Abstract
Global warming is one of the most alarming phenomena facing our planet today. There is a consensus among scientists that human-induced greenhouse gