UMCV Forecasting of Indian Energy Exchange Using Artificial Intelligence

8 Pages Posted: 14 Jun 2019

See all articles by Sumit Saroha

Sumit Saroha

Guru Jambheshwar University of Science & Technology

Vinod Kumar

Guru Jambheshwar University of Science and Technology, Hisar

Date Written: March 31, 2019

Abstract

The accuracy of estimation tool is very much needed for the development of any system. The growth of electricity consumption of developing countries is more as compare to develop. Therefore, the presented work addresses a review of Indian Electricity Exchange (IEX) including efficient demand estimation technique, error evaluation for one year with all seasonal components. In this regard, three years real Unconstrained Market Clearing Volume (UMCV) data from January 2012 to December 2015 has been collected and tested for one year from January to December 2015. For the estimation, neural network (NN) model with Levenberg-Marquardt (LM) and Genetic Algorithms (GA) based NN has been trained using one year data with one moth moving window. By the experimental analysis yearly MAPE of 3.74% and 3.62% by NN and GA based NN respectively has been achieved.

Suggested Citation

Saroha, Sumit and Kumar, Vinod, UMCV Forecasting of Indian Energy Exchange Using Artificial Intelligence (March 31, 2019). Proceedings of International Conference on Sustainable Computing in Science, Technology and Management (SUSCOM), Amity University Rajasthan, Jaipur - India, February 26-28, 2019. Available at SSRN: https://ssrn.com/abstract=3363083 or http://dx.doi.org/10.2139/ssrn.3363083

Sumit Saroha (Contact Author)

Guru Jambheshwar University of Science & Technology ( email )

Hisar
India

Vinod Kumar

Guru Jambheshwar University of Science and Technology, Hisar ( email )

V.P.O.Balawas (Nalwa)
Haryana
Hisar, 125037
India

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