NONE 20260515082325943 wseas/wseas content-registration-form+ja@crossref.org content-registration-form WSEAS TRANSACTIONS ON POWER SYSTEMS 1790-5060 2224-350X Krasimira Stoilova Institute of Information and Communication Technologies – Bulgarian Academy of Sciences, Acad. G. Bonchev str. bl.2, 1113 Sofia BULGARIA Todor Stoilov Institute of Information and Communication Technologies – Bulgarian Academy of Sciences, Acad. G. Bonchev str. bl.2, 1113 Sofia BULGARIA Denis Chikurtev Institute of Information and Communication Technologies – Bulgarian Academy of Sciences, Acad. G. Bonchev str. bl.2, 1113 Sofia BULGARIA The paper aims to develop a model for forecasting energy production from a photovoltaic (PV) system given a short range of data. Real data for a recently installed PV system is available. An analytical model based on time series analysis has been developed. A feature of modeling is the insufficient amount of available data needed to make predictions. This limitation necessitates the use of a relatively simple forecasting model, such as the linear autoregressive model AR(1). To achieve better forecasting accuracy, a set of technologies, such as optimization, the least squares method, model predictive control, and a sliding procedure for shifting the beginning of historical data, was used. A comparison between actual and forecasted values has been made where possible. The proposed innovative approach is a good tool for planning energy production from photovoltaic systems. This can be beneficial for the declared power generation of an energy supplier, which has a cost-effective result. In addition, the forecast of photovoltaic system generation can help in the correct design of the inverter and battery parameters of the PV system. 12 31 2025 12 31 2025 503 40 https://creativecommons.org/licenses/by/4.0/deed.en_US 10.37394/232016.2025.20.40 https://wseas.com/journals/ps/2025/a805116-023(2025).pdf S. Karabanov, Y. Kukhmistrov, B. 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