IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i18p4945-d416687.html
   My bibliography  Save this article

A Novel Probabilistic Approach to Optimize Stand-Alone Hybrid Wind-Photovoltaic Renewable Energy System

Author

Listed:
  • Wei Li

    (Key Laboratory of Far-Shore Wind Power Technology of Zhejiang Province, Hangzhou 311122, China
    Powerchina Huadong Engineering Corporation Limited, Hangzhou 311122, China)

  • Jikang Li

    (Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China)

  • Zhenzhong Hu

    (Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China
    Department of Civil Engineering, Tsinghua University, Beijing 100084, China)

  • Sunwei Li

    (Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China
    Pengcheng Laboratory, Shenzhen, Gaungdong 518000, China)

  • P. W. Chan

    (Hong Kong Observatory, Kowloon, Hong Kong)

Abstract

In the present study, a novel probabilistic approach is proposed to optimize a stand-alone hybrid wind-photovoltaic renewable energy system installed in the South China Sea. In detail, the probability distribution of power generated from a hybrid wind-photovoltaic system is estimated based on the probabilistic descriptions of wind and solar energy resources in the South China Sea. In addition, the present study proposed a battery level coefficient model to calculate the battery capacity of the hybrid system. As the battery level coefficient implies the expected power deficit in a specific continuous duration, it reflects the reliability of the battery system and, hence, the performance of the system under the power deficit condition. Given the probabilistic models estimated the stability of power generations, a genetic algorithm is applied to optimize the sizes of the system components (the installed capacities of wind turbines and photovoltaic modules and the load) when the levelized cost of energy (LCOE) is used as the indicator. The optimization verifies that the proposed probabilistic approach provides reasonable estimates of the power generation of a hybrid system in an optimization process. In addition, the comparisons with the conventional deterministic approach implies that the widely used loss of power supply probability (LPSP) could be interpreted, in a statistical sense, as the expected duration of power deficit. More importantly, the LPSP is connected to the localized sea condition, and therefore, this stability assessment criterion should be specified according to the location where the system is installed.

Suggested Citation

  • Wei Li & Jikang Li & Zhenzhong Hu & Sunwei Li & P. W. Chan, 2020. "A Novel Probabilistic Approach to Optimize Stand-Alone Hybrid Wind-Photovoltaic Renewable Energy System," Energies, MDPI, vol. 13(18), pages 1-21, September.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:18:p:4945-:d:416687
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/18/4945/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/13/18/4945/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Chang, Tian-Pau & Liu, Feng-Jiao & Ko, Hong-Hsi & Cheng, Shih-Ping & Sun, Li-Chung & Kuo, Shye-Chorng, 2014. "Comparative analysis on power curve models of wind turbine generator in estimating capacity factor," Energy, Elsevier, vol. 73(C), pages 88-95.
    2. 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.
    3. Anthony Roy & François Auger & Florian Dupriez-Robin & Salvy Bourguet & Quoc Tuan Tran, 2018. "Electrical Power Supply of Remote Maritime Areas: A Review of Hybrid Systems Based on Marine Renewable Energies," Energies, MDPI, vol. 11(7), pages 1-27, July.
    4. Yang, Hongxing & Wei, Zhou & Chengzhi, Lou, 2009. "Optimal design and techno-economic analysis of a hybrid solar-wind power generation system," Applied Energy, Elsevier, vol. 86(2), pages 163-169, February.
    5. Chen, Hung-Cheng, 2013. "Optimum capacity determination of stand-alone hybrid generation system considering cost and reliability," Applied Energy, Elsevier, vol. 103(C), pages 155-164.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Thirunavukkarasu, M. & Sawle, Yashwant & Lala, Himadri, 2023. "A comprehensive review on optimization of hybrid renewable energy systems using various optimization techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 176(C).

