extended state vector, obtaining a distributed dynamic extended predictive model, and rolling optimization of real-time control output signal by adopting an adaptive population extremal optimization algorithm, where the fitness is evaluated by the weighted sum of square predicted errors and square future control values. The superiority of the proposed PEO-EDMPC method to a traditional distributed model predictive control method, a population extremal optimization-based distributed proportional-integral control algorithm and a traditional distributed integral control method is demonstrated by the simulation studies on two-area and three-area interconnected power systems in cases of normal, perturbed system parameters and dynamical load disturbances.     

Event triggering power sharing control for AC/DC microgrids based on P -F droop curve method

The power sharing of AC/DC micro-grids is researched in this paper. The proposed strategy mainly include two parts: the primary power event triggering control with secondary control and an adaptive quasi sliding mode voltage control in inner-loop. Firstly, a event triggering power sharing control (ETPSC) based on $P?F$ droop curve is developed to regulate the voltage and frequency of AC and voltage of DC with the aim of the proportional power sharing between AC and DC micro-grids. The triggered threshold of ETPSC can be chosen to decide the transmitted power between AC and DC micro-grids. When the difference power between AC and DC micro-grids is less than the triggered threshold of power flow, there is no power sharing between AC and DC micro-grids, which can less the number of switching the power flow direction and the transmitted line power loss. The ETPSC has a great robust for the disturbances of load and improve the stability of the system. An adaptive quasi-sliding-mode control,which is implemented easily and flexibly with small computational burden and only based on input/output (I/O) measurement data but not the model any more, is used to control voltage in inner-loop. The effectiveness of the proposed control schemes is demonstrated by some numerical simulations and experimental results.     

Determination of feeding rate ratio in coupled fed-batch fermentation with pH feedback considering limited number of switches

This paper focuses on binary optimal control of fed-batch fermentation of glycerol by Klebsiella pneumoniaewith pH feedback considering limited number of switches. To maximize the concentration of 1,3-propanediol at terminal time, we propose a binary optimal control problem subjected to time-coupled combinatorial constraint with the ratio of feeding rate of glycerol to that of NaOH as control variables. Based on time-scaling transformation and discretization, the binary optimal control problem is first transformed into a mixed binary parameter optimization problem consisting of not only continuous variables but also binary variables, which is then divided into two subproblems via combinatorial integral approximation decomposition. Finally, a novel fruit fly optimizer with modified sine cosine algorithm and adaptive maximum dwell rounding are applied to solve the obtained subproblems numerically. Numerical results show the rationality and feasibility of the proposed method.     

Adaptive multi objective differential evolution with fuzzy decision making in preventive and corrective control approaches for voltage security enhancement

This paper presents a multi objective differential evolution (MODE) based voltage security enhancement through combined preventive-corrective control strategy. Load shedding, generation rescheduling and optimal utilization of FACTS devices are considered for security enhancement. Maximum l-index of load buses is taken as the indicator of voltage stability. Minimization of cost of FACTS devices, minimization of amount of load shedding along with improvement in voltage stability are the objectives of this multi objective optimization problem. The optimal location of FACTS devices are selected using modal analysis technique. The buses for load shedding are selected based on the minimum eigen value of load flow Jacobian. The proposed MODE algorithm employs DE/randSF/1/bin strategy scheme with self tuned parameter which employs binomial crossover and difference vector based mutation. A fuzzy based decision making algorithm is employed to get the best compromise solution from the non dominated solutions. The proposed MODE is also tested with statistical performance metrices. The proposed methodology is implemented on IEEE 30 bus and IEEE 57 bus test systems. The proposed MODE method provides better solutions in the pareto optimal front than the other optimization techniques such as MOGA and NSGA II under combined preventive–corrective control approach. In IEEE 30 bus system, the amount of load shedding is reduced by 40% and voltage stability is improved by 15% and in IEEE 57 bus system, the amount of load shedding is reduced by 15.4% and voltage stability is improved by 13% by the proposed approach. Hence the simulation results show that the proposed approach provides considerable reduction in the amount of load shedding and enhancement of voltage stability by including generation rescheduling and utilization of FACTS devices.     

Distributed fixed-Time secondary control for islanded microgrids: Tackling abnormal data

This paper deals with the distributed secondary control problem for multiple distributed generators in an islanded microgrid. A distributed fixed-time secondary controller is designed for each generator using only its neighbors’ information, where saturation functions are introduced to the designed controllers to constrain the adverse influence of abnormal data from neighbors. Several indicator variables are introduced to reformulate the saturation function to reduce conservatism. The objective of this paper is to realize the recovery of the frequency and voltage as well as the active power-sharing within a fixed time. The fixed-time convergence of the proposed distributed control algorithm is analyzed through rigorous analysis. Also, the upper bound of the settling time is derived, which does not depend on the system’s initial state. Finally, a simulation example is utilized to verify the effectiveness of the proposed distributed control scheme by using the MATLAB/SimPowerSystems toolbox.