Next Article in Journal
Fusion of Linear and Mel Frequency Cepstral Coefficients for Automatic Classification of Reptiles
Previous Article in Journal
Measurement and Analysis of Channel Characteristics in Reflective Environments at 3.6 GHz and 14.6 GHz
Article Menu
Issue 2 (February) cover image

Export Article

Open AccessArticle
Appl. Sci. 2017, 7(2), 163; doi:10.3390/app7020163

Multi-Objective Configuration Optimization of a Hybrid Energy Storage System

1
Hubei Provincial Collaborative Innovation Center for New Energy Microgrid (China Three Gorges University), Yichang 443002, China
2
College of Electrical Engineering and New Energy, China Three Gorges University, Yichang 443002, China
*
Author to whom correspondence should be addressed.
Academic Editor: Luisa F. Cabeza
Received: 5 January 2017 / Accepted: 6 February 2017 / Published: 13 February 2017
(This article belongs to the Section Energy)
View Full-Text   |   Download PDF [2667 KB, uploaded 23 February 2017]   |  

Abstract

This study aims to investigate multi-objective configuration optimization of a hybrid energy storage system (HESS). In order to maximize the stability of the wind power output with minimized HESS investment, a multi-objective model for optimal HESS configuration has been established, which proposes decreasing the installation and operation & maintenance costs of an HESS and improving the compensation satisfaction rate of wind power fluctuation. Besides, fuzzy control has been used to allocate power in the HESS for lengthening battery lifetime and ensuring HESS with enough energy to compensate the fluctuation of the next time interval. Instead of converting multiple objectives into one, a multi-objective particle swarm optimization with integration of bacteria quorum sensing and circular elimination (BC-MOPSO) has been applied to provide diverse alternative solutions. In order to illustrate the feasibility and effectiveness of the proposed model and the application of BC-MOPSO, simulations along with analysis and discussion are carried out. The results verified the feasibility and effectiveness of the proposed approach. View Full-Text
Keywords: wind power; hybrid energy storage system; multi-objective particle swarm optimization wind power; hybrid energy storage system; multi-objective particle swarm optimization
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Cheng, S.; Sun, W.-B.; Liu, W.-L. Multi-Objective Configuration Optimization of a Hybrid Energy Storage System. Appl. Sci. 2017, 7, 163.

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.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Appl. Sci. EISSN 2076-3417 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top