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Electricity Price and Load Forecasting Using Data Analytics in Smart Grid: A Survey

Conference paper
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Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 47)

Abstract

Smart grid (SG) is bringing revolutionary changes in the electric power system. SG is supposed to provide economic, social, and environmental benefits for many stakeholders. A smart meter is an essential part of the SG. Data acquisition, transmission, processing, and interpretation are factors to determine the success of smart meters due to the excess amount of data in the grid. Electricity price and load are considered the most influential factors in the energy management system. Moreover, electricity price and load forecasting performed through data analytics give future trends and patterns of consumption. The energy market trade is based on price forecasting. Accurate forecasting of electricity price and load improves the reliability and management of electricity market operations. The aim of this paper is to explore the state of the art proposed for price and load forecasting in terms of their performance for reliable and efficient smart energy management systems.

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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.COMSATS University IslamabadIslamabadPakistan

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