IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i21p15622-d1274120.html
   My bibliography  Save this article

Photovoltaic/Hydrokinetic/Hydrogen Energy System Sizing Considering Uncertainty: A Stochastic Approach Using Two-Point Estimate Method and Improved Gradient-Based Optimizer

Author

Listed:
  • Mustafa Kamal

    (Department of Basic Sciences, College of Science and Theoretical Studies, Saudi Electronic University, Dammam 32256, Saudi Arabia)

  • Renzon Daniel Cosme Pecho

    (Salutem Diagnostic Imaging Center, Lima 15498, Peru)

  • Hassan Falah Fakhruldeen

    (Computer Techniques Engineering Department, Faculty of Information Technology, Imam Ja’afar Al-Sadiq University, Baghdad 10011, Iraq
    Computer Technical Engineering Department, College of Technical Engineering, The Islamic University, Najaf 54001, Iraq)

  • Hailer Sharif

    (Medical Technical College, Al-Farahidi University, Baghdad 10001, Iraq)

  • Vedran Mrzljak

    (Faculty of Engineering, University of Rijeka, Vukovarska 58, 51000 Rijeka, Croatia)

  • Saber Arabi Nowdeh

    (Power and Energy Group, Institute of Research Sciences, Johor Bahru 81310, Malaysia)

  • Igor Poljak

    (Department of Maritime Sciences, University of Zadar, Mihovila Pavlinovića 1, 23000 Zadar, Croatia)

Abstract

In this paper, stochastic sizing of a stand-alone Photovoltaic/Hydrokinetic/Hydrogen storage energy system is performed with aim of minimizing the cost of project life span (COPL) and satisfying the reliability index as probability of load shortage (POLS). The stochastic sizing is implemented using a novel framework considering two-point estimate method (2m+1 PEM) and improved gradient-based optimizer (IGBO). The 2m+1 PEM is used to evaluate the impact of uncertainties of energy resource generation and system demand on sizing problem. The 2m+1 PEM utilizes the approximate method to account for these uncertainties. In order to avoid premature convergence, the gradient-based optimizer (GBO), a meta-heuristic algorithm influenced by Newtonian concepts, is enhanced using a dynamic lens-imaging learning approach. The size of the system devices, which is determined utilizing the IGBO with the COPL minimization and optimally satisfying the POLS, is one of the optimization variables. The results of three hPV/HKT/FC, hPV/FC, and hHKT/FC configurations of the system are presented in two situations of deterministic and stochastic sizing without and with taking uncertainty into consideration. The findings showed that the hPV/HKT/FC configuration and the IGBO performed better than other configurations and techniques like conventional GBO, particle swarm optimization (PSO), and artificial electric field algorithm (AEFA) to achieve the lowest COPL and POLS (higher reliability) in various cases. Additionally, the COPL for the hPV/HKT/FC, hPV/FC, and hHKT/FC configurations increased by 7.63%, 7.57%, and 7.65%, respectively, while the POLS fell by 5.01%, 4.48%, and 4.59%, respectively, contrasted to the deterministic sizing, according to the results of stochastic sizing based on 2m+1 PEM. As a result, the findings indicate that in the deterministic sizing model, the quantity of output and energy storage is insufficient to meet demand under unknown circumstances. Applying stochastic sizing while taking into account the volatility of both supply and demand can, therefore, be an economically sound way to meet demand.

