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Optimal Sizing of a Stand-Alone Hybrid Power System Based on Battery/Hydrogen with an Improved Ant Colony Optimization

Author

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  • Weiqiang Dong

    (School of Information and Electrical Engineering, Zhejiang University City College, Hangzhou 310015, Zhejiang, China
    College of Control Science and Engineering, Zhejiang University, Hangzhou 310027, Zhejiang, China)

  • Yanjun Li

    (School of Information and Electrical Engineering, Zhejiang University City College, Hangzhou 310015, Zhejiang, China)

  • Ji Xiang

    (College of Electrical Engineering, Zhejiang University, Hangzhou 310027, Zhejiang, China)

Abstract

A distributed power system with renewable energy sources is very popular in recent years due to the rapid depletion of conventional sources of energy. Reasonable sizing for such power systems could improve the power supply reliability and reduce the annual system cost. The goal of this work is to optimize the size of a stand-alone hybrid photovoltaic (PV)/wind turbine (WT)/battery (B)/hydrogen system (a hybrid system based on battery and hydrogen (HS-BH)) for reliable and economic supply. Two objectives that take the minimum annual system cost and maximum system reliability described as the loss of power supply probability (LPSP) have been addressed for sizing HS-BH from a more comprehensive perspective, considering the basic demand of load, the profit from hydrogen, which is produced by HS-BH, and an effective energy storage strategy. An improved ant colony optimization (ACO) algorithm has been presented to solve the sizing problem of HS-BH. Finally, a simulation experiment has been done to demonstrate the developed results, in which some comparisons have been done to emphasize the advantage of HS-BH with the aid of data from an island of Zhejiang, China.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:9:y:2016:i:10:p:785-:d:79215
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    10. Le, Tay Son & Nguyen, Tuan Ngoc & Bui, Dac-Khuong & Ngo, Tuan Duc, 2023. "Optimal sizing of renewable energy storage: A techno-economic analysis of hydrogen, battery and hybrid systems considering degradation and seasonal storage," Applied Energy, Elsevier, vol. 336(C).
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    12. Pedro Bento & Hugo Nunes & José Pombo & Maria do Rosário Calado & Sílvio Mariano, 2019. "Daily Operation Optimization of a Hybrid Energy System Considering a Short-Term Electricity Price Forecast Scheme," Energies, MDPI, vol. 12(5), pages 1-25, March.
    13. Myada Shadoul & Rashid Al Abri & Hassan Yousef & Abdullah Al Shereiqi, 2024. "Designing a Dispatch Engine for Hybrid Renewable Power Stations Using a Mixed-Integer Linear Programming Technique," Energies, MDPI, vol. 17(13), pages 1-27, July.
    14. El-Sattar, Hoda Abd & Kamel, Salah & Hassan, Mohamed H. & Jurado, Francisco, 2022. "An effective optimization strategy for design of standalone hybrid renewable energy systems," Energy, Elsevier, vol. 260(C).
    15. Le, Son Tay & Nguyen, Tuan Ngoc & Bui, Dac-Khuong & Teodosio, Birch & Ngo, Tuan Duc, 2024. "Comparative life cycle assessment of renewable energy storage systems for net-zero buildings with varying self-sufficient ratios," Energy, Elsevier, vol. 290(C).
    16. 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.
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