Evolving Competitive Electricity Markets: an Enablement through Digital Approach

 
 
 
  • Abstract
  • Keywords
  • References
  • PDF
  • Abstract


    Introduction: Globally instituting competitive electricity markets focus on enablement of suppliers and end consumers digitally to benefit from open access. Open access transformation is a crucial entry point for the establishment of wholesale and retail competitive electricity markets. Technology reforms have been acknowledged worldwide in the electricity sector to orchestrate transforming electric industry business models. In addition to initiatives viz., unbundling (a kind of Industry stakeholder restructuring) of vertically integrated monopolies, upgrade of legal and deregulation frameworks, setting up of management guidelines for energy and wire charges, etc. guaranteeing right data availability and assuring the best informed decision making capabilities with a right validation and security of data to all stakeholders have been recognized as key enabler through an appropriate evidence-based survey recently conducted in the state of Tamilnadu across consumers and suppliers of electricity. This paper is focussed on various approaches for digitally transforming transmission and distribution stakeholders of the electricity industry with an objective to advance reliability, accomplish costs and sales economically, sustain the availability, assure the security and energy sustainability for providing safe electricity supply and thus to empower superior benefits to the consumers.

    Research Methodology: The study examined prospects and challenges for the establishment of wholesale and retail competitive electricity market in Tamil Nadu, India. This study included the survey of a sample size of 325 individuals from electricity consumers’, and 80 individuals from suppliers’ is collected in Tamil Nadu using a structured questionnaire.

    Findings: The study proposes appropriate digital technology strategy along with high spot on proposed governance, legal and regulatory framework. This study deliberates various plans of Orchestrations and an approach to challenge the prospective Obstacles towards the establishment of competitive electricity markets in Tamil Nadu state.

    Implications of the study: The study discusses influences on stakeholders of the electricity market in Tamil Nadu state to consider developing technology strategies.

    JEL Classification: J11, C02, C15, C53, C55, C61, F17, F63, F64

     


  • Keywords


    Competitive Electricity Market, Wholesale Electricity, Retail Electricity, technology strategy.

  • References


      [1] CEA, India. (2017, July 27). Power Sector at a Glance ALL INDIA. Retrieved July 29, 2017, from Government of India, Ministry of Power: http://powermin.nic.in/en/content/power-sector-glance-all-india

      [2] CEWD. (2013). Gaps in the Energy Workforce Pipeline 2013 Survey Results. Retrieved April 29, 2016, from Center for Energy Workforce Development: http://www.cewd.org/Documents/2013CEWDSurveyExecutiveSummary.pdf

      [3] E.ON. (2016). History Profile. Retrieved April 29, 2016, from E.ON.: http://www.eon.com/en/about-us/profile/history.html

      [4] Effatnejad, R. A. (2015). Modeling and Simulation of Hybrid System in DC Micro-Grid Based on Photovoltaic and Energy Storage. Indian Journal of Science and Technology, 1-8.

      [5] Energy Department. (2017). Tamil Nadu Energy Department Policy Note 2016-17. Chennai: Energy Department.

      [6] IBM CAI, IBM IBV. (2012). Outperforming in a data-rich, hyper-connected world. New York, United States: IBM Center for Applied Insights study, IBM Institute of Business Value.

      [7] IBM, MIT Sloan Management. (2011). The New Intelligent Enterprise. New York, United States: IBM Institute of Business Value Analytics research, Massachusetts Institute of Technology.

      [8] IDC. (2011). State of the U.S. Business Analytics Software Market: End-User Perspective by Vertical Industry and Company Size. Framingham: IDC.

      [9] IEA. (2016). Key world energy statistics. Paris: International Energy Agency.

      [10] Jayaprakash, P. G. (2016). IBM Global Business Services. The requirements and an approach to build cognitive utility. Tokyo, Japan: Jayaprakash, P., Glen, G.,.

