Impact of the penetration of distributed generation on optimal reactive power dispatch

Optimal reactive power dispatch (ORPD) is a complex and non-linear problem, and is one of the sub-problems of optimal power flow (OPF) in a power system. ORPD is formulated as a single-objective problem to minimize the active power loss in a transmission system. In this work, power from distributed generation (DG) is integrated into a conventional power system and the ORPD problem is solved to minimize transmission line power loss. It proves that the application of DG not only contributes to power loss minimization and improvement of system stability but also reduces energy consumption from the conventional sources. A recently proposed meta-heuristic algorithm known as the JAYA algorithm is applied to the standard IEEE 14, 30, 57 and 118 bus systems to solve the newly developed ORPD problem with the incorporation of DG. The simulation results prove the superiority of the JAYA algorithm over others. The respective optimal values of DG power that should be injected into the four IEEE test systems to obtain the minimum transmission line power losses are also provided.     

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.     

基于多目标进化算法的统一潮流控制器稳定控制器鲁棒运行点选择

针对多机电力系统中UPFC稳定控制器鲁棒运行点的选择问题,提出了综合考虑UPFC装置向系统提供阻尼以及受控电力系统本身阻尼两个目标的选择方法,将该问题转化为一个多目标问题,并提出求解该问题的相应多目标进化算法（MOEA）,该算法基于Pareto排序选择方法,采取模糊修正、小生境算子、精英选种策略等技术,具有收敛速度快等优点.最后通过对新英格兰电力系统的仿真分析,验证了多目标进化方法在选取UPFC稳定控制器鲁棒运行点问题上的有效性.     

A hybrid BFOA–MOL approach for FACTS-based damping controller design using modified local input signal

A hybrid Bacteria Foraging Optimization Algorithm and Many Optimization Liaisons (hBFOA–MOL) is employed in this paper to design a Flexible Ac Transmission Systems (FACTS)-based damping controller for power system stability improvement. The input signal to the FACTS-based damping controller is derived from the locally measurable line active power. The design problem of the proposed controller is formulated as an optimization problem and hBFOA–MOL algorithm is employed to search for the optimal controller parameters. At the outset, this concept is applied to a Static Synchronous Series Compensator (SSSC) connected in a single-machine infinite bus (SMIB) power system and then extended to a two-area four-machine power system. The performances of the proposed controllers are evaluated in SMIB and multi-machine power system subjected to various severe disturbances. To show the effectiveness and robustness of the proposed design approach, simulation results are presented and compared with both local and remote signals. It is observed that the proposed controller with modified local input signal exhibits a superior damping performance in comparison to both remote and local input signals.     

Robust coordinated design of multiple and multi-type damping controller using differential evolution algorithm

A robust coordination scheme to improve the stability of a power system by optimal design of multiple and multi-type damping controllers is presented in this paper. The controllers considered are power system stabilizer (PSS) and static synchronous series compensator (SSSC)-based controller. Local measurements are provided as input signals to all the controllers. The coordinated design problem is formulated as an optimization problem and differential evolution (DE) algorithm is employed to search for the optimal controller parameters. The performance of the proposed controllers is evaluated for both single-machine infinite-bus power system and multi-machine power system. Nonlinear simulation results are presented over a wide range of loading conditions and system configurations to show the effectiveness and robustness of the proposed coordinated design approach. It is observed that the proposed controllers provide efficient damping to power system oscillations under a wide range of operating conditions and under various disturbances. Further, simulation results show that, in a multi-machine power system, the modal oscillations are effectively damped by the proposed approach.     

Power system stabilizer design based on the pole assignment technique for SIMO systems

A new power system stabilizer (PSS) design method for single-machine infinite-bus systems is developed. This design method not only assigns the poles corresponding to the electro-mechanical oscillation modes in the system, but also locates other system poles in suitable places in the s-plane. The design procedure is used first to translate a PSS design problem to an equivalent constant output feedback controller design problem for a single-input multi-output (SIMO) system. Then, a new algorithm developed in this paper is applied to design a constant output feedback controller to achieve the desired closed-loop system pole locations. Finally, the controller gains are transferred back to the parameters in the PSS. The extension of the method to multi-machine power systems is also illustrated.     

梯级水电站多目标模糊优化调度模型及其求解方法

根据梯级水电站不仅具有电力联系而且具有水力联系的运行特点,提出一种以年发电量和一级水电站耗水量为优化目标的梯级水电站多目标长期优化调度模型.通过定义各目标的隶属度函数,将多目标优化问题模糊化;采用最大模糊满意度法将多目标优化问题转化为单目标非线性规划问题;应用协调粒子群算法(CPSO)求解单目标优化问题.仿真验证了模型的正确性和求解方法的可行性,为梯级水电站优化调度提供了一种新颖有效的途径.     

