Energy Consumption Forecasting for the Digital-Twin Model of the Building

Energies

Joanna Henzel¹  Łukasz Wróbel¹  Marek Sikora¹  Marcin Fice² 

[1] Department of Computer Networks and Systems, Silesian University of Technology, Akademicka 16, 44-100 Gliwice, Poland;Prosumer Energy Center, Silesian University of Technology, Akademicka 2, 44-100 Gliwice, Poland;

关键词: energy consumption forecasting;    residential building energy consumption;    digital-twin model;    time series forecasting;   

DOI  :  10.3390/en15124318

来源: DOAJ

【 摘 要 】

The aim of the paper is to propose a new approach to forecast the energy consumption for the next day using the unique data obtained from a digital twin model of a building. In the research, we tested which of the chosen forecasting methods and which set of input data gave the best results. We tested naive methods, linear regression, LSTM and the Prophet method. We found that the Prophet model using information about the total energy consumption and real data about the energy consumption of the top 10 energy-consuming devices gave the best forecast of energy consumption for the following day. In this paper, we also presented a methodology of using decision trees and a unique set of conditional attributes to understand the errors made by the forecast model. This methodology was also proposed to reduce the number of monitored devices. The research that is described in this article was carried out in the context of a project that deals with the development of a digital twin model of a building.

【 授权许可】

Unknown