A review on long-term electrical power system modeling with energy storage

被引:83
作者
Lai, Chun Sing [1 ,2 ,3 ]
Locatelli, Giorgio [1 ]
Pimm, Andrew [4 ]
Wu, Xiaomei [2 ]
Lai, Loi Lei [2 ]
机构
[1] Univ Leeds, Fac Engn & Phys Sci, Sch Civil Engn, Leeds LS2 9JT, W Yorkshire, England
[2] Guangdong Univ Technol, Sch Automat, Dept Elect Engn, Guangzhou 510006, Peoples R China
[3] Brunel Univ London, Brunel Inst Power Syst, Dept Elect & Comp Engn, London UB8 3PH, England
[4] Univ Leeds, Fac Engn & Phys Sci, Sch Chem & Proc Engn, Low Carbon Energy Res Grp, Leeds LS2 9JT, W Yorkshire, England
基金
英国工程与自然科学研究理事会;
关键词
Electrical power system model; Generation-integrated energy storage; Energy storage; Economics; PUMPED-HYDRO STORAGE; BIG DATA ANALYTICS; COMPRESSED-AIR; RENEWABLE ENERGY; LIQUID AIR; THERMODYNAMIC ANALYSIS; LEVELIZED COST; MOLTEN-SALT; CAPACITY EXPANSION; BOTTOM-UP;
D O I
10.1016/j.jclepro.2020.124298
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Driven by the demand for intermittent power generation, Energy Storage (ES) will be widely adopted in future electricity grids to provide flexibility and resilience. Technically, there are two classes of ES for storing low-carbon energy: Generation-Integrated Energy Storage (GIES) and non-GIES. GIES stores energy along with the transformation between the primary energy form (e.g., thermal energy) and electricity. Long-term Electrical Power System Models (LEPSMs) support analysis including decarbonization studies and energy technology assessments. Current LEPSMs are limited in describing the power system with ES (e.g., considering one type of ES and not considering GIES). Consequently, a novel LEPSM is needed, and this paper paves the way towards this goal by bringing together the literature on ES and LEPSMs. This paper provides a state-of-the-art review of LEPSMs and shows that (a) existing models are inadequate to address grids with a high percentage of renewables and ES; and (b) there is a challenge in integrating short-term temporal changes in LEPSMs due to model complexity and computational cost. Finally, this paper proposes a framework for long-term electrical power system modeling considering ES and low-carbon power generation, which we have named the long-term power flow electrical power system framework. The key features of this novel framework are its agent-based modeling of consumer behavior, scenario reduction for renewables, and power flow analysis. (C) 2020 The Authors. Published by Elsevier Ltd.
引用
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页数:21
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