Chaos embedded krill herd algorithm for optimal VAR dispatch problem of power system

Chaotic krill herd algorithm (KHA) (CKHA) is proposed in this paper to solve the optimal VAR dispatch problem of power system considering either minimization of real power loss or that of absolute value of total voltage deviation or improvements of voltage profile as an objective while satisfying all the equality and the inequality constraints of the power system network. Detailed studies of different chaotic maps are illustrated. Among these, Logistic map is considered in the proposed technique to improve the performance of the basic KHA. The performance of the proposed CKHA is implemented, successfully, on standard IEEE 14- and IEEE 118-bus test power systems in which the control of bus voltages, tap position of transformers and reactive power sources are involved. The results offered by the proposed CKHA are compared to other evolutionary optimization based techniques surfaced in the recent state-of-the-art literature. Simulation results indicate that the proposed CKHA approach yields better optimization efficacy over some other recent popular techniques in terms of results offered, effectiveness, quality of solution and convergence speed.     

含UPFC的电力系统最优潮流计算

由于UPFC能够控制母线电压和线路潮流,包含UPFC的电力系统最优潮流模型中须引入附加的等式约束和不等式的约束,增加了优化计算的复杂性,本文应用直接非线性原一对偶路径跟踪内点算法进行求解,并给出了3个试验系统的优化计算结果,验证该方法的有效性。     

考虑电能质量的分布式电源优化配置

针对大量电力电子设备投入电网造成严重电能质量问题的现状,提出考虑谐波畸变和电压暂降损失的分布式电源(Distributed Generator,DG)优化配置方法。该方法以DG配置成本、有功损耗、电压暂降损失最小为目标函数,并在满足配网潮流等式和不等式约束的基础上增加谐波畸变限值的约束条件,建立多目标优化模型,最后采用非劣排序遗传算法(Nondominated Sorting Genetic Algorithm-II,NSGA-II)求得最优配置方案。通过IEEE 33节点配电网络对此配置算法进行仿真验证,结果证明该方法得到的DG配置方案可有效降低谐波畸变率、暂降损失及网络损耗。     

电压稳定约束的最优潮流研究

针对电力系统将运行在更加接近电压稳定临界点的情况,建立了一种包含电压稳定约束的最优潮流(OPF)数学模型,在常规OPF模型基础上增加了一组电压稳定裕度约束作为不等式约束。引入能正确反映系统当前电压稳定程度的L指标函数作为电压稳定约束,通过调整该约束的上限值,可以获得系统所要求的电压稳定裕度。利用基于扰动KKT(Karush-Kuhn-Tucker)条件的原始-对偶内点算法对问题进行求解。多个IEEE测试系统上的仿真结果表明,该模型能较好地兼顾系统对电压安全性与经济性的要求;在电压稳定约束起作用时,发电总费用会随着系统对电压稳定要求的提高而增大;L指标约束的加入对系统的调节能力有一定影响;所用算法收敛性好、鲁棒性强,能有效地处理大量等式和不等式约束。     

Active and reactive dispatch with minimum control movements

This paper proposes a new formulation of the combined Optimal Active and Reactive Dispatch (OARD) problem with Minimum Control Movements (MCM) for the voltage control devices. The main objective of the proposed model is to minimize the total power system operation cost which include fuel cost of generators and switching cost of equipments like tap transformers and shunt capacitors. Practical constraints such as maximum allowable number of switching operation in a day for tap changing transformers and switchable capacitors are taken into consideration. A penalty based approach has been formulated to tackle with the switching costs of adjustable equipments. The problem has been formulated as a nonlinear dynamic optimization problem with the presence of both continuous and discrete control variables and solved using Artificial Bee’s Colony (ABC) algorithm. The approach has been tested on IEEE 30 bus system and the simulation is carried out in MATLAB. In order to verify the effectiveness of the results obtained, both active and reactive power dispatch problems have been solved separately and compared with the proposed approach. Results demonstrate the effectiveness of the proposed approach.     

