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Simulating Power Generation from Photovoltaics in the Polish Power System Based on Ground Meteorological Measurements-First Tests Based on Transmission System Operator Data
Mälardalen University, School of Business, Society and Engineering, Future Energy Center. AGH Univ Sci & Technol, Fac Management, Dept Engn Management, PL-30059 Krakow, Poland..ORCID iD: 0000-0001-9576-7877
Natl Res Inst, Inst Meteorol & Water Management, PL-01673 Warsaw, Poland..ORCID iD: 0000-0003-2693-0946
Natl Res Inst, Inst Meteorol & Water Management, PL-01673 Warsaw, Poland.;Gdansk Univ Technol, Fac Civil & Environm Engn, PL-80233 Gdansk, Poland..ORCID iD: 0000-0001-9602-5007
2020 (English)In: Energies, E-ISSN 1996-1073, Vol. 13, no 16, article id 4255Article in journal (Refereed) Published
Abstract [en]

The Polish power system is undergoing a slow process of transformation from coal to one that is renewables dominated. Although coal will remain a fundamental fuel in the coming years, the recent upsurge in installed capacity of photovoltaic (PV) systems should draw significant attention. Owning to the fact that the Polish Transmission System Operator recently published the PV hourly generation time series in this article, we aim to explore how well those can be modeled based on the meteorological measurements provided by the Institute of Meteorology and Water Management. The hourly time series of PV generation on a country level and irradiation, wind speed, and temperature measurements from 23 meteorological stations covering one month are used as inputs to create an artificial neural network. The analysis indicates that available measurements combined with artificial neural networks can simulate PV generation on a national level with a mean percentage error of 3.2%.

Place, publisher, year, edition, pages
MDPI , 2020. Vol. 13, no 16, article id 4255
Keywords [en]
photovoltaics, artificial neural networks, national power system
National Category
Energy Engineering
Identifiers
URN: urn:nbn:se:mdh:diva-58640DOI: 10.3390/en13164255ISI: 000564814100001Scopus ID: 2-s2.0-85090922319OAI: oai:DiVA.org:mdh-58640DiVA, id: diva2:1665910
Available from: 2022-06-08 Created: 2022-06-08 Last updated: 2023-09-13Bibliographically approved

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Jurasz, Jakob

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