      [11] John, J. (2013, December 16). Will 2014 be the year that big data hype becomes reality? Retrieved April 24, 2016, from Greentechmedia: https://www.greentechmedia.com/articles/read/Big-Datas-5-Big-Steps-to-Smart-Grid-Growth-in-2014

      [12] Jonathan, W. M. (2015). Tokyo drift: How Japan can turn its aging workforce into an advantage. Retrieved April 29, 2016, from Mckinsey: http://www.mckinsey.com/mgi/overview/in-the-news/tokyo-drift

      [13] Kenneth, R. N. (2008). The Smart Alternative: Securing and Strengthening Our Nation’s Vulnerable Electric Grid. Retrieved October 24, 2015, from The Reform Institute: http://www.reforminstitute.org/uploads/publications/Smart_Grid_Final.pdf

      [14] Kumar, Rajesh. (2010). Promoting Competition though Open Access in the Power Sector. Jaipur, India: CUTS International.

      [15] Luiz Friedrich, A. A. (2015). Short-term forecasting of the Abu Dhabi electricity load using multiple weather variables. Energy Procedia, 3014 – 3026.

      [16] Luke, O. (2016). Four things household batteries can do. Retrieved April 29, 2016, from Reposit Power: http://www.repositpower.com/theblog/four-things-household-batteries-can-do.

      [17] MOHAMED A. ABU-EL-MAGD, N. K. (1982). Short-Term Load Demand Modeling and Forecasting: A Review. IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS, 371-282.

      [18] National Renewable Energy Laboratory. (2015, February 17). Market Evolution: Wholesale Electricity Market Design for 21st Century Power Systems. Retrieved from NREL: http://www.nrel.gov/publications/

      [19] North American Utility Reliability Corporation. (2014, October 1). Glossary of terms. United States of America. Retrieved from www.nerc.com/files/glossary_of_terms.pdf

      [20] planning, E. (2012). 2013 Long-Term Hourly Peak Demand and Energy Forecast. TEXAS: Electric Reliability Council of Texas, Inc.

      [21] Planning, E. (2012). 2013 Long-Term Hourly Peak Demand and Energy Forecast. TEXAS: Electric Reliability Council of Texas, Inc.

      [22] Pradeep S Mehta. (2007). Competition and Regulation in India. Calcutta: CUTS Institute for Regulation and Competition.

      [23] Rajamani, G. S. (2004, March 08). Power trading: open access key to success. Retrieved June 2015, from The Hindu: http://www.hindu.com/biz/2004/03/08/stories/2004030800771500.htm

      [24] Ria Langheim, M. S. (June 2014, Vol. 27, Issue 5). Smart Grid Coverage in U.S.Newspapers: Characterizing Public Conversations. The Electricity Journal, 78-87.

      [25] Taylor, J. W. (2003). Short term electricity demand forecasting using double seasonal exponential smoothing. Journal of the Operational Research Society, 799-805.

      [26] The Climate Group. (2008). Smart 2020: Enabling the low carbon economy in the information age. Retrieved March 28, 2016, from The climate group: http://www.theclimategroup.org/assets/resources/publications/Smart2020Report.pdf

      [27] Wiki. (2016). Grid Parity. Retrieved April 29, 2016, from Wikipedia: https://en.wikipedia.org/wiki/Grid_parity

      [28] Wiki. (2016). Growth of Photovoltaics. Retrieved April 2016, 2016, from Wikipedia: https://en.wikipedia.org/wiki/Growth_of_photo voltaics

      [29] Yamzaki. (2015, Jul 7). Japan’s Electricity Market Reform and Beyond. Retrieved Apr 24, 2016, from Ministry of Economy, Trade and Industry: https://www.iea.org/media/workshops/2015/esapplenaryjuly2015/Yamazaki.pdf


 

View

Download

Article ID: 17911
 
DOI: 10.14419/ijet.v7i2.33.17911




Copyright © 2012-2015 Science Publishing Corporation Inc. All rights reserved.