International Journal of Advanced Computing and Communication Systems

Short Term Power Demand Forecasting Techniques for Smart Grid

Sonali N Kulkarni, Electronics & Telecom Engg., Rajiv Gandhi Institute of Technology, Versova, Andheri(W), Mumbai, Maharashtra, India - 400053.

Prashant Shingare, Emerson Network Power India Pvt. Ltd, NITCO Business Park, Wagle Industrial Estate, Thane(W), Maharashtra, India - 400604.

International Journal of Advanced Computing and Communication Systems

Received On :

Revised On :

Accepted On :

Published On :

Volume 06, Issue 02

Page No :027-032

Abstract

The penetration of renewable energy (RE) into existing electricity system is ever increasing in order to meet exponential increase in power demand. The number of consumers producing renewable energy participating in the power network is also increasing drastically. This has posed serious issues to grid stability as the renewable energy generation is inherently intermittent and unpredictable in nature. Precise demand-supply balancing helps in maintaining stability of the grid system. The accurate forecasting models for power demand and generation are essential for demand-supply management which is one of the important characteristics of upcoming modern smart grid.

Keywords

Auto-regressive Model, Demand forecasting, Exponential Smoothing, Naïve Forecast, Mean Absolute Percentage Error, Mean Squared Error, Power Quality, Prosumer, Renewable Energy, Smart Grid, Time Series Analysis

Cite this Article

Sonali N Kulkarni and Prashant Shingare, “Short Term Power Demand Forecasting Techniques for Smart Grid, ”International Journal of Advanced Computing and Communication Systems, pp. 001-008, July 2019.

Copyright

© 2019 Sonali N Kulkarni and Prashant Shingare. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.