Optimal restoration of power distribution system through particle swarm optimization

2015 ◽  
Author(s):  
Leonardo W. Oliveira ◽  
Edimar J. Oliveira ◽  
Ivo C. Silva ◽  
Flavio V. Gomes ◽  
Thiago T. Borges ◽  
...  
Keyword(s):  
Particle Swarm Optimization ◽  
Power Distribution ◽  
Distribution System ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Power Distribution System

scholarly journals Power System Reconfiguration in Distribution Network for Improving Reliability Using Genetic Algorithm and Particle Swarm Optimization

2021 ◽  
Vol 11 (7) ◽  
pp. 3092
Author(s):  
Omar Kahouli ◽  
Haitham Alsaif ◽  
Yassine Bouteraa ◽  
Naim Ben Ali ◽  
Mohamed Chaabene
Keyword(s):  
Genetic Algorithm ◽  
Particle Swarm Optimization ◽  
Distribution System ◽  
Distribution Network ◽  
Mathematical Formulation ◽  
Particle Swarm ◽  
Network Reconfiguration ◽  
Power Losses ◽  
Swarm Optimization ◽  
Power Distribution System

This paper presents an optimal method for optimizing network reconfiguration problems in a power distribution system in order to enhance reliability and reduce power losses. Network reconfiguration can be viewed as an optimization problem involving a set of criteria that must be reduced when adhering to various constraints. The energy not supplied (ENS) during permanent network faults and active power losses are the objective functions that are optimized in this study during the reconfiguration phase. These objectives are expressed mathematically and will be integrated into various optimization algorithms used throughout the study. To begin, a mathematical formulation of the objectives to be optimized, as well as all the constraints that must be met, is proposed. Then, to solve this difficult combinatorial problem, we use the exhaustive approach, genetic algorithm (GA), and particle swarm optimization (PSO) on an IEEE 33-bus electrical distribution network. Finally, a performance evaluation of the proposed approaches is developed. The results show that optimizing the distribution network topology using the PSO approach contributed significantly to improving the reliability, node voltage, line currents, and calculation time.

scholarly journals Multi-Objective Power Distribution Network Reconfiguration using Chaotic Fractional Particle Swarm Optimization

2021 ◽  
Vol 19 (1) ◽  
pp. 43-50
Author(s):  
Yashar Mousavi ◽  
Mohammad Hosein Atazadegan ◽  
Arash Mousavi
Keyword(s):  
Particle Swarm Optimization ◽  
Power Distribution ◽  
Distribution Network ◽  
Particle Swarm ◽  
Superior Performance ◽  
Network Reconfiguration ◽  
Power Distribution Network ◽  
Swarm Optimization ◽  
Distribution Network Reconfiguration ◽  
Multi Objective

Optimization of power distribution system reconfiguration is addressed as a multi-objective problem, which considers the system losses along with other objectives, and provides a viable solution for improvement of technical and economic aspects of distribution systems. A multi-objective chaotic fractional particle swarm optimization customized for power distribution network reconfiguration has been applied to reduce active power loss, improve the voltage profile, and increase the load balance in the system through deterministic and stochastic structures. In order to consider the prediction error of active and reactive loads in the network, it is assumed that the load behaviour follows the normal distribution function. An attempt is made to consider the load forecasting error on the network to reach the optimal point for the network in accordance with the reality. The efficiency and feasibility of the proposed method is studied through standard IEEE 33-bus and 69-bus systems. In comparison with other methods, the proposed method demonstrated superior performance by reducing the voltage deviation and power losses. It also achieved better load balancing.

scholarly journals Enhanced Particle Swarm Optimization-Based Feeder Reconfiguration Considering Uncertain Large Photovoltaic Powers and Demands

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Ying-Yi Hong ◽  
Faa-Jeng Lin ◽  
Fu-Yuan Hsu
Keyword(s):  
Particle Swarm Optimization ◽  
Power Systems ◽  
Distribution System ◽  
Urban Areas ◽  
Distribution Systems ◽  
Particle Swarm ◽  
Solar Pv ◽  
Swarm Optimization ◽  
Rural And Urban Areas ◽  
Enhanced Particle Swarm Optimization