基于拉格朗日函数鞍距分配的广义内点法

不等式约束的处理是电力系统优化分析中比较困难的问题。文中根据拉格朗日函数的鞍点理论,将优化问题的等式约束进行松弛,形成计及等式约束的原始问题以及相应的对偶问题。通过定义原始和对偶问题之间的鞍距,并将鞍距在不等式约束之间进行分配,从而形成不同的针对不等式约束拉格朗日乘子的修正方程,进一步形成不同的优化算法。推导表明,内点罚函数法只是拉格朗日鞍点理论应用的一个特例。所提出的基于拉格朗日函数鞍距分配的广义内点法可以在电力系统优化分析中进行应用,将其应用于大规模间歇式电源接入情况下的电力系统最大传输能力问题中时,IEEE 30节点系统的计算结果及IEEE 14节点系统中不同算法的比较结果表明,此算法能够有效处理潮流问题不等式约束。     

考虑相邻时段投切次数约束的动态无功优化启发式策略

在开关日动作次数约束基础上,考虑分接头挡位的相邻时段动作次数约束,建立了一种更加实用的动态无功优化新模型。按照"先投先切、后投后切"原则,将同一母线的多个电容器组等效为1个集中变量,并根据其中的电容器组个数来确定等效变量的动态约束值。由此,既满足了电容器的实际动态约束,又减小了模型的变量规模。在求解动态无功优化问题时,以混合智能算法为基础,提出处理动态约束的启发式调整策略,采用稀疏技术,有效提高了算法的效率。IEEE14与IEEE30节点系统和一个实际系统的仿真结果验证了所述模型的正确性和算法的有效性。     

Improved artificial bee colony algorithm considering harvest season for computing economic dispatch on power system

This paper proposes the harvest season artificial bee colony (HSABC) algorithm, a novel improvement of the artificial bee colony (ABC) algorithm, for computing an economic dispatch solution of a power system based on fuel consumption and the produced emissions. A standard model of the power system, the IEEE‐62 bus system, is used to show the performance of HSABC using equality and inequality constraints to determine the optimal solution for the economic operation of the power system. Simulations involving the proposed algorithm show that HSABC has better ability to determine the minimum values for the operating cost problem with faster convergence and shorter running time when compared to the traditional ABC algorithm. © 2014 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

Performance assessment of PSO,DE and hybrid PSO–DE algorithms when applied to the dispatch of generation and demand

This work presents a comparison of three evolutionary algorithms, the particle swarm optimization, the differential evolution algorithm and a hybrid algorithm derived from the previous, when applied to the generation and demand dispatch problem. An optimization problem is formulated in the context of a small grid with partially flexible demand that can be shifted along a time horizon. It is assumed that grid operator dispatches generation and flexible demand along the time horizon aiming at minimizing generation costs. Consumption restrictions associated with flexible demand are modeled by equality and inequality energy constraints. Power flow equality constraints and inequality constraints due to operational limits for each dispatch interval are represented. The paper discusses a methodology for evolutionary algorithms performance assessment and states the importance of using statistical tools. The comparison is initially conducted using the IEEE 30-bus test system. Problem dimension effect is addressed considering different number of dispatch intervals in the time horizon. Moreover, the algorithms are applied to the 192-bus system of a Brazilian distribution utility, in the particular context of a load management program for large consumers of the company. In this application, the quality of the near-optimal solution obtained with the stochastic algorithms is evaluated by comparing with an analytical optimization algorithm solution.     

