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A fuzzy based method for leveling output power fluctuations of photovoltaic-diesel hybrid power system

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  • Datta, Manoj
  • Senjyu, Tomonobu
  • Yona, Atsushi
  • Funabashi, Toshihisa

Abstract

A Photovoltaic system’s output power fluctuates as insolation varies with weather condition. Fluctuating PV power causes frequency deviations when large PV power is penetrated in the isolated utility. In this paper, a fuzzy based method for leveling the fluctuations of PV power in a PV-diesel hybrid power system is proposed. By means of the proposed method, output power control of PV system becomes possible considering power utility conditions and the conflicting objective of output power leveling and maximizing energy capture is achieved. Here, fuzzy control is used to generate the output leveling power command. The fuzzy control has three inputs of average insolation, variance of insolation, and absolute average of frequency deviation. First, the proposed method is compared with the method where captured maximum power is given to the utility without leveling. Second, the proposed method is compared with a conventional method where captured maximum power is leveled by using an energy storage system and is given to the isolated utility. Simulation results show that the proposed method is effective in leveling PV power fluctuations and is feasible to reduce the frequency deviations of the isolated power utility.

Suggested Citation

  • Datta, Manoj & Senjyu, Tomonobu & Yona, Atsushi & Funabashi, Toshihisa, 2011. "A fuzzy based method for leveling output power fluctuations of photovoltaic-diesel hybrid power system," Renewable Energy, Elsevier, vol. 36(6), pages 1693-1703.
    • Handle: RePEc:eee:renene:v:36:y:2011:i:6:p:1693-1703
    DOI: 10.1016/j.renene.2010.12.009
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    2. Patrick Sunday Onen & Geev Mokryani & Rana H. A. Zubo, 2022. "Planning of Multi-Vector Energy Systems with High Penetration of Renewable Energy Source: A Comprehensive Review," Energies, MDPI, vol. 15(15), pages 1-25, August.
    3. Indu Rani, B. & Saravana Ilango, G. & Nagamani, C., 2012. "Power flow management algorithm for photovoltaic systems feeding DC/AC loads," Renewable Energy, Elsevier, vol. 43(C), pages 267-275.
    4. Haisheng Hong & Quanyuan Jiang, 2019. "Model Predictive Control-Based Coordinated Control Algorithm with a Hybrid Energy Storage System to Smooth Wind Power Fluctuations," Energies, MDPI, vol. 12(23), pages 1-17, December.
    5. Irshad, Ahmad Shah & Samadi, Wais Khan & Fazli, Agha Mohammad & Noori, Abdul Ghani & Amin, Ahmad Shah & Zakir, Mohammad Naseer & Bakhtyal, Irfan Ahmad & Karimi, Bashir Ahmad & Ludin, Gul Ahmad & Senjy, 2023. "Resilience and reliable integration of PV-wind and hydropower based 100% hybrid renewable energy system without any energy storage system for inaccessible area electrification," Energy, Elsevier, vol. 282(C).
    6. Suganthi, L. & Iniyan, S. & Samuel, Anand A., 2015. "Applications of fuzzy logic in renewable energy systems – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 48(C), pages 585-607.
    7. Sa-ngawong, Nattapol & Ngamroo, Issarachai, 2015. "Intelligent photovoltaic farms for robust frequency stabilization in multi-area interconnected power system based on PSO-based optimal Sugeno fuzzy logic control," Renewable Energy, Elsevier, vol. 74(C), pages 555-567.

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