Microgrid energy management with energy storage systems: a review

Microgrids (MGs) are playing a fundamental role in the transition of energy systems towards a low carbon future due to the advantages of a highly efficient network architecture for flexible integration of various DC/AC loads, distributed renewable energy sources, and energy storage systems, as well...

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Main Authors: Liu, Xiong, Zhao, Tianyang, Deng, Hui, Wang, Peng, Liu, Jizhen, Blaabjerg, Frede
Other Authors: School of Electrical and Electronic Engineering
Format: Article
Language:English
Published: 2023
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Online Access:https://hdl.handle.net/10356/169613
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1696132023-07-28T15:40:03Z Microgrid energy management with energy storage systems: a review Liu, Xiong Zhao, Tianyang Deng, Hui Wang, Peng Liu, Jizhen Blaabjerg, Frede School of Electrical and Electronic Engineering Engineering::Electrical and electronic engineering Architecture Energy Management Microgrids (MGs) are playing a fundamental role in the transition of energy systems towards a low carbon future due to the advantages of a highly efficient network architecture for flexible integration of various DC/AC loads, distributed renewable energy sources, and energy storage systems, as well as a more resilient and economical on/off-grid control, operation, and energy management. However, MGs, as newcomers to the utility grid, are also facing challenges due to economic deregulation of energy systems, restructuring of generation, and market-based operation. This paper comprehensively summarizes the published research works in the areas of MGs and related energy management modelling and solution techniques. First, MGs and energy storage systems are classified into multiple branches and typical combinations as the backbone of MG energy management. Second, energy management models under exogenous and endogenous uncertainties are summarized and extended to transactive energy management. Mathematical programming, adaptive dynamic programming, and deep reinforcement learning-based solution methods are investigated accordingly, together with their implementation schemes. Finally, problems for future energy management systems with dynamics-captured critical component models, stability constraints, resilience awareness, market operation, and emerging computational techniques are discussed. Published version This work was supported in part by the State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources under Grant LAPS21002, in part by the National Natural Science Foundation of China under Grant 52061635102, in part by Guangdong Basic and Applied Basic Research Foundation under Grant 2021A1515110583. 2023-07-26T03:01:58Z 2023-07-26T03:01:58Z 2023 Journal Article Liu, X., Zhao, T., Deng, H., Wang, P., Liu, J. & Blaabjerg, F. (2023). Microgrid energy management with energy storage systems: a review. CSEE Journal of Power and Energy Systems, 9(2), 483-504. https://dx.doi.org/10.17775/CSEEJPES.2022.04290 2096-0042 https://hdl.handle.net/10356/169613 10.17775/CSEEJPES.2022.04290 2-s2.0-85152621072 2 9 483 504 en CSEE Journal of Power and Energy Systems © 2022 CSEE. Published by IEEE. This is an open-access article distributed under the terms of the Creative Commons Attribution License. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Electrical and electronic engineering
Architecture
Energy Management
spellingShingle Engineering::Electrical and electronic engineering
Architecture
Energy Management
Liu, Xiong
Zhao, Tianyang
Deng, Hui
Wang, Peng
Liu, Jizhen
Blaabjerg, Frede
Microgrid energy management with energy storage systems: a review
description Microgrids (MGs) are playing a fundamental role in the transition of energy systems towards a low carbon future due to the advantages of a highly efficient network architecture for flexible integration of various DC/AC loads, distributed renewable energy sources, and energy storage systems, as well as a more resilient and economical on/off-grid control, operation, and energy management. However, MGs, as newcomers to the utility grid, are also facing challenges due to economic deregulation of energy systems, restructuring of generation, and market-based operation. This paper comprehensively summarizes the published research works in the areas of MGs and related energy management modelling and solution techniques. First, MGs and energy storage systems are classified into multiple branches and typical combinations as the backbone of MG energy management. Second, energy management models under exogenous and endogenous uncertainties are summarized and extended to transactive energy management. Mathematical programming, adaptive dynamic programming, and deep reinforcement learning-based solution methods are investigated accordingly, together with their implementation schemes. Finally, problems for future energy management systems with dynamics-captured critical component models, stability constraints, resilience awareness, market operation, and emerging computational techniques are discussed.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Liu, Xiong
Zhao, Tianyang
Deng, Hui
Wang, Peng
Liu, Jizhen
Blaabjerg, Frede
format Article
author Liu, Xiong
Zhao, Tianyang
Deng, Hui
Wang, Peng
Liu, Jizhen
Blaabjerg, Frede
author_sort Liu, Xiong
title Microgrid energy management with energy storage systems: a review
title_short Microgrid energy management with energy storage systems: a review
title_full Microgrid energy management with energy storage systems: a review
title_fullStr Microgrid energy management with energy storage systems: a review
title_full_unstemmed Microgrid energy management with energy storage systems: a review
title_sort microgrid energy management with energy storage systems: a review
publishDate 2023
url https://hdl.handle.net/10356/169613
_version_ 1773551306908106752