基于混合整数线性规划的含ZIP负荷有源配电网重构方法

随着分布式电源并网和负荷类型的日益复杂,传统配电网重构模型尚未考虑复杂的综合负荷模型。提出了考虑ZIP综合负荷模型的有源配电网混合整数线性规划方法。在辐射状配电网二阶锥潮流模型的基础上,通过线性回归法将ZIP负荷模型等效为ZP负荷模型,建立基于混合整数二阶锥规划的有源配电网重构模型。通过多面体近似将二阶锥约束进行线性化,建立基于混合整数线性规划的有源配电网重构模型。在三个不同规模配电系统的仿真结果表明,基于混合整数线性规划的有源配电网重构模型精度与基于混合整数二阶锥规划的几乎相同,但优化效率提高了15%~30%,具有较高的优化精度和效率。     

基于遗传算法和TS算法的配电网电容器实时优化投切策略

分析比较了遗传算法（ＧＡ）和ＴａｕｂＳｅａｒｃｈ（ＴＳ）算法的特点,针对配电网电容器实时投切的非线性、整数寻优和快速必的特点,提出了改进的ＧＡ／ＴＳ混合算法并用于配电网电容器的实时投切。该算法用ＧＡ求解ＴＳ的初值,然后用ＴＳ求出量优势。算例结果说明了该算法的有效性和可行性,它具有在线运动的潜力。     

基于混合整数半定规划的含分布式电源配电网无功优化

含分布式电源配电网的无功优化是一个复杂的非凸非线性混合整数规划问题。提出一种求解含分布式电源配电网无功优化问题的新方法。该方法首先将不含离散变量的无功优化原始数学模型转化并松弛为凸的半定规划模型,以保证解的全局最优性,且能在多项式时间内完成;然后,加入离散变量将该模型扩展为混合整数半定规划模型。采用奔德斯分解法将该模型分解为简单的混合整数线性规划主问题和仅含连续变量的半定规划子问题,通过主子问题的交替迭代求得最优解。最后,通过算例系统仿真验证了所提方法具有松弛精确、求解高效、寻优准确等优点。     

中压配电变压器优化规划

建立了城市电网中压配电变压器位置、容量和供电范围优化规划的模型,然后在此基础上给出了求解这一大规模、非线性混合整数规划问题的实用的、大范围首寻优的三角连续分割算法。实际算例表明,该模型和算法能更好地满足规划的要求。     

基于混合整数二阶锥规划的主动配电网最优潮流研究

最优潮流是一个非线性优化问题,其具有复杂繁琐、维数高、约束多以及变量多的特性。将其应用于主动配电网也是当下研究热点。文章建立了使主动配电网有功损耗最小的最优潮流模型;考虑配电网可控单元和开关状态,采用改进后的辐射状约束与潮流约束进行变换,合理松弛后变为二阶锥约束,建立混合整数二阶锥规划模型。采用Yalmip工具包进行建模,调用Gurobi商用算法包对其进行求解计算;通过算例对采用粒子群算法与采用混合整数二阶锥规划方法的计算结果进行对比分析,结果证明混合整数二阶锥方法更适用于主动配电网,验证了该方法的高效性和稳定性。     

配电网补偿电容分组优化投切的一种实用算法

无功补偿电容器投切是一个带有整数约束的组合优化问题。“禁限”算法是近年来出现的求解整数规划、混合整数规划、组合优化问题的一种高效算法。本文对基本禁限算法进行了改进,并借助于“改进遗传算法”中的优化编码技术,处理配电网补偿电容分组优化投切问题,取得良好的效果。     

基于半定规划的三相主动配电网无功优化

配电网无功优化是一个非凸非线性混合整数规划问题,一直难以获得最优解。在考虑配电网三相不平衡的基础上,将配电网无功优化问题松弛为一个凸的半定规划(semi-definite programming,SDP),而凸问题可以得到最优解。采用灵敏度分析和分支定界相结合的方法处理含离散-连续变量的混合规划问题。基于改进的IEEE33节点三相配电系统进行了算例分析,验证了该方法能够精确求解非凸非线性规划问题。     