    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. Ma, Tao & Yang, Hongxing & Lu, Lin, 2014. "A feasibility study of a stand-alone hybrid solar–wind–battery system for a remote island," Applied Energy, Elsevier, vol. 121(C), pages 149-158.
    2. Chen, Jincheng & Wang, Feng & Stelson, Kim A., 2018. "A mathematical approach to minimizing the cost of energy for large utility wind turbines," Applied Energy, Elsevier, vol. 228(C), pages 1413-1422.
    3. Myeong Jin Ko & Yong Shik Kim & Min Hee Chung & Hung Chan Jeon, 2015. "Multi-Objective Optimization Design for a Hybrid Energy System Using the Genetic Algorithm," Energies, MDPI, vol. 8(4), pages 1-26, April.
    4. Imran Shafi & Harris Khan & Muhammad Siddique Farooq & Isabel de la Torre Diez & Yini Miró & Juan Castanedo Galán & Imran Ashraf, 2023. "An Artificial Neural Network-Based Approach for Real-Time Hybrid Wind–Solar Resource Assessment and Power Estimation," Energies, MDPI, vol. 16(10), pages 1-18, May.
    5. Zhang, Debao & Liu, Junwei & Jiao, Shifei & Tian, Hao & Lou, Chengzhi & Zhou, Zhihua & Zhang, Ji & Wang, Chendong & Zuo, Jian, 2019. "Research on the configuration and operation effect of the hybrid solar-wind-battery power generation system based on NSGA-II," Energy, Elsevier, vol. 189(C).
    6. Jichun Liu & Yangfang Yang & Yue Xiang & Junyong Liu, 2019. "A Power Exchange Strategy for Multiple Areas with Hydro Power and Flexible Loads," Energies, MDPI, vol. 12(6), pages 1-17, March.
    7. Nadège Bouchonneau & Arnaud Coutrey & Vivianne Marie Bruère & Moacyr Araújo & Alex Costa da Silva, 2023. "Finite Element Modeling and Simulation of a Submerged Wave Energy Converter System for Application to Oceanic Islands in Tropical Atlantic," Energies, MDPI, vol. 16(4), pages 1-17, February.
    8. Singh, Bharat & Kumar, Ashwani, 2023. "Optimal energy management and feasibility analysis of hybrid renewable energy sources with BESS and impact of electric vehicle load with demand response program," Energy, Elsevier, vol. 278(PA).
    9. Feras Alasali & Mohammad Salameh & Ali Semrin & Khaled Nusair & Naser El-Naily & William Holderbaum, 2022. "Optimal Controllers and Configurations of 100% PV and Energy Storage Systems for a Microgrid: The Case Study of a Small Town in Jordan," Sustainability, MDPI, vol. 14(13), pages 1-20, July.
    10. Al-Falahi, Monaaf D.A. & Jayasinghe, Shantha D.G. & Enshaei, Hossein, 2019. "Hybrid algorithm for optimal operation of hybrid energy systems in electric ferries," Energy, Elsevier, vol. 187(C).
    11. Xu, Xiao & Hu, Weihao & Cao, Di & Liu, Wen & Huang, Qi & Hu, Yanting & Chen, Zhe, 2021. "Enhanced design of an offgrid PV-battery-methanation hybrid energy system for power/gas supply," Renewable Energy, Elsevier, vol. 167(C), pages 440-456.
    12. Yazhou Zhao & Xiangxi Qin & Xiangyu Shi, 2022. "A Comprehensive Evaluation Model on Optimal Operational Schedules for Battery Energy Storage System by Maximizing Self-Consumption Strategy and Genetic Algorithm," Sustainability, MDPI, vol. 14(14), pages 1-34, July.
    13. Aldersey-Williams, John & Broadbent, Ian D. & Strachan, Peter A., 2020. "Analysis of United Kingdom offshore wind farm performance using public data: Improving the evidence base for policymaking," Utilities Policy, Elsevier, vol. 62(C).
    14. Salameh, Tareq & Ghenai, Chaouki & Merabet, Adel & Alkasrawi, Malek, 2020. "Techno-economical optimization of an integrated stand-alone hybrid solar PV tracking and diesel generator power system in Khorfakkan, United Arab Emirates," Energy, Elsevier, vol. 190(C).
    15. Prasad, Abhnil A. & Taylor, Robert A. & Kay, Merlinde, 2017. "Assessment of solar and wind resource synergy in Australia," Applied Energy, Elsevier, vol. 190(C), pages 354-367.
    16. Mehrjoo, Mehrdad & Jafari Jozani, Mohammad & Pawlak, Miroslaw, 2021. "Toward hybrid approaches for wind turbine power curve modeling with balanced loss functions and local weighting schemes," Energy, Elsevier, vol. 218(C).
    17. Xiangyuan Zheng & Huadong Zheng & Yu Lei & Yi Li & Wei Li, 2020. "An Offshore Floating Wind–Solar–Aquaculture System: Concept Design and Extreme Response in Survival Conditions," Energies, MDPI, vol. 13(3), pages 1-23, January.
    18. 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.
    19. Shou, Chunhui & Luo, Zhongyang & Wang, Tao & Shen, Weidong & Rosengarten, Gary & Wei, Wei & Wang, Cheng & Ni, Mingjiang & Cen, Kefa, 2012. "Investigation of a broadband TiO2/SiO2 optical thin-film filter for hybrid solar power systems," Applied Energy, Elsevier, vol. 92(C), pages 298-306.
    20. Chen, Jun & Garcia, Humberto E., 2016. "Economic optimization of operations for hybrid energy systems under variable markets," Applied Energy, Elsevier, vol. 177(C), pages 11-24.

    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:jeners:v:13:y:2020:i:18:p:4945-:d:416687. 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.