TMY versus multi-year time series of meteorological conditions for the characterization of central Poland's suitability for photovoltaics

Nelken, K.; Żmudzka, Elwira

doi:10.1127/metz/2016/0755

Cited by 7 publications

(3 citation statements)

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“…There are some recent results showing that TMY data sets should not be considered as a proper alternative to long-term measured data. Some studies show the limitations of using the TMY instead of long-term data [15,[34][35][36][37]. It is an argument for the use of longer time series instead of relying on TMY data.…”

Section: Comparisonmentioning

confidence: 99%

Assessment of Typical Meteorological Year Data in Photovoltaic Geographical Information System 5.2, Based on Reanalysis and Ground Station Data from 147 European Weather Stations

Kulesza,

Martinez,

Taylor

2023

Atmosphere

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The Photovoltaic Geographical Information System (PVGIS) is a web application that provides free access to solar radiation and temperature data, typical meteorological year (TMY) data, and to photovoltaic performance assessment tools for any place in most parts of the world. The PVGIS was originally developed over 20 years ago, and since then, it has been under continuous development. At present, there are two versions of the PVGIS online—the older version 5.1 and the newest version 5.2. PVGIS 5.2 includes substantial improvements compared to the previous version, e.g., the update of the underlying data sets both in terms of quality, resolution, and geographical coverage and the extension of the time period used. This paper focuses on comparing the TMYs (and more specifically the TMY time series of air temperature), coming from both PVGIS 5.1 and 5.2, with the TMY produced on the basis of ground station meteorological data and with the ground station data itself. The results show that whereas overall the errors and biases for most locations are within the expected range (mean stationRMSE 4.27), these differences increase in places with complicated topography, e.g., in the Alps (maximum stationRMSE 9.50).

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Section: Comparisonmentioning

confidence: 99%

Assessment of Typical Meteorological Year Data in Photovoltaic Geographical Information System 5.2, Based on Reanalysis and Ground Station Data from 147 European Weather Stations

Kulesza,

Martinez,

Taylor

2023

Atmosphere

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“…Comparing to the TMY the heating demand was lower in a range from 2% (warmer climatic zones) to 28% (coldest zone). Analogous considerations, but concerning photovoltaics, were shown in (Nelken and Zmudzka, 2016). The TMY's and data from measurements during the period 1971-2000 for 16 weather stations were used.…”

Section: Literature Reviewmentioning

confidence: 99%

Modelling of global solar irradiance on sloped surfaces in climatic conditions of Kraków

Michalak

2019

New Trends in Production Engineering

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The paper presents calculations of global solar irradiance on inclined surfaces of any orientation in the hourly time step. For computational purposes there were used the data from typical meteorological years (TMY) available in a form of text files on the website of the Ministry of Infrastructure and Development. Hourly solar global horizontal irradiance from measurements from the file for Kraków was used as input for five anisotropic models (Hay, Muneer, Reindl, Perez and Perez according to the new PN-EN ISO 52010-1 standard). Direct normal and diffuse horizontal and then global irradiances were calculated. To illustrate the effects of using different models, for the exemplary residential building, monthly solar heat gains and heating demand was determined according to the monthly method of PN-EN ISO 13790. In comparison to the solar data from the TMY, an average decrease in the value of solar gains amounted 37%, what resulted in an increase in the calculated heat demand of the building by 10%. This is very important since this change takes place without any modernisation works.

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“…In such studies, error metrics and deterministic predictions were used to calculate error, simplified mean, variance, and standard deviation values, which are limited and cannot reflect the inherent integrated uncertainty 8) . Although these studies used deterministic methods, the corresponding statistical analyses generated unreliable means of values, suggesting that the TMY is not an appropriate tool for assessing individual sites to secure investments in long-term planning models and that risk levels associated with solar energy projects can be very high 9) . Table 1 summarizes different studies of validation of TMY by using traditional statistics.…”

Section: Introductionmentioning

confidence: 99%

Accuracy Assessment of Typical Meteorological Year Data for a Photovoltaic System using a Bootstrap Method

Uwineza

Kim

et al. 2021

kses

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The typical meteorological year (TMY) is a key element in the long-term performance predictions of photovoltaic systems. However, there is a loss of some hourly measured weather data during the formation of the TMY dataset owing to a lack of observations. Therefore, various statistical techniques or satellite observations can be utilized to address this limitation, and these interpolated data may represent some degree of uncertainty that can influence the accuracy of the TMY data. This may in turn affect the long-term planning reliability of the photovoltaic systems. Therefore, a bootstrap method was used in this study to evaluate the accuracy of TMY datasets in the prediction of long-term photovoltaic yields. The electricity production uncertainties obtained through a simulation conducted using this TMY were calculated with a confidence level of 95% for each resulting value as validated based on the long-term average electricity yield. The results show that the bootstrap method provides valid and more useful information than the deterministic approach. Therefore, it is the best method for quantitatively analyzing uncertainty in TMY datasets. The results described herein can serve as a guide for risk management strategies and other business decisions related to solar energy projects. In addition, the results can help planners achieve greater confidence when applying TMY data to feasibility studies.

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TMY versus multi-year time series of meteorological conditions for the characterization of central Poland's suitability for photovoltaics

Cited by 7 publications

References 0 publications

Assessment of Typical Meteorological Year Data in Photovoltaic Geographical Information System 5.2, Based on Reanalysis and Ground Station Data from 147 European Weather Stations

Assessment of Typical Meteorological Year Data in Photovoltaic Geographical Information System 5.2, Based on Reanalysis and Ground Station Data from 147 European Weather Stations

Modelling of global solar irradiance on sloped surfaces in climatic conditions of Kraków

Accuracy Assessment of Typical Meteorological Year Data for a Photovoltaic System using a Bootstrap Method

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