Bibliographical progress in hybrid renewable energy systems' integration, modelling, optimization, and artificial intelligence applications: A critical review and future research perspective

被引:15
作者
Wei, Pengyu [1 ]
Bamisile, Olusola [1 ]
Adun, Humphrey [2 ]
Cai, Dongsheng [1 ]
Obiora, Sandra [3 ]
Li, Jian [4 ]
Huang, Qi [1 ,4 ]
机构
[1] Chengdu Univ Technol, Sichuan Ind Internet Intelligent Monitoring & Appl, Chengdu 610059, Sichuan, Peoples R China
[2] Cyprus Int Univ, Energy Syst Engn Dept, Haspolat Lefkosa, Turkiye
[3] Univ Elect Sci & Technol China, Sch Management & Econ, Chengdu, Sichuan, Peoples R China
[4] Univ Elect Sci & Technol China, Sch Mech & Elect Engn, Chengdu, Sichuan, Peoples R China
基金
中国国家自然科学基金;
关键词
Hybrid renewable energy systems; artificial intelligence; energy storage systems; optimization methods; review; SIMULATED ANNEALING ALGORITHM; PARTICLE SWARM OPTIMIZATION; POWER-SUPPLY PROBABILITY; WIND-BATTERY SYSTEM; LIFE-CYCLE COST; OPTIMAL-DESIGN; BEE COLONY; RURAL ELECTRIFICATION; FEASIBILITY ANALYSIS; MULTIOBJECTIVE OPTIMIZATION;
D O I
10.1080/15567036.2023.2181888
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Global energy demand has consistently increased in recent decades, owing to the rapid population increase. Energy consumption is higher than it has ever been, and most fossil supplies are on the verge of exhaustion with the current rate of exploitation. Facing the double pressure of meeting energy demands and reducing carbon emissions, the integration of renewable energy into different aspects of the energy ecosystem has become a unified agreement for all countries globally. Hybrid renewable energy systems that integrate multiple energy sources can effectively solve this problem. In the hybrid renewable energy system, optimizing the unit size is the key to achieving efficient utilization of renewable energy. Research trends show that artificial intelligence methods are gaining attention from researchers and can provide good system optimization in the absence of long-term weather data to provide good system optimization. While different studies have presented articles in this research domain, it is important to give a comprehensive collation/summary of the research trend while highlighting key models/methods utilized in this research domain. Hence, based on the published literature, this paper provides a comprehensive bibliographical review of the current trends/status of hybrid renewable energy systems research. Key research articles published in the Web of Science between the years 2000 and 2022 in this research domain have been reviewed. This paper describes the hybrid renewable energy systems, summarizes many different energy systems in existing literature, compares the differences between various energy systems, and analyzes the physical models of different systems, as well as the optimization methods and the optimization of the systems. Further, the uncertainty of electricity generation from renewable energy sources is analyzed in the literature review and the future challenges of hybrid renewable energy systems are summarized.
引用
收藏
页码:2058 / 2088
页数:31
相关论文
共 50 条
[21]   Optimization and Integration Strategies for Hybrid Renewable Energy Systems in the Brazilian Power Grid: A Systematic Review [J].
Guedes Filho, Dalton F. ;
Miranda, Rodrigo L. ;
Correia, Lucas A. ;
Fernandes, Lucas Do E. S. ;
Medrado, Ricardo C. ;
De, C. Marcio ;
Jose, B. M. ;
Marinho, Manoel H. N. ;
Nascimento, Erick G. Sperandio .
IEEE ACCESS, 2025, 13 :84170-84187
[22]   A review of the hybrid artificial intelligence and optimization modelling of hydrological streamflow forecasting [J].
Ibrahim, Karim Sherif Mostafa Hassan ;
Huang, Yuk Feng ;
Ahmed, Ali Najah ;
Koo, Chai Hoon ;
El-Shafie, Ahmed .
ALEXANDRIA ENGINEERING JOURNAL, 2022, 61 (01) :279-303
[23]   Hybrid Renewable Energy Systems and Their Optimization for Remote Community Applications [J].
Qiu, Kuanrong ;
Entchev, Evgueniy .
2024 13TH INTERNATIONAL CONFERENCE ON RENEWABLE ENERGY RESEARCH AND APPLICATIONS, ICRERA 2024, 2024, :359-363
[24]   Scrutiny of Hybrid Renewable Energy Systems for Control, Power Management, Optimization and Sizing: Challenges and Future Possibilities [J].
Rathod, Asmita Ajay ;
Subramanian, Balaji .
SUSTAINABILITY, 2022, 14 (24)
[25]   Hydrogen energy storage integrated hybrid renewable energy systems: A review analysis for future research directions [J].
Arsad, A. Z. ;
Hannan, M. A. ;
Al-Shetwi, Ali Q. ;
Mansur, M. ;
Muttaqi, K. M. ;
Dong, Z. Y. ;
Blaabjerg, F. .
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY, 2022, 47 (39) :17285-17312
[26]   A review on pump-hydro storage for renewable and hybrid energy systems applications [J].
Das, Pronob ;
Das, Barun K. ;
Mustafi, Nirendra N. ;
Sakir, Md Takmil .
ENERGY STORAGE, 2021, 3 (04)
[27]   Swarm intelligence-based optimization of grid-dependent hybrid renewable energy systems [J].
Mohamed, Mohamed A. ;
Eltamaly, Ali M. ;
Alolah, Abdulrahman I. .
RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2017, 77 :515-524
[28]   A review of artificial intelligence-based optimization techniques for the sizing of integrated renewable energy systems in smart cities [J].
Kanase-Patil A.B. ;
Kaldate A.P. ;
Lokhande S.D. ;
Panchal H. ;
Suresh M. ;
Priya V. .
Environmental Technology Reviews, 2020, 9 (01) :111-136
[29]   Artificial intelligence application in a renewable energy-driven desalination system: A critical review [J].
He, Qian ;
Zheng, Hongfei ;
Ma, Xinglong ;
Wang, Lu ;
Kong, Hui ;
Zhu, Ziye .
ENERGY AND AI, 2022, 7
[30]   A review of algorithms for control and optimization for energy management of hybrid renewable energy systems [J].
Saharia, Barnam Jyoti ;
Brahma, Honey ;
Sarmah, Nabin .
JOURNAL OF RENEWABLE AND SUSTAINABLE ENERGY, 2018, 10 (05)