基于人工免疫算法的电力系统最优潮流计算

基于一阶或二阶梯度的优化算法在计算电力系统最优潮流时经常陷入局部最优点，模拟进化算法具有较好的全局搜索能力，但是有时也由于过早成熟的现象而陷入局部最优点，文中提出了一种计算电力系统最优潮流的新算法－人工免疫算法，该算法是根据人或其他高等动物免疫系统的机理而设计的，将目标函数和一部分不等式约束条件作为抗原，将搜索空间的解作为抗体，依据抗原与抗体的结合力以及抗体之间的结合力对解进行评价和选择，通过抗体之间的相互激励作用提高了最优点附近的搜索效率，通过记忆细胞对抗体的抑制作用有效地摆脱局部最优点，应用此算法进行电力系统最优潮流计算，对IEEE30节点系统的计算结果说明了该算法的有效性。     

基于含连通图约束的背包问题的图分割方法

图分割技术(网络分割技术)在互联网研究、交通运输、电网故障诊断和电力系统解列等方面有着重要的意义。首次建立一个新的图分割问题——含连通图约束的背包问题(connected graph constrained knapsack problem,CGKP),并提出其有效近似算法。引入与图连通性相关的4个新节点集合,证明这些新节点集合的性质,并提出这些节点集合的搜索方法;结合新节点集合的性质及搜索算法,通过对含图约束的背包问题近似算法进行扩展,提出求解CGKP的近似算法,并讨论此算法的计算复杂性。算例结果证明了该算法的有效性。因电力系统主动最优解列问题在一定条件下可归结为一个CGKP,该研究成果为电力系统最优主动解列断面搜索问题的求解奠定了理论基础。     

Optimal Location of Thyristor-controlled Series Capacitor to Enhance Power Transfer Capability Using Firefly Algorithm

Abstract—The optimal power flow problem seeks to find an optimal profile of active and reactive power generations along with voltage magnitudes in such a manner as to minimize the total operating costs of a power system while satisfying network security constraints. This article presents a firefly algorithm to solve the optimal power flow problem incorporating a thyristor-controlled series capacitor. A thyristor-controlled series capacitor is considered to find the optimal location in transmission lines to enhance the power transfer capability of the transmission line. To assess the effectiveness of the proposed algorithm, it was tested on a 5-bus test system, an IEEE 14-bus system, and a modified IEEE 30-bus system, and it was compared with the genetic algorithm and differential evolution with and without a thyristor-controlled series capacitor. It has also been observed that the proposed algorithm can be applied to larger systems and does not suffer with computational difficulties. The results show that the firefly algorithm produces better results than others and has fast computing time for solving the optimal power flow problem with a thyristor-controlled series capacitor.     

一种无源滤波器的优化设计

针对电力系统谐波问题,提出了一种无源滤波器的优化设计方法.在研究了无源滤波器的构建基础之上,通过多目标遗传算法并结合整数与实数编码,采用目标函数的滤波效率来求解.优化设计方法与对应的遗传算法可有效的提高算法的全局搜索能力.最后,通过仿真实验对比研究,充分地验证了该无源滤波器设计方法的有效性,并具有较高的谐波抑制效率.     

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.     

Pole placement approach for robust optimum design of PSS and TCSC-based stabilizers using reinforcement learning automata

Power system stability enhancement via robust optimum design of power system stabilizers (PSSs) and thyristor controlled series capacitor (TCSC)-based stabilizers is thoroughly investigated in this paper. The design problem of PSS and TCSC-based stabilizers is formulated as an optimization problem where a reinforcement learning automata-based optimization algorithm is applied to search for the optimal setting of the proposed PSS and CSC parameters. A pole placement based objective function is considered to shift the dominant system eigenvalues to the left in the s-plane. For evaluation of the effectiveness and robustness of the proposed stabilizers, their performances have been examined on a weakly connected power system subjected to different disturbances, loading conditions, and system parameter variations. The nonlinear simulation results and eigenvalues analysis demonstrate the high performance of the proposed stabilizers and their ability to provide efficient damping of low frequency oscillations. In addition, it is observed that the proposed CSC has greatly improved the voltage profile of system under severe disturbances.     

基于MVO算法与改进目标函数的电力系统负荷频率控制

针对风电并网时的随机波动功率、负荷频率控制(load frequency control, LFC)系统参数变化所引起的电力系统频率稳定问题,提出了一种基于智能优化算法与改进目标函数的互联电网LFC系统最优PID控制器设计方法。首先,分析了基于PID控制的含风电互联电力系统LFC闭环模型。其次,在时间乘误差绝对值积分(integral of time multiplied absolute error, ITAE)性能指标的目标函数中考虑了区域控制器的输出信号偏差,对优化目标函数进行改进。采用性能优良的多元宇宙优化(multi-verse optimizer, MVO)算法先计算后验证的思路,寻优获得最优PID控制器参数。最后,以两区域4机组互联电力LFC系统为例,仿真验证了基于MVO算法结合改进目标函数所获得的PID控制器,比基于MVO算法所获得的PID控制器,对阶跃负荷扰动、随机负荷扰动、风电功率偏差扰动以及系统的参数变化,具有相对较好的鲁棒性能。并且,对控制器参数也具有相对较好的非脆弱性指标。     

