Improved techno-economic optimization of hybrid solar/wind/fuel cell/diesel systems with hydrogen energy storage

In spite of concerns about pollution and high operational costs, diesel engines continue to dominate local electricity generation in off-grid areas. However, there is significant untapped potential worldwide for utilizing local renewable energy sources (RES) instead of fossil fuel generation, partic...

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Main Authors: Mohamed H. Hassan, Salah Kamel, M. Kh. Safaraliev, S. E. Kokin, Мохаммед Х. Хассан, Салах Камель, М. Х. Сафаралиев, С. Е. Кокин
Format: Article in Journal/Newspaper
Language:English
Published: Международный издательский дом научной периодики "Спейс 2024
Subjects:
Hydrogen storage
Quadratic interpolation-based artificial rabbits optimization
Renewable energy resources
Battery storage
Electrolysis
Beluga
Beluga whale
Beluga*
Online Access:https://www.isjaee.com/jour/article/view/2397
https://doi.org/10.15518/isjaee.2024.03.133-167
id ftjisjaee:oai:oai.alternative.elpub.ru:article/2397
record_format openpolar
institution Open Polar
collection Alternative Energy and Ecology (ISJAEE)
op_collection_id ftjisjaee
language English
topic Hydrogen storage
Quadratic interpolation-based artificial rabbits optimization
Renewable energy resources
Battery storage
Electrolysis
spellingShingle Hydrogen storage
Quadratic interpolation-based artificial rabbits optimization
Renewable energy resources
Battery storage
Electrolysis
Mohamed H. Hassan
Salah Kamel
M. Kh. Safaraliev
S. E. Kokin
Мохаммед Х. Хассан
Салах Камель
М. Х. Сафаралиев
С. Е. Кокин
Improved techno-economic optimization of hybrid solar/wind/fuel cell/diesel systems with hydrogen energy storage
topic_facet Hydrogen storage
Quadratic interpolation-based artificial rabbits optimization
Renewable energy resources
Battery storage
Electrolysis
description In spite of concerns about pollution and high operational costs, diesel engines continue to dominate local electricity generation in off-grid areas. However, there is significant untapped potential worldwide for utilizing local renewable energy sources (RES) instead of fossil fuel generation, particularly in remote regions. To address the intermittent nature of RES, energy storage systems are crucial for off-grid communities, enabling them to rely on locally collected renewable energy. This study explores various off-grid renewable power system configurations, including batteries and hydrogen as energy storage options, to determine the most economically viable setup for remote areas. The analysis includes the Nickel-Iron (Ni-Fe) battery and considers electrolysis technology for hydrogen production. Two Integrated Hybrid Renewable Energy System (IHRES) configurations are modeled and evaluated: PV/Diesel Generator (DG)/Battery (Ni-Fe) and PV/Wind Turbines (WT)/DG/Hydrogen Storage System (HSS). The study employs a cycle charging (CC) strategy. A novel optimization algorithm called Quadratic interpolation-based artificial rabbits optimization (QIARO) is introduced to optimize the sizing of system components, ensuring cost-effective and reliable fulfillment of load demands. The effectiveness of the QIARO algorithm is initially validated through a comprehensive performance assessment, comparing it with the original artificial rabbits optimization (ARO) algorithm and other established optimization techniques across 7 benchmark functions. The results demonstrate that the QIARO algorithm surpasses the ARO algorithm, as well as other optimization techniques such as beluga whale optimization (BWO), pelican optimization algorithm (POA), weighted mean of vectors (INFO), and RUN ge Kutta optimizer (RUN), in terms of convergence speed and solution quality. After validation, the proposed algorithm is applied to the Baris Oasis in New Valley, Egypt, chosen as a representative case study of insular microgrid environments. The ...
