This paper presents the concept of an information-analytical system for assessing and forecasting the energy generation of solar power plants on the basis of meteorological forecasts and real-time monitoring data. The proposed system integrates weather information, plant-side measurements, SCADA streams, digital performance models, and analytical decision support for short-term and medium-term forecasting. In addition to generation prediction, the study introduces practical monitoring-based methods for extending equipment lifetime and ensuring operational safety. The approach combines solar resource assessment, photovoltaic performance modeling, power forecasting, condition monitoring, availability analysis, and risk-based maintenance support within a unified architecture. A conceptual framework is proposed in which forecast meteorological variables and real-time electrical and thermal measurements are processed by an information-analytical core that evaluates expected generation, identifies deviations, estimates technical condition, and recommends preventive actions. Illustrative simulation-style graphs and engineering diagrams are provided to demonstrate the behavior of the proposed models and the structure of the analytical system.
Development of An Information-Analytical System for Assessing and Forecasting Solar Power Plant Energy Generation Based on Meteorological Forecasts and Real-Time Monitoring, With Applications to Reliable and Safe Operation
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Abstract
References
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