Open AccessPREDICTION MODELS FOR ELECTRICITY CONSUMPTION UNDER INFLUENCE OF METEOFACTORS
Author(s) -
Guzel' Raisovna Tokareva,
Rastyam Raisovich Sanzhapov,
Maxim Vladimirovich Savenkov,
Dmitry Aleksandrovich Ilyin
Publication year - 2018
Publication title -
vestnik astrahanskogo gosudarstvennogo tehničeskogo universiteta. seriâ: upravlenie, vyčislitelʹnaâ tehnika i informatika
Language(s) - English
Resource type - Journals
eISSN - 2224-9761
pISSN - 2072-9502
DOI - 10.24143/2072-9502-2018-4-99-106
Subject(s) - electricity , consumption (sociology) , electric power , energy consumption , econometrics , power (physics) , environmental science , work (physics) , sample (material) , precipitation , statistics , computer science , mathematics , meteorology , thermodynamics , engineering , electrical engineering , social science , physics , sociology
The purpose of the study is to assess the effect of meteorological factors on electricity consumption. The object of the study is the power system of the Astrakhan region. As the initial data, a sample was compiled of the data of 12 months of 2015 and 2016. One of the main indicators in planning the work of the energy association and the energy system is the magnitude of the forecasts of the expected power consumption (electricity and power consumption) as a whole for the system, groups and individual consumers, the nodes of the electrical scheme. The magnitude of the forecast of power consumption is a reference indicator for the subsequent planning of energy balances, power and calculation of electrical regimes. The need for accurate forecasting is due to technological and economic reasons. Accurate calculations to ensure the optimal distribution of the load between stations, from an economic point of view, facilitate sales of economically viable operations for the purchase and sale of electricity. There has been given analysis of energy consumption depending on temperature changes and the amount of precipitation during the accounting period. Calculations are made for the deviations of each indicator. The graphs of the dependences of power consumption on the amount of precipitation and temperature are plotted. For these dependencies, polynomial equations are compiled. For a constant relationship between power consumption and the temperature of the calculated correlation coefficients. The correlation coefficient makes it possible to determine how proportional the variability of the two variables is. Taking into account the set of meteorological factors makes it possible to increase the effectiveness of the predicted changes in the energy sector.