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Battery Energy Storage Systems (BESSs) and the Economy-Dynamics of Microgrids: Review, Analysis, and Classification for Standardization of BESSs Applications

Authors: Zhao Yang Dong; Mohammad H. Moradi; Andrey Savkin; Amin Rajabi; Mohsen Eskandari;

Battery Energy Storage Systems (BESSs) and the Economy-Dynamics of Microgrids: Review, Analysis, and Classification for Standardization of BESSs Applications

Abstract

The literature on microgrid (MG) studies can be categorized as those that investigated the dynamics or economics of MG systems. Due to the important roles of battery energy storage systems (BESSs) in MGs, the BESSs have been involved in both economics and dynamics studies but mostly separately due to the different time constants of studies. Whereas, in the complicated modern MGs, the BESS is the joint point that bridges these two studies. Thus, studying merely one aspect of economy-dynamic without considering the other aspect would not be accurate. To bridge this gap, this paper reviews, analysis and classifies the BESSs applications, based on their time constants, by merging of which helps researchers to develop joint economy-dynamics models that would be the future trend in the field. The classified BESS applications are 1) inertia synthesis, 2) primary frequency response to compensate slow response time of micro-sources (MSs) for load tracking, 3) real-time energy management for the integration of intermittent renewables, 4) economic dispatch and optimal power flow for improving steady-state performance, and 5) slack bus realization. The research gaps and future trends have been discussed throughout the paper and are summarized in the future trend section.

Countries
Singapore, Australia
Keywords

690, anzsrc-for: 4009 Electronics, 330, Engineering::Electrical and electronic engineering, Battery Energy Storage, 333, anzsrc-for: 40 Engineering, 4009 Electronics, :Electrical and electronic engineering [Engineering], 7 Affordable and Clean Energy, Renewable Energy, Sensors and Digital Hardware, 40 Engineering

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    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
42
Top 10%
Top 10%
Top 1%