The Influence of the Wind Speed Prediction Error on the Size of the Storage Controlled Operation Zone in the System With the Wind Generator

Klen, Kateryna Serhiivna; Yaremenko, Mykhailo Kostiantynovych; Zhuykov, Valeriy

doi:10.15407/publishing2020.57.035

Cited by 5 publications

(4 citation statements)

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“…But available batery capacity varies depending on parameters like ambient temperature, depth of discharge and wind power predic�on error that depends on wind speed predic�on error [8], Peukert's effect and the equa�on (1) doesn't take them into account. In 1897 Peukert presented empirical equa�ons (Peukert's law) dedicated to ascertaining the dependence of the batery capacity on the discharge current in lead-acid bateries [9]:…”

Section: A Minimum Energy Storage Sizingmentioning

confidence: 99%

The Impact of Wind Power and Load Power Fluctuations on Energy Storage Sizing

Yaremenko,

Klen

2023

Microsyst., Electron. & Acoust.

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The study presents a method of taking into account the impact of wind power and load power fluctuations on the energy storage sizing, comprised of batteries of identical capacity. To account the impact, two methods of calculating the difference between wind power generation and load consumption were presented over some time interval: 1st and 2nd order difference methods. Each of the methods can be parameterized and non-parameterized method with and without taking into account parameters respectively, where the parameters are: discharge current, required discharge duration, depth of discharge, battery capacity, Peukert’s constant, discharge time from 100% capacity, ambient temperature and wind power prediction error. Using the parameterized method compared allows to refine the value of the number of batteries. Using the 2nd order difference method compared to the 1st order difference method can significantly reduce the required number of batteries.

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Section: A Minimum Energy Storage Sizingmentioning

confidence: 99%

The Impact of Wind Power and Load Power Fluctuations on Energy Storage Sizing

Yaremenko,

Klen

2023

Microsyst., Electron. & Acoust.

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“…Thus, to calculate the number of batteries, we need to consider the depth of discharge, ambient temperature, and prediction error (Klen et al, 2020).…”

Section: Taking Into Account the Influence Of Measurement Errormentioning

confidence: 99%

Influence of the Expected Wind Speed Fluctuation on the Number of Batteries of the Balancing System

Yaremenko

Klen

2022

Power Electronics and Drives

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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.

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“…Для побудови прогнозної моделі потужності на виході сонячної панелі обрано поліноми Лагранжа 3-го та 5-го степеня [11], [12], [13], [14], [15], [16] IV. КОРЕКЦІЯ ПРОГНОЗУВАННЯ МЕТОДОМ ХОЙНА Для підвищення точності прогнозування потужності на виході сонячної панелі необхідно проводити корекцію отриманих прогнозних значень методом предиктора-коректора [21], [22], [23], [24] [25]:…”

Section: побудова прогнозної моделіunclassified

Prediction of the Power of the Solar Panel

Myroshnichenko

Klen

2022

Microsyst., Electron. & Acoust.

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The article presents the results of predicting the power at the output of the solar panel by polynomials of different degrees. The article indicates the need for solar power forecast. The article describes what factors affect the forecast of solar power at the output of the solar panel. Forecasting the amount of electricity generated by a solar power plant is primarily a prediction of the amount of solar radiation received by the solar panel, which in turn depends on environmental conditions and parameters. Data were taken from 04.05.2019 - 05.05.2019 with a discreteness of 1 minute. In order to calculate the forecast, the values of solar insolation were converted to power. The hourly curve of change of solar power with a discreteness in 1 minute is presented. A two-hour curve of the change in solar power with a resolution of 10 minutes is presented. The daily curve of change of solar power with a discreteness in 1 hour is presented. The horizon at 1 hour and 1 day was chosen for forecasting. Approximation of data by means of polynomials of various degrees is checked. The article shows graphs of changes in real and predicted values of solar power at the output of the solar panel. The graphs clearly show which method of forecasting is more accurate. The accuracy of the predicted values was assessed using the average relative error. Of all the considered methods of calculating the predicted value of the power of the solar panel, the smallest error is obtained when the data are selected for 2 hours, differ by no more than 2 times and have a discreteness of 10 minutes. The benefit of using the correction of the predicted data by the Hoyne method is checked. To predict the power of the solar panel by approximation, it is advisable to adjust the predicted data. To correct the data, it is advisable to use the method of predictor-corrector. Predictor - is the predicted value, and the corrector - is the adjusted value After calculating the power forecast at the output of solar power, an algorithm was developed with which you can calculate the predicted value of power. The developed algorithm for calculating the forecast uses the following parameters: data discreteness, the period for which the data are taken for analysis, the degree of the polynomial. First, the algorithm selects data for the selected period, selects discreteness. If you want to increase the discreteness, it averages the value. But on the basis of the selected values calculates the polynomial of the selected degree. Then, based on the calculated equation, the forecast is calculated and the predicted values are displayed in the form of a graph.

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The Influence of the Wind Speed Prediction Error on the Size of the Storage Controlled Operation Zone in the System With the Wind Generator

Cited by 5 publications

References 5 publications

The Impact of Wind Power and Load Power Fluctuations on Energy Storage Sizing

The Impact of Wind Power and Load Power Fluctuations on Energy Storage Sizing

Influence of the Expected Wind Speed Fluctuation on the Number of Batteries of the Balancing System

Prediction of the Power of the Solar Panel

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