Radial Network Configuration Research Articles

A Novel Proposed Algorithm to Enhance the Overcurrent Relays’ Performance in Active Distribution Networks

This research addresses two topics: the first is the optimal coordination of overcurrent relays (OCRs), which has recently become a major challenge to ensure reliability and speed of relays’ operation, and the second is a modified circuit added to the OCR to vanquish the barriers caused by the ever-increasing participation of distributed energy resources (DERs), at a lower cost. For robust and reliable OCRs coordination, various types of optimization techniques are frequently used to find optimal OCRs settings in distribution networks (DNs). In this study, the improved wild horse optimization (IWHO) algorithm is used as a novel metaheuristic method for solving optimization issues in coordination of OCRs in a distribution network, for the first time. This technique is used to determine the optimal time multiplier setting (TMS) and optimal pickup setting (PS) of OCRs in order to minimize the overall operating time. The results of the proposed algorithm are compared with those obtained from other recent metaheuristic techniques. The obtained TMS and PS settings of each relay show the effectiveness of the proposed IWHO technique in terms of accuracy and speed in a medium scale radial network configuration. To replace the costly mitigation methods employed in the DN comprising DER, a simple circuit was proposed to be added to the OCR. Using the angle’s sign of positive sequence current component (PSCC) of fault current solely, this proposed circuit can detect the fault direction and assist the OCR in making the correct decision in fault detection and clearing with high penetration of DERs. IEEE-33 bus electrical power system has been used to validate the newly proposed protective solutions.

Planning models for optimal routing of radial distribution systems

<span>This paper presents three planning models for optimal routing of radial distribution systems. In the first two models, the cost function includes capital cost of lines, energy loss cost, and bays cost. The constraints equations include power balance equations, voltage drop equations, radiality equations, logic equations, thermal limit equations, and bus voltage limit equations. The first model considers the energy loss equation in its quadratic form while the second model approximates the energy loss equation of each cable size by a simple linear segment considering the economic loading of each cable size. In the third model, two sub-models are used where the first one gets the optimal radial network configuration regardless of the cable sizes and voltage constraints. In the second sub-model the best cable size on each selected line of the first model is determined to minimize the system costs while considering the bus voltage limit constraint and thermal limit constraint. Verification of the proposed planning models has been made using a real 11 kV 34-bus distribution network with 68 initial lines.</span>

A Comprehensive Review of Metaheuristic Methods for the Reconfiguration of Electric Power Distribution Systems and Comparison With a Novel Approach Based on Efficient Genetic Algorithm

The distribution system reconfiguration (DSR) is a complex large-scale optimization problem, which is usually formulated with one or more objective functions and should satisfy multiple sets of linear and non-linear constraints. As the exploration of feasible solutions in large and nonconvex search space of DSR is typically hard, it is important to develop efficient algorithms and methods for finding optimal solutions for DSR problem in reasonably short computational times. In traditional DSR, the configuration of distribution network can be changed by opening and closing sectional and tie switches, where active power losses are minimized, while radial network configuration and supply to all connected loads are both preserved. Accordingly, this paper provides a comprehensive review of a number of existing metaheuristic reconfiguration methods and introduces a novel efficient genetic algorithm (efficient GA) for DSR with loss minimization. In order to demonstrate benefits and effectiveness of the proposed efficient GA for DSR, the paper also provides a detailed comparison of results with an improved genetic algorithm (improved GA) for several test systems and real distribution networks. The obtained simulation results clearly show higher accuracy and improved convergence performance of the proposed efficient GA method, compared to the improved GA and other considered reconfiguration methods.

Application of genetic algorithm for problem of optimizing location and capacity of distributed generation considering distributed network reconfiguration

This paper presents a method of determining the location and size of distributed generation (DG) considering to operate the configuration of distribution network to minimize the real power loss. The proposed method which is based on the genetic algorithm (GA) is divided into two stages. In the first stage, GA is used to optimize the location and size of DG in the mesh distribution network, while in the second stage, GA is used to determine the radial network configuration after installing DG. The simulation results on the 33-nodes and 69-nodes systems show that the proposed method can be an efficient method for the placing DG problem and that is considering to solve the problem of distribution network reconfiguration.

An Iterative Method for Detecting and Localizing Islands Within Sparse Matrixes Using DSSim-RT

Nowadays, the simulation tools used to perform power system analysis are evolving into the many-core computation era; some of these techniques propose to tear the power system network into several subnetworks (islands) for its parallel processing. The island's detection is an issue considered by the power flow analysis due to management activities such as feeder reconfiguration, fault detection, and isolation, among others, that generate topological changes. These methods include graph theory, checking the circuit breaker status and on-site measurements, decision trees, frequency deviation, and pattern recognition, among other techniques, which are focused to detect topology changes that may generate islands and affect the state estimation of the system. In contrast, other techniques such as the approximate minimum degree perform a reorganization of the $Y_{{\text{BUS}}}$ matrix that describes the network components and their connectivity, looking to factorizing the $Y_{{\text{Bus}}}$ matrix to solve the power flow problem. These techniques are very functional and efficient; however, some of them require detailed information of the network, and are addressed to cover meshed and radial network configurations separately. This paper presents an iterative algorithm that uses the compressed coordinate branch-to-node matrix for detecting, classifying, and grouping islands within sparse matrixes, describing mesh or radial networks. This algorithm is a valuable tool to simplify islands location and can be implemented using any programing language due to its simplicity. This method is used in Distribution System Simulator - Real Time Version (DSSim-RT), which is a simulator based in OpenDSS, for tearing the power system network to allow the multithread power flow analysis of distribution systems in real time.

