Forecasting the Development of Offshore Wind Energy in Poland in the Context of the Energy Transformation and Sustainable Development Goals

Aurelia Rybak (), Aleksandra Rybak and Spas D. Kolev
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Aurelia Rybak: Faculty of Mining, Safety Engineering and Industrial Automation, Silesian University of Technology, 44-100 Gliwice, Poland
Aleksandra Rybak: Department of Physical Chemistry and Technology of Polymers, Faculty of Chemistry, Silesian University of Technology, Strzody 7, 44-100 Gliwice, Poland
Spas D. Kolev: School of Chemistry, The University of Melbourne, Melbourne, VIC 3010, Australia

Energies, 2025, vol. 18, issue 20, 1-21

Abstract: This article presents the results of research on the potential development of offshore wind energy in Poland. Wind energy generated in offshore farms is intended to be the second pillar (alongside nuclear power) of Poland’s energy transition, creating the foundation for a zero-emission energy system. The authors constructed a neural network that allowed them to forecast the development of the installed offshore energy capacity for Poland by 2030. For this purpose, the factors that have the greatest impact on the development of wind energy in Poland were identified. This knowledge will facilitate the development of state policy consistent with the Sustainable Development Goals (SDGs) and the European Green Deal. Since Poland currently does not have installed offshore wind energy capacity, Germany was used as a benchmark to train the model. The research results fill the identified gap: to date, forecasts of offshore development in Poland based on a model trained on German data have not been presented in the literature. The research results show that by 2030, Poland can achieve the goals set by the United Nations, the European Union, and the Polish Energy Policy 2040 (PEP2040). The PEP2040 assumes that Poland should have 5.9 GW of energy installed in offshore wind farms in the Baltic Sea by 2030. The forecast indicates that this will be approximately 5.3 GW, with the difference between these values remaining within the model’s margin of error.

Keywords: offshore wind energy; LSTM model; SVR model; energy transition (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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