M. Mustapha

An overview of Non-intrusive load monitoring methodologies

Load monitoring is essential in every energy consuming system. Traditional load monitoring system, which used to be intrusive in nature require the installation of sensor to every load of interest which makes the system to be costly and time consuming. Nonintrusive load monitoring (NILM) system uses the aggregated measurement at the utility service entry to identify and disaggregate the appliances connected in the building, which means only one set of sensors is required and it does not require entrance into the consumer premises. Having studied much and working in the area, this paper aim to provide a comprehensive review of the state of art of NILM, the different methods applied by researchers so far, before concluding with the future research direction, which include automatic home energy saving using NILM.

Classification of electricity load forecasting based on the factors influencing the load consumption and methods used: An-overview

Electrical energy consumption is affected by many parameters. These includes the variables related to power system itself, weather and climatic factors and socio-economic being of the energy consumers. In this paper, two components of load forecasting are classified. The parameters that influence the energy consumption and the methods used to forecast the energy consumption are reviewed. It is observed that, many factors have great influence on the energy consumption, and the forecasting accuracy depends on the amount of data used. Also the methods applied contribute in the forecasting accuracy and complexity of the method. It is therefore important to use large data, and apply an appropriate method (technique) while forecasting electrical energy. A lot of methods are reviewed, from time series method to artificial intelligence with varying parameters, most of which are weather related, demography of the area, economy class of the consumers and the history of electrical energy consumed.