基于遗传算法和内点法的无功优化混合策略

基于遗传算法与内点法，文中提出了一种新颖的混合策略来求解无功优化问题：不考虑无功优化中的离散约束，采用内点法求解得到初始解；根据优化变量的不同性质，将原无功优化问题分解为离散优化和连续优化2个子问题，并采用遗传算法和内点法交替求解。在遗传迭代的不同阶段，针对种群个体的不同特点，分别对遗传算法和内点法的具体实施方案进行了动态调整，使两者的优化结果互为基础、相互利用，保证了混合策略的整体寻优效率。IEEE30和IEEE118节点系统的仿真计算结果表明：与其他混合算法相比，该混合策略在计算速度和优化效果方面都具有明显的优势。     

基于内点法和改进粒子群算法的无功优化混合策略

基于内点法与粒子群算法,提出了一种混合策略来求解电力系统无功优化问题。根据优化变量的不同性质将无功优化问题分解为离散优化和连续优化两个子问题,采用改进的粒子群优化算法和内点法交替求解,使两者的优化结果互为基础,提高了混合策略的整体寻优效率;根据粒子运动趋势及目标函数中网损与节点电压无功的相关性,对基本粒子群算法进行改进,自适应调整惯性权重和罚因子;以IEEE30节点系统和某实际地区电网作为试验系统,验证了该算法的正确性和有效性。     

离散粒子群与内点法结合的电力系统无功优化

基于离散粒子群优化算法与内点法,提出了一种新颖的混合策略来求解电力系统无功优化问题：不考虑无功优化中的离散约束,采用内点法求解得到初始解;根据优化变量的不同性质将无功优化问题分解为离散优化和连续优化2个子问题,并采用离散粒子群优化算法和内点法交替求解,使两者的优化结果互为基础、相互利用,从而保证了混合策略的整体寻优效率。以IEEE30和IEEE118节点作为试验系统,与常规的离散优化算法做比较,验证了该算法的正确性和有效性。     

基于内点法和改进遗传算法的无功优化组合策略

提出了一种求解无功优化问题的组合策略,该策略将无功优化问题分解为连续优化和离散优化2个子问题,分别用预测–校正内点法和改进遗传算法进行求解。考虑到实际电网在进行无功优化控制时,发电机是主要的调节手段,先不考虑离散变量的约束,采用预测–校正内点法优化连续变量;然后保持连续变量不变,用改进遗传算法优化离散变量;再返回到连续优化阶段,如此交替求解。当出现相邻的连续优化阶段和离散优化阶段网损变化的差值小于设定值时,停止优化。IEEE14、30、57、118节点系统的仿真结果表明,该策略比其它组合算法在收敛性和计算效率上更具优越性。     

基于混沌免疫混合算法的多目标无功优化

针对目前评价多目标函数解的不足，提出了将多目标函数各个解映射成多维空间中不同的点，利用这些点与理想点之间的欧氏距离来衡量各个解的优劣；同时针对无功优化、混沌优化算法和免疫算法的特点，提出了在采用免疫算法进行无功优化的记忆抗体群中，运用混沌优化方法和免疫算法的交叉和变异等操作对无功优化的连续变量和离散变量进行交替优化求解，并将它们运用于以降低有功损耗，提高电压稳定裕度及减小电压偏移为目标的无功优化中；通过 IEEE-30和IEEE-118节点算例系统验证了混合算法及最优解评价方法的正确性和可行性。     

基于内点法与改进遗传法的无功规划优化混合算法

建立了利用调节发电机端电压、可带载调压变压器分接头与静止电容器组的补偿容量来获得系统年综合费用最小的无功规划优化数学模型。将此问题分成连续优化和离散优化两个子问题,采用非线性内点法和改进遗传算法交替求解的混合算法。在迭代的不同阶段,分别对内点法和改进遗传算法进行收敛条件改进,使两者的优化结果互为基础、相互利用,保证了混合算法的整体寻优效率。118节点系统的无功优化计算表明,所提算法可有效提高单一算法的收敛性能和运算速度。     

Decomposition-coordination interior point method and its application to multi-area optimal reactive power flow

A decomposition-coordination interior point method (DIPM) is presented and applied to the multi-area optimal reactive power flow (ORPF) problem in this paper. In the method, the area distributed ORPF problem is first formed by introducing duplicated border variables. Then the nonlinear primal dual interior point method (IPM) is directly applied to the distributed ORPF problem in which a Newton system with border-matrix-blocks is formulated. Finally the overall ORPF problem is solved in decomposition iterations with the Newton system being decoupled. The proposed DIPM inherits the good performance of the traditional IPM with a feature appropriate for distributed calculations among multiple areas. It can be easily extended to other distributed optimization problems of power systems. Numeric results of five IEEE Test Systems are demonstrated and comparisons are made with those obtained using the traditional auxiliary problem principle (APP) method. The results show that the DIPM for the multi-area OPRF problem requires less iterations and CPU time, has better stability in convergence, and reaches better optimality compared to the traditional auxiliary problem principle method.     

