Interval Load Forecasting for Individual Households in the Presence of Electric Vehicle Charging

Raiden Skala, Mohamed Ahmed T. A. Elgalhud, Katarina Grolinger () and Syed Mir
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Raiden Skala: Department of Electrical and Computer Engineering, Western University, London, ON N6A 5B9, Canada
Mohamed Ahmed T. A. Elgalhud: Department of Electrical and Computer Engineering, Western University, London, ON N6A 5B9, Canada
Katarina Grolinger: Department of Electrical and Computer Engineering, Western University, London, ON N6A 5B9, Canada
Syed Mir: London Hydro, London, ON N6A 4H6, Canada

Energies, 2023, vol. 16, issue 10, 1-21

Abstract: The transition to Electric Vehicles (EV) in place of traditional internal combustion engines is increasing societal demand for electricity. The ability to integrate the additional demand from EV charging into forecasting electricity demand is critical for maintaining the reliability of electricity generation and distribution. Load forecasting studies typically exclude households with home EV charging, focusing on offices, schools, and public charging stations. Moreover, they provide point forecasts which do not offer information about prediction uncertainty. Consequently, this paper proposes the Long Short-Term Memory Bayesian Neural Networks (LSTM-BNNs) for household load forecasting in presence of EV charging. The approach takes advantage of the LSTM model to capture the time dependencies and uses the dropout layer with Bayesian inference to generate prediction intervals. Results show that the proposed LSTM-BNNs achieve accuracy similar to point forecasts with the advantage of prediction intervals. Moreover, the impact of lockdowns related to the COVID-19 pandemic on the load forecasting model is examined, and the analysis shows that there is no major change in the model performance as, for the considered households, the randomness of the EV charging outweighs the change due to pandemic.

Keywords: residential load forecasting; Long Short-Term Memory; Bayesian Neural Network; Bayesian optimization; interval forecasting; EV charging; analysis of variance (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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