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Optimal Sizing, Control, and Management Strategies for Hybrid Renewable Energy Systems: A Comprehensive Review

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  • Akhlaque Ahmad Khan

    (Electrical Engineering Department, Integral University, Lucknow 226026, India)

  • Ahmad Faiz Minai

    (Electrical Engineering Department, Integral University, Lucknow 226026, India)

  • Rupendra Kumar Pachauri

    (EEED, SoE, UPES, Dehradun 248007, India)

  • Hasmat Malik

    (Division of Electrical Power Engineering, School of Electrical Engineering, Faculty of Engineering, Universiti Teknologi Malaysia (UTM), Johor Bahru 81310, Malaysia)

Abstract

To meet the expanding energy demand, all available energy sources must be utilized. Renewable energies are both eternal and natural, but their major downside is their inconsistency. Due to the rising costs of fossil fuels and the CO 2 they emit, hybrid renewable energy (HRE) sources have gained popularity as an alternative in remote and rural areas. To address this issue, a hybrid renewable energy system (HRES) can be developed by combining several energy sources. In order to build modern electrical grids that have advantages for the economy, environment, and society, the hybrid system is preferable. A summary of various optimization methods (modeling techniques) of an HRES is presented in this paper. This study offers an in-depth analysis of the best sizing, control methodologies, and energy management strategies, along with the incorporation of various renewable energy sources to form a hybrid system. Modern hybrid renewable energy system utilities rely more on an optimal design to reduce the cost function. Reviews of several mathematical models put out by various academicians are presented in this work. These models were created based on reliability analyses incorporating design factors, objective functions, and economics. The reader will get familiar with numerous system modelling optimization strategies after reading this study, and they will be able to compare different models based on their cost functions. Numerous modeling approaches and software simulation tools have been created to aid stakeholders in the planning, research, and development of HRES. The optimal use of renewable energy potential and the meticulous creation of applicable designs are closely tied to the full analysis of these undoubtedly complicated systems. In this field, as well, several optimization restrictions and objectives have been applied. Overall, the optimization, sizing, and control of HRES are covered in this paper with the energy management strategies.

