Advancements in intelligent cloud computing for power optimization and battery management in hybrid renewable energy systems: A comprehensive review
A cloud computing-based power optimization system (CC-POS) is an important enabler for hybrid renewable-based power systems with higher output, optimal solutions to extend battery storage life, and remotely flexible power distribution control. Recent advancements in cloud computing have begun to del...
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my.uniten.dspace-339782024-10-14T11:17:34Z Advancements in intelligent cloud computing for power optimization and battery management in hybrid renewable energy systems: A comprehensive review AL-Jumaili A.H.A. Muniyandi R.C. Hasan M.K. Singh M.J. Paw J.K.S. Amir M. 57212194331 14030355800 55057479600 58765817900 58168727000 57210089902 Battery life Battery management Cloud computing Power consumption Renewable energy systems State of charge Adaptive control systems Battery management systems Charging (batteries) Cloud computing Computing power Electric power distribution Electric power transmission Green computing Renewable energy resources Search engines Secondary batteries Battery life Battery Management Cloud-computing Energy systems Hybrid renewable energies Optimization system Power Optimization Renewable energies Renewable energy system States of charges Electric power utilization A cloud computing-based power optimization system (CC-POS) is an important enabler for hybrid renewable-based power systems with higher output, optimal solutions to extend battery storage life, and remotely flexible power distribution control. Recent advancements in cloud computing have begun to deliver critical insights, resulting in adaptive-based control of storage systems with improved performance. This study aims to review the recently published literature on the topic of power management systems and battery charging control. The role of intelligent based cloud computing is to improve the battery life and manage the battery state of charge (SoC). To achieve this purpose, publishers� databases and search engines were used to obtain the studies reviewed in this paper. We identify and review the purpose, achievements, tools/algorithm, and recommendations for each survey work, and thus outline a number of key findings and future directions. Furthermore, the review includes a listing of novels and recently used algorithms. Additionally, a critical review of 174 research articles were analyzed as per Web of Science (WoS) and Scopus database. The key findings of this study are discussed in two key conceptual frameworks that contain a power optimization system and an optimal battery management system. The power transmission, distribution, and charge and discharge processes are controlled and stored on cloud computing using the power mix between hybrid renewable energy and other power sources. � 2023 The Author(s) Final 2024-10-14T03:17:34Z 2024-10-14T03:17:34Z 2023 Review 10.1016/j.egyr.2023.09.029 2-s2.0-85171323575 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85171323575&doi=10.1016%2fj.egyr.2023.09.029&partnerID=40&md5=e0dbc7b80dc1dff0de0f89edbe660e34 https://irepository.uniten.edu.my/handle/123456789/33978 10 2206 2227 All Open Access Gold Open Access Elsevier Ltd Scopus |
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Battery life Battery management Cloud computing Power consumption Renewable energy systems State of charge Adaptive control systems Battery management systems Charging (batteries) Cloud computing Computing power Electric power distribution Electric power transmission Green computing Renewable energy resources Search engines Secondary batteries Battery life Battery Management Cloud-computing Energy systems Hybrid renewable energies Optimization system Power Optimization Renewable energies Renewable energy system States of charges Electric power utilization |
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Battery life Battery management Cloud computing Power consumption Renewable energy systems State of charge Adaptive control systems Battery management systems Charging (batteries) Cloud computing Computing power Electric power distribution Electric power transmission Green computing Renewable energy resources Search engines Secondary batteries Battery life Battery Management Cloud-computing Energy systems Hybrid renewable energies Optimization system Power Optimization Renewable energies Renewable energy system States of charges Electric power utilization AL-Jumaili A.H.A. Muniyandi R.C. Hasan M.K. Singh M.J. Paw J.K.S. Amir M. Advancements in intelligent cloud computing for power optimization and battery management in hybrid renewable energy systems: A comprehensive review |
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A cloud computing-based power optimization system (CC-POS) is an important enabler for hybrid renewable-based power systems with higher output, optimal solutions to extend battery storage life, and remotely flexible power distribution control. Recent advancements in cloud computing have begun to deliver critical insights, resulting in adaptive-based control of storage systems with improved performance. This study aims to review the recently published literature on the topic of power management systems and battery charging control. The role of intelligent based cloud computing is to improve the battery life and manage the battery state of charge (SoC). To achieve this purpose, publishers� databases and search engines were used to obtain the studies reviewed in this paper. We identify and review the purpose, achievements, tools/algorithm, and recommendations for each survey work, and thus outline a number of key findings and future directions. Furthermore, the review includes a listing of novels and recently used algorithms. Additionally, a critical review of 174 research articles were analyzed as per Web of Science (WoS) and Scopus database. The key findings of this study are discussed in two key conceptual frameworks that contain a power optimization system and an optimal battery management system. The power transmission, distribution, and charge and discharge processes are controlled and stored on cloud computing using the power mix between hybrid renewable energy and other power sources. � 2023 The Author(s) |
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57212194331 |
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57212194331 AL-Jumaili A.H.A. Muniyandi R.C. Hasan M.K. Singh M.J. Paw J.K.S. Amir M. |
format |
Review |
author |
AL-Jumaili A.H.A. Muniyandi R.C. Hasan M.K. Singh M.J. Paw J.K.S. Amir M. |
author_sort |
AL-Jumaili A.H.A. |
title |
Advancements in intelligent cloud computing for power optimization and battery management in hybrid renewable energy systems: A comprehensive review |
title_short |
Advancements in intelligent cloud computing for power optimization and battery management in hybrid renewable energy systems: A comprehensive review |
title_full |
Advancements in intelligent cloud computing for power optimization and battery management in hybrid renewable energy systems: A comprehensive review |
title_fullStr |
Advancements in intelligent cloud computing for power optimization and battery management in hybrid renewable energy systems: A comprehensive review |
title_full_unstemmed |
Advancements in intelligent cloud computing for power optimization and battery management in hybrid renewable energy systems: A comprehensive review |
title_sort |
advancements in intelligent cloud computing for power optimization and battery management in hybrid renewable energy systems: a comprehensive review |
publisher |
Elsevier Ltd |
publishDate |
2024 |
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1814061160644739072 |
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13.214268 |