Author:
Shklyarskiy J.E.,Batueva D.E.
Abstract
The object of the study is the territory, which is characterized by household and production load, and their characteristic tendencies of changes in the volume of electricity consumption, and therefore it is necessary to create forecast models that take into account the influence of external climatic fac-tors and their contribution to the forecast of energy consumption of the ob-ject. In the work, theoretical methods and experimental studies were used, consisting in a scientific analysis of trends in changes in power consumption depending on changes in factors, methods of mathematical statistics, statis-tical samples, factors and data from the weather service. During this study, external climatic factors that influence the process of changing the energy consumption of an object and their degree of influence on changing con-sumption were determined. To improve the accuracy of forecasting, it is pro-posed to break the data into working days and days off, since consumption in these periods is of a different nature.
Reference20 articles.
1. Zhang X., Yuan J.: Electricity Consumption Forecasting Based on Improved BP Neural Network. In: 2008 International Conference on Risk Management & Engineering Management, 357-360. IEEE, China (2008)
2. Xu Y.Y., Hsieh R., Lu Y.L., Shen Y.C., Chuang S.C., Fu H.C., Bock C., Pao H.T., Forecasting electricity market prices: a neural network based approach. In: 2004 IEEE International Joint Conference on Neural Networks, 4, 2789-2794. IEEE, Hungary (2004)
3. Gavrilas M., Member S., Ivanov O., Gavrilas G., Customer Classification and Load Profiling using Data from Smart Meters. In: 12th Symp. Neural Netw. Appl. Electr. Eng., 1-6. Serbia (2014)
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