Andrzej Mazur

Abstract

Previous studies identified regions of Poland privileged in terms of their wind energy resources, given that they are in areas in which energy values exceed 750 kWh/m²/year at 10 metres above ground level. These are mainly the Baltic coast, the Suwałki region, the ranges of mountains and hills called Bieszczady, Beskid Śląski and Beskid Żywiecki, and central Wielkopolska and Mazowsze. Comparing these results with research over an analyzed period, the author concludes that there has been a certain displacement of energy-privileged areas. The coast remains the most advantageous area from the point of view of new developments in wind energy, but central and eastern Podkarpacie is no longer as favourable as, for example, the Sudety Mountains, with the same being true of the comparison between the Suwałki Region and Warmia. Finally, the privileged area in central Poland “shifted” north-north-east, from Wielkopolska towards Kujawy and the northern part of Mazovia.

The comparison of the results for individual seasons (warm and cold) allows for the conclusion (based on both measurement and model data) that, due to the location of Poland, dominant wind directions, and maximum velocities achieved in different seasons, average wind speed and the value of generated wind energy are much greater during the (October-March) cold season. On the other hand, the warm season (April-September) contributes to resources of wind energy to a much more limited extent.

The basic input data for the programmes for the assessment of wind-energy resources (especially the “older” ones whose development began before 2000) were the results of measurements at Meteorological Stations. Exemplary evaluations of this kind used to be prepared with the aid of a Danish model called WAsP (the Wind Atlas Analysis and Application Program). This made it possible to produce wind-energy calculations on the basis of data from synoptic stations.

Requirements attached to programs of this type of course combined with input data, necessitate generalisation of results or limited applicability to lowland areas with a non-complex orography (mainly given a need to “transfer” the results of calculations from the vicinity of a meteorological station to the place in which the construction of a wind turbine is foreseen. The use of the calculation results of the numerical meteorological model in high spatial resolution allows for such problems to be overcome with no loss of quality or representativeness of results.

This paper presents a comparison of the results of calculations of wind-energy resources based on measurements at meteorological stations and on the basis of the results of the COSMO meteorological model in three basic resolutions in the period 2011‑2019. The results of this work encouraged a conclusion that the products of the numerical meteorological model, especially those launched at high resolution, on a convection-permitting scale, can be deployed successfully in both pure and applied circumstances. Comparison of measurements revealed that, with a view to correct and true-to-reality results being obtained, it was worth increasing model resolution for computational purposes – up to several kilometers, even taking into account the related extension of computing time, as well as the increase in disk space necessary for data storage.

The desirability – in terms of investment – of increasing the heights and sizes of planned wind power plants was also confirmed, as more energy may be obtained in this way. Even as the costs of such structures increase with their heights, the results of the work presented here show clearly that the use of taller power plants (specifically those for which the rotor axis is at the level of 50, 100 or more meters above ground level) offers the chance of a major increase in the gross amount of energy that can be generated. This is due to the change with the mean wind speed linearly with the power profile, while the amount of wind energy obtained depends on the wind speed taken to the third power. Thus, a raising of the level of the rotor axis to a height ten times higher – e.g. from 10 to 100m agl. – on average results in about a fivefold increase in the amount of wind energy obtainable each year.

Keywords: nergia wiatru, model meteorologiczny, rozdzielczość siatki obliczeniowej, profil prędkości wiatru

Andrzej Mazur [andrzej.mazur@imgw.pl], Instytut Meteorologii i Gospodarki Wodnej – Państwowy Instytut Badawczy

Citation

APA: Mazur, A. (2022). Określenie zasobów energii wiatru w Polsce z wykorzystaniem rezultatów numerycznych modeli meteorologicznych. Przegląd Geograficzny, 94(1), 87-102. https://doi.org/10.7163/PrzG.2022.1.4
MLA: Mazur, Andrzej. "Określenie zasobów energii wiatru w Polsce z wykorzystaniem rezultatów numerycznych modeli meteorologicznych". Przegląd Geograficzny, vol. 94, no. 1, 2022, pp. 87-102. https://doi.org/10.7163/PrzG.2022.1.4
Chicago: Mazur, Andrzej. "Określenie zasobów energii wiatru w Polsce z wykorzystaniem rezultatów numerycznych modeli meteorologicznych". Przegląd Geograficzny 94, no. 1 (2022): 87-102. https://doi.org/10.7163/PrzG.2022.1.4
Harvard: Mazur, A. 2022. "Określenie zasobów energii wiatru w Polsce z wykorzystaniem rezultatów numerycznych modeli meteorologicznych". Przegląd Geograficzny, vol. 94, no. 1, pp. 87-102. https://doi.org/10.7163/PrzG.2022.1.4