The Kyoto protocol recommended that industrialized countries limit their green gas emissions in 2012 to 5.2% below 1990 levels. Photovoltaic (PV) arrays provide clear and sustainable renewable energy to electric power systems. Solar PV arrays can be installed in distribution systems of rural and urban areas, as opposed to wind-turbine generators, which cause noise in surrounding environments. However, a large PV array (several MW) may incur several operation problems, for example, low power quality and reverse power. This work presents a novel method to reconfigure the distribution feeders in order to prevent the injection of reverse power into a substation connected to the transmission level. Moreover, a two-stage algorithm is developed, in which the uncertain bus loads and PV powers are clustered by fuzzy-c-means to gain representative scenarios; optimal reconfiguration is then achieved by a novel mean-variance-based particle swarm optimization. The system loss is minimized while the operational constraints, including reverse power and voltage variation, are satisfied due to the optimal feeder reconfiguration. Simulation results obtained from a 70-bus distribution system with 4 large PV arrays validate the proposed method.

Power Distribution Network Reconfiguration by Using EPSO for Loss Minimizing

2014 ◽  
Vol 699 ◽  
pp. 809-815 ◽  
Author(s):  
Mohamad Fani Sulaima ◽  
Mohd Hafiz Jali ◽  
Wan Mohd Bukhari ◽  
M.N.M. Nasir ◽  
Hazriq Izzuan Jaafar
Keyword(s):  
Particle Swarm Optimization ◽  
Power Distribution ◽  
Distribution Network ◽  
Heuristic Method ◽  
Particle Swarm ◽  
Computational Time ◽  
Network Reconfiguration ◽  
Voltage Profile ◽  
Power Distribution Network ◽  
Swarm Optimization

Due to the complexity of modern power distribution network, a hybridization of heuristic method which is called as Evolutionary Particle Swarm Optimization (EPSO) is introduced to identify the open and closed switching operation plans for network reconfiguration. The objectives of this work are to reduce the power losses and improve the voltage profile in the overall system meanwhile minimizing the computational time. The proposed combination of Particle Swarm Optimization (PSO) and Evolutionary Programming (EP) is introduced to make it faster in order to find the optimal solution. The proposed method is applied and it impacts to the network reconfiguration for real power loss and voltage profiles is investigated respectively. The proposed method is tested on a IEEE 33-bus system and it is compared to the traditional PSO and EP method accordingly. The results of this study is hoped to help the power engineer to configure the smart and less lossed network in the future.

Power Factor Optimization of Distributed Generations in Distribution Networks Based on Improved Particle Swarm Optimization Method

2012 ◽  
Vol 516-517 ◽  
pp. 1408-1413 ◽  
Author(s):  
Cheng Xi Li ◽  
Wen Jun Yan ◽  
Qiang Yang
Keyword(s):  
Particle Swarm Optimization ◽  
Power Factor ◽  
Power Distribution ◽  
Power Loss ◽  
Particle Swarm ◽  
Distribution Networks ◽  
Optimization Method ◽  
Small Scale ◽  
Swarm Optimization ◽  
Power Utilities

The gradually extensive penetration of small-scale distributed renewable generators in existing medium-voltage power distribution networks highlights many technical challenges which call for urgent solutions from power utilities. This paper attempts to optimize the power factor of distributed generators (DGs) integrated in distribution networks and presents a novel algorithmic solution. With the aim of minimizing power loss whilst maintaining the node voltage, the problem is formulated with a mathematical model elaborating the DGs and a set of constraints in distribution networks and addressed through adopting an extended particle swarm optimization (PSO) approach. The suggested algorithm is assessed through numerical simulation experiments with the IEEE 33-bus system and the outcome shows that the optimization algorithm can effectively reduce the power loss and promote the node voltages across the overall distribution network.

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