Suggested Citation

  • Akhlaque Ahmad Khan & Ahmad Faiz Minai & Rupendra Kumar Pachauri & Hasmat Malik, 2022. "Optimal Sizing, Control, and Management Strategies for Hybrid Renewable Energy Systems: A Comprehensive Review," Energies, MDPI, vol. 15(17), pages 1-29, August.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:17:p:6249-:d:899189
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    as
    1. Santarelli, M. & Pellegrino, D., 2005. "Mathematical optimization of a RES-H2 plant using a black box algorithm," Renewable Energy, Elsevier, vol. 30(4), pages 493-510.
    2. Yuan, Yupeng & Wang, Jixiang & Yan, Xinping & Li, Qing & Long, Teng, 2018. "A design and experimental investigation of a large-scale solar energy/diesel generator powered hybrid ship," Energy, Elsevier, vol. 165(PA), pages 965-978.
    3. Kalogirou, Soteris A., 2004. "Optimization of solar systems using artificial neural-networks and genetic algorithms," Applied Energy, Elsevier, vol. 77(4), pages 383-405, April.
    4. Liu, Wen Hui & Wan Alwi, Sharifah Rafidah & Hashim, Haslenda & Lim, Jeng Shiun & Mohammad Rozali, Nor Erniza & Ho, Wai Shin, 2016. "Sizing of Hybrid Power System with varying current type using numerical probabilistic approach," Applied Energy, Elsevier, vol. 184(C), pages 1364-1373.
    5. Ma, Weiwu & Xue, Xinpei & Liu, Gang, 2018. "Techno-economic evaluation for hybrid renewable energy system: Application and merits," Energy, Elsevier, vol. 159(C), pages 385-409.
    6. Sanajaoba, Sarangthem & Fernandez, Eugene, 2016. "Maiden application of Cuckoo Search algorithm for optimal sizing of a remote hybrid renewable energy System," Renewable Energy, Elsevier, vol. 96(PA), pages 1-10.
    7. Ramli, Makbul A.M. & Bouchekara, H.R.E.H. & Alghamdi, Abdulsalam S., 2018. "Optimal sizing of PV/wind/diesel hybrid microgrid system using multi-objective self-adaptive differential evolution algorithm," Renewable Energy, Elsevier, vol. 121(C), pages 400-411.
    8. Lamedica, Regina & Santini, Ezio & Ruvio, Alessandro & Palagi, Laura & Rossetta, Irene, 2018. "A MILP methodology to optimize sizing of PV - Wind renewable energy systems," Energy, Elsevier, vol. 165(PB), pages 385-398.
    9. Mengjun Ming & Rui Wang & Yabing Zha & Tao Zhang, 2017. "Multi-Objective Optimization of Hybrid Renewable Energy System Using an Enhanced Multi-Objective Evolutionary Algorithm," Energies, MDPI, vol. 10(5), pages 1-15, May.
    10. Athari, M.H. & Ardehali, M.M., 2016. "Operational performance of energy storage as function of electricity prices for on-grid hybrid renewable energy system by optimized fuzzy logic controller," Renewable Energy, Elsevier, vol. 85(C), pages 890-902.
    11. Eriksson, E.L.V. & Gray, E.MacA., 2019. "Optimization of renewable hybrid energy systems – A multi-objective approach," Renewable Energy, Elsevier, vol. 133(C), pages 971-999.
    12. Nogueira, Carlos Eduardo Camargo & Vidotto, Magno Luiz & Niedzialkoski, Rosana Krauss & de Souza, Samuel Nelson Melegari & Chaves, Luiz Inácio & Edwiges, Thiago & Santos, Darlisson Bentes dos & Wernck, 2014. "Sizing and simulation of a photovoltaic-wind energy system using batteries, applied for a small rural property located in the south of Brazil," Renewable and Sustainable Energy Reviews, Elsevier, vol. 29(C), pages 151-157.
    13. Khan, Faizan A. & Pal, Nitai & Saeed, Syed.H., 2018. "Review of solar photovoltaic and wind hybrid energy systems for sizing strategies optimization techniques and cost analysis methodologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 92(C), pages 937-947.
    14. Acuña, Luceny Guzmán & Padilla, Ricardo Vasquez & Mercado, Alcides Santander, 2017. "Measuring reliability of hybrid photovoltaic-wind energy systems: A new indicator," Renewable Energy, Elsevier, vol. 106(C), pages 68-77.
    15. Prasad, A. Rajendra & Natarajan, E., 2006. "Optimization of integrated photovoltaic–wind power generation systems with battery storage," Energy, Elsevier, vol. 31(12), pages 1943-1954.
    16. Li, Qian & Loy-Benitez, Jorge & Nam, KiJeon & Hwangbo, Soonho & Rashidi, Jouan & Yoo, ChangKyoo, 2019. "Sustainable and reliable design of reverse osmosis desalination with hybrid renewable energy systems through supply chain forecasting using recurrent neural networks," Energy, Elsevier, vol. 178(C), pages 277-292.
    17. Guangqian, Du & Bekhrad, Kaveh & Azarikhah, Pouria & Maleki, Akbar, 2018. "A hybrid algorithm based optimization on modeling of grid independent biodiesel-based hybrid solar/wind systems," Renewable Energy, Elsevier, vol. 122(C), pages 551-560.
    18. Gupta, R.A. & Kumar, Rajesh & Bansal, Ajay Kumar, 2015. "BBO-based small autonomous hybrid power system optimization incorporating wind speed and solar radiation forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 1366-1375.
    19. Rouholamini, Mehdi & Mohammadian, Mohsen, 2016. "Heuristic-based power management of a grid-connected hybrid energy system combined with hydrogen storage," Renewable Energy, Elsevier, vol. 96(PA), pages 354-365.
    20. Padrón, Isidro & Avila, Deivis & Marichal, Graciliano N. & Rodríguez, José A., 2019. "Assessment of Hybrid Renewable Energy Systems to supplied energy to Autonomous Desalination Systems in two islands of the Canary Archipelago," Renewable and Sustainable Energy Reviews, Elsevier, vol. 101(C), pages 221-230.
