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Influence of Environmental Factors on the Intelligent Management of Photovoltaic and Wind Sections in a Hybrid Power Plant

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  • Jacek Kusznier

    (Department of Photonics, Electronics and Light Engineering, Faculty of Electrical Engineering, Bialystok University of Technology, Wiejska 45D, 15-351 Bialystok, Poland)

Abstract

The high-efficiency operation of photovoltaic and wind systems is affected by many factors and parameters that should be continuously monitored. Since most of the variable factors are related to weather conditions, they are difficult to predict. Therefore, in order to optimize the operating point of a photovoltaic or wind power plant, it is necessary to observe changes in the subject area. The operation of photovoltaic and wind power plants can complement each other. The results recorded at the hybrid power plant of the Faculty of Electrical Engineering of Bialystok University of Technology are useful for a comprehensive analysis of the power plant operation and the ways to optimize it. This paper presents the influence of environmental factors on the operation of a hybrid photo-voltaic–wind power plant located in the city of Bialystok, Poland. The aim of the study was to present the variable factors on the optimal adjustment of the location of the power plant elements at the stage of its design and selection of the energy management system. The presented measurement data from 2015–2021 allow conclusions to be drawn on the significant impact on the power plant’s operation, taking into account both the average conditions corresponding to the analysed location and the full range of changes in the listed factors.

Suggested Citation

  • Jacek Kusznier, 2023. "Influence of Environmental Factors on the Intelligent Management of Photovoltaic and Wind Sections in a Hybrid Power Plant," Energies, MDPI, vol. 16(4), pages 1-15, February.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:4:p:1716-:d:1062702
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    References listed on IDEAS

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    1. Jacek Kusznier & Wojciech Wojtkowski, 2021. "IoT Solutions for Maintenance and Evaluation of Photovoltaic Systems," Energies, MDPI, vol. 14(24), pages 1-24, December.
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    5. Shaheer Ansari & Afida Ayob & Molla S. Hossain Lipu & Mohamad Hanif Md Saad & Aini Hussain, 2021. "A Review of Monitoring Technologies for Solar PV Systems Using Data Processing Modules and Transmission Protocols: Progress, Challenges and Prospects," Sustainability, MDPI, vol. 13(15), pages 1-34, July.
    6. Amjad Ali & K. Almutairi & Muhammad Zeeshan Malik & Kashif Irshad & Vineet Tirth & Salem Algarni & Md. Hasan Zahir & Saiful Islam & Md Shafiullah & Neeraj Kumar Shukla, 2020. "Review of Online and Soft Computing Maximum Power Point Tracking Techniques under Non-Uniform Solar Irradiation Conditions," Energies, MDPI, vol. 13(12), pages 1-37, June.
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    Cited by:

    1. Haobo Shi & Yanping Xu & Baodi Ding & Jinsong Zhou & Pei Zhang, 2023. "Long-Term Solar Power Time-Series Data Generation Method Based on Generative Adversarial Networks and Sunrise–Sunset Time Correction," Sustainability, MDPI, vol. 15(20), pages 1-19, October.
    2. Grzegorz Drałus & Damian Mazur & Jacek Kusznier & Jakub Drałus, 2023. "Application of Artificial Intelligence Algorithms in Multilayer Perceptron and Elman Networks to Predict Photovoltaic Power Plant Generation," Energies, MDPI, vol. 16(18), pages 1-23, September.
    3. Beata Hysa & Anna Mularczyk, 2024. "PESTEL Analysis of the Photovoltaic Market in Poland—A Systematic Review of Opportunities and Threats," Resources, MDPI, vol. 13(10), pages 1-29, September.

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