电力市场环境下的无功潮流优化

为了满足电力市场环境下的无功潮流优化运行,详细分析了电力市场环境下无功成本的发生;由于系统发生故障或系统负荷增长而造成系统的无功短缺是电压失稳的主要原因,提出了一个简单实用的故障筛选和排序方法,并以严重事故下电压稳定作为约束条件建立了电力市场环境下无功潮流优化的数学模型,再用免疫算法求解此模型。IEEE-30系统算例结果表明该模型的正确性和算法的可行性。详细比较不同电压稳定标准下及不同体制环境下无功潮流优化的结果得出,在电力市场环境下必须将减少无功成本纳入无功潮流优化目标函数中。     

考虑发电机安全运行极限的非固定分段无功优化模型及其算法

针对目前无功优化中没有根据不同发电机运行区域建立相应的无功辅助费用的问题，考虑了发电机安全运行极限约束，按照无功输出能力的不同，把发电机运行域分为了4个区，并给出了各个区域的发电机无功辅助费用计算函数。建立了以系统有功网损费用与发电机无功辅助费用之和最小为目标函数的无功优化模型，其对应的优化问题是一个具有非固定分段特点的非线性混合整数规划问题。文中提出了2种优化算法来求解该优化问题：结合启发式规则的混合整数规划内点法HEUIPM，其计算速度虽快，但为局部优化算法，并且在某些情况下存在不收敛的可能性；基于非线性内点法和免疫遗传算法所提出的启发式混合随机优化算法IPMIGA，该算法是全局优化的, 没有收敛性问题, 但其计算速度比HEUIPM慢很多。所以文中将2种方法结合起来，在程序设计时, 先用HEUIPM算法, 遇到不收敛时自动转到IPMIGA算法。对节点数从14到171的5个测试系统进行了仿真计算，结果验证了所提算法的有效性。     

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).     

A hybrid genetic algorithm-interior point method for optimal reactive power flow

By integrating a genetic algorithm (GA) with a nonlinear interior point method (IPM), a novel hybrid method for the optimal reactive power flow (ORPF) problem is proposed in this paper. The proposed method can be mainly divided into two parts. The first part is to solve the ORPF with the IPM by relaxing the discrete variables. The second part is to decompose the original ORPF into two sub-problems: continuous optimization and discrete optimization. The GA is used to solve the discrete optimization with the continuous variables being fixed, whereas the IPM solves the continuous optimization with the discrete variables being constant. The optimal solution can be obtained by solving the two sub-problems alternately. A dynamic adjustment strategy is also proposed to make the GA and the IPM to complement each other and to enhance the efficiency of the hybrid proposed method. Numerical simulations on the IEEE 30-bus, IEEE 118-bus and Chongqing 161-bus test systems illustrate that the proposed hybrid method is efficient for the ORPF problem.     

考虑二重预想事故的在线电压稳定预防控制

提出了一种基于原对偶内点算法的安全约束最优潮流的数学模型,以控制代价最小化为目标,不仅考虑了正常状态下的安全约束,还同时考虑到了预想事故后的安全约束以及电压稳定裕度的约束。在线电压稳定评估系统中,同时考虑单重预想事故及其引发的继发性二重预想事故,分别进行筛选和排序,综合形成预想事故集。根据预想事故集,基于上述模型依次对其中每一预想事故进行预防控制,构建在线电压稳定预防控制模块,当系统处于不安全状态时,能够及时提供合理的预防控制策略,保证系统安全运行。以IEEE 118节点测试系统为算例,验证了所提出模型的正确性。     

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。     

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。     

Multi-objective optimal reactive power flow including voltage security and demand profile classification

This paper proposes a method to optimize reactive power flow (ORPF) with regard to multiple objectives while maintaining system voltage security across a time-domain. Compromise programming is employed in the ORPF formulation, which is designed to minimize both losses and payment for the reactive power service in the framework of the UK daily balancing market. In coordination with ORPF, continuation power flow (CPF) is applied to evaluate and maintain the voltage security margin of the system. Prior to the optimisation procedure, the related control parameters can be grouped with the aid of a load classification method in order to simplify the control actions. During the optimisation, through the application of both ORPF and CPF, multi-objective optimisation can be achieved with voltage security at an acceptable level. The Ward and Hale 6-bus system and a 60-bus UK test system are presented to illustrate the application of the proposed modeling framework.     

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。     

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.     