Optimal VAR control for improvements in voltage profiles and for real power loss minimization using Biogeography Based Optimization

In this paper, a Biogeography Based Optimization (BBO) technique is introduced to solve multi-constrained optimal reactive power flow (ORPF) problem in power system. ORPF is a multi-objective nonlinear optimization problem that minimizes the bus voltage deviation and real power loss. The feasibility of the proposed algorithm is demonstrated for IEEE 30-bus system and IEEE 118-bus system. A comparison of simulation results reveals optimization efficacy of the proposed scheme over other well established population based optimization techniques like conventional particle swarm optimization (PSO), general passive congregation PSO (GPAC), local passive congregation PSO (LPAC), coordinated aggregation (CA) and interior point based OPF (IP-OPF).     

基于IPM-intPSO的两阶段动态无功优化算法

提出一种基于内点法(IPM)和整数粒子群(intPSO)算法相结合的启发搜索-变量校正两阶段动态无功优化算法。首先,采用intPSO算法求解离散变量,并利用IPM处理连续变量,通过两者交替迭代得到静态无功优化的求解方法;然后,在保证网损最小的同时,自适应得到最优动态分段数,克服传统依据负荷曲线人为分段方法的缺点;最后,对目标函数在启发搜索的结果上进行变量校正的再优化。IEEE 9、14、30、57、118节点测试系统的仿真结果验证了所提算法的有效性。     

基于广义主从分裂的输配电网一体化分布式无功优化方法

大量分布式电源接入配电网后,输、配电网间无功电压关系更加密切,传统输、配电网无功优化孤立进行已不再合适。根据输、配电网运行管理的独立性,提出了一种基于广义主从分裂思想的输配电网一体化分布式无功优化方法。输配全局无功优化问题分解为输电网优化主子问题、各配电网优化从子问题及边界一致性判别问题。各子网无功优化子问题采用对偶规划类算法求解,离散变量采用罚函数法处理以保持增广拉格朗日函数的可微性。通过由对偶乘子构造的边界灵敏度实现输、配电网子问题间的解耦,输配电网控制中心间通过传递边界变量及其灵敏度信息实现分布式协调。对IEEE 30节点系统(输电网)和含多种分布式电源的IEEE 33节点系统(配电网)进行仿真,验证了所提方法的有效性。     

Artificial bee colony algorithm for solving multi-objective optimal power flow problem

This paper presents a new and efficient method for solving optimal power flow (OPF) problem in electric power systems. In the proposed approach, artificial bee colony (ABC) algorithm is employed as the main optimizer for optimal adjustments of the power system control variables of the OPF problem. The control variables involve both continuous and discrete variables. Different objective functions such as convex and non-convex fuel costs, total active power loss, voltage profile improvement, voltage stability enhancement and total emission cost are chosen for this highly constrained nonlinear non-convex optimization problem. The validity and effectiveness of the proposed method is tested with the IEEE 9-bus system, IEEE 30-bus system and IEEE 57-bus system, and the test results are compared with the results found by other heuristic methods reported in the literature recently. The simulation results obtained show that the proposed ABC algorithm provides accurate solutions for any type of the objective functions.     

基于多种群分层粒子群优化算法的电力系统低压减载优化方法研究

低压减载是维护电力系统电压稳定的一道重要防线。最优减载问题是离散变量(地点和轮次)和连续变量(各轮的控制量)的混合优化问题。提出了一种利用多种群分层粒子群优化算法(HSPPSO)求解最优减载问题的新思路,采用受动态电压约束的系统最优潮流所建立的优化模型,以所切负荷总量最小为目标函数。最后以IEEE-39节点作为算例,结果与标准粒子群算法(PSO)和遗传算法(GA)对比,得出在同样的稳定裕度和迭代次数要求下,HSPP-SO算法总能够得到最小的减载量,表现出了在求解UVLS问题时的良好适应性。     

基于遗传算法和内点法的旋转备用经济分配

从经济角度分析,构建以系统发电成本和旋转备用成本最小为目标,以系统安全性要求为约束的电力系统短期经济调度数学模型。将此问题划分为离散优化和连续优化两个子问题,采用遗传算法和内点法相结合的混合算法来求解。仿真结果表明,提出的模型和算法是合理的和可行的。     

A new hybrid approach for the solution of nonconvex economic dispatch problem with valve-point effects

Economic dispatch (ED) generally formulated as convex problem using optimization techniques by approximating generator input/output characteristic curves of monotonically increasing nature results in an inaccurate dispatch. The genetic algorithm has previously been used for the solution of problem for economic dispatch but takes longer time to converge to near optimal results. The hybrid approach is one of the methodologies used to fine tune the near optimal results produced by GA. This paper proposes new hybrid approach to solve the ED problem by using the valve-point effect. The approach we propose combines the genetic algorithm (GA) with active power optimization (APO) based on the Newton's second order approach (NSO). The genetic algorithm acts as a global optimizer giving near optimal generation schedule, which becomes the input for generation buses in APO algorithm. This algorithm acting as local search technique dispatching the generated active power of units for minimization of cost and gives optimum generation schedule. Three machines 6-bus, IEEE 5-machines 14-bus, and IEEE 6-mchines 30-bus systems have been tested for validation of our approach. Results of the proposed scheme compared with results obtained from GA alone give significant improvements in the generation cost showing the promise of the proposed approach.     

