Electrical engineering

Physics

Meteorology

Automotive engineering

Demand forecasting

Autoregressive integrated moving average

Demand response

Operations research

Term (time)

Exponential smoothing

Machine learning

Time series

Engineering

Peak demand

Econometrics

Economics

Power (physics)

Geography

Electricity

Blackout

Computer science

Quantum mechanics

Electric power system

Peak load

Energy Reports

Peak load demand forecasting is important in building unit sectors, as climate change, technological development, and energy policies are causing an increase in peak demand. Thus, accurate peak load forecasting is a critical role in preventing a blackout or loss of energy. This paper presents a study forecasting peak load demand for an institutional building in Seoul. The dataset were collected from campus area consisting of 23 buildings. ARIMA models, ARIMA-GARCH models, multiple seasonal exponential smoothing, and ANN models are used. We find an optimal model with moving window simulations and step-ahead forecasts. Also, including weather and holiday variables is crucial to predict peak load demand. The ANN model with external variables (NARX) worked best for 1-h to 1-d ahead forecasting.

Short term electricity load forecasting for institutional buildings