Перегляд за Автор "Matushkin, D."

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    Analysis of factors for forecasting electric power generation by solar power plants
    (КПІ ім. Ігоря Сікорського, 2020) Matushkin, D.; Bosak, А.; Kulakovskyi, L.
    The new model of the wholesale electricity market in Ukraine causes appearance the market for the day ahead. In this market, the generating company undertakes to supply a certain amount of electricity. So, it is necessary to carry on the most accurate forecast of possible electricity generation by solar power plant (SPP). Generation value depends on certain factors. A brief summary of different influence of parameters on the PV cell performance has been provided. The article analyzes and identifies the factors that should be included in the forecast mathematical model of electricity generation by a solar power plant for a certain short-term period. According to analyzed data from SPP located in the Kyiv region, such parameters are the intensity of solar radiation, temperature and humidity, wind speed, and atmospheric pressure. The degree of influence of these factors on the initial function of electric energy generation were estimated by analyzing the scatter plot diagrams of relationship between parameters and correlation coefficients. Thus, the analysis of the influence of factors on the magnitude of electricity generation allowed to determine the priority of including each of the parameters in the mathematical model of the SPP power forecast. It was established that the influence of certain climate parameters for target function is different in each season. Therefore, in the mathematical model for forecasting electric power generation, it is necessary to take into account seasonality. In addition, the dynamic value change of factors also affects the current magnitude of electricity generation. Moreover, at different times of the year and with different combination of the corresponding values of climatic parameters, this effect may have different magnitudes. Therefore, the data obtained from the last periods before the forecasting should have a greater impact on obtaining the predicted value than the data from previous periods.
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    Concept of an ensemble forecasting system for optimization problems of control of solar MicroGrid
    (КПІ ім. Ігоря Сікорського, 2023) Matushkin, D.; Bosak, A.
    Accurate probabilistic forecasts of renewable generation are the driving force for optimizing the operation and management of MicroGrid systems. Combining forecasts of different individual models can improve forecast accuracy, but unlike combining point forecasts, for which simple weighted averaging is often a plausible solution, combining probabilistic forecasts is a much more complex task. Today, ensembles of forecasting models are one of the promising directions for problem solving, where forecasting accuracy is more important than the ability to interpret the model. The main idea of ensembles is the training of several basic models and the aggregation of the results of their work. Empirical studies show that combinations of forecasts, on average, are more likely to produce better forecasts than methods that are based on selecting only one forecasting model. When building ensembles, the issue of ensuring diversity of models and effective training of model members of the ensemble becomes especially relevant. The article is devoted to solving the issues of building an ensemble model for forecasting photovoltaic (PV) power, which combines the results of several basic probabilistic models. Using the ensemble method proposed by the authors can improve forecasting accuracy and reduce the time required for training and evaluation of ensemble member models. Directions and prospects of further research are formulated.
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    Modeling of aircraft steering control system with traction electric drive by used an adaptive fuzzy controller
    (КПІ ім. Ігоря Сікорського, 2020) Matushkin, D.; Bosak, A.; Kulakovskyi, L.; Dubovyk, V.; Priadko, S.
    One of the main tasks of the last two decades is to find ways to optimize energy consumptions for aircrafts. The commercial aviation business is increasingly using environmental monitoring systems and electrical control by using AC and DC tires. One of the trends in the development of aircraft control systems is the replacement of hydraulic and pneumatic systems with electrical ones. The aerospace industry and airlines are interested in performing steering operations without major engines. This operation method allows to save fuel, reduce brake wear, eliminates towing and achieve decreasing of environmental pollution. In the future it is necessary to implement electric steering using a traction drive (TD) based on a synchronous motor with permanent magnets (PMSM). This system is powered by an available auxiliary power unit or other sources such as fuel cells or batteries. This study presents a highly efficient electric steering system as a modern solution for improving the ground operations of modern aircraft powered by main engines. The system was investigated using steering profiles for takeoff and landing. The study determined the effectiveness of its use for steering. The influence of external factors and the change of parameters of the electromechanical system of wheel with an elastic tire were investigated. The results of modeling the dynamic processes of an electromechanical system containing elastic links in the conditions of parametric perturbations confirmed the robust stabilization of dynamic control quality indicators based on the laws of fuzzy logic.