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  2. All Volumes and Issues
  3. Volume 86, no.4, 2025
  4. A SCALABLE WEB-BASED TOOL FOR WIND AND SOLAR ENERGY POTENTIAL ASSESSMENT AND GENERATION FORECASTING

A SCALABLE WEB-BASED TOOL FOR WIND AND SOLAR ENERGY POTENTIAL ASSESSMENT AND GENERATION FORECASTING

ISTCMTM.
2025;
Volume 86(4), Number 4
: 7-13
https://doi.org/10.23939/istcmtm2025.04
Authors:
  1. Vladyslav Verpeta
  2. Artur Zaporozhets
1
General Energy Institute of the National Academy of Sciences of Ukraine
2
General Energy Institute of National Academy of Sciences of Ukraine

Ukraine’s energy sector is undergoing rapid transformation due to both the need to restore generation capacity following large-scale infrastructure damage and the accelerated transition to renewable energy sources (RES). Accurate forecasting of electricity production from solar and wind power plants is a key factor for balancing the energy system and reducing investment risks associated with the development of distributed generation. This paper presents GreenPowerAtlas — a software-information platform that integrates long-term satellite climatic datasets from NASA POWER with short-term weather forecasts from Open Meteo. The system implements advanced forecasting algorithms, including statistical models (ARIMA), neural networks (LSTM), and stochastic wind speed distributions (Weibull, Gamma). This ensures both long-term potential assessment and short-term generation forecasting. The architecture of GreenPowerAtlas provides scalability, high performance, and secure user access, while interactive visualization tools support decision-making for investors, engineers, and energy network operators. The platform has been successfully tested on real projects in Ukraine, particularly in assessing the solar energy potential of the Novyi Rozdil Industrial Park, confirming its practical value and readiness for large-scale implementation.

Energy Forecasting
renewable energy sources
solar generation
Wind Generation
ARIMA Models
LSTM Neural Networks
Stochastic Wind Modelling
NASA POWER Satellite Data
Meteorological Forecasts
Distributed generation
Energy Analytics
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