LOSS REDUCTION IN DISTRIBUTION NETWORKS USING NEW NETWORK RECONFIGURATION ALGORITHM

ABSTRACT

Network reconfiguration is an operation task, and consists in the determination of the switching operations such to reach the minimum loss conditions of the distribution networks. In this paper, a general formulation of the network reconfiguration for loss minimization is given for the optimization of distribution loss reduction and a solution approach is presented. The solution employs a search over different radial configurations, created by considering branch exchange type switches. The solution algorithm for loss minimization has been developed based on the two stage solution methodology. The first stage of this solution algorithm finds a loop which gives the maximum loss reduction in the network. For this purpose a simple-to-use formula, called loop loss reduction formula, has been developed. To find a branch exchange, which results in the maximum loss reduction in the loop, the second stage applies a proposed technique called distance-center technique. Therefore, the solution algorithm of the proposed method can identify the most effective branch exchange operations for loss reduction, with a minimum computational efforts. The solution algorithm of the proposed method has been tested, with very promising results, on a 69-bus radial distribution system. Test results prove that, via proposed network reconfiguration for loss minimization, real power loss is reduced significantly, and that the voltage profile of the network is considerably improved. As compared to the established methods the proposed method eliminates the need to run numerous load flows.     

Multi-year expansion planning for distribution systems

A multi-term distribution system expansion planning method is proposed. Many mathematical programming approaches have been proposed in this area. However, because of the complexity of the problem or the limitations of a computational time and memory size, these methods can only be applied to a small-scale system. To solve large-scale problems, the authors propose a new decomposition algorithm based on the branch exchange method. A n-years planning problem is decomposed into n one-year planning problems, and one-year results are coordinated through what can be called the forward/backward path. The validity and effectiveness of the algorithm are ascertained by applying it to real-scale numerical examples     

Joint Optimization for Power Loss Reduction in Distribution Systems

In distribution systems, network reconfiguration and capacitor control, generally, are used to reduce real power losses and to improve voltage profiles. Since both capacitor control and network reconfiguration belong to the complicated combinatorial optimization problems, it is hard to combine them efficiently for better optimization results. In this paper, a joint optimization algorithm of combining network reconfiguration and capacitor control is proposed for loss reduction in distribution systems. To achieve high performance and high efficiency of the proposed algorithm, an improved adaptive genetic algorithm (IAGA) is developed to optimize capacitor switching, and a simplified branch exchange algorithm is developed to find the optimal network structure for each genetic instance at each iteration of capacitor optimization algorithm. The solution algorithm has been implemented into a software package and tested on a 119-bus distribution system with very promising results.     

基于多智能体Actor-Critic算法的异构网络能效优化

为了最大限度地提高异构网络（Heterogeneous Hetworks,HetNets）的能量利用率,本文将能效优化问题设计为一个多级决策问题,根据优化目标的资源分配,首先将初始问题分解为对参数ABS（几乎空白子帧,Almost Blank Subframe）比例和CRE（小区间范围扩展,Cell Range Expansion）进行优化的两个子问题,采用多智能体Actor-Critic（Multi-Agent Actor-Critic,MAAC）算法对子问题进行求解,然后通过迭代各优化子问题的解,解决初始优化问题。在参数优化过程中,将单个小基站作为一个智能体,采用MAAC算法对各自CRE寻找最优解,实现小区间异步CRE优化。实验结果表明,该方法在保持能效稳定提高的前提下,相比较于表格式Q学习的循环Q学习算法,其收敛速度提高了40％,并且通过异步优化CRE的方式取得了基站间更均衡的负载。     

基于最优流法与Mayeda生成树算法相结合的单阶段配网重构新方法

针对随机类优化算法用于配网重构计算时间长,而启发式算法用于配网重构存在的低精度解等的缺点,提出一种基于最优流法与Mayeda生成树算法相结合的单阶段配网重构新方法。该方法利用最优流法从支路交换的候选集中快速确定用于Mayeda生成树算法中用于支路交换的支路,从而既回避了随机进化选择方法进化慢的缺点,又回避了穷举法生成过多的劣树的缺点,等效于采用优化技术局部剔除了部分比当前树更劣的树,而明显加快其最优树的搜索过程。方法的优点是充分利用了最优流方法的快速性、Mayeda生成树算法的解空间的完备性,进行良好的结合实现了两者的优势互补,而提高其计算效率。算例验证了方法的有效性。方法因其快速性及至少得到次优解的特点而具有工程应用价值。     

A multistage multiobjective substation siting and sizing model based on operator–repair genetic algorithm