Suggested Citation

  • Mustafa Kamal & Renzon Daniel Cosme Pecho & Hassan Falah Fakhruldeen & Hailer Sharif & Vedran Mrzljak & Saber Arabi Nowdeh & Igor Poljak, 2023. "Photovoltaic/Hydrokinetic/Hydrogen Energy System Sizing Considering Uncertainty: A Stochastic Approach Using Two-Point Estimate Method and Improved Gradient-Based Optimizer," Sustainability, MDPI, vol. 15(21), pages 1-30, November.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:21:p:15622-:d:1274120
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/21/15622/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/21/15622/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Niveditha, N. & Rajan Singaravel, M.M., 2022. "Optimal sizing of hybrid PV–Wind–Battery storage system for Net Zero Energy Buildings to reduce grid burden," Applied Energy, Elsevier, vol. 324(C).
    2. Gustavo L. Aschidamini & Gederson A. da Cruz & Mariana Resener & Maicon J. S. Ramos & Luís A. Pereira & Bibiana P. Ferraz & Sérgio Haffner & Panos M. Pardalos, 2022. "Expansion Planning of Power Distribution Systems Considering Reliability: A Comprehensive Review," Energies, MDPI, vol. 15(6), pages 1-29, March.
    3. Asim Kumar Sarker & Abul Kalam Azad & Mohammad G. Rasul & Arun Teja Doppalapudi, 2023. "Prospect of Green Hydrogen Generation from Hybrid Renewable Energy Sources: A Review," Energies, MDPI, vol. 16(3), pages 1-17, February.
    4. Jing Yang & Yen-Lin Chen & Por Lip Yee & Chin Soon Ku & Manoochehr Babanezhad, 2023. "An Improved Artificial Ecosystem-Based Optimization Algorithm for Optimal Design of a Hybrid Photovoltaic/Fuel Cell Energy System to Supply A Residential Complex Demand: A Case Study for Kuala Lumpur," Energies, MDPI, vol. 16(6), pages 1-21, March.
    5. Liu, Zeyu & Li, Hang & Hou, Kai & Xu, Xiandong & Jia, Hongjie & Zhu, Lewei & Mu, Yunfei, 2023. "Risk assessment and alleviation of regional integrated energy system considering cross-system failures," Applied Energy, Elsevier, vol. 350(C).
    6. Rania M. Ghoniem & Ali Alahmer & Hegazy Rezk & Samer As’ad, 2023. "Optimal Design and Sizing of Hybrid Photovoltaic/Fuel Cell Electrical Power System," Sustainability, MDPI, vol. 15(15), pages 1-19, August.
    7. Ahmed S. Menesy & Hamdy M. Sultan & Ibrahim O. Habiballah & Hasan Masrur & Kaisar R. Khan & Muhammad Khalid, 2023. "Optimal Configuration of a Hybrid Photovoltaic/Wind Turbine/Biomass/Hydro-Pumped Storage-Based Energy System Using a Heap-Based Optimization Algorithm," Energies, MDPI, vol. 16(9), pages 1-26, April.
    8. Mohammadali Kiehbadroudinezhad & Adel Merabet & Homa Hosseinzadeh-Bandbafha, 2022. "Review of Latest Advances and Prospects of Energy Storage Systems: Considering Economic, Reliability, Sizing, and Environmental Impacts Approach," Clean Technol., MDPI, vol. 4(2), pages 1-25, June.
    9. Sk. A. Shezan & Innocent Kamwa & Md. Fatin Ishraque & S. M. Muyeen & Kazi Nazmul Hasan & R. Saidur & Syed Muhammad Rizvi & Md Shafiullah & Fahad A. Al-Sulaiman, 2023. "Evaluation of Different Optimization Techniques and Control Strategies of Hybrid Microgrid: A Review," Energies, MDPI, vol. 16(4), pages 1-30, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Busiswe Skosana & Mukwanga W. Siti & Nsilulu T. Mbungu & Sonu Kumar & Willy Mulumba, 2023. "An Evaluation of Potential Strategies in Renewable Energy Systems and Their Importance for South Africa—A Review," Energies, MDPI, vol. 16(22), pages 1-27, November.
    2. Yan, Jingjing & Zhang, Huan & Wang, Yaran & Zhu, Zhaozhe & Bai, He & Li, Qicheng & You, Shijun, 2024. "Pump-stopping-induced hydraulic oscillations in long-distance district heating system: Modelling and a comprehensive analysis of critical factors," Energy, Elsevier, vol. 294(C).
    3. Naimul Haque & Abul Kalam Azad, 2023. "Comparative Study of Hydrogen Production from Organic Fraction of Municipal Solid Waste and Its Challenges: A Review," Energies, MDPI, vol. 16(23), pages 1-16, November.
    4. Moradi, Mehran & Farzaneh, Hooman, 2025. "Demand response programs in decentralized hybrid local energy markets: Evaluating the impact of risk-adjusted behavior of market players and the integration of renewable energy sources, using a novel ," Applied Energy, Elsevier, vol. 390(C).
    5. Belqasem Aljafari & Gunapriya Devarajan & Sivaranjani Subramani & Subramaniyaswamy Vairavasundaram, 2023. "Intelligent RBF-Fuzzy Controller Based Non-Isolated DC-DC Multi-Port Converter for Renewable Energy Applications," Sustainability, MDPI, vol. 15(12), pages 1-22, June.
