Load forecasting techniques and methodologies: A review

Recent Trends in Load Forecasting Technology for the Operation Optimization of Distributed Energy System

“…Typical studies on the load forecasting in recent years are summarized in Table 2. With reference to review papers in a related research area published prior to 2015, it can be seen that the research in this field is expanding from pure electricity load forecasting towards the cooling and heating load forecasting [15,16]. More and more novel algorithms are established, and the research is transitioning towards the more challenging short-time forecast.…”

A Taxonomy of electricity demand forecasting techniques and a selection strategy

“…Autoregressive integrated moving average model (ARIMA; also called Box-Jenkins model) offers a method for making the series static by introducing a operator as described in Equations (37), (38), and (39) …”

“…Examples are: day (working day or a weekend), humidity, wind speed, intensity of light, and temperature. At = a transposed vector of regression coefficients ℰt = total error in the model This model is based on the assumption that the influencing variables chosen affect the load variation linearly and there is an internal correlation among the variables plotted on multiple time series [38] [39]. This is a low cost method with moderate data requirements and moderate accuracy for short-term forecasting [37] [45].…”

Long-Term Load Forecasting of Southern Governorates of Jordan Distribution Electric System

“…Load forecasting can be broadly divided into three categories: short-term forecasts which are usually from one hour to one week, medium forecasts which are usually from a week to a year, and long-term forecasts which are longer than a year [1]. Traditional studies for long-term load forecasting were based on regression method, which could not provide a true representation of power system behavior in a volatile electricity market.…”