Daily load curve prediction for Jordan based on statistical techniques

Abstract

Abstract The article proposes a mathematical prediction model for daily load curves (DLCs) in Jordan from 2023–2050. The historical hourly peak loads based on the growth rate statistical method in 1994–2020 and the annual forecasted peak loads during the morning and evening periods taken from the long-term load forecast (LTLF) study of National Electric Power Company (NEPCO) during 2022–2050 are employed in the prediction model. The results show that the actual hourly growth rates, the annual forecasted growth rates, and the hourly peak loads in the reference year 2022 are the main input variables used in the prediction formula. The LTLF study conducted by NEPCO employs various sophisticated methods depending on the end-user sectorial electricity consumption that imply an econometric approach, market survey, and Gomprtz extrapolation techniques. The peak load in Jordan relies upon several climatic and nonclimatic variables, implying the ambient temperature, gross domestic product, income, demographic, urbanization, electricity tariff, average oil prices, and other factors related to technology and new aspects of energy saving and space heating/cooling systems, the DLC in Jordan is variable and changing from year to year. The proposed model considers a variation in the future DLC and suggests three different scenarios of DLC’s prediction based on the time occurrence of the peak load: the first is the daytime peak occurrence scenario, the second is the evening peak occurrence scenario, and finally is the daytime and evening peaks may be close to each other.