Using a Hybrid Evolutionary Method for Optimal Planning, and Reducing Loss of Distribution Networks (original) (raw)
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In This paper presents an approach for optimal placement and sizing of fixed capacitor banks and also optimal conductor selection in radial distribution networks for the purpose of economic minimization of loss and enhancement of voltage profile. The objective function includes the cost of power losses, capacitors and conductors. Constraints include voltage limit, maximum permissible carrying current of conductors, size of available capacitors and type of conductors. The optimization problem is solved by the genetic algorithm method and the size and the type of the capacitors and conductors is determined. By applying the proposed method, the economic costs and power losses are reduced to a considerable degree while enhancing the voltage profile. To demonstrate the validity of the proposed algorithm, computer simulations are carried out on actual power network of Kerman Province, Iran and the simulation results are presented and discussed
Using PSO for Optimal Planning, and Reducing Loss of Distribution Networks
In this paper the practical planning of distribution system includes the selection of optimal conductor size and capacitor placement in radial distribution network considering increasing rate of loads. Technical operational constraints are available conductors and capacitors, voltage limit, maximum permissible carrying current of conductors and maximum reactive power could be injected. The power loss minimization problem is solved using particle swarm optimization (PSO). By applying this method, final cost of network planning, losses and their cost are considerably reduced and voltage profile of the network has improved to a semiflat shape. Simulation results are investigated on a practical radial distribution network in Iran (Miandoab 20 kv distribution network), in addition self supporting cables are used for optimization which avoids illegal use of electricity.
Iraqi Journal for Electrical And Electronic Engineering
Development of distribution systems result in higher system losses and poor voltage regulation. Consequently, an efficient and effective distribution system has become more urgent and important. Hence proper selection of conductors in the distribution system is important as it determines the current density and the resistance of the line. This paper examines the use of different evolutionary algorithms, genetic algorithm (GA), to optimal branch conductor selection in planning radial distribution systems with the objective to minimize the overall cost of annual energy losses and depreciation on the cost of conductors and reliability in order to improve productivity. Furthermore, The Backward-Forward sweep iterative method was adopted to solve the radial load flow analysis. Simulations are carried out on 69-bus radial distribution network using GA approach in order to show the accuracy as well as the efficiency of the proposed solution technique.
Placement and Sizing of DG Using PSO&HBMO Algorithms in Radial Distribution Networks
International Journal of Intelligent Systems and Applications, 2012
Optimal placement and sizing of DG in distribution network is an optimization problem with continuous and discrete variables. Many researchers have used evolutionary methods for finding the optimal DG p lacement and sizing. This paper proposes a hybrid algorith m PSO&HBMO for optimal placement and sizing of distributed generation (DG) in radial d istribution system to minimize the total power loss and improve the voltage profile. The proposed method is tested on a standard 13 bus radial distribution system and simulat ion results carried out using MATLAB software. The simulation results indicate that PSO&HBM O method can obtain better results than the simp le heuristic search method and PSO algorithm. The method has a potential to be a tool for identifying the best location and rating of a DG to be installed for improving voltage profile and line losses reduction in an electrical power system. Moreover, current reduction is obtained in distribution system.
PLACEMENT AND SIZING OF DG IN RADIAL DISTRIBUTION NETWORK USING PSO
Optimal placement and sizing of DG in distribution network is an optimization problem with continuous and discrete variables. Many researchers have used evolutionary methods for finding the optimal DG placement and sizing. This paper proposes a hybrid algorithm PSO&HBMO for optimal placement and sizing of distributed generation (DG) in radial distribution system to minimize the total power loss and improve the voltage profile. The proposed method is tested on a standard 13 bus radial distribution system and simulation results carried out using MATLAB software. The simulation results indicate that PSO&HBMO method can obtain better results than the simple heuristic search method and PSO algorithm. The method has a potential to be a tool for identifying the best location and rating of a DG to be installed for improving voltage profile and line losses reduction in an electrical power system. Moreover, current reduction is obtained in distribution system.
2016
The active and reactive power flow in distribution networks can be effectively controlled by optimally placing Shunt Capacitors (SCs) and Distributed Generators (DGs). This paper presents improved versions of three evolutionary or swarm-based search algorithms, namely, Improved Genetic Algorithm (IGA), Improved Particle Swarm Optimization (IPSO) and Improved Cat Swarm Optimization (ICSO) to efficiently handle the problem of simultaneous allocation of SCs and DGs in radial distribution networks while considering variable load scenario. The benefit of network reconfiguration has also been taken into account after optimal allocation of these devices. Several algorithm specific modifications are suggested in the standard forms of GA, PSO and CSO to overcome their inherent drawbacks. In addition, an intelligent search approach is proposed to enhance overall performance of proposed algorithms. The proposed methods are investigated on IEEE 33-bus and 69-bus test distribution systems showin...
IEEE PES Innovative Smart Grid Technologies, Europe, 2014
This paper presents a study of the impact of Distributed Generation (DG) in the operational planning and design of Medium Voltage (MV) distribution networks. The proposed model considers the planning of MV networks for reducing power losses, voltage drop and investments in reinforcements using Genetic Algorithm (GA). Planning MV distribution networks involves cable replacement, sizing and positioning of capacitor and DG and phase load balancing .The objective function to be minimized includes operational costs of proposed changes, power losses and voltage constraints. A power flow for radial distribution networks based on a backward/forward sweep using current summation was developed to validate the solutions.
Power losses issues persevered over few decades in the high demand utilization of energy electricity in developing countries. Thus, the radial structure of distribution network configuration is extensively used in high populated areas to ensure continuity of power supply in the event of fault. This paper proposes heuristic Genetic Algorithm known as SIGA (Selection Improvement in Genetic Algorithm) in consideration of genetic operator probabilities likewise the progression of switch adjustment in Distribution Network Reconfiguration (DNR) while satisfying the parameters constraints. The SIGA algorithm was embodied throughout the process in IEEE 33-bus distribution system in selection of five tie switches. As a consequence, the power losses were ranked in accordance to the minimum values and voltage profile improvement obtainable by the proposed algorithm. The results show that the SIGA performs better than GA by giving the minimized value of power losses.
Power losses issues persevered over few decades in the high demand utilization of energy electricity in developing countries. Thus, the radial structure of distribution network configuration is extensively used in high populated areas to ensure continuity of power supply in the event of fault. This paper proposes heuristic Genetic Algorithm known as SIGA (Selection Improvement in Genetic Algorithm) in consideration of genetic operator probabilities likewise the progression of switch adjustment in Distribution Network Reconfiguration (DNR) while satisfying the parameters constraints. The SIGA algorithm was embodied throughout the process in IEEE 33-bus distribution system in selection of five tie switches. As a consequence, the power losses were ranked in accordance to the minimum values and voltage profile improvement obtainable by the proposed algorithm. The results show that the SIGA performs better than GA by giving the minimized value of power losses.