Towards Sustainable Social Development: Optimal Demand Forecasting
Authors: Pradip Neupane
Abstract—Energy is one of the essential entity of social development and it is also regarded as the index of development. Electricity consumption pattern gives the information regarding the trend of socio-economic development of nation. Therefore future electricity demand is important not only for planning and operation of utility but also necessary for the recognizing and planning of social development area too. Different convectional and machine learning technique have been used for the electricity demand forecasting. In this paper three different technique are used for the electricity demand forecasting i.e. linear regression (LR), auto regressive integrated moving average (ARIMA) and fuzzy logic (FL) model. Among them LR is set as benchmark. LR and ARIMA here used as univariate models whereas fuzzy logic model is multivariate. Fuzzy logic model considered population growth and gross domestic product growth rate along with historical load demand. The result revealed that fuzzy logic model provides more realistic future value as compared to remaining models.
Keywords—demand forecasting, linear regression, ARIMA, fuzzy logic
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Published In: International Conference on Role of Energy for Sustainable Social Development in ‘New Normal’ Era (RESSD-2020)
Date of Conference: 28th-29th December 2020
Conference Location: Kathmandu, Nepal
Publisher: IEEE Power and Energy Society Nepal Chapter
Cite the paper as:
P. Neupane, “Towards Sustainable Social Development: Optimal Demand Forecasting”, International Conference on Role of Energy for Sustainable Social Development in ‘New Normal’ Era, 28th-29th December 2020, Kathmandu, Nepal