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Smart meter as part of a new grid system recently introduced in many countries. In Bahrain also, EWA starts installing a smart meter in the households. This device creates a huge amount of data. Although the prediction of feature needed electricity was traditionally in the domain of electrical engineering, but smart meter reading creates a lot of opportunities for data scientists to explore and extract knowledge. Accurate and computationally cheap load forecasting techniques are a crucial part of the grid system. This type of forecasting participates in different aspects of grid systems like planning, maintenance and supplying. It is also an important part of the Home Electricity Management System (HEMS). This paper used feature engineering to reform smart meter data as uni variant time series and use Facebook prophet for easy load forecasting. The prophet methods will be used to forecast the feature data by considering the holiday. The efficiency of the proposed methods is assessed with three different metrics.
Inspec keywords: smart meters; power consumption; power engineering computing; social networking (online); load forecasting; smart power grids; time series
Subjects: Information networks; Other topics in statistics; Power system planning and layout; Biology and medical computing; Social and behavioural sciences computing; Data handling techniques; Power engineering computing; Power system measurement and metering