Service Restoration In Distribution Systems Research Articles

Distribution system service restoration using fuzzy Petri Net models

This paper proposes a new fuzzy Petri Net (FPN) modeling technique to achieve the on-line service-restoration plan of the distribution system. Service restoration is a complicated combinatorial optimization problem that often has a great number of candidate solutions to be selected by the dispatchers. According to practical guidelines and experiences of the dispatchers on the service restoration of distribution systems, an FPN model is built to represent the related knowledge and inference scheme about the task of restoration. The proposed FPN model has been practically tested on a typical distribution system of Taiwan Power Company (TPC). Flexibility and effectiveness of the FPN model have been validated as a decision support for restoration scheduling of distribution systems.

Comparative study of modern heuristic algorithms to service restoration 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.

Switching operation decision making by using petri‐net approach for power distribution systems

In this paper, the artificially intelligent Petri‐Net is applied to find optimal switching operations for service restoration and feeder loading balancing of distribution systems. For contingencies, the Petri‐Net model with an inference mechanism is derived to provide the optimal load transfer among distribution feeders after the fault location has been identified and isolated. For normal operation, the load balancing among distribution feeders is obtained by the Petri‐Net model to enhance the operation efficiency of distribution systems. To represent the load behavior of distribution systems more practically, the load profiles of distribution feeders are derived by load survey study. Load flow analysis is then performed to solve the hourly current flows of all line switches. The switching operation, which will result in the loading balance among distribution feeders, is derived by the Petri‐Net model according to the loading cost to the distribution system. To demonstrate the effectiveness of the proposed methodology, a sample distribution system has been selected for computer simulation. It is found that the proposed Petri‐Net algorithm can enhance fault restoration with proper load transfer and improve feeder load balance for distribution systems by considering the load characteristics of the service customers.

Comparative Study of Modern Heuristic Algorithms to Service Restoration in Distribution Systems

This article presents a comparative study for four modem 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.

A mathematical programming approach to service restoration for distribution systems

AbstractThis paper aims to develop a suitable power system restoration method by using mathematical programming (MP). Generally, the problem of determining the target configuration can be formulated as a mixed integer programming (MIP) problem. Whether or not each branch is included in a target system is expressed as a 0–1 variable, while the other constraints such as the demand and supply balance conditions are formulated in terms of continuous variables. Although an MP‐based method can obtain an optimal solution under specified operational constraints, in the case of large‐scale problems the solution time often exceeds the computation time that is practically available due to combinatorial explosion. The object of this paper is to develop an efficient solution algorithm for service restoration in distribution systems. First, an MIP problem is solved to determine the sound network configuration that maximizes the available power to the out‐of‐service area, then an MIP problem is solved to determine the target configuration for the out‐of‐service network. The proposed method has been applied to distribution system restoration problems, and simulation results demonstrate its effectiveness. © 2001 Scripta Technica, Electr Eng Jpn, 135(4): 35–42, 2001

Network reconfiguration for service restoration in shipboard power distribution systems

Network reconfiguration for service restoration in shipboard power distribution systems

An application of reactive tabu search for service restoration in distribution systems and its comparison with the genetic algorithm and parallel simulated annealing

Service restoration in distribution systems can be formulated as a combinatorial optimization problem. It is the problem to determine power sources for each load considering various operational constraints in distribution systems. Up to now, the problem has been dealt with using conventional methods such as the branch and bound method, expert systems, neural networks, and fuzzy reasoning. Recently, modern heuristic methods such as genetic algorithms (GA), simulated annealing (SA), and tabu search (TS) have been attracting notice as efficient methods for solving large combinatorial optimization problems. Moreover, reactive tabu search (RTS) can solve the parameter tuning problem, which is recognized as the essential problem of the TS. Therefore, RTS, GA, and SA can be efficient search methods for service restoration in distribution systems. This paper develops an RTS for service restoration and compares RTS, GA, and PSA (parallel SA) for the problem. The feasibility of the proposed methods is shown and compared on a typical distribution system model with promising results. © 2000 Scripta Technica, Electr Eng Jpn, 133(3): 71–82, 2000

復旧戦略を導入した配電系統事故復旧の数理計画的方式

This paper aims to develop a suitable power system restoration method by using mathematical programming (MP). Generally, the problem of determining the target configuration can be formulated as a mixed integer programming (MIP) problem. Whether or not each branch is included in a target system is expressed as a 0–1 variable, while the other constraints such as the demand and supply balance conditions are formulated in terms of continuous variables. Although an MP-based method can obtain an optimal solution under specified operational constraints, in the case of large-scale problems the solution time often exceeds the computation time that is practically available due to combinatorial explosion. The object of this paper is to develop an efficient solution algorithm for service restoration in distribution systems. First, an MIP problem is solved to determine the sound network configuration that maximizes the available power to the out-of-service area, then an MIP problem is solved to determine the target configuration for the out-of-service network. The proposed method has been applied to distribution system restoration problems, and simulation results demonstrate its effectiveness. © 2001 Scripta Technica, Electr Eng Jpn, 135(4): 35–42, 2001

A fuzzy heuristic algorithm for distribution systems' service restoration

This paper describes a fuzzy heuristic algorithm for the service restoration of distribution systems. Its main objectives are: (a) to supply energy to the largest possible number of customers, (b) to minimize the number of switching operations, (c) to represent the operator's knowledge and (d) to reduce the computational effort. This fuzzy algorithm, along with a fuzzy load estimator method, provided very good results, showing to be an efficient restoration tool.