基于改进Benders分解的配电网扩展规划机会约束优化方法

为了解决已有配电系统规划中非线性潮流模型建模问题和不确定性优化效率问题,本文提出了基于双线性Benders分解的配电网扩展规划机会约束优化方法。首先通过在规划投资层面和运行优化层面进行分阶段,构建了两阶段随机混合整数二阶锥规划模型;然后为了避免极端场景下导致的高昂投资成本,进一步扩展了传统的Benders分解方法,设计了基于双线性Benders分解的机会约束优化方法。通过三个算例系统验证了本文所提出方法的卓越的优化性能。     

基于混合整数二阶锥规划的三相有源配电网无功优化

三相有源配电网无功优化本质上属于非线性非凸规划问题,目前尚缺乏严格的有效求解方法。针对配电网辐射状运行特点,文中建立了基于支路潮流形式的配电网的三相无功优化模型,然后采用二阶锥松弛技术将原始优化模型转化为具有凸可行域的数学规划形式。考虑电容器等离散的补偿设备后,模型进一步扩展为含离散变量的混合整数二阶锥规划模型。该模型可被现有优化算法包高效求解。采用IEEE 33节点和IEEE 123节点系统进行算例分析,验证了所提出的方法的寻优稳定性和计算高效性。     

配电网故障恢复重构算法研究

首先给出了一个综合考虑开关操作次数最少和网损最小的故障恢复重构的混合整数规划模型。Tabu搜索技术是一种高效的启发式搜索技术,适合于解决整数规划和混合整数规划问题。文中将Tabu搜索技术应用于所建立的故障模型,并较详细地介绍了其求解过程。最后运用算例验证了Tabu搜索法能有效地求解所给出的故障恢复问题。     

Tabu search algorithm for network synthesis

Large scale combinatorial problems such as the network expansion problem present an amazingly high number of alternative configurations with practically the same investment, but with substantially different structures (configurations obtained with different sets of circuit/transformer additions). The proposed parallel tabu search algorithm has shown to be effective in exploring this type of optimization landscape. The algorithm is a third generation tabu search procedure with several advanced features. This is the most comprehensive combinatorial optimization technique available for treating difficult problems such as the transmission expansion planning. The method includes features of a variety of other approaches such as heuristic search, simulated annealing and genetic algorithms. In all test cases studied there are new generation, load sites which can be connected to an existing main network: such connections may require more than one line, transformer addition, which makes the problem harder in the sense that more combinations have to be considered     

Comparative study of modern heuristic algorithms to servicerestoration in distribution systems

This paper presents a comparative study for four modern heuristic algorithms (MHAs) to service restoration in distribution systems: reactive tabu search, tabu search, parallel simulated annealing, and genetic algorithm. Since service restoration is an emergency control in distribution control centers to restore out-of-service areas as soon as possible, it requires fast computation and high quality solutions for customers' satisfaction. The problem can be formulated as a combinatorial optimization problem to divide the out-of-service area to each power source. The effectiveness of the MHAs is compared against each other on typical service restoration problems     

基于改进蜂群算法的工业机器人路径规划研究

针对工业机器人在复杂环境中运动的避障及路径优化问题,提出基于改进人工蜂群算法的工业机器人避障路径规划策略。首先针对传统人工蜂群算法搜索能力不足且容易陷入局部最优的问题,将禁忌搜索思想引入到人工蜂群算法最优解搜索过程中,形成了基于禁忌搜索的改进型人工蜂群算法,然后将其应用到工业机器人的路径规划问题中,并进行了仿真实验。结果表明,改进后的方法能够得到最优的路径,且寻优速度快、过程稳定。该方法可用于解决工业机器人路径规划问题。     

基于改进粒子群优化算法的配电网络重构

提出了一种求解配电网络重构的改进粒子群优化（PSO）算法。结合配电网络的特点改进了PSO算法粒子位置的更新规则，提高了迭代过程中有效解的产生概率；并结合禁忌（Tabu）搜索的记忆功能和藐视准则，克服了PSO算法的早熟问题。算，其结果与最优解吻合，证实了算法的有效性，并与较，表明了算法具有更好的搜索效率。最后对3个典型IEEE测试系统进行优化计Tabu搜索算法和遗传算法的计算结果相比     