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 security-constrained power scheduling by Benders decomposition

This paper presents a Benders decomposition approach to determine the optimal day-ahead power scheduling in a pool-organized power system, taking into account dispatch, network and security constraints. The study model considers the daily market and the technical constraints resolution as two different and consecutive processes. The daily market is solved in a first stage subject to economical criteria exclusively and then, the constraints solution algorithm is applied to this initial dispatch through the redispatching method. The Benders partitioning algorithm is applied to this constraints solution process to obtain an optimal secure power scheduling.     

考虑电压稳定约束的无功优化新模型

为了提高电力系统的安全水平,有必要在无功优化中考虑静态电压稳定约束.现有模型以发电机组恒定不变的无功上下限值来确定电压稳定极限,由此可能导致无功的优化运行不满足实际发电机组的运行极限约束.建立了一种含静态电压稳定约束的无功优化新模型.其中,目标函数为正常状态的有功网损最小,约束方程包括正常状态和临界状态的潮流及其他安全约束和电压稳定裕度约束.由于采用一组基于发电机运行极限图的分段函数来准确反映发电机组的无功限制,从而克服了现有模型可能违反发电机组运行极限约束的问题.采用预测-校正原对偶内点法来求解无功优化新模型,通过IEEE30节点系统的仿真计算,验证了本文所建模型的可行性.     

含暂态能量裕度约束多故障最优潮流计算

借助暂态能量裕度对发电机有功和无功出力的解析灵敏度，将暂态能量裕度约束直接加入最优潮流模型中，建立含暂态能量裕度约束多故障最优潮流逐次线性规划模型，采用单纯形法求解，取得了较好的效果。此外，还提出了根据大步长单故障最优潮流近似计算获得的暂态能量裕度进行故障扫描方法，并寻找到同一失稳模式下影响系统稳定的关键故障，验证了满足关键故障稳定性要求的最优潮流解可以同时满足同失稳模式下的其它故障的稳定约束。新英格兰10机39节点系统的最优潮流及暂态稳定计算验证了所提方法的有效性。所有优化结果均用一个在电力系统中广泛使用的暂态稳定仿真程序进行了验证。     

二重预想事故排序的快速计算

在线安全分析中 ,二重预想事故由于其后果的严重性已受到越来越多的关注。在本文中 ,提出仅考虑由于一重预想事故引发的继发性二重预想事故 ,即不考虑由于偶然原因引起的两预想事故同时发生的情况 ,在进行计算时 ,采用了完全边界法和自适应边界法相结合的方法 ,并提出了包含电压、无功与有功的综合性能指标 ,从而大大提高了预想事故筛选的速度 ,并且预想事故筛选过程同时进行了一重预想事故筛选和二重预想事故筛选 ,为运行人员提供了更多有用的信息。     

一种多分区互联电网分布式无功优化算法

电网互联进程不断加快和系统规模的不断扩大对互联电网无功优化计算提出了更高的要求。提出了一种基于子网边界节点等值注入功率的多分区互联电网无功优化分布式协调优化算法。基于电网监控分层分区的特点,通过建立保留分区间联络线的简化外网模型,将子网间边界向量相等的耦合约束转化为边界节点注入功率修正方程的等式约束。构造边界节点电压加权修正的外层协调环节,依靠等值注入功率和对应边界节点电压向量的数值更新与传递实现全网无功优化问题的分布式求解。该方法有效地降低了协调层的参与度,进一步提高了子网无功优化的独立性,符合无功优化和控制的本地性要求。对多个IEEE试验系统进行了数值仿真测试与分析,结果表明方法具有良好的有效性和适用性。     

基于非线性内点法的安全约束最优潮流(二)算法实现

提出一种考虑多预想事故的安全约束最优潮流内点算法实施方案.讨论了预想事故集中,起作用预想事故的监视与强制策略及不可行预想事故的辨识.根据简约KKT(Karush-Kuhn-Tucker)系统的带边列分块对角特殊结构,推导了内点安全约束最优潮流的一种分解协调实施算法.为保证预想事故扫描对安全约束最优潮流的支撑,提出了一种能量管理系统中安全约束最优潮流和静态安全分析模块间的衔接和交互方案.算法在IEEE 14节点等4个系统上,对全部非解列型开断事故进行了大量的计算,结果表明,算法有效、可靠.安全约束最优潮流解与经典最优潮流解在安全性和经济性上的比较则显示了将静态安全约束引入经典最优潮流的必要性.     

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。     

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.     

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。