To read the full version of this content please select one of the options below:

Design of electricity tariff plans using gap statistic for K-means clustering based on consumers monthly electricity consumption data

Ravindra R. Rathod (Department of Civil Engineering, Indian Institute of Technology Roorkee, Roorkee, India and Department of Information Technology, Walchand College of Engineering, Sangli, India)
Rahul Dev Garg (Department of Civil Engineering, Indian Institute of Technology Roorkee, Roorkee, India)

International Journal of Energy Sector Management

ISSN: 1750-6220

Article publication date: 5 June 2017

Abstract

Purpose

Electricity consumption around the world and in India is continuously increasing over the years. Presently, there is a huge diversity in electricity tariffs across states in India. This paper aims to focus on development of new tariff design method using K-means clustering and gap statistic.

Design/methodology/approach

Numbers of tariff plans are selected using gap-statistic for K-means clustering and regression analysis is used to deduce new tariffs from existing tariffs. The study has been carried on nearly 27,000 residential consumers from Sangli city, Maharashtra State, India.

Findings

These tariff plans are proposed with two objectives: first, possibility to shift consumer’s from existing to lower tariff plan for saving electricity and, second, to increase revenue by increasing tariff charges using Pay-by-Use policy.

Research limitations/implications

The study can be performed on hourly or daily data using automatic meter reading and to introduce Time of Use or demand based tariff.

Practical implications

The proposed study focuses on use of data mining techniques for tariff planning based on consumer’s electricity usage pattern. It will be helpful to detect abnormalities in consumption pattern as well as forecasting electricity usage.

Social implications

Consumers will be able to decide own monthly electricity consumption and related tariff leading to electricity savings, as well as high electricity consumption consumers have to pay more tariff charges for extra electricity usage.

Originality/value

To remove the disparity in various tariff plans across states and country, proposed method will help to provide a platform for designing uniform tariff for entire country based on consumer’s electricity consumption data.

Keywords

Acknowledgements

The authors are thankful to MAHADISCOM Sangli, for providing the data. MAHADISCOM (Maharashtra State Electricity Distribution Company) is a public sector undertaking company controlled by the Government of Maharashtra, India, which is the second largest electricity distribution utility in the world.

Citation

Rathod, R.R. and Garg, R.D. (2017), "Design of electricity tariff plans using gap statistic for K-means clustering based on consumers monthly electricity consumption data", International Journal of Energy Sector Management, Vol. 11 No. 2, pp. 295-310. https://doi.org/10.1108/IJESM-02-2016-0005

Publisher

:

Emerald Publishing Limited

Copyright © 2017, Emerald Publishing Limited