    6. Aswad Adib & Joao Onofre Pereira Pinto & Madhu S. Chinthavali, 2023. "GA-Based Voltage Optimization of Distribution Feeder with High-Penetration of DERs Using Megawatt-Scale Units," Energies, MDPI, vol. 16(13), pages 1-10, June.
    7. Ayiguzhali Tuluhong & Qingpu Chang & Lirong Xie & Zhisen Xu & Tengfei Song, 2024. "Current Status of Green Hydrogen Production Technology: A Review," Sustainability, MDPI, vol. 16(20), pages 1-47, October.
    8. Takele Ferede Agajie & Armand Fopah-Lele & Isaac Amoussou & Ahmed Ali & Baseem Khan & Om Prakash Mahela & Ramakrishna S. S. Nuvvula & Divine Khan Ngwashi & Emmanuel Soriano Flores & Emmanuel Tanyi, 2023. "Techno-Economic Analysis and Optimization of Hybrid Renewable Energy System with Energy Storage under Two Operational Modes," Sustainability, MDPI, vol. 15(15), pages 1-31, July.
    9. Ruggero Angelico & Ferruccio Giametta & Biagio Bianchi & Pasquale Catalano, 2025. "Green Hydrogen for Energy Transition: A Critical Perspective," Energies, MDPI, vol. 18(2), pages 1-47, January.
    10. Adoum Abdoulaye, Mahamat & Waita, Sebastian & Wabuge Wekesa, Cyrus & Mwabora, Julius Mwakondo, 2024. "Optimal sizing of an off-grid and grid-connected hybrid photovoltaic-wind system with battery and fuel cell storage system: A techno-economic, environmental, and social assessment," Applied Energy, Elsevier, vol. 365(C).
    11. Francisco L. D. Simões & Diogo M. F. Santos, 2024. "A SWOT Analysis of the Green Hydrogen Market," Energies, MDPI, vol. 17(13), pages 1-23, June.
    12. Ren, Yan & Sun, Ketao & Zhang, Kai & Han, Yuping & Zhang, Haonan & Wang, Meijing & Jing, Xiang & Mo, Juhua & Zou, Wenhang & Xing, Xinyang, 2024. "Optimization of the capacity configuration of an abandoned mine pumped storage/wind/photovoltaic integrated system," Applied Energy, Elsevier, vol. 374(C).
    13. Rasool, Muhammad Haseeb & Taylan, Onur & Perwez, Usama & Batunlu, Canras, 2023. "Comparative assessment of multi-objective optimization of hybrid energy storage system considering grid balancing," Renewable Energy, Elsevier, vol. 216(C).
    14. Nadaleti, Willian Cézar & Cardozo, Emanuélle & Bittencourt Machado, Jones & Maximilla Pereira, Peterson & Costa dos Santos, Maele & Gomes de Souza, Eduarda & Haertel, Paula & Kunde Correa, Erico & Vie, 2023. "Hydrogen and electricity potential generation from rice husks and persiculture biomass in Rio Grande do Sul, Brazil," Renewable Energy, Elsevier, vol. 216(C).
    15. Zhang, Chenwei & Wang, Ying & Zheng, Tao & Wang, Chen & Zhang, Kaifeng, 2024. "Identifying critical weak points of power-gas integrated energy system based on complex network theory," Reliability Engineering and System Safety, Elsevier, vol. 246(C).
    16. Yang, Haobo & Guan, Bowen & Zhang, Ji & Zhang, Tao & Liu, Xiaohua & Wang, Xinke, 2025. "Application potential of rooftop photovoltaics (PV) in elevated metro station for a low-carbon future: Characteristic analysis and strategies for supply-demand mismatch," Renewable Energy, Elsevier, vol. 238(C).
    17. Katarzyna Markowska & Kamil Wittek & Patrycja Kabiesz & Kinga Stecuła & Barış Aydın & Szymon Pawlak & Agata Markowska, 2025. "Hydrogen-Powered Engines: A Study on Selected Technological and Emissions Issues," Energies, MDPI, vol. 18(7), pages 1-17, March.
    18. Zheng, Yangbing & Zhou, Xu & Yu, Jiantao & Xue, Xiao & Wang, Xin & Tu, Xiaohan, 2025. "Predictive analytics for sustainable energy: An in-depth assessment of novel Stacking Regressor model in the off-grid hybrid renewable energy systems," Energy, Elsevier, vol. 324(C).
    19. Mohammad Alrbai & Sameer Al-Dahidi & Loiy Al-Ghussain & Hassan Hayajneh & Ali Alahmer, 2023. "A Sustainable Wind–Biogas Hybrid System for Remote Areas in Jordan: A Case Study of Mobile Hospital for a Zaatari Syrian Refugee Camp," Sustainability, MDPI, vol. 15(20), pages 1-21, October.
    20. Qu, Jiawei & Liu, Zeyu & Hou, Kai & Zhou, Yue & Zhu, Lewei & Dong, Xiaohong & Mu, Yunfei & Jia, Hongjie, 2025. "Joint planning of economy and reliability for integrated community energy systems: A similarity-based massive scenario optimization approach," Applied Energy, Elsevier, vol. 381(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:15:y:2023:i:21:p:15622-:d:1274120. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.