Two-stage optimization algorithm for short-term reactive power planning based on zonal approach

There are various methods for procurement of reactive power as an ancillary service in deregulated market environment. Reactive power market model based on voltage control zones and two-step optimal power flow algorithm is proposed in this paper. Zones are formed by splitting the power system or a control area of an interconnected power system into autonomous voltage sub-areas with sufficient reactive power reserves using the electrical distance method. Every zone formes a single reactive power market. First step of an optimization algorithm determines zonal reactive power prices based on generator's cost functions for reactive power production. Total cost minimization is the goal of the second optimization step where the final dispatching decision is made according to transmission losses and zonal reactive power prices respecting power system planned conditions and security constraints. Proposed algorithm is tested on IEEE 39 bus test system ensuring the system operator's minimal payment for reactive power and transmission losses, without jeopardizing power system security.     

Siting and Sizing of Distributed Generation and Shunt Capacitor Banks in Radial Distribution System Using Constriction Factor Particle Swarm Optimization

Abstract

This article proffers an advanced solution to allocate the distributed generation (DG) and shunt capacitor (SC) banks optimally in radial distribution system (RDS) to alleviate the power losses, revamp the voltage profile, inflate the voltage stability index, shrink the total voltage deviation, and acquire more energy savings. In the framework of finding the optimal site and size of DGs and SC banks, Particle swarm optimization (PSO) technique is modified with constriction factor and the same is aimed to apply in IEEE 33-bus system and practical Brazil 136-bus RDS. Different case studies are carried out for multiobjective problems while considering equality and inequality constraints. A comparative analysis with PSO and modified PSO is presented to project the precedence of the adopted algorithm. In addition, the obtained results are also compared to the recently surfaced few state-of-the-art algorithms to present the optimizing capability of the implemented algorithm.     

Steady-state load shedding schemes: a performance comparison

This paper presents a formulation of the optimal steady-state load shedding problem that uses the sum of the squares of the difference between the connected active and reactive load and the supplied active and reactive power. The latter are treated as dependent variables modelled as functions of bus voltages only. The equality constraints associated with the power system load curtailment problem are the power flow equations in polar form utilizing the nodal admittance matrix approach. The inequality constraints are characterized by limits on line flows, voltage magnitudes and angles, and active and reactive power generations. The MINOS nonlinear optimization package is used to implement the optimization process. Testing is done using IEEE 14- and 30-bus power systems, and results obtained. The optimal results are compared with results obtained using two earlier approaches. The results obtained using the proposed approach appear to give a better optimal state of the power system.     

一种基于Karmarkar内点法的最优潮流算法

以原－对偶内点算法（Ｋａｒｍａｒｋａｒ内点法的一种变形）为基本算法解算最优潮流问题，综合考虑非线性目标函数和约束条件，结合牛顿法最优潮流先进的稀疏矩阵技术，并且提出了一种新的原－对偶内点算法迭代步长选取原则和障碍参数修正策略。算例表明本算法有较好的数值稳定性，优化结果精确，对不等式约束有较强的处理能力，显示了内点算法应用于大规模电力系统优化问题的良好前景。     

电力市场初期两部制无功定价方法

提出了一种电力市场初期的两部制无功定价方法,以有功电能成本和无功电量成本最优为目标函数,以潮流方程为等式约束,以运行及安全约束为不等式约束。建议的内点非线性规划法原理简单、计算量小。所提两部制无功电价模型的核心想法为:一方面,提出电力市场下无功源以运行成本参与竞争,以解决现有的一部制电价对无功的运行成本补偿不足的问题;另一方面,提出一种新的无功容量电价分解方案,以解决现有的一部制电价对无功投资成本回收不明确的问题。电量电价加容量电价形成了建议的两部制无功电价。IEEE-30节点系统算例验证了建议的无功优化算法和无功价格模型的有效性和实用性。     

最小化能量损耗的配电网络动态无功优化算法

提出了一种完整的配电网络非线性混合整数动态无功优化模型及数学优化算法.该模型以全天能量损耗最小为目标,其约束条件不仅包括了各个时间断面的等式和不等式约束,而且还包括了有载调压变压器分接头和可投切并联电容器组的动作次数约束.为此,提出采用非线性原对偶内点法内嵌变量离散化罚函数的方法求解该模型,所推导出的高阶修正方程具有特殊的分块矩阵结构,可以充分利用稀疏处理技巧以提高算法的速度及对配电网络规模的适应性.最后以广州鹿鸣网配电系统作为算例,分析不同动作次数限制对配电网络电容器最优投切结果的影响,验证了该算法的正确性和有效性以及在限制控制设备动作次数方面取得的成功.     