基于免疫禁忌混合算法的多目标最优潮流计算

针对电力系统多目标最优潮流计算问题,提出了一种基于免疫禁忌混合算法的多目标模糊优化潮流计算的新方法。该方法运用模糊集理论来构造评价函数,实现了多目标优化问题向单目标优化问题的转化,兼顾了各子目标,保证了较高的整体优化水平;采用求解精度高、使用灵活的免疫禁忌混合算法来进行单目标寻优,准确地获取了符合实际的全局最优解。通过对IEEE 30节点系统进行多次多目标最优潮流仿真计算,并将计算结果分别与单目标最优潮流计算及采用粒子群算法、免疫算法等其它算法的结果进行比较和分析,验证了该方法是解决电力系统多目标最优潮流问题的一种有效方法。     

基于遗传算法的超导磁储能装置H2/H∞鲁棒控制器设计

提出了应用GA（遗传算法）设计H2／H∞鲁棒控制器的一般方法，使得在满足闭环系统的H∞范数小于指定的工程要求的条件下误差信号的H2范数最小，该问题可归结为一个带约束条件的极小值优化问题，并通过一种改进的遗传算法加以解决，该设计方法能对具有任意控制器结构的控制系统进行参数优化，与传统的鲁棒控制器设计方法相比，所提出的方法不仅可以提高控制器的鲁棒性，还具有易于进行参数优化的优点，将所提出的方法应用于超导磁储能装置（SMES）PI型鲁棒控制器的设计，时域仿真结果表明所设计的控制器具有很好的鲁棒性，在不同的运用工况下均能有效阻尼电力系统的振荡，此外，控制器还具有结构简单，易于工程实现的优点。     

Coordinated design of PSS and TCSC to mitigate interarea oscillations

Thyristor controlled series compensator (TCSC) as a promising series flexible AC transmission system (FACTS) device is generally used for controlling the real power flow in transmission lines. It can increase the system stability as the complementary functionality by minimizing the power oscillations. The effectiveness of TCSC in its primary and supplementary applications depends on the selection of its optimal location and defining a proper input signal. In this paper, a new method based on the active power sensitivity approach is applied to find the optimal location of TCSC. In addition, Hankel singular values (HSVs) and right half plane-zeros (RHP-zeros) analyses have been proposed to find the most appropriate stabilizing input signal for the supplementary functionality of TCSC to damp out the interarea modes of oscillation. Finally, the optimal design of power oscillation damper (POD) and simultaneous coordinated design of power system stabilizer (PSS) and POD are implemented separately in a large-scale power system. The tuning problem of POD-TCSC parameters as well as the coordinated POD-TCSC & PSS are converted to a multi-objective optimization problem and solved using particle swarm optimization (PSO) algorithm. The performance of the proposed method has been validated through eigenvalue analysis and nonlinear time domain simulation in a 16-machine 68-bus test system. The simulation results show a satisfactory robust performance with an excellent capability in damping of local and interarea power oscillations.     

电力系统无功优化的多智能体粒子群优化算法

无功优化是电力系统实现电压和无功功率最优控制和调度的基础,提出了一种全新的优化算法一多智能体粒子群优化算法来求解此类优化问题。该算法结合multi-agent系统和粒子群优化技术,构造了一个格子环境,所有Agent都固定在格子环境中。每一个Agent相当于粒子群优化算法中的一个粒子,它们通过与其邻居的竞争、合作和自学习操作,并且吸收了粒子群优化算法的进化机理,能够更快地、更精确地收敛到全局最优解。在IEEE30节点系统上进行校验,并与其它方法比较,结果表明,提出的算法具有质量高的解、收敛特性好、运行速度快的突出优点。     

邻域拓扑粒子群优化算法在电力系统无功优化中的应用

提出了一种基于邻域拓扑粒子群优化算法(NTPSO)的大规模电力系统无功优化新算法。该算法在概念上比标准PSO算法更精确,认为每个粒子是受它邻域范围内最优粒子的影响。研究了当前流行的五种邻域拓扑结构得到五种邻域拓扑粒子群优化算法,其中包括已在一系列标准函数上测试过的比其它拓扑效果更好的Square拓扑。文中应用这五种NTPSO分别对IEEE30节点系统和IEEE57节点系统进行了无功优化的仿真计算,结果表明基于Square拓扑的NTPSO算法的优化效果最好,为求解大规模电力系统无功优化问题提供了新的思路。     

基于改进细菌群体趋药性算法的无功优化

基于细菌群体趋药性（Bacterial Colony Chemotaxis,BCC）算法提出变速菌群趋药性（Gear Bacterial Colony Chemotaxis,GBCC）算法,将其应用于电力系统无功优化。GBCC算法引入带有权重系数的变速公式,使得GBCC算法前期能够较快地收敛于几个最优解的周围,后期能够在最优解周围进行细致搜索,克服了BCC算法易于收敛于局部最优解的缺点。建立基于GBCC算法的无功优化数学模型,给出GBCC算法的具体步骤。通过对IEEE30节点算例的测试,得到GBCC算法在无功优化问题上的收敛速度和优化效果。