http://www.iaeme.com/IJMET/index.asp 213 editor@iaeme.com International Journal of Mechanical Engineering and Technology (IJMET) Volume 8, Issue 12, December 2017, pp. 213–226, Article ID: IJMET_08_12_022 Available online at http://www.iaeme.com/IJMET/issues.asp?JType=IJMET&VType=8&IType=12 ISSN Print: 0976-6340 and ISSN Online: 0976-6359 © IAEME Publication Scopus Indexed EVOLVING COMPETITIVE ELECTRICITY MARKETS: RESEARCH PAPER ON OPERATIONS TECHNOLOGY AND MARKET MANAGEMENT SOLUTIONS - DEMAND FORECASTING Jayaprakash Ponraj* Research Scholar, VELS Institute of Science, Technology and Advanced Studies, Pallavaram, Chennai, India Dr. A. Chandramohan Registrar, Rajiv Gandhi National Institute of Youth Development, Sriperumpudur, Chennai, India Dr. Sandeep Jain Senior Managing Consultant, IBM GBS, Advance Analytics Center of Competence, India ABSTRACT Background / Objectives: Worldwide governments, electricity regulatory bodies and utility organizations are converging on instituting new business models towards achievement of open access and thus autonomous electricity market objectives. Market operations and management solutions play an important in influencing the evolution of utilities transformation to autonomous state. The utilities are challenged to manage their power procurement decisions every day basis due to various uncertainties such as economic parameters, government policies on renewables, storage, energy efficiency, weather parameters, holidays and special events like rally, election etc., on a short, medium and long term basis. And this inefficiency is transferred to the consumers in to increasing tariffs. Availability of accurate forecasting & optimizations tools and algorithms interlaced with the utilities processes would significantly bring in synergy and hence reduce the inefficiencies in energy portfolio management. The optimization of revenue or procurement cost is associated with uncertainties in demand and supply. Accurate forecasting of demand and supply changes over intra-day, day ahead, weekly, monthly and a yearly is helps utility in buy and sell decisions of energy through energy exchanges, banking and bilateral contracts. Demand forecasting is dependent on various independent factors such as weather conditions, hour of a day, day of a week, holiday patterns, special events, etc.,