scholarly journals A Multi-Agent Particle Swarm Optimization for Power System Economic Load Dispatch

2015 ◽  
Vol 03 (09) ◽  
pp. 83-89 ◽  
Author(s):  
Chenbin Wu ◽  
Haiming Li ◽  
Lei Wu ◽  
Zhengyang Wu
Keyword(s):  
Particle Swarm Optimization ◽  
Power System ◽  
Particle Swarm ◽  
Economic Load Dispatch ◽  
Swarm Optimization ◽  
Multi Agent ◽  
Agent Particle

A Novel Hybrid Optimization Algorithm Based on Multi-Agent and Particle Swarm

2011 ◽  
Vol 460-461 ◽  
pp. 512-517
Author(s):  
De Jia Shi ◽  
Wei Jin Jiang ◽  
Xiao Ling Ding
Keyword(s):  
Particle Swarm Optimization ◽  
Power System ◽  
Optimization Algorithm ◽  
Particle Swarm Optimization Algorithm ◽  
Reactive Power ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Agent Interactions ◽  
Fitness Value ◽  
Multi Agent

A novel multi-agent particle swarm optimization algorithm (MAI'SO) is proposed for optimal reactive power dispatch and voltage control of power system. The method integrates multi-agent system (MAS) and particle swarm optimization algorithm (PSO). An agent in MAI.SO represents a particle to PSO and a candidate solution to the optimization problem. All agents live in a lattice-like environment, with each agent fixed on a lattice-point. In order to decrease fitness value, quickly, agents compete and cooperate with their neighbors. and they can also use knowledge. Making use of these agent interactions and evolution mechanism of I.SO. MAPSO realizes the purpose of' minimizing the value of' objective function. MAPSO applied for optimal reactive power is evaluated on an IEEE 30-bus power system. It is shown that the proposed approach converges to better solutions much faster than the earlier reported approaches

scholarly journals Energy Storage Coordination in Energy Internet Based on Multi-Agent Particle Swarm Optimization

2018 ◽  
Vol 8 (9) ◽  
pp. 1520 ◽  
Author(s):  
Jicheng Liu ◽  
Dandan He ◽  
Qiushuang Wei ◽  
Suli Yan
Keyword(s):  
Particle Swarm Optimization ◽  
Energy Storage ◽  
Particle Swarm ◽  
Energy Utilization ◽  
Utilization Efficiency ◽  
Swarm Optimization ◽  
Energy Internet ◽  
Energy Networks ◽  
Multi Agent ◽  
Agent Particle

With the rapid development of energy Internet (EI), energy storage (ES), which is the key technology of EI, has attracted widespread attention. EI is composed of multiple energy networks that provide energy support for each other, so it has a great demand for diverse energy storages (ESs). All of this may result in energy redundancy throughout the whole EI system. Hence, coordinating ESs among various energy networks is of great importance. First of all, we put forward the necessity and principles of energy storage coordination (ESC) in EI. Then, the ESC model is constructed with the aim of economic efficiency (EE) and energy utilization efficiency (EUE) respectively. Finally, a multi-agent particle swarm optimization (MAPSO) algorithm is proposed to solve this problem. The calculation results are compared with that of PSO, and results show that MAPSO has good convergence and computational accuracy. In addition, the simulation results prove that EE plays the most important role when coordinating various ESs in EI, and an ES configuration with the multi-objective optimization of EE and EUE is concluded at last.

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