The establishment of a multistage multiobjective substation siting and sizing planning model, taking into account various constraints such as load flow constraint, maximum capacity constraint, and maximum power supply radius constraint makes possible substation planning between multiple years to be adjusted to achieve an optimal overall plan. Through multiple optimization objectives, it is possible to prevent the plan from becoming useless because of excessive changes in power supply affiliation during the multistage optimization process. To find the optimal solution for the model, a repair operator is proposed and used with an improved multiobjective genetic algorithm to repair the decision variables for each chromosome corresponding to one stage so as to satisfy the constraints while ensuring that population diversity evolves heuristically to the optimal solution. Moreover, a tournament selection operator based on crowding distance is adopted, which can prevent the algorithm from premature convergence and make populations trend to the Pareto frontier. Experimental results show that the proposed model and algorithm can efficiently solve the issue of rolling planning between multiple target years and achieve a joint optimal planning. © 2014 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

Combined heat and power economic dispatch using exchange market algorithm

Combined heat and power economic dispatch (CHPED) is one of the critical issues in power systems, playing key role in economic performance of the system. CHPED is a challenging optimization problem of non-linear and non-convex type. Thus, evolutionary and heuristic algorithms are employed as effective tools in solving this problem. This paper applies newly proposed exchange market algorithm (EMA) on CHPED problem. EMA is a powerful and robust algorithm. With two powerful absorbing operators pulling solutions toward optimality and two smart searching operators, EMA is able to extract optimum point in optimization problem. In order to examine the proposed algorithm’s capabilities and find optimum solution for CHPED problem, several test systems considering valve-point effect, system power loss and system constraints are optimized. The obtained results prove high capability of EMA in extracting optimum points. The results also show that this algorithm can be utilized as an efficient and reliable tool in solving CHPED problem.     

基于支路交换和声搜索算法的配网重构

采用标准和声搜索算法HSA(harmony search algorithm)进行配网重构时,在搜索最优方案的过程中容易陷入局部最优,且搜索结果受初始参数值的影响。为此,引入结合启发式规则的支路交换法对新和声进行局部搜索,生成第2个新和声,增加了和声记忆库的多样性,使得算法能够逃离局部最优,进而提高了算法的全局搜索能力;采用基于环路分解的编码方式对和声编码,保证初始解集中每个和声都是可行解。采用IEEE 33节点系统进行算例分析,与标准和声搜索算法、遗传算法进行对比分析,结果表明该算法的收敛更迅速,可以快速逃离局部寻优,且寻优性能不受初始参数的影响,验证了改进算法满足可实现性较高的寻优性能。     

自适应粒子群优化算法及其在无功优化中的应用

针对传统的粒子群优化(PSO)算法中的某些参数需通过试验确定因而影响了其实用性的问题,提出了一种自适应粒子群优化(APSO)算法,并将其应用于电力系统无功优化问题的求解。该算法能在优化过程中自动调整各参数,从而取得问题的全局优化解。某具有151个节点、71个控制变量的实际电网无功优化结果表明,该算法较传统的PSO算法具有更强的全局寻优能力。     

Optimal multistage modernization of power system subject to reliability and capacity requirements

This paper addresses the multistage modernization problem for power systems with series-parallel structure. The study period is divided into several stages according to demand forecast. At each stage the consumer demand distribution is predicted in the form of a cumulative load curve. Different actions, such as modifying existing equipment, changing maintenance policy, or adding new elements, may be undertaken in any system component at any stage to increase the total system capacity and/or reliability. The objective is to minimize the sum of costs of system modernization actions over the study period while satisfying reliability constraints at each stage. In order to solve the problem, a genetic algorithm is used as an optimization tool. The solution encoding technique developed allows the genetic algorithm to manipulate integer strings representing multistage system modernization planes. A solution quality index is comprised of both reliability and cost estimations. The procedure based on the universal generating function is used for evaluation of the availability of multistate series-parallel power systems. This technique allows one to estimate the effect on the entire system availability when both capacity and availability of system elements are varied. An illustrative example is presented in which the optimal expansion plan is found for a coal transportation system of a power station.     

一种新型的配电网供电恢复重构寻优算法

将蚁群算法应用于非故障失电区域的供电恢复重构问题,在建立新型、可行供电恢复方案搜索策略的基础上,结合图论相关知识引入了可操作开关集的概念,缩小了寻优空间,提出了一种新型配电网供电恢复重构寻优算法。在随后的迭代求解过程中,蚁群算法具有的正反馈、分布式计算和富于贪婪启发式搜索等特点使该算法的计算效率得到了显著提高。某18节点配电网的寻优比较结果表明,该算法具有高收敛性、快实时性和强全局稳定性。     

基于改进TLBO算法的输电网规划

输电网规划问题维数高、变量多以及约束条件复杂,导致问题难于求解。本文采用新型的智能算法教与学算法(TLBO)对问题进行求解。教与学算法具有收敛速度快、设置参数少的优点,但在求解时容易陷入局部最优解。本文通过加入自主学习环节和反思环节以及自适应扰动策略,提高算法寻找全局最优解的能力,使其适应大规模输电网规划问题的求解。采用目标函数为线路投资费用、网损费用、过负荷费用之和的输电网规划模型,通过在Garver-6节点系统和IEEE-18节点系统中的计算,验证了该算法可以正确有效地解决输电网规划问题。     

电力系统机组组合问题的改进粒子群优化算法

机组组合问题是一个大规模的非线性混合整数规划问题.文章首先对机组组合问题的0、1变量进行松弛,应用罚函数方法将此问题转化为一个非线性连续变量的规划问题,并应用改进粒子群优化算法求解.该算法在标准的粒子群优化算法的基础上,每个粒子速度和位置的更新不仅考虑自身个体极值和全局极值的信息,还考虑其它粒子所包含的信息.通过收敛性分析可知,若合适地选择算法的控制参数,该算法能较好地收敛到最优解.算例表明文章所提出的算法具有解的质量高、收敛速度快的优点.     