    21. Wang, Kejun & Qi, Xiaoxia & Liu, Hongda, 2019. "A comparison of day-ahead photovoltaic power forecasting models based on deep learning neural network," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    22. Talent, Orlando & Du, Haiping, 2018. "Optimal sizing and energy scheduling of photovoltaic-battery systems under different tariff structures," Renewable Energy, Elsevier, vol. 129(PA), pages 513-526.
    23. Yan, Jie & Menghwar, Mohan & Asghar, Ehtisham & Kumar Panjwani, Manoj & Liu, Yongqian, 2019. "Real-time energy management for a smart-community microgrid with battery swapping and renewables," Applied Energy, Elsevier, vol. 238(C), pages 180-194.
    24. Rullo, P. & Braccia, L. & Luppi, P. & Zumoffen, D. & Feroldi, D., 2019. "Integration of sizing and energy management based on economic predictive control for standalone hybrid renewable energy systems," Renewable Energy, Elsevier, vol. 140(C), pages 436-451.
    25. Zhou, Wei & Lou, Chengzhi & Li, Zhongshi & Lu, Lin & Yang, Hongxing, 2010. "Current status of research on optimum sizing of stand-alone hybrid solar-wind power generation systems," Applied Energy, Elsevier, vol. 87(2), pages 380-389, February.
    26. Fathima, A. Hina & Palanisamy, K., 2015. "Optimization in microgrids with hybrid energy systems – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 45(C), pages 431-446.
    27. Weiqiang Dong & Yanjun Li & Ji Xiang, 2016. "Optimal Sizing of a Stand-Alone Hybrid Power System Based on Battery/Hydrogen with an Improved Ant Colony Optimization," Energies, MDPI, vol. 9(10), pages 1-17, September.
    28. Kosmas A. Kavadias & Panagiotis Triantafyllou, 2021. "Hybrid Renewable Energy Systems’ Optimisation. A Review and Extended Comparison of the Most-Used Software Tools," Energies, MDPI, vol. 14(24), pages 1-28, December.
    29. Ashok, S., 2007. "Optimised model for community-based hybrid energy system," Renewable Energy, Elsevier, vol. 32(7), pages 1155-1164.
    30. Rodríguez-Gallegos, Carlos D. & Yang, Dazhi & Gandhi, Oktoviano & Bieri, Monika & Reindl, Thomas & Panda, S.K., 2018. "A multi-objective and robust optimization approach for sizing and placement of PV and batteries in off-grid systems fully operated by diesel generators: An Indonesian case study," Energy, Elsevier, vol. 160(C), pages 410-429.
    31. Kalantar, M. & Mousavi G., S.M., 2010. "Dynamic behavior of a stand-alone hybrid power generation system of wind turbine, microturbine, solar array and battery storage," Applied Energy, Elsevier, vol. 87(10), pages 3051-3064, October.
    32. Eriksson, E.L.V. & Gray, E.MacA., 2017. "Optimization and integration of hybrid renewable energy hydrogen fuel cell energy systems – A critical review," Applied Energy, Elsevier, vol. 202(C), pages 348-364.
    33. Wakui, Tetsuya & Sawada, Kento & Yokoyama, Ryohei & Aki, Hirohisa, 2019. "Predictive management for energy supply networks using photovoltaics, heat pumps, and battery by two-stage stochastic programming and rule-based control," Energy, Elsevier, vol. 179(C), pages 1302-1319.
    34. Konak, Abdullah & Coit, David W. & Smith, Alice E., 2006. "Multi-objective optimization using genetic algorithms: A tutorial," Reliability Engineering and System Safety, Elsevier, vol. 91(9), pages 992-1007.
    35. Ghiasi, Mohammad, 2019. "Detailed study, multi-objective optimization, and design of an AC-DC smart microgrid with hybrid renewable energy resources," Energy, Elsevier, vol. 169(C), pages 496-507.
    36. Zhang, Weiping & Maleki, Akbar & Rosen, Marc A. & Liu, Jingqing, 2018. "Optimization with a simulated annealing algorithm of a hybrid system for renewable energy including battery and hydrogen storage," Energy, Elsevier, vol. 163(C), pages 191-207.
    37. Zamora, Ramon & Srivastava, Anurag K., 2010. "Controls for microgrids with storage: Review, challenges, and research needs," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(7), pages 2009-2018, September.
    38. Forough, Atefeh Behzadi & Roshandel, Ramin, 2018. "Lifetime optimization framework for a hybrid renewable energy system based on receding horizon optimization," Energy, Elsevier, vol. 150(C), pages 617-630.
    39. Heydari, Azim & Astiaso Garcia, Davide & Keynia, Farshid & Bisegna, Fabio & De Santoli, Livio, 2019. "A novel composite neural network based method for wind and solar power forecasting in microgrids," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    40. Yang, Kyoungboo & Kwak, Gyeongil & Cho, Kyungho & Huh, Jongchul, 2019. "Wind farm layout optimization for wake effect uniformity," Energy, Elsevier, vol. 183(C), pages 983-995.
    41. Starke, Allan R. & Cardemil, José M. & Escobar, Rodrigo & Colle, Sergio, 2018. "Multi-objective optimization of hybrid CSP+PV system using genetic algorithm," Energy, Elsevier, vol. 147(C), pages 490-503.
    42. Sinha, Sunanda & Chandel, S.S., 2014. "Review of software tools for hybrid renewable energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 32(C), pages 192-205.
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