format Article in Journal/Newspaper
author Mohamed H. Hassan
Salah Kamel
M. Kh. Safaraliev
S. E. Kokin
Мохаммед Х. Хассан
Салах Камель
М. Х. Сафаралиев
С. Е. Кокин
author_facet Mohamed H. Hassan
Salah Kamel
M. Kh. Safaraliev
S. E. Kokin
Мохаммед Х. Хассан
Салах Камель
М. Х. Сафаралиев
С. Е. Кокин
author_sort Mohamed H. Hassan
title Improved techno-economic optimization of hybrid solar/wind/fuel cell/diesel systems with hydrogen energy storage
title_short Improved techno-economic optimization of hybrid solar/wind/fuel cell/diesel systems with hydrogen energy storage
title_full Improved techno-economic optimization of hybrid solar/wind/fuel cell/diesel systems with hydrogen energy storage
title_fullStr Improved techno-economic optimization of hybrid solar/wind/fuel cell/diesel systems with hydrogen energy storage
title_full_unstemmed Improved techno-economic optimization of hybrid solar/wind/fuel cell/diesel systems with hydrogen energy storage
title_sort improved techno-economic optimization of hybrid solar/wind/fuel cell/diesel systems with hydrogen energy storage
publisher Международный издательский дом научной периодики "Спейс
publishDate 2024
url https://www.isjaee.com/jour/article/view/2397
https://doi.org/10.15518/isjaee.2024.03.133-167
genre Beluga
Beluga whale
Beluga*
genre_facet Beluga
Beluga whale
Beluga*
op_source Alternative Energy and Ecology (ISJAEE); № 3 (2024); 133-167
Альтернативная энергетика и экология (ISJAEE); № 3 (2024); 133-167
1608-8298
op_relation https://www.isjaee.com/jour/article/view/2397/1944
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op_doi https://doi.org/10.15518/isjaee.2024.03.133-16710.1016/j.enpol.2016.03.04310.1016/j.enconman.2020.11276810.1016/j.egypro.2019.01.40610.1016/j.est.2019.10104710.1016/j.rser.2018.03.04710.1016/j.ijhydene.2020.11.25610.1016/j.enconman.2020.11325210.1016/B978
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spelling ftjisjaee:oai:oai.alternative.elpub.ru:article/2397 2024-06-23T07:51:42+00:00 Improved techno-economic optimization of hybrid solar/wind/fuel cell/diesel systems with hydrogen energy storage Усовершенствованная технико-экономическая оптимизация гибридных систем на солнечной энергии/ветре/топливных элементах/дизельном топливе с накоплением энергии на водороде Mohamed H. Hassan Salah Kamel M. Kh. Safaraliev S. E. Kokin Мохаммед Х. Хассан Салах Камель М. Х. Сафаралиев С. Е. Кокин 2024-06-07 application/pdf https://www.isjaee.com/jour/article/view/2397 https://doi.org/10.15518/isjaee.2024.03.133-167 eng eng Международный издательский дом научной периодики "Спейс https://www.isjaee.com/jour/article/view/2397/1944 Blechinger P., Cader C., Bertheau P., Huyskens H., Seguin R., Breyer C. Global analysis of the techno-economic potential of renewable energy hybrid systems on small islands. Energy Policy 2016; 98:674-87. https://doi.org/10.1016/j.enpol.2016.03.043. Nagpal D., Parajuli B. Off-grid renewable energy solutions to expand electricity access: An opportunity not to be missed. International Renewable Energy Agency (IRENA), Abu Dhabi 2019. Marocco P., Ferrero D., Gandiglio M., Ortiz M. M., Sundseth K., Lanzini A. et al. A study of the techno-economic feasibility of H2-based energy storage systems in remote areas. Energy Convers Manag 2020; 211:112768. https://doi.org/10.1016/j.enconman.2020.112768. Kalamaras E., Belekoukia M., Lin Z., Xu B., Wang H., Xuan J. Techno-economic Assessment of a Hybrid Off-grid DC System for Combined Heat and Power Generation in Remote Islands. Energy Procedia 2019; 158:6315–20. https://doi.org/10.1016/j.egypro.2019.01.406. Koohi-Fayegh S., Rosen M. A. A review of energy storage types, applications and recent developments. J Energy Storage 2020; 27:101047. https://doi.org/10.1016/j.est.2019.101047. Yang