Optimal reactive power dispatch based on harmony search algorithm

This paper presents a harmony search algorithm for optimal reactive power dispatch (ORPD) problem. Optimal reactive power dispatch is a mixed integer, nonlinear optimization problem which includes both continuous and discrete control variables. The proposed algorithm is used to find the settings of control variables such as generator voltages, tap positions of tap changing transformers and the amount of reactive compensation devices to optimize a certain object. The objects are power transmission loss, voltage stability and voltage profile which are optimized separately. In the presented method, the inequality constraints are handled by penalty coefficients. The study is implemented on IEEE 30 and 57-bus systems and the results are compared with other evolutionary programs such as simple genetic algorithm (SGA) and particle swarm optimization (PSO) which have been used in the last decade and also other algorithms that have been developed in the recent years.     

基于改进QPSO算法的BIPV建筑削峰填谷双层优化配置策略

针对BIPV建筑负荷削峰填谷和接入配电网后考虑网损、电压偏差的选址优化问题,提出了一种BIPV建筑双层能源系统优化模型。模型下层在考虑DG成本和环境成本的前提下,利用储能对负荷进行削峰填谷,模型上层在考虑配电网网损、电压偏差的前提下对BIPV和储能的选址方案进行优化。在求解该双层模型时利用量子理论中的量子行为和概率表达特性设计了一种改进的多目标量子粒子群算法,在解的处理上引入了一种动态ε不可行度约束支配函数。以IEEE30节点系统为参考系统,算例优化结果表明:BIPV建筑负荷峰谷差、配电网网损和电压偏差得到了有效降低,证明了所提配置优化策略的可行性;同时也表明,所提算法在全局寻优能力和种群多样性方面得到了明显提升。     

SFOA算法在电力系统多目标无功优化的应用

电力系统由于无功分布不合理引起的事故越来越多。以系统网损、电压平均偏离、电压安全稳定裕度3个指标建立无功优化模型,引入了动态罚函数体现状态变量约束在优化过程的影响,并用个人偏好约束下的权值分配方法根据用户的需求对各个指标分配权值,采用SFOA算法求得电力系统多目标无功优化在可行域内的最优解。从SFOA算法和PSO算法运用于IEEE 30和IEEE 57节点系统优化结果比较表明:所提出的算法是可行有效的。     

考虑SVC和储能接入电网的多目标协同经济调度

针对风电并网引起的电网功率波动和安全运行问题,提出一种考虑SVC和储能的多目标协同经济调度优化方法。以典型日运行为例,建立了以系统综合运行成本、电压偏差和系统网损最小为目标函数的经济调度多目标优化模型,在优化过程中对经济调度和无功优化模型的目标进行协同迭代,获取兼顾电网经济性和安全性的最优解,并将结果与利用权重系数法获得的Pareto前沿面进行对比分析,通过对IEEE RTS-24节点系统进行仿真分析,验证其算法的合理性和可行性。     

基于人工鱼群算法的静态电压稳定评估

提出一种静态电压稳定裕度计算的新方法——人工鱼群算法,该算法就是根据鱼群觅食和生长特点,通过构造人工鱼来模仿鱼群的觅食、聚群及追尾行为,从而实现寻优,能快速寻找到全局最优解,从而求得电压稳定裕度的最大值。运用该算法对IEEE14和IEEE39等节点系统进行仿真计算,计算结果与连续潮流算法和原-对偶内点算法比较,证明此算法的有效性。