Method for minimum‐loss reconfiguration of distribution system by tabu search

This paper proposes a loss minimum reconfiguration method by tabu search for an open‐loop radial distribution system with distributed generators. The problem is to find the optimal normal open sectionalizing switch positions which minimize the total distribution line losses subjected to the line/transformer capacity constraints and voltage constraint. Generally, the problem is mathematically formulated as a complex combinatorial optimization problem or mixed integer programming problem, and is solved by using mathematical programming method, heuristic algorithm, intelligent method, and so on. However, a satisfactory algorithm for power companies has not yet been attained in both computational burden and solution accuracy. Thus, in this paper, the authors propose a method to solve the above problem by using tabu search (TS). Reverse power flow caused by distributed generators can be included in the solution algorithm. TS is one of the meta‐heuristic algorithms, and sometimes has been evaluated to be better than genetic algorithm (GA) or simulated annealing (SA) from viewpoints of both computational speed and solution accuracy. In order to evaluate the validity and efficiency of the algorithm, several numerical examples are shown in this paper. © 2005 Wiley Periodicals, Inc. Electr Eng Jpn, 152(2): 18–25, 2005; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20086     

蚁群算法在配电网重构的应用

配电网络重构是一个非常复杂的大规模组合优化问题。蚁群算法作为一种现代启发式寻优技术,适合于求解组合优化问题,其主要特点是正反馈、分布式计算、易与其它算法结合以及富于建设性贪婪启发式搜索。对配电网络从图论拓扑结构上进行分析,将配网重构问题转化为求图的生成树问题,并以破圈法为基础得到快速而有效地求解图的生成树的方法。在应用蚁群算法求解配网重构问题时,通过首支路选择随机化和取消蚁群算法常用的启发值的方法,扩大算法搜索范围,使算法可以跳出局部最优化陷阱,改善算法的搜索效果。对IEEE 69网络的算例表明,该方法能以较少的计算量和较大的概率收敛于全局最优解。     

Application of genetic algorithms to service restoration in distribution systems

Service restoration in distribution systems can be formulated as a combinatorial optimization problem to determine power sources for each load considering radial network constraints and power source limits. Until now, the problem has been considered using conventional methods, e.g., the branch-and-bounds method, expert system, neural networks, and fuzzy reasoning. Recently, Genetic Algorithms (GA) have been recognized as one of the efficient methods for solving large combinatorial optimization problems. The method can perform parallel search, and can more easily search optimal solutions. This paper presents an application of GA to service restoration in distribution systems. The feasibility of the proposed method is demonstrated on a typical distribution system model. The result shows that the method can solve the problem efficiently, and this tendency becomes dominant by increasing problem dimensions.     

用改进的Tabu搜索方法优化补偿电容器分档投切的研究

对基本的 Tabu搜索方法进行了改进 ,将“改进遗传算法”中的优化编码技术引入 Tabu搜索方法 ,并在此基础上引入动态管理退出迭代判定条件、动态管理 Tabu表深度和动态管理邻域搜索规模等 ,用以处理补偿电容器分档投切的组合优化问题 ,并给出了算例     

多阶段输电网络最优规划的并行蚁群算法

多阶段输电网络最优规划是一个复杂的非线性组合优化问题,难以采用传统的数学优化方法求解。蚁群算法是近年来出现的用于解决组合优化问题的一种高效的内启发式搜索技术,但存在着未成熟收敛问题。文中给出了多阶段输电网络最优规划的数学模型及其解的向量形式;详细分析了传统蚁群算法的未成熟收敛现象及其原因;提出一种并行蚁群算法并用于求解多阶段输电网络最优规划问题。并行蚁群算法无需初始可行解,能很好地协调局部搜索与全局搜索,在加快计算速度的同时有效地避免了因参数设置、种群规模等不同而引起的未成熟收敛。对实际算例的计算结果表明,该方法具有很高的计算效率和良好的全局收敛性。     

基于人工鱼群算法的智能交流接触器虚拟样机优化设计

人工鱼群算法是一种新型的随机搜索优化算法,为求解组合的复杂优化问题提供了一种新的方法.基于网格划分策略和禁忌搜索算法的改进型人工鱼群算法使优化过程能够更好地取得全局最优精确解.本文将改进型人工鱼群算法引入到智能交流接触器吸合与释放全动态过程控制参数和机构结构参数的优化设计中,不仅取得了综合优化的效果,而且保证了机构的快...