Forecasting Time Series for Power Consumption Data in Different Buildings Using the Fractional Brownian Motion

V. Bondarenko (1, 2, 3) , Simona Petrakieva (4) , Ina Taralova (2, 3) , Desislav Andreev (5)

1 National Technical University of Ukraine "Kyiv Polytechnic Institute" [Kiev]
2 LS2N - Laboratoire des Sciences du Numérique de Nantes
3 ECN - École Centrale de Nantes
4 Technical University Sofia
5 TU-Sofia - Technical University of Sofia [Bulgaria]

In the present paper will be discussed the problem related to the individual household electric power consumption of objects in different areas-industry, farmers, banks, hospitals, theaters, hostels, supermarkets, universities. The main goal of the directed research is to estimate the active P and full S power consumptions for all studied buildings. The defined goal is achieved by solving of the following three problems. The first problem studies which buildings increase their power consumption. The second one finds which objects have the greatest increase of power consumption. And the third problem regards if it is possible to make a short-term forecast, based on the solutions of previous two problems. The present research and solving of the aforementioned problems is conducted using fractional Brownian motion theory. The applicability of this approach is illustrated on the example with 20 real objects in different areas. The paper ends with conclusion notes about possibilities to make short-term forecasts about power consumption of the considered buildings.

Mots clés: parameters estimation; fractional Brownian motion (fBm); forecasting power consumption; modelling; Index Terms-stochastic model

Domaines: Dynamique Chaotique [nlin.CD]

V. Bondarenko, Simona Petrakieva, Ina Taralova, Desislav Andreev. Forecasting Time Series for Power Consumption Data in Different Buildings Using the Fractional Brownian Motion. International Journal of Circuits, Systems and Signal Processing, 2018. ⟨hal-02059586⟩