An improved pre-forecasting analysis of electrical loads of pumping station; Resource-Efficient Technologies; No 4

Podrobná bibliografie
Parent link:Resource-Efficient Technologies: electronic scientific journal/ National Research Tomsk Polytechnic University (TPU).— , 2015-.— 2405-6537
No 4.— 2019.— [P. 20-29]
Hlavní autor: Voloshko A. V. Anatolii
Korporace: National Technical University of Ukraine «Ihor Sikorskyi Kyiv Polytechnic Institute» (570), PJSC «AZOT», Central Ukrainian National Technical University
Další autoři: Bederak Ya. S. Yaroslav, Kozlovskyi O. A. Oleksandr
Shrnutí:Title screen
Relevance of research. In order to reduce energy losses, an accurate and timely forecast of the amount of consumed electricity is necessary. Accurate forecasting of electrical loads of industrial enterprises and their divisions (productions, workshops, departments etc.) allows planning of normal operating conditions, concluding contracts for the electricity supply with the electricity supply company under more favorable conditions, and improving the electricity quality, which ultimately affects the final cost of the products produced by an enterprise. So far, more than 150 forecasting methods of electrical loads have been developed. Usually, the most convenient one is selected based on the forecaster experience by creating and analyzing several forecasting models in order to identify the best. Therefore, in order to simplify the forecasting procedure, it is necessary to develop the methodology for forecasting analysis. This methodology should enable canceling forecasting algorithms that will create lower quality forecasts. The main objective is to develop the methodology for making a forecasting analysis of power consumption on the example of a pumping station of an enterprise with a continuous cycle of work to increase the efficiency of energy consumption and implementation of energy-saving measures.
Objects of research: the process of forecasting electrical loads of a pumping station of the enterprise with a continuous cycle of work. Methods of research: fundamental principles of the theory of electrical engineering, statistical methods for power consumption forecasting, the method for detecting the trend of radio signals, and fractal analysis of time series. Research results. The methodology for forecasting analysis of power consumption, which makes it possible to apply the most appropriate methods to forecast the operational power consumption, is developed. For the first time, the radio signal trend detection method is applied to identify the trend of electrical loads. The variation ranges of the fractal parameters of time series of electrical loads are established depending on the variation coefficient of the time series for different periods of time. The Brown method of exponential smoothing that is used to forecast the electrical loads, in the case of identifying the smoothing constant α is in the beyond set ( 1 2 < a < ), is further improved. The regularity of changes in the fractal parameters of time series of power consumption of a pumping station with an increase in the time series duration and their field of application are explained.
Jazyk:angličtina
Vydáno: 2019
Témata:
On-line přístup:http://earchive.tpu.ru/handle/11683/57915
https://doi.org/10.18799/24056537/2019/4/265
Médium: Elektronický zdroj Kapitola
KOHA link:https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=585198

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330 |a Relevance of research. In order to reduce energy losses, an accurate and timely forecast of the amount of consumed electricity is necessary. Accurate forecasting of electrical loads of industrial enterprises and their divisions (productions, workshops, departments etc.) allows planning of normal operating conditions, concluding contracts for the electricity supply with the electricity supply company under more favorable conditions, and improving the electricity quality, which ultimately affects the final cost of the products produced by an enterprise. So far, more than 150 forecasting methods of electrical loads have been developed. Usually, the most convenient one is selected based on the forecaster experience by creating and analyzing several forecasting models in order to identify the best. Therefore, in order to simplify the forecasting procedure, it is necessary to develop the methodology for forecasting analysis. This methodology should enable canceling forecasting algorithms that will create lower quality forecasts. The main objective is to develop the methodology for making a forecasting analysis of power consumption on the example of a pumping station of an enterprise with a continuous cycle of work to increase the efficiency of energy consumption and implementation of energy-saving measures. 
330 |a Objects of research: the process of forecasting electrical loads of a pumping station of the enterprise with a continuous cycle of work. Methods of research: fundamental principles of the theory of electrical engineering, statistical methods for power consumption forecasting, the method for detecting the trend of radio signals, and fractal analysis of time series. Research results. The methodology for forecasting analysis of power consumption, which makes it possible to apply the most appropriate methods to forecast the operational power consumption, is developed. For the first time, the radio signal trend detection method is applied to identify the trend of electrical loads. The variation ranges of the fractal parameters of time series of electrical loads are established depending on the variation coefficient of the time series for different periods of time. The Brown method of exponential smoothing that is used to forecast the electrical loads, in the case of identifying the smoothing constant α is in the beyond set ( 1 2 < a < ), is further improved. The regularity of changes in the fractal parameters of time series of power consumption of a pumping station with an increase in the time series duration and their field of application are explained. 
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463 1 |0 (RuTPU)RU\TPU\prd\287306  |t No 4  |v [P. 20-29]  |d 2019 
610 1 |a электронный ресурс 
610 1 |a electrical load 
610 1 |a time series 
610 1 |a pre-forecasting analysis 
610 1 |a fractal analysis 
610 1 |a statistical analysis 
610 1 |a электрические нагрузки 
610 1 |a насосные станции 
610 1 |a потери 
610 1 |a энергия 
610 1 |a прогнозный анализ 
610 1 |a энергопотребление 
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701 1 |a Bederak  |b Ya. S.  |g Yaroslav 
701 1 |a Kozlovskyi  |b O. A.  |g Oleksandr 
712 0 2 |a National Technical University of Ukraine «Ihor Sikorskyi Kyiv Polytechnic Institute»  |4 570 
712 0 2 |a PJSC «AZOT»  |4 570 
712 0 2 |a Central Ukrainian National Technical University  |4 570 
801 2 |a RU  |b 63413507  |c 20220418  |g RCR 
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856 4 |u https://doi.org/10.18799/24056537/2019/4/265 
942 |c BK