Survey on Machine Learning based Electric Consumption Forecasting using Smart Meter Data

Abstract

The use of smart meter in electric power consumption plays great roll benefiting customer to control and manage their electric power usage. It creates smooth communication to build fair electric power distribution for customers and better management of whole electric system for suppliers. Machine learning predictive frameworks have been worked in order to utilize the electric energy assets effectively, productively and acknowledgment of advanced energy generation, circulation and utilization. This paper presents outline of research works identified with machine learning based forecasting of customers electric power utilization from smart meter data. The paper concentrates on exhaustive study of strategies and relative examination of classifier models utilized as a part of determining customer electric power consumption. Moreover, limitations, difficulties, points of interest and disadvantage of the past works identified with machine learning based methods determining of customers electric power consumption are over viewed.

Condition monitoring systems: a systematic literature review on machine-learning methods improving offshore-wind turbine operational management

“…There is a collection of survey articles related to the energy industry, for example (Voyant et al 2017), applies regression models to determine the solar radiation to make predictions for photovoltaic panels (Heinermann and Kramer 2016), similarly makes predictions on wind power forecasting (Zemene and Khedkar 2017), has applied various methods to determine consumer electric power consumption.…”