Determination of newly installed feeder route considering use of existing feeder

In planning a distribution system for an urban area, when a feeder is newly installed, the route of the feeder must be determined among many candidates, considering investment cost and constraints. However, it is difficult for planners to find the optimal route of the newly installed feeder, because too many candidate routes exist which can be constructed along roads in the service area of the power company, and it must be considered whether the end part of an existing feeder can be used as a part of a newly installed feeder within specified loaded value. In this paper, in order to support planners' decision making in selecting an optimal route for newly installed feeders, the authors have formulated the problem mathematically, and propose a new solution algorithm to find the optimal route by the Dijkstra method. Through numerical examples, the authors demonstrate the validity of the proposed method. © 1999 Scripta Technica, Electr Eng Jpn, 129(3): 40–50, 1999     

A Method of Determining Target Configurations for Power System Restoration Using a Mixed Integer Programming Approach

When electricity supply is interrupted due to a fault, it is essential that the power system be restored promptly according to an adequately planned restoration procedure. A problem of obtaining an appropriate target system for restoration is referred to as a power system restoration problem. The authors have already proposed a very efficient method based on the network simplex method which is in the category of mathematical programming approaches. Although the method is effective for most system conditions, it is likely to give an undesirable result in the case of abnormal network conditions. This paper proposes an effective and computationally fast solution algorithm based on the mixed integer programming approach, which can resolve the shortcoming of the former method The solution speed is improved greatly by incorporating the, restoration strategies of system operators. The following assumptions are postulated in this approach: (1)0–1 variables are allocated to branches and loads to present their status; (2) continuous variables are taken to represent branch flows: and (3) costs are assigned to branches to represent their priorities during restorative operations and power flow limits. The proposed approach can be used to complement the former approach. The new approach has been applied to restoration problems of practical size, and simulation results demonstrate its advantage over the former method for intricate operating conditions.     

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     

A Multistage Algorithm for Identification of Nonlinear Aggregate Power System Loads

A multistage identification algorithm for dynamic power system load models is proposed in this paper. The multistage approach is used to address the nonconvexity of the identification problem. Initial stages are used to find good preliminary estimates for the parameters of the model. Specifically, the initial stages are as follows: Equations for dynamic power system loads are discretized using the zero-order hold method and then approximated with a 2nd-order polynomial NARMAX model. Finally, an extended least squares approach is used to estimate the parameters of the NARMAX model, from which initial estimates for the parameters of the original model are obtained. In the final stage, the values found in the initial stages are used as the starting point for a Levenberg-Marquardt optimization routine that computes the optimal parameters. Numerical experiments using data from both simulated and real systems illustrate the computational complexity and accuracy of the proposed algorithm. Curve-fitting experiments are used to justify the polynomial NARMAX approximation.     

HSA based solution to the UC problem

Unit-commitment (UC) as a complicated problem needs powerful methods to solve. This paper presents the use of harmony search algorithm (HSA), a recently developed meta-heuristic algorithm, in order to obtain optimal solution for the UC problem. The proposed algorithm has simple implementation and provides optimal solutions in a reasonable time. The method is tested using small and large scale test cases in the literature. Numerical results show that the proposed algorithm can find better solutions in comparison with conventional methods and it is an efficient way to solve UC problems especially in large-scale power systems.     

基于最优流法和遗传算法的配电网重构

提出了一种基于改进最优流和遗传算法的配电网重构算法.该算法先利用配电网的同胚图将重构问题的全局寻优空间划分为若干子空间,然后利用改进最优流法寻找子空间内的最优解,之后再利用遗传算法搜索全局最优解所在的子空间,从而实现在局部最优解中寻找全局最优解.该算法既通过压缩寻优空间提高了遗传算法的搜索效率,又利用改进最优流法改善了局部寻优能力.算例计算结果表明了文中所提算法的可行性和有效性.     

支路交换法在配电网优化规划中的应用

为了实现大规模配电网的优化规划，以配电网扩建投资总额为目标函数，建立了混合整数规划模型，满足配电网的电流和电压方程、线路和变电所的容量约束及电压要求。文中利用基于线性规划换基运算的支路交换法求解该模型，得到了快速、实用的结果。算例结果证明了该方法的可行性和实用性。