Next Article in Journal
Effect of Time on a Hierarchical Corn Skeleton-Like Composite of [email protected] as Capacitive Electrode Material for High Specific Performance Supercapacitors
Previous Article in Journal
Assessment of the Territorial Energy Security in the Context of Energy Systems Integration
 
 
Article

A Multi-Agent-Based Optimization Model for Microgrid Operation Using Dynamic Guiding Chaotic Search Particle Swarm Optimization

by 1,2, 1,2,*, 1,2, 3 and 1,2
1
School of Economics and Management, North China Electric Power University, Beijing 102206, China
2
Beijing Key Laboratory of New Energy and Low-Carbon Development (North China Electric Power University), Changping, Beijing 102206, China
3
Industrial Engineering, Purdue University, West Lafayette, IN 47907, USA
*
Author to whom correspondence should be addressed.
Energies 2018, 11(12), 3286; https://doi.org/10.3390/en11123286
Received: 29 October 2018 / Revised: 20 November 2018 / Accepted: 21 November 2018 / Published: 25 November 2018
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. View Full-Text
Keywords: multi-agent system; demand response; microgrid optimization; particle swarm optimization; energy storage multi-agent system; demand response; microgrid optimization; particle swarm optimization; energy storage
Show Figures

Figure 1

MDPI and ACS Style

Liu, J.; Xu, F.; Lin, S.; Cai, H.; Yan, S. A Multi-Agent-Based Optimization Model for Microgrid Operation Using Dynamic Guiding Chaotic Search Particle Swarm Optimization. Energies 2018, 11, 3286. https://doi.org/10.3390/en11123286

AMA Style

Liu J, Xu F, Lin S, Cai H, Yan S. A Multi-Agent-Based Optimization Model for Microgrid Operation Using Dynamic Guiding Chaotic Search Particle Swarm Optimization. Energies. 2018; 11(12):3286. https://doi.org/10.3390/en11123286

Chicago/Turabian Style

Liu, Jicheng, Fangqiu Xu, Shuaishuai Lin, Hua Cai, and Suli Yan. 2018. "A Multi-Agent-Based Optimization Model for Microgrid Operation Using Dynamic Guiding Chaotic Search Particle Swarm Optimization" Energies 11, no. 12: 3286. https://doi.org/10.3390/en11123286

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop