Battery Energy Storage Technology in Renewable Energy Integration: a Review

被引：4
作者：
Javadi, Masoud [1 ]
Liang, Xiaodong [1 ]
Gong, Yuzhong [1 ]
Chung, Chi Yung [2 ]
机构：
[1] Univ Saskatchewan, Dept Elect & Comp Engn, Saskatoon, SK, Canada
[2] Hong Kong Polytech Univ, Dept Elect Engn, Hong Kong, Peoples R China
来源：
2022 IEEE CANADIAN CONFERENCE ON ELECTRICAL AND COMPUTER ENGINEERING (CCECE) | 2022年
基金：
加拿大自然科学与工程研究理事会;
关键词：
Battery energy storage system; renewable energy; PV power; wind power; OPTIMAL ALLOCATION; DISTRIBUTION-SYSTEMS; HIGH PENETRATION; ION BATTERIES; POWER; WIND; PV; MANAGEMENT; ARBITRAGE; DISPATCH;
D O I：
10.1109/CCECE49351.2022.9918504
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
Renewable energy sources reduce greenhouse gas emissions caused by traditional fossil fuel-based power plants, and experience rapid developments recently. Despite the benefits, due to their intermittent nature, renewables may result in power oscillations, and deteriorate stability, reliability, and power quality of power grids. Integration of battery energy storage systems (BESSs) with renewable generation units, such as solar photovoltaic (PV) systems and wind farms, can effectively smooth out power fluctuations. In this paper, an extensive literature review is conducted on various BESS technologies and their potential applications in renewable energy integration. To improve the quality of service with the lowest costs, BESSs should be optimized in the planning and operation stages to control the unit and its charging/discharging output power. As the cost of BESSs is still high, optimal decision-making to improve the profitability of these devices considering technical and lifetime constraints is of paramount importance.
引用
收藏
页码：435 / 440
页数：6
相关论文
共 80 条
[1]   Integrated PV Capacity Firming and Energy Time Shift Battery Energy Storage Management Using Energy-Oriented Optimization [J].
Abdelrazek, Sherif A. ;
Kamalasadan, Sukumar .
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, 2016, 52 (03) :2607-2617
[2]   Congestion Risk-Aware Unit Commitment With Significant Wind Power Generation [J].
Abedi, Sajjad ;
He, Miao ;
Obadina, Diran .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2018, 33 (06) :6861-6869
[3]   Reinforcement Learning-Based Distributed BESS Management for Mitigating Overvoltage Issues in Systems With High PV Penetration [J].
Al-Saffar, Mohammed ;
Musilek, Petr .
IEEE TRANSACTIONS ON SMART GRID, 2020, 11 (04) :2980-2994
[4]  
[Anonymous], 2021, BloombergNEF
[5]   Optimal Allocation of ESS in Distribution Systems With a High Penetration of Wind Energy [J].
Atwa, Yasser Moustafa ;
El-Saadany, E. F. .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2010, 25 (04) :1815-1822
[6]   Global fossil energy markets and climate change mitigation - an analysis with REMIND [J].
Bauer, Nico ;
Mouratiadou, Ioanna ;
Luderer, Gunnar ;
Baumstark, Lavinia ;
Brecha, Robert J. ;
Edenhofer, Ottmar ;
Kriegler, Elmar .
CLIMATIC CHANGE, 2016, 136 (01) :69-82
[7]  
BloombergNEF, 2019, SCEN TAK LITH IV BAT
[8]   Study of hourly and daily solar irradiation forecast using diagonal recurrent wavelet neural networks [J].
Cao, Jiacong ;
Lin, Xingchun .
ENERGY CONVERSION AND MANAGEMENT, 2008, 49 (06) :1396-1406
[9]   Grid-scale energy storage applications in renewable energy integration: A survey [J].
Castillo, Anya ;
Gayme, Dennice F. .
ENERGY CONVERSION AND MANAGEMENT, 2014, 87 :885-894
[10]  
Chen C., 2021, IEEE T TRANSP ELECTR
12345678