異種個体集団が共存する遺伝的アルゴリズムによる負荷融通問題の解法

異種個体集団が共存する遺伝的アルゴリズムによる負荷融通問題の解法

Service restoration of primary distribution systems based on fuzzy evaluation of multi-criteria

Due to many conflicting goals, the power service restoration problem is a multiple-criteria decision making problem. This paper proposes a new restoration strategy consisting of two steps: candidate set generation and fuzzy decision making, which can generate the most preferable plan. The object-oriented paradigm has been adopted in the development of the system and three models-object model, functional model, dynamic model-have been designed. The test results have shown the effectiveness of the proposed method.

Fast service restoration for large-scale distribution systems with priority customers and constraints

A fast, effective service restoration method is designed for large-scale distribution systems with priority customers. The service restoration problem is formulated as a constrained multi-objective optimization problem. A ranking-based search method employing analytical information obtained from three-phase power flow simulations is designed to restore service to as many priority customers as possible while maximizing the amount of total load restored and minimizing the number of required switch operations. The proposed method is designed with consideration to networks which have predominantly manual switches. Comprehensive simulation results of the search method, including priority customers, single and multiple faults and multiple out-of-service areas are presented for a 416 bus distribution network.

Knowledge-based methodology for intelligent sequence switching, fault identification and service restoration of distribution system

In this paper a new approach to intelligent sequence switching in substations and service restoration of distribution system using finite stochastic processes in conditional probability is presented. The technique exploits the results of probability by initially predicting the future states of the nodes in the search procedure. The knowledge base is handled through probabilistic reasoning. This is coupled with direct reasoning or searching. This improves the reliability of the heuristics. The fault identifier uses deductive logic for identifying the fault point. The proposed technique is tested for a 66/11 kV substation, having 4 U.G cable feeders with 36 load points and 8 RTUs, in Mysore, South India.

Parallel genetic algorithm for service restoration in electric power distribution systems

Parallel genetic algorithm for service restoration in electric power distribution systems

Parallel genetic algorithm for service restoration in electric power distribution systems

This paper develops a coarse-grain parallel genetic algorithm for solving a service restoration problem in electric power distribution systems. Service restoration is performed to restore electricity for out-of-service areas. Developing effective service restoration procedures is a cost-effective approach to improving service reliability and enhancing customer satisfaction. The main objective in service restoration procedures is to restore as much load as possible by transferring de-energized loads via network reconfigurations to other supporting distribution feeders without violating operating and engineering constraints. Details of the parallel genetic algorithm developed in this paper are described. The proposed method is implemented on transputers for parallel computations. The feasibility of the developed algorithm for service restoration is demonstrated on several distribution networks with promising results.

Application of genetic algorithms to service restoration in distribution systems

AbstractService 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.

Distribution system service restoration using the artificial neural network approach and pattern recognition method

Service restoration of a distribution system is investigated by using artificial intelligence. The purpose is to reach a proper restoration plan for the unfaulted zone after a fault has been identified and isolated. To reduce the outage period and improve service reliability, the restoration plan must be devised in a very short period. In the paper, two approaches using artificial intelligence, i.e. the artificial neural network (ANN) approach and the pattern recognition method, are developed to determine the restoration plan in a very efficient manner. The effectiveness of the proposed approaches is demonstrated by the restoration of electricity service following a fault in a distribution system in Taipei, Taiwan. It is concluded from the example that a proper restoration plan can be reached very efficiently using the proposed approaches. Therefore, it can be used by distribution system operators to reach a restoration plan.

A new algorithm for service restoration in large-scale urban distribution systems

A method is suggested for (near) optimal restoration of large-scale urban distribution systems after heavy disturbances. The method is conceived to provide the minimum total load interruption cost by taking into account the current, voltage and system operating and structural constraints. An efficient restoration of load points is achieved by utilizing the MV busbars in HV/MV transformer stations which facilitate the load transfer among transformers and feeders while keeping low the number of switching operations. The optimal alternatives in supplying the nodes of the out-of-service area are searched for by generating the minimal paths to the boundary branches connecting this area with the sound area, which broadens the search domain.

A heuristic based fuzzy reasoning approach for distribution system service restoration

A fuzzy reasoning approach is proposed for the service restoration of a distribution system. After the location of a fault has been identified and the faulted zone has been isolated, it is important for the operators to reach a proper service restoration plan in order to restore the electricity service outside the faulted zone. The operators tend to use their past experience and heuristic rules to devise such a restoration plan because it must satisfy a lot of practical needs and objectives. In addition, the operators' needs and heuristic rules are often expressed in imprecise linguistic terms. In this paper, fuzzy set notation is employed to deal with these imprecise linguistic variables and a set of fuzzy reasoning procedures are developed to implement the operators' heuristic rules. These procedures can be employed to solve the multiple-objective problem of service restoration described in imprecise linguistic variables. To demonstrate the effectiveness of the proposed fuzzy reasoning approach, service restoration on a distribution system within the service area of Taipei West District Office of Taiwan Power Company is examined. It is found that a proper restoration plan can be reached very efficiently by the proposed approach. >

負荷融通問題への遺伝的アルゴリズムの適用

負荷融通問題への遺伝的アルゴリズムの適用