Hybrid energy storage systems and control strategies for stand-alone renewable energy power systems

被引:192
作者
Chong, Lee Wai [1 ]
Wong, Yee Wan [1 ]
Rajkumar, Rajprasad Kumar [1 ]
Rajkumar, Rajpartiban Kumar [1 ]
Isa, Dino [1 ]
机构
[1] Univ Nottingham, Dept Elect & Elect Engn, Malaysia Campus,Jalan Broga, Semenyih 43500, Selangor, Malaysia
关键词
Renewable Energy; Stand-alone renewable energy storage system; Hybrid energy storage system; Classical control strategy; Intelligent control strategy; FUZZY-LOGIC CONTROLLER; BATTERY LIFETIME EXTENSION; MANAGEMENT-SYSTEM; ELECTRIC VEHICLES; TECHNOLOGIES; OPTIMIZATION; HYDROGEN; COST; PREDICTION; MODEL;
D O I
10.1016/j.rser.2016.07.059
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The energy storage system (ESS) in a conventional stand-alone renewable energy power system (REPS) usually has a short lifespan mainly due to irregular output of renewable energy sources. In certain systems, the ESS is oversized to reduce the stress level and to meet the intermittent peak power demand. A hybrid energy storage system (HESS) is a better solution in terms of durability, practicality and cost-effectiveness for the overall system implementation. The structure and the common issues of stand-alone REPS with ESS are discussed in this paper. This paper presents different structures of stand-alone REPS with HESS such as passive, semi-active, and active HESS. As there are a variety of energy storage technologies available in the market, decision matrixes are introduced in this paper to evaluate the technical and economic characteristics of the energy storage technologies based on the requirements of stand-alone REPS. A detailed review of the state-of-the-art control strategies such as classical control strategies and intelligent control strategies for REPS with HESS are highlighted. The future trends for REPS with HESS combination and control strategies are also discussed. (C) 2016 Elsevier Ltd. All rights reserved.
引用
收藏
页码:174 / 189
页数:16
相关论文
共 111 条
[1]   Application of adaptive neuro-fuzzy controller for SRM [J].
Akcayol, MA .
ADVANCES IN ENGINEERING SOFTWARE, 2004, 35 (3-4) :129-137
[2]  
Akhil A. A., 2015, SANDIA REPORT DOE EP
[3]   Review of energy storage technologies for sustainable power networks [J].
Akinyele, D. O. ;
Rayudu, R. K. .
SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS, 2014, 8 :74-91
[4]   Dynamic control and advanced load management of a stand-alone hybrid renewable power system for remote housing [J].
Alnejaili, Tareq ;
Drid, Said ;
Mehdi, Driss ;
Chrifi-Alaoui, Larbi ;
Belarbi, Rafik ;
Hamdouni, Aziz .
ENERGY CONVERSION AND MANAGEMENT, 2015, 105 :377-392
[5]   A novel maximum power fuzzy logic controller for photovoltaic solar energy systems [J].
Altas, I. H. ;
Sharaf, A. M. .
RENEWABLE ENERGY, 2008, 33 (03) :388-399
[6]   dSPACE based adaptive neuro-fuzzy controller of grid interactive inverter [J].
Altin, Necmi ;
Sefa, Ibrahim .
ENERGY CONVERSION AND MANAGEMENT, 2012, 56 :130-139
[7]  
[Anonymous], IEEE T CONTROL SYST
[8]  
[Anonymous], SAND20010765
[9]  
[Anonymous], INVESTIGATION ENERGY
[10]  
[Anonymous], 2010, AS PAC POW EN ENG C