A Multi-Agent-Based Optimization Model for Microgrid Operation Using Dynamic Guiding Chaotic Search Particle Swarm Optimization
The optimal operation of microgrids is a comprehensive and complex energy utilization and management problem. In order to guarantee the efficient and economic operation of microgrids, a three-layer multi-agent system including distributed management system agent, microgrid central control agent and...
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Online Access: | https://www.mdpi.com/1996-1073/11/12/3286 |
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doaj-d93ae1c476f34d1a9aa5f45e4ac1fae92020-11-24T21:23:00ZengMDPI AGEnergies1996-10732018-11-011112328610.3390/en11123286en11123286A Multi-Agent-Based Optimization Model for Microgrid Operation Using Dynamic Guiding Chaotic Search Particle Swarm OptimizationJicheng Liu0Fangqiu Xu1Shuaishuai Lin2Hua Cai3Suli Yan4School of Economics and Management, North China Electric Power University, Beijing 102206, ChinaSchool of Economics and Management, North China Electric Power University, Beijing 102206, ChinaSchool of Economics and Management, North China Electric Power University, Beijing 102206, ChinaIndustrial Engineering, Purdue University, West Lafayette, IN 47907, USASchool of Economics and Management, North China Electric Power University, Beijing 102206, ChinaThe optimal operation of microgrids is a comprehensive and complex energy utilization and management problem. In order to guarantee the efficient and economic operation of microgrids, a three-layer multi-agent system including distributed management system agent, microgrid central control agent and microgrid control element agent is proposed considering energy storage units and demand response. Then, based on this multi-agent system and with the objective of cost minimization, an operation optimization model for microgrids is constructed from three aspects: operation cost, environmental impact and security. To solve this model, dynamic guiding chaotic search particle swarm optimization is adopted and three scenarios including basic scenario, energy storage participation and demand response participation are simulated and analyzed. The results show that both energy storage unit and demand response can effectively reduce the cost of microgrid, improve the operation and management level and ensure the safety and stability of power supply and utilization.https://www.mdpi.com/1996-1073/11/12/3286multi-agent systemdemand responsemicrogrid optimizationparticle swarm optimizationenergy storage |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Jicheng Liu Fangqiu Xu Shuaishuai Lin Hua Cai Suli Yan |
spellingShingle |
Jicheng Liu Fangqiu Xu Shuaishuai Lin Hua Cai Suli Yan A Multi-Agent-Based Optimization Model for Microgrid Operation Using Dynamic Guiding Chaotic Search Particle Swarm Optimization Energies multi-agent system demand response microgrid optimization particle swarm optimization energy storage |
author_facet |
Jicheng Liu Fangqiu Xu Shuaishuai Lin Hua Cai Suli Yan |
author_sort |
Jicheng Liu |
title |
A Multi-Agent-Based Optimization Model for Microgrid Operation Using Dynamic Guiding Chaotic Search Particle Swarm Optimization |
title_short |
A Multi-Agent-Based Optimization Model for Microgrid Operation Using Dynamic Guiding Chaotic Search Particle Swarm Optimization |
title_full |
A Multi-Agent-Based Optimization Model for Microgrid Operation Using Dynamic Guiding Chaotic Search Particle Swarm Optimization |
title_fullStr |
A Multi-Agent-Based Optimization Model for Microgrid Operation Using Dynamic Guiding Chaotic Search Particle Swarm Optimization |
title_full_unstemmed |
A Multi-Agent-Based Optimization Model for Microgrid Operation Using Dynamic Guiding Chaotic Search Particle Swarm Optimization |
title_sort |
multi-agent-based optimization model for microgrid operation using dynamic guiding chaotic search particle swarm optimization |
publisher |
MDPI AG |
series |
Energies |
issn |
1996-1073 |
publishDate |
2018-11-01 |
description |
The optimal operation of microgrids is a comprehensive and complex energy utilization and management problem. In order to guarantee the efficient and economic operation of microgrids, a three-layer multi-agent system including distributed management system agent, microgrid central control agent and microgrid control element agent is proposed considering energy storage units and demand response. Then, based on this multi-agent system and with the objective of cost minimization, an operation optimization model for microgrids is constructed from three aspects: operation cost, environmental impact and security. To solve this model, dynamic guiding chaotic search particle swarm optimization is adopted and three scenarios including basic scenario, energy storage participation and demand response participation are simulated and analyzed. The results show that both energy storage unit and demand response can effectively reduce the cost of microgrid, improve the operation and management level and ensure the safety and stability of power supply and utilization. |
topic |
multi-agent system demand response microgrid optimization particle swarm optimization energy storage |
url |
https://www.mdpi.com/1996-1073/11/12/3286 |
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