Scalable algorithm for the dynamic reconfiguration of the distribution network using the Lagrange relaxation approach

This paper proposes a new methodology for the dynamic reconfiguration of the distribution network (DRDN) which is based on the Lagrange relaxation approach. The aim of DRDN is to determine the optimal topologies (configurations) of the distribution network over the specified time interval. The objective is to minimize the active power losses, subject to the following constraints: branch power flow capacities, allowed ranges of bus voltages, radial network configuration, and limited number of switching (open/close) operations for all switching devices. The paper first introduces the “path-switch-to-switch” approach for the modelling of distribution networks, which is used to formulate DRDN as the mixed integer linear programming (MILP) problem. Then, the specified MILP problem is solved using the Lagrange relaxation approach in two-step procedure. In the first step, the associated Lagrange dual problem is solved, which is created by relaxing the switching operation constraints. The Lagrange dual problem is decoupled and much easier to solve than the original problem. In the second step, the solution of the Lagrange dual problem is used to perform the heuristic search, providing the suboptimal, though feasible solution of the original problem. Finally, the presented DRDN model is extended to multi-objective formulation, which also includes the impact of the network reliability and the switching costs to the DRDN process. The robustness and scalability of the developed algorithm (for application in large-scale distribution networks) are demonstrated with two test examples: 15-bus test benchmark and 1021-bus real-world test system.

Planning of Low-Voltage Distribution Networks Using Hierarchical Methods

Low-voltage distribution networks represent a component of the power system with the most prominent problems in terms of voltage quality and losses of electrical power which is delivering to the end customers. Overcoming of such problems is a real challenge for distribution companies, since they are obliged to deliver electricity of standard quality to the end customers, but at the same time taking care of their own interests. In this paper, a method based on hierarchical algorithms applicable in the planning of low-voltage distribution networks is presented. The planning of such networks includes determining of an optimum location of substation, radial network configuration, as well as appropriate types of power lines, all in order to achieve the prescribed voltage levels and minimize the power losses in electricity transmission.

Multiobjective service restoration in electric distribution networks using a local search based heuristic

Contingency situations may cause emergency states in distribution systems; these states are defined as the interruption of power supply. Such situations should be avoided whenever possible in order to maintain certain quality limits related to frequency and duration of interruptions. The main objective of service restoration is to minimize the number of consumers affected by the fault, by transferring them to energized support feeders. Electrical and operational conditions, such as radial network configuration, equipment and voltage drop limits, must be respected. This paper presents a new multiobjective local search based heuristic for the restoration of service which considers the minimization of two conflicting criteria: the load not supplied and the number of switching operations involved. Computational experiments with three network systems have shown the flexibility and effectiveness of the proposed method.

MULTIOBJECTIVE HEURISTIC SEARCH FOR SERVICE RESTORATION IN ELECTRIC DISTRIBUTION NETWORKS

Power system distribution networks can face emergency situations, defined by the interruption of the power supply in certain regions. As certain quality of service limits must be maintained, especially those related to interruption frequency and duration, efforts should be made to reduce or eliminate the lack of services in any region. The main objective of service restoration is to minimize the number of consumers affected by the fault, transferring them to distribution support feeders to restore power while maintaining electrical and operational conditions, such as radial network configuration, equipment and voltage drop limits. This paper proposes a multiobjective heuristic search method that considers two criteria: the maximization of the restored load and the minimization of the number of switching operations.

A Novel Heuristic Method for Distribution System Planning

Numerous mathematical optimization methods have been used to obtain the optimal solution to the problem of distribution system planning, which often are time consuming and only restricted to small size distribution systems. In this paper, a novel heuristic method is developed to solve the problem of distribution system planning. The method is composed of three steps. First of all, an initial redundant network is formed by combining the existing network and the probable new additions. A new efficient two-stage load flow method is presented and integrated into a recursive process to determine the optimal combination of substations and derive their service areas. Secondly, a heuristic approach is used to obtain the radial network configuration of each substation. Finally, an algorithm based on branch exchange technique is implemented between elements of adjacent distribution zones to obtain the final planning scheme. A distribution system with 6 substations and 98 feeders is studied, which demonstrates the feasibility and efficiency of the proposed method.

線形計画法を適用した放射状系統構成決定法

It is important for power system operators to determine the optimum network configuration. This paper proposes a new theoretical method to derermine the optimum radial network configuration of a power system. This algorithm consists of processes as follows, (1) a power system equation can be represented by using node-flow matrix based on Kirch Hoffs 1st law, (2) after diagonalizing the matrix, branches related to non-basic variables of simplex matrix are regarded as open ones, while branches related to basic variables are regarded as close ones of a radial network, (3) branch on-off operation corresponds to the pivot operation of LP method, (4) the objective function is renewed on every pivot operation. By using this method on a distribution power system with 539 branches, it is found that calculated results are practically useful. And the calculation time (11 seconds) is also practically satisfied by taking measures as follows, (1) pivot selection only from remote controllable branches, (2) per unit description and sign reverse operation of branch flow. Moreover, even if the calculated value is the minimum solution by the effects of blanch capacity constraints, quasi optimum solution is obtained by using double pivot operation. This logic can be applied to not only a distribution network but also a transmission network at any system state such as normal situation, outage, maintenance, and restoration.

A modified linear programming method for distribution system reconfiguration

This paper presents a reconfiguration method for radial distribution systems. The reconfiguration problem is formulated and solved using a modified linear programming approach. The modifications are introduced mainly to maintain a radial network configuration while enforcing the line flow capacity limits. The implementation details are explained using a small tutorial example. Simulation results for sample distribution systems are also given.