Optimal Allocation of Distributed Generators in a Distribution Network Using Adaptive Multi-Objective Particle Swarm Optimization

2012 ◽  
pp. 1707-1715 ◽  
Author(s):  
Shan Cheng ◽  
Min-You Chen ◽  
Peter J. Fleming ◽  
Xia Li
Keyword(s):  
Particle Swarm Optimization ◽  
Optimal Allocation ◽  
Distribution Network ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Multi Objective ◽  
Distributed Generators

Optimal allocation of distributed energy storage in active distribution network via hybrid teaching learning and multi-objective particle swarm optimization algorithm

2021 ◽  
pp. 002072092098369
Author(s):  
Jijun Liu ◽  
Yuxin Bai ◽  
Yingfeng He
Keyword(s):  
Particle Swarm Optimization ◽  
Energy Storage ◽  
Optimal Allocation ◽  
Storage System ◽  
Distribution Network ◽  
Particle Swarm ◽  
Economic Cost ◽  
Energy Storage System ◽  
Swarm Optimization ◽  
Active Distribution Network

This work aims at solving complex problems of the optimal scheduling model of active distribution network, teaching strategies are proposed to improve the global search ability of particle swarm optimization. Moreover, based on the improved Euclidean distance cyclic crowding sorting strategy, the convergence ability of Li Zhiquan algorithm is improved. With the cost and voltage indexes of the energy storage system of the distribution network as the goal, different optimized configuration schemes are constructed, and the improved HTL-MOPSO algorithm is adopted to find the solution. The results show that compared with the traditional TV-MOPSO algorithm, the proposed algorithm has better convergence performance and optimization ability, and has a lower economic cost. In short, the algorithm proposed can provide a basis for improving the optimization of active distribution network scheduling strategies.

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.

Security/cost-based optimal allocation of multi-type FACTS devices using multi-objective particle swarm optimization

SIMULATION ◽  
2012 ◽  
Vol 88 (8) ◽  
pp. 999-1010 ◽  
Author(s):  
Hamid Reza Baghaee ◽  
Mojtaba Mirsalim ◽  
Geveorg B Gharehpetian ◽  
Ali Kashefi Kaviani
Keyword(s):  
Particle Swarm Optimization ◽  
Optimal Allocation ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Multi Objective ◽  
Facts Devices
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