Development of empirical electricity demand equation based on climatic variables - Nornabila, Abu; Nurul Nadrah Aqilah, Tukimat; Noratikah, Abu; Nur Arina Bazilah, Kamisan; Nuramidah, Hamidon (Taylor's University, 2025)
Nowadays, the electricity demand (ED) is rising quickly in line with the rapid development. As a result, hydropower becomes a significant energy sources for generating sufficient electrical energy to cater the demand in the particular local areas. However, rising greenhouse gases (GHGs) concentration significantly increase carbon dioxide which traps more heat and eventually affects the reservoir’s water availability for hydropower generation. Therefore, the objective of the study was to develop the empirical ED equation in relation to the climatic variables. It is very significant to estimate the future ED affected by the climate changes. This study employed the Statistical Downscaling Model (SDSM) for 3 types of representative concentration pathways scenarios (RCPs); RCP2.6 (lowest impact), RCP4.5 (middle impact), and RCP8.5 (highest impact) to analyse the pattern changes of climate variables in anticipating the future evaporation rates. Then, a multiple linear regression analysis was conducted to investigate the relationships between these climate variables and the equation for ED had been developed. From the analysis, the rainfall projection each year are set to decrease during the inter-monsoon and Southwest monsoon and begin to increase as the Northeast monsoon happens. The projection of maximum temperature under all the RCPs show a gradual increase and peaked from February to October from 4.5% to 6.5% each year. The projection of relative humidity was seen to decrease for all RCPs especially RCP4.5 that gradually decreased to 4.5% in 2070 to 2100 for November until January. Projection of evaporation for months September and November showed the biggest difference where the evaporation under all RCPs were expected to decrease to about 22% and 24%. Backward elimination found that the most significance variable were the minimum temperature, mean temperature, and evaporation with give the smallest p-value and highest correlation coefficient, r, which are subsequently incorporated as independent variables within the ED equation. Based on ED equation, there are some significant increase of the projected ED throughout the years of 2025-2100 especially in February, July and October.