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Selection of Photovoltaic Panels Based on Ranges of Criteria Weights and Balanced Assessment Criteria

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  • Paweł Ziemba

    (Institute of Management, University of Szczecin, Aleja Papieża Jana Pawła II 22A, 70-453 Szczecin, Poland)

Abstract

In recent years, the share of PV (photovoltaic) panels in the generation of renewable energy has been dynamically growing. During this time, the Polish government introduced numerous programs to assist households in switching to PV panels as the primary source of energy. Therefore, the aim of the article is to indicate the PV panels that are best suited to work for individual users in households in Poland. PV panels were assessed using the PROSA multi-criteria decision analysis method, supported by a stochastic approach, based on the Monte Carlo method. This approach made it possible to choose the most balanced solutions, in terms of individual criteria, and to take into account the uncertainty and imprecision of the weights of the assessment criteria. In particular, the use of reliable weight ranges in the Monte Carlo simulations allowed the construction of a whole spectrum of evaluation and ranking models. These models indicate the PV panels that best meet the requirements and have the best balance between the individual assessment criteria. As a result of the research, it was found that the requirements of PV installations in households in Poland are best met by panels produced in China and in the Chinese–Polish cooperation. Panels of Polish production ranked further down, which means that Polish producers do not offer products that are tailored to the needs of PV installations for households in Poland.

Suggested Citation

  • Paweł Ziemba, 2023. "Selection of Photovoltaic Panels Based on Ranges of Criteria Weights and Balanced Assessment Criteria," Energies, MDPI, vol. 16(17), pages 1-18, September.
  • Handle: RePEc:gam:jeners:v:16:y:2023:i:17:p:6382-:d:1231949
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    1. Paweł Ziemba & Abdullah Zair, 2023. "Temporal Analysis of Energy Transformation in EU Countries," Energies, MDPI, vol. 16(23), pages 1-21, November.

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