Analysis of forecasted meteorological data (NWP) for efficient spatial forecasting of wind power generation
Paweł Piotrowski , Dariusz Baczyński , Marcin Kopyt , K. Szafranek , Piotr Helt , T. Gulczyński
This paper presents a first step towards developing a method and an IT system for spatial forecasting of energy generation from renewable energy sources. Spatial forecasting is understood here as simultaneous forecasting for both large (e.g. country) and small (e.g. district) areas. Such approach is very useful to different stakeholders of the power industry, and especially to system operators. The first step mentioned above was an analysis of Numerical Weather Prediction (NWP) data to find out to what extent one can reduce the quantity of NWP data. The impact of reduced data on the quality of predictions was also investigated. The paper comprises three main parts: a literature review, statistical analysis of NWP data and tests of the possible reduction of NWP data employing different methods. Multiple linear regression models and artificial neural networks were the methods analysed for compensating of the reduced data. The authors have succeeded in identifying a way to process NWP data that provides an acceptable quality of wind power generation forecasts. This paper ends with conclusions.
|Journal series||Electric Power Systems Research, ISSN 0378-7796, e-ISSN 1873-2046, (N/A 100 pkt)|
|Score||= 100.0, 26-02-2020, ArticleFromJournal|
|Publication indicators||= 1; = 0; = 1.0; : 2018 = 1.391; : 2018 = 3.022 (2) - 2018=3.135 (5)|
|Citation count*||1 (2020-04-07)|
* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.