alternativeАльтернативная энергетика и экология (ISJAEE)Alternative Energy and Ecology (ISJAEE)1608-8298Международный издательский дом научной периодики "Спейс10.15518/isjaee.2024.03.133-167alternative-2397Research ArticleXI. ИННОВАЦИОННЫЕ РЕШЕНИЯ, ТЕХНОЛОГИИ, УСТРОЙСТВА И ИХ ВНЕДРЕНИЕ. 26. Инновационные решения в области энергетики и альтернативной энергетикиXI. INNOVATION SOLUTIONS, TECHNOLOGIES, FACILITIES AND THEIR INNOVATION. 26. Information solutions in the field of energy and alternative energyУсовершенствованная технико-экономическая оптимизация гибридных систем на солнечной энергии/ветре/топливных элементах/дизельном топливе с накоплением энергии на водородеImproved techno-economic optimization of hybrid solar/wind/fuel cell/diesel systems with hydrogen energy storageХассанМохаммед Х.HassanMohamed H.

Мохаммед Х. Хассан - инженер

Египет, Каир, ул. Рамсиса Аббасея, 2 

Mohamed H. Hassan - engineer  

Egypt, Cairo, Ramsis St. Abbassia 

КамельСалахKamelSalah

Салах Камель - доцент кафедры электротехники, Руководитель исследовательской лаборатории  передовых энергетических систем (PAR Lab), исследовательской группы энергетических систем 

81542 Асуан, Египет 

Salah Kamel - currently an Associate Professor with the Departmentof Electrical Engineering, Advanced Power Systems Research Laboratory (APSR Lab), Power Systems Research Group 

81542, Aswan, Egypt 

СафаралиевМ. Х.SafaralievM. Kh.

Сафаралиев Муродбек Холназарович -  к.т.н., старший научный сотрудник кафедры  «Автоматизированных электрических систем» 

 620002 Екатеринбург 

 тел.: +7 (950) 5644967

Murodbek Safaraliev -   PhD, Senior Researcher, Department of «Automated Electrical Systems» 

 620002, Yekaterinburg 

 tel: +7 (950) 5644967 

murodbek_03@mail.ruКокинС. Е.KokinS. E.

Кокин Сергей Евгеньевич - доктор. техн. наук, профессор кафедры «Автоматизированных  электрических систем» 

 620002 Екатеринбург 

 Sergey Kokin -  doctor tech. sciences, Professor of the Department of «Automated Electrical Systems»  

 620002, Yekaterinburg 

Министерство электроэнергетики и возобновляемых источников энергииЕгипетMinistry of Electricity and Renewable EnergyEgyptАсуанский университетЕгипетAswan UniversityEgyptУральский федеральный университетРоссияUral Federal UniversityRussian Federation20240706202403133167Copyright © Международный издательский дом научной периодики "Спейс, 20232023Международный издательский дом научной периодики "СпейсМеждународный издательский дом научной периодики "Спейсhttps://www.isjaee.com/jour/about/submissions#copyrightNoticehttps://www.isjaee.com/jour/article/view/2397

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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 resulting outcomes are compared with those obtained using the original ARO algorithm, further highlighting the effectiveness of the proposed approach. Using the QIARO algorithm, the PV/DG/Battery (Ni-Fe) configuration and PV/WT/DG/HSS configuration achieve optimal Life Cycle Cost values of 645,271 USD and 1,852,421 USD, respectively.

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The authors declare that there are no conflicts of interest present.