The article analyzes the influence of wind speed prediction error on the size of the controlled operation zone of the storage. The equation for calculating the power at the output of the wind generator according to the known values of wind speed is given. It is shown that when the wind speed prediction error reaches a value of 20%, the controlled operation zone of the storage disappears. The necessity of comparing prediction methods with different data discreteness to ensure the minimum possible prediction error and determining the influence of data discreteness on the error is substantiated. The equations of the "predictor-corrector" scheme for the Adams, Heming, and Milne methods are given. Newton's second interpolation formula for interpolation/extrapolation is given at the end of the data table. The average relative error of MARE was used to assess the accuracy of the prediction. It is shown that the prediction error is smaller when using data with less discreteness. It is shown that when using the Adams method with a prediction horizon of up to 30 min, within ± 34% of the average energy value, the drive can be controlled or discharged in a controlled manner. References 13, figures 2, tables 3.

In the energy balancing system of distributed generation systems with RES (renewable energy sources), in particular with wind turbines, the effective use of the battery of the balancing system depends on the charge-discharge modes that are implemented. To be effectively used in an energy balancing system, the RES control system should coordinate the processes of energy generation and accumulation in the system through the implementation of operational management with forecasting. Depending on the characteristics of the battery and the accuracy of the measurement or prediction of the energy the battery capacity (or the number of batteries) that will provide the specified control range (controlled operation area) needs to be chosen. Empirical relations (equations) devoted to the dependence of the battery capacity on the discharge current and to the change of voltage at the terminals of the battery during direct current discharge were listed. Among the equations Peukert’s law was chosen. A general view of the dependence of the battery capacity on the discharge current was shown. The formula for Peukert's constant (coefficient) was given. 5 Packert's law limitations were listed including the fact that the effect of temperature on the battery is not taken into account. The influence of depth charge-discharge and the number of discharge cycles on the capacitance was shown. In the process of using the battery and increasing the number of charge-discharge cycles, the capacity decreases. Peukert’s formula was extended to be influenced by temperature: both the Peukert’s capacity and the Peukert’s coefficient depend on the temperature because the Peukert’s coefficient depends on the capacity. For further calculations, a rechargeable battery HZB12-180FA from manufacturer HAZE Battery Campany Ltd was chosen. The temperature was taken into account by empirical dependences from the manufacturer and then they were approximated by 3rd order polynomials. Graphical results of the approximation were shown. The formula of dependency between the power of the wind turbine and the wind speed was shown. The connection between wind speed prediction error, amount of power that could not be obtained because of that and the number of batteries that would provide the specified control range (controlled operation area) was shown. Thus, for calculation of the number of batteries the depth of discharge, temperature and prediction (measurement) error were taken into account. Example dependences of the number of batteries on the wind speed error at temperatures of -20 °C, 0 °C and 20 °C were shown. Curves of dependence of the number of batteries of the balancing system on the ambient temperature and the error of wind speed forecasting was constructed. As an example, when the prediction error increases from 10% to 15%, the number of batteries needs to be increased by 1.17 times, and when the temperature decreases from 20 °C to 0 °C, the number of batteries needs to be increased by 1.48 times. The results of the work can be used at the stage of planning the wind turbine when choosing the number and capacity of the batteries to be installed. Possible areas of further research are using Peukert's formulas, generalized for other or different types of batteries, using other formulas, except for Peukert’s one, for taking into account the dependence of battery capacity on discharge current, using a non-empirical approach to include dependency on temperature.

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Оцінка рівня енергії вітрового потоку за супровідними даними Яременко f М. К., ORCID 0000-0001-8782-1642 Клен s К.С., к.т.н., ORCID 0000-0002-6674-8332 Кафедра промислової електроніки kaf-pe.kpi.ua Факультет електроніки fel.kpi.ua Національний технічний університет України «Київський політехнічний інститут імені Ігоря Сікорського» kpi.ua Київ, УкраїнаАнотація-У статті наведено методику оцінки рівня енергії вітрового потоку за супровідними даними. Проведено розрахунок матриці коефіцієнтів кореляції Пірсона для таких метеоданих, як швидкість вітру, температура повітря, тиск на рівні моря. Проведено оцінку значущості коефіцієнтів кореляції за критерієм Стьюдента, з'ясовано, що величина коефіцієнтів кореляції та їх значущість залежать від конкретної реалізації вибірки. Побудовано графіки залежності коефіцієнтів кореляції від часу при різних розмірах вибірки, а також графік залежності коефіцієнта зв'язку між коефіцієнтом кореляції між швидкістю вітру та тиском та коефіцієнтом кореляції між швидкістю вітру та температурою від часу. Проведено оцінку оптимального розміру вибірки спостережень, для якого графіки коефіцієнтів кореляції Пірсона будуть мати такий вигляд, який дозволить прогнозувати подальшу зміну коефіцієнтів. Наведено методику вибору супровідних метеоданих та їх кореляційних функцій для прогнозування на певний інтервал часу. Наведено формули для визначення потужності за відомими значеннями швидкості вітру та рівня енергії за відомою потужністю.Бібл. 19, рис. 13, табл. 4. Ключові слова -системи роззосередженої генерації; метеодані; прогнозування; коефіцієнт кореляції; апроксимація; ряд Фур'єAbstract-In the article the matrix of Pearson correlation coefficients for wind speed, air temperature, pressure at sea level and time on meteorological data taken from 19-02-2019-27-02-2019 in Kyiv was calculated. The matrix was calculated for the size of the sample equal to 24. The significance of the coefficients according to Student's t-criterion was determined, that the value of the correlation coefficients and their significance depend on the concrete sample. It is concluded that due to the stochastic nature of the wind mass movement, the amount of solar heat received and other parameters, the significance of the correlation coefficients of the investigated values and their magnitude may vary depending on the time and day of observations. Graphs of changes in correlation coefficients between wind speed and time, between wind speed and pressure, between wind speed and temperature, between temperature and pressure, depending on the number of observations, have been constructed, the character of the change and the required minimum number of observations have been found. Near Fourier with 7-8 harmonics, graphs of functions of correlation coefficients between wind speed and time, between wind speed and pressure using the MATLAB ® Curve Fitting Toolbox application are approximated. The number of harmonics was chosen with the best approximation of the approximated graph to the original. According to the approximated graphs,...

The article discusses a method of assessing the of dependence of the number of batteries that would be needed to achieve energy balance in distributed generation systems with wind turbines on ambient temperature and on the error involved in predicting the parameters of wind flow (wind speed). To describe the relationship between current rate and capacity in a given current range, Peukert’s law is used. Dependence of the Peukert’s constant on ambient temperature for the lead-acid battery HZB12-180FA is calculated. Taking the lead-acid battery and wind turbine VE-2 as a reference, dependence of area of controlled operation of the battery on the wind speed forecasting error is calculated. The technique of considering ambient temperature, depth of discharge, and wind speed forecasting error when deciding the size of energy storage of the balancing system (the number of batteries and their capacity) is provided. A family of curves representing the dependence of the number of batteries constituting the balancing system on the ambient temperature and the wind speed forecasting error are presented. It is shown that as the wind speed forecasting error increases from 0% to 15% and the ambient temperature decreases from 20 °C to 20 °C, the number of batteries should be increased by approximately 2.81 times in order to maintain the same area of controlled operation of a battery.