Prediction of electricity consumption demand pattern for 2018 in Ogun State, Nigeria

Abstract

This study uses probabilistic load forecast technique to predict the load demand pattern in Ogun State for year 2018. Energy consumption data for Ogun State for year 2016 and 2017 was obtained from the regional headquarter of the Ibadan Electricity Distribution Company (IBEDC), Abeokuta. The results of the study show that the energy consumption in Ogun State has the probability tendency of rising above 98,469.40 MWHR by 2.68%. Similarly, it was also established that the probability of energy consumed in the state rising below 46,494.68 MWHR within the next few months will be 5.98%. The probability that energy consumption in year 2018 will fall between 98,469.40 MWHR and 46,494.68 MWHR is 91.84%. Energy consumption in year 2018 will mostly fall between 63,500 MWHR -86,000 MWHR. The result also indicated that energy consumption in 2018, has the highest probability of falling between 72,500 MWHR and 77,000 MWHR by 15.34%. It is unlikely it falls between 45,000 MWHR to 50,000 MWHR and 95,000 MWHR to 99,500 MWHR, with both range having their percentage probabilities at 0.19% and 2.99% respectively. Result of this study is useful to IBEDC for their operational planning and control activities.

Fuzzy Logic Approach to Energy Planning in Nigeria

“…According to the 2006 census, the population of Ogun state was 3,751,140, it was projected to 4,742,477 in 2013 using the population projection formula in equation (1). The projected population in 2013 was used as the base population for the projection of the quarterly population of Ogun state.…”

“…The projected population in 2013 was used as the base population for the projection of the quarterly population of Ogun state. The population projection formula is given by Malthusian population growth equation [1].…”

“…Energy planning involves several activities such as load flow, contingency, load security and energy forecasting. However, energy forecast takes a vintage position because other forms of planning depend on it for operation [1][2]. Energy forecasting in the energy industry includes the prediction of the supply, demand and price of electricity, gas, water, and renewable energy.…”

“…Energy forecasting in the energy industry includes the prediction of the supply, demand and price of electricity, gas, water, and renewable energy. Load forecasting, a form of energy forecasting is predicting the electricity demand of a particular geographical and/or temporal interval into the future [1,3,4]. The primary aim of planning is to ensure future demands are met effectively both economically and in terms of engineering [5].…”

“…As presented in [6], the performance of two (2) Medium-Term Load Forecasting schemes which are the least square approach and regression exponential approach for Ogun State in Nigeria were compared having a MAPE value of 1.82% and 6.18% respectively. However, the most recent and shared methodology in the present has been subsumed into a term called artificial intelligence (a combination of artificial neural networks (ANN) and fuzzy logic) [1,7]. The artificial intelligence methods also known as soft-computing techniques, includes Fuzzy Logical System (FLS), Artificial Neural Network (ANN), and Genetic Algorithms' (GA).…”