基于分支定界—原对偶内点法的日前无功优化

现有的日前无功优化模型较少考虑次日电压稳定问题,且算法无法准确处理离散变量及时段间耦合约束。针对此现状,提出了一种计及分区动态无功储备的日前无功优化模型,并采用分支定界—原对偶内点法对其进行求解。在求解过程中,利用分支定界树使离散变量逐步逼近离散值,通过合理的分支剪支策略满足离散变量的时段间耦合约束,将日前无功优化问题转换为一系列仅含连续变量的单时段无功优化问题进行求解。IEEE 30和IEEE 118节点系统的仿真结果表明了所提模型与方法的有效性。     

一种混合智能算法在配电网络重构中的应用

提出了一种新的混合智能方法用来解决配电网络重构问题。该方法结合了遗传算法（GA）和粒子群优化算法（PSO）两者的优点，体现出较GA和PSO更好的寻优性能。在寻优过程中，部分个体以PSO方法迭代，其它个体进行GA中的交叉和变异操作，整个群体信息共享，同时采用自适应参数机制和优胜劣汰的思想进化。通过对IEEE16节点、IEEE33节点、IEEE69节点测试系统的计算和分析表明，该方法在解决配电网络重构问题上具有很高的搜索效率和寻优性能。     

PCPDIPM based optimal reactive power flow model with discrete variables

This paper presents a new approach to deal with the optimal reactive power flow (ORPF) problem with the discrete control variables. First, a quadratic ORPF model based on augmented rectangular coordinates is established by treatment with the TLC branch; and then quadratic penalty functions are incorporated into the proposed model to handle the discrete control variables; at last, the predictor corrector primal dual interior point method (PCPDIPM) is used to implement the optimization.In the PCPDIPM based ORPF solution, the quadratic discretization formulation results in the constant Hessians that all have elements of 1, or −1, or the penalty factor, and mostly being zero, thereby accelerating the entire optimal process significantly. Experimental results are provided comparing the performance of the proposed discretization approach with that of the conventional one.     

电力系统无功优化的LRS-PSO算法

提出一种应用局部随机搜索粒子群优化（LRS—PSO）算法求解电力系统无功优化的新方法。使用概率调用策略调用局部随机搜索（LRS）算子。给出了适合无功优化问题的LRS算子的具体实现以及应用LRS—PSO算法求解电力系统无功优化的步骤。对IEEE30节点测试系统进行了无功优化计算,并与标准遗传算法（SGA）、粒子群优化（PSO）算法的测试结果进行了比较。仿真结果表明,与SGA、PSO算法相比,应用LRS—PSO算法求解无功优化问题具有质量更高的解,收敛特性更好。     

Single and Multi-objective Optimal Power Flow Using Grey Wolf Optimizer and Differential Evolution Algorithms

This article applies the grey wolf optimizer and differential evolution (DE) algorithms to solve the optimal power flow (OPF) problem. Both algorithms are used to optimize single objective functions sequentially under the system constraints. Then, the DE algorithm is utilized to solve multi-objective OPF problems. The indicator of the static line stability index is incorporated into the OPF problem. The fuzzy-based Pareto front method is tested to find the best compromise point of multi-objective functions. The proposed algorithms are used to determine the optimal values of the continuous and discrete control variables. These algorithms are applied to the standard IEEE 30-bus and 118-bus systems with different scenarios. The simulation results are investigated and analyzed. The achieved results show the effectiveness of the proposed algorithms in comparison with the other recent heuristic algorithms in the literature.     

单相光伏大量接入的三相不平衡配电网无功优化

随着光伏发电等大量非全相运行的分布式电源(DG)接入,配电网固有的三相不平衡特征更加突出,传统无功优化方法因忽略了三相不平衡导致效果较差。文中提出一种三相不平衡主动配电网的无功优化模型,以系统负序电压最小和网络损耗最小为目标,考虑有载调压变压器、分组投切电容器、静止无功补偿装置等离散和连续控制变量,形成一个带有二次约束的混合整数二次规划问题。利用分支定界法处理该混合整数规划问题,将原问题松弛为多个不含离散变量的子问题,分别求得各子问题中设备的控制量,进而求得原问题的最优解。采用扩展的IEEE 33节点三相测试系统仿真计算,验证了所述模型和方法的有效性。