Next Article in Journal
Improving SBR Performance Alongside with Cost Reduction through Optimizing Biological Processes and Dissolved Oxygen Concentration Trajectory
Next Article in Special Issue
SOC Estimation with an Adaptive Unscented Kalman Filter Based on Model Parameter Optimization
Previous Article in Journal
Effects of Fineness and Dosage of Fly Ash on the Fracture Properties and Strength of Concrete
Previous Article in Special Issue
Adaptive Dual Extended Kalman Filter Based on Variational Bayesian Approximation for Joint Estimation of Lithium-Ion Battery State of Charge and Model Parameters
Open AccessFeature PaperArticle

Cooperative Optimization of Electric Vehicles and Renewable Energy Resources in a Regional Multi-Microgrid System

State Key Laboratory of Advanced Electromagnetic Engineering and Technology, School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
*
Author to whom correspondence should be addressed.
Appl. Sci. 2019, 9(11), 2267; https://doi.org/10.3390/app9112267
Received: 18 April 2019 / Revised: 23 May 2019 / Accepted: 27 May 2019 / Published: 31 May 2019
(This article belongs to the Special Issue Battery Management System for Future Electric Vehicles)
By integrating renewable energy sources (RESs) with electric vehicles (EVs) in microgrids, we are able to reduce carbon emissions as well as alleviate the dependence on fossil fuels. In order to improve the economy of an integrated system and fully exploit the potentiality of EVs’ mobile energy storage while achieving a reasonable configuration of RESs, a cooperative optimization method is proposed to cooperatively optimize the economic dispatching and capacity allocation of both RESs and EVs in the context of a regional multi-microgrid system. An across-time-and-space energy transmission (ATSET) of the EVs was considered, and the impact of ATSET of EVs on economic dispatching and capacity allocation of multi-microgrid system was analyzed. In order to overcome the difficulty of finding the global optimum of the non-smooth total cost function, an improved particle swarm optimization (IPSO) algorithm was used to solve the cooperative optimization problem. Case studies were performed, and the simulation results show that the proposed cooperative optimization method can significantly decrease the total cost of a multi-microgrid system. View Full-Text
Keywords: electric vehicles; renewable energy sources; microgrid; economic dispatching; capacity allocation; cooperative optimization electric vehicles; renewable energy sources; microgrid; economic dispatching; capacity allocation; cooperative optimization
Show Figures

Figure 1

MDPI and ACS Style

Chen, J.; Chen, C.; Duan, S. Cooperative Optimization of Electric Vehicles and Renewable Energy Resources in a Regional Multi-Microgrid System. Appl. Sci. 2019, 9, 2267.

Show more citation formats Show less citations formats
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