Fuzzy logic, being a very robust artificial intelligence technique, was employed to forecast short term load in this work. The algorithm was demonstrated with the help of seven months average daily load data collected from Power Holding Company of Nigeria (PHCN). The outcome realized from the model or simulation illustrate that the projected forecasting technique, which propose the use of weather alteration such as temperature and humidity, gives load forecasting results with substantial precision, in the range of 0.71% Mean Absolute Percentage Error (MAPE). Using the conventional technique provided forecast with a large MAPE up to 3.18% which shows a high level of inaccuracy or less precision as compared with the use of Fuzzy logic.
Benson, S. (2019). IMPACT OF WEATHER VARIABLES ON ELECTRICITY POWER DEMAND FORECAST USING FUZZY LOGIC TECHNIQUE. Afribary. Retrieved from https://track.afribary.com/works/impact-of-weather-variables-on-electricity-power-demand
Benson, Stephen "IMPACT OF WEATHER VARIABLES ON ELECTRICITY POWER DEMAND FORECAST USING FUZZY LOGIC TECHNIQUE" Afribary. Afribary, 20 Sep. 2019, https://track.afribary.com/works/impact-of-weather-variables-on-electricity-power-demand. Accessed 23 Nov. 2024.
Benson, Stephen . "IMPACT OF WEATHER VARIABLES ON ELECTRICITY POWER DEMAND FORECAST USING FUZZY LOGIC TECHNIQUE". Afribary, Afribary, 20 Sep. 2019. Web. 23 Nov. 2024. < https://track.afribary.com/works/impact-of-weather-variables-on-electricity-power-demand >.
Benson, Stephen . "IMPACT OF WEATHER VARIABLES ON ELECTRICITY POWER DEMAND FORECAST USING FUZZY LOGIC TECHNIQUE" Afribary (2019). Accessed November 23, 2024. https://track.afribary.com/works/impact-of-weather-variables-on-electricity-power-demand