The characteristics of a submersible induction motor are described with sufficient reliability for practice by the theory of multi-motor electric drive. In this case, the classical circuit of a submersible induction motor is a coupled system of several equivalent-T circuits. In turn, this significantly increases its computational complexity and reduces the speed of ACS. It is proposed to construct a mathematical model of the submersible electric motor in the form of polynomials with significantly higher speed using the methods of experiment planning. In the area of applicability, the differences in the estimation of energy performance do not exceed 1.1%, between the proposed models and classical equivalent-T circuits.
Keywords: automated control system, mathematical model, polynomial, mean absolute percentage error, computational complexity, design of experiment, scatter diagram, modal interval, submersible electrical motor, rotor package
The article discusses a methodology for predicting global horizontal radiation for the day ahead, based on the concept of characteristic days – typical daily profiles of global horizontal insolation. The method is aimed at use in the absence of operational meteorological information and is intended as an alternative (backup) method of short-term forecasting in autonomous energy systems. As a test case, data from the Murino station (Khanty-Mansiysk Autonomous Okrug), obtained from the PVGIS service based on ERA5 reanalysis, was used. The average and median characteristic days for each month are constructed and the accuracy of forecasts using the RMSE, MAE, MdAE and R2 metrics is compared. It is shown that median profiles provide more stable results in conditions of increased weather variability. The method can be used for approximate planning of photovoltaic installations in remote and northern regions with limited access to meteorological data.
Keywords: solar radiation, global horizontal insolation, ERA5, statistical forecasting methods, forecasting in energy systems, forecasting horizon, forecasting for the day ahead, methods for constructing characteristic days, average and median profiles