Y., Bremner S., Menictas C., Kay M. Battery energy storage system size determination in renewable energy systems: A review. Renewable and Sustainable Energy Reviews 2018; 91:109-25. https://doi.org/10.1016/j.rser.2018.03.047. Kovač A., Paranos M., Marciuš D. Hydrogen in energy transition: A review. Int J Hydrogen Energy 2021; 46:10016-35. https://doi.org/10.1016/j.ijhydene.2020.11.256. You C., Kim J. Optimal design and global sensitivity analysis of a 100 % renewable energy sources based smart energy network for electrified and hydrogen cities. Energy Convers Manag 2020; 223:113252. https://doi.org/10.1016/j.enconman.2020.113252. Buffo G., Marocco P., Ferrero D, Lanzini A, Santarelli M. Power-to-X and power-to-power routes. Solar Hydrogen Production, Elsevier; 2019, p. 529-57. https://doi.org/10.1016/B978-0-12-814853-2.00015-1. Malheiro A., Castro P. M., Lima R. M., Estanqueiro A. Integrated sizing and scheduling of wind/PV/diesel/battery isolated systems. Renew Energy, 2015; 83:646-57. https://doi.org/10.1016/j.renene.2015.04.066. Cai W., Li X., Maleki A., Pourfayaz F., Rosen M. A., Alhuyi Nazari M. et al. Optimal sizing and location based on economic parameters for an off-grid application of a hybrid system with photovoltaic, battery and diesel technology. Energy, 2020; 201:117480. https://doi.org/10.1016/j.energy.2020.117480. Odou O. D. T., Bhandari R., Adamou R. Hybrid off-grid renewable power system for sustainable rural electrification in Benin. Renew Energy, 2020; 145:1266-79. https://doi.org/10.1016/j.renene.2019.06.032. Bukar A. L., Tan C. W., Lau K. Y. Optimal sizing of an autonomous photovoltaic/wind/battery/diesel generator microgrid using grasshopper optimization algorithm. Solar Energy, 2019; 188:685-96. https://doi.org/10.1016/j.solener.2019.06.050. Bukar A. L., Tan C. W. A review on stand-alone photovoltaic-wind energy system with fuel cell: System optimization and energy management strategy. J Clean Prod, 2019; 221:73-88. https://doi.org/10.1016/j.jclepro.2019.02.228. Sinha S., Chandel S. S. Review of software tools for hybrid renewable energy systems. Renewable and Sustainable Energy Reviews, 2014; 32:192-205. https://doi.org/10.1016/j.rser.2014.01.035. Man K. F., Tang K. S., Kwong S. Genetic algorithms: concepts and applications [in engineering design]. IEEE Transactions on Industrial Electronics, 1996; 43:519-34. https://doi.org/10.1109/41.538609. Kennedy J., Eberhart R. Particle swarm optimization. Proceedings of ICNN’95-international conference on neural networks, vol. 4, IEEE; 1995, p. 1942-8. Saremi S., Mirjalili S., Lewis A. Grasshopper Optimisation Algorithm: Theory and application. Advances in Engineering Software. 2017; 105:30-47. https://doi.org/10.1016/j.advengsoft.2017.01.004. Mirjalili S., Mirjalili S. M., Lewis A. Grey Wolf Optimizer. Advances in Engineering Software. 2014; 69:46-61. https://doi.org/10.1016/j.advengsoft.2013.12.007. Alamir N., Kamel S., Hassan M. H., Abdelkader S. M. An effective quantum artificial rabbits optimizer for energy management in microgrid considering demand response. Soft Comput, 2023; 27:15741-68. https://doi.org/10.1007/s00500-023-08814-5. Wang Y., Li F., Yu H., Wang Y., Qi C., Yang J. et al. Optimal operation of microgrid with multi-energy complementary based on moth flame optimization algorithm. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, 2020; 42:785-806. https://doi.org/10.1080/15567036.2019.1587067. Almashakbeh A. S., Arfoa A. A., Hrayshat E. S. Techno-economic evaluation of an off-grid hybrid PVwind-diesel-battery system with various scenarios of system’s renewable energy fraction. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects 2023; 45:6162-85. https://doi.org/10.1080/15567036.2019.1673515. Ramesh M., Saini R. P. Effect of different batteries and diesel generator on the performance of a standalone hybrid renewable energy system. 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Авторы, публикующие статьи в данном журнале, соглашаются на следующее:Авторы сохраняют за собой автороские права и предоставляют журналу право первой публикации работы, которая по истечении 6 месяцев после публикации автоматически лицензируется на условиях Creative Commons Attribution License , которая позволяет другим распространять данную работу с обязательным сохранением ссылок на авторов оригинальной работы и оригинальную публикацию в этом журнале.Авторы имеют право размещать их работу в сети Интернет (например в институтском хранилище или персональном сайте) до и во время процесса рассмотрения ее данным журналом, так как это может привести к продуктивному обсуждению и большему количеству ссылок на данную работу (См. The Effect of Open Access). Alternative Energy and Ecology (ISJAEE); № 3 (2024); 133-167 Альтернативная энергетика и экология (ISJAEE); № 3 (2024); 133-167 1608-8298 Hydrogen storage Quadratic interpolation-based artificial rabbits optimization Renewable energy resources Battery storage Electrolysis info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion 2024 ftjisjaee https://doi.org/10.15518/isjaee.2024.03.133-16710.1016/j.enpol.2016.03.04310.1016/j.enconman.2020.11276810.1016/j.egypro.2019.01.40610.1016/j.est.2019.10104710.1016/j.rser.2018.03.04710.1016/j.ijhydene.2020.11.25610.1016/j.enconman.2020.11325210.1016/B978 2024-06-12T23:30:15Z In spite of concerns about pollution and high operational costs, diesel engines continue to dominate local electricity generation in off-grid areas. However, there is significant untapped potential worldwide for utilizing local renewable energy sources (RES) instead of fossil fuel generation, particularly in remote regions. To address the intermittent nature of RES, energy storage systems are crucial for off-grid communities, enabling them to rely on locally collected renewable energy. This study explores various off-grid renewable power system configurations, including batteries and hydrogen as energy storage options, to determine the most economically viable setup for remote areas. The analysis includes the Nickel-Iron (Ni-Fe) battery and considers electrolysis technology for hydrogen production. Two Integrated Hybrid Renewable Energy System (IHRES) configurations are modeled and evaluated: PV/Diesel Generator (DG)/Battery (Ni-Fe) and PV/Wind Turbines (WT)/DG/Hydrogen Storage System (HSS). The study employs a cycle charging (CC) strategy. A novel optimization algorithm called Quadratic interpolation-based artificial rabbits optimization (QIARO) is introduced to optimize the sizing of system components, ensuring cost-effective and reliable fulfillment of load demands. The effectiveness of the QIARO algorithm is initially validated through a comprehensive performance assessment, comparing it with the original artificial rabbits optimization (ARO) algorithm and other established optimization techniques across 7 benchmark functions. The results demonstrate that the QIARO algorithm surpasses the ARO algorithm, as well as other optimization techniques such as beluga whale optimization (BWO), pelican optimization algorithm (POA), weighted mean of vectors (INFO), and RUN ge Kutta optimizer (RUN), in terms of convergence speed and solution quality. After validation, the proposed algorithm is applied to the Baris Oasis in New Valley, Egypt, chosen as a representative case study of insular microgrid environments. The ... Article in Journal/Newspaper Beluga Beluga whale Beluga* Alternative Energy and Ecology (ISJAEE)

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