SARIMA Modelling for Forecasting the Electricity Consumption of a Health Care Building
Harveen Kaur1, Sachin Ahuja2
1Harveen Kaur, Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India
2Sachin Ahuja, Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India
Manuscript received on September 16, 2019. | Revised Manuscript received on 24 September, 2019. | Manuscript published on October 10, 2019. | PP: 2795-2799 | Volume-8 Issue-12, October 2019. | Retrieval Number: L25751081219/2019©BEIESP | DOI: 10.35940/ijitee.L2575.1081219
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Abstract: Healthcare buildings have an immense demand for electricity, because of which they exhibit distinctive ability for forecasting of electricity consumption. In this work, ability for forecasting electricity consumption of a large healthcare building was researched. Both the techniques change non stationary data into stationary data to make an effective and simple data representation and removing of noise subspaces. The comparison of experimental results is done among the SARIMA and ARIMA models. Analysis of the results concludes that performance of SARIMA is better when compared to ARIMA model. The analysis of data from 11 years in the hospital demonstrates that these dynamic models are sufficiently adaptable to forecast the electricity consumption at required accuracy levels.
Keywords: ARIMA Model, SARIMA Model, Electricity Consumption, Load forecasting, Electricity
Scope of the Article: Building Energy