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|Title||Load Forecasting for building and residential electrical load demand|
Currently the efficient use of households being interested research sujet in Vietnam not only is occupped 40% of electricity consumption, but also that is the new and potential research topic. There are some proposed solutions, among them smart metering system has been considered as an effective method for improving the pattern of power consumption of energy consumers  . Smart metering system be used to collect data in house or building and a short-term electrical load forecasting problem can be solved. Load forecasting finds in use in sales, planning and manufacturing divisions of every industry. Literature review indicates the need to consider several factors such as time of a day, weather data and possible customer classes for effective one-step ahead and day ahead load forecasting on a feeder. There are some proposed models such as AR, ARMA, ARIMA, ARIMAX and Artificial Neural Network (ANN). The student need to analyse and evaluation of some short-term load forecasting techniques to get the best forecasting techniques to solve daily demand of residential load in take into account the weather variables (temperature, humidity) and seasons (hours, daily, seasons) variables.
This subject is dedicated to Vietnamese students as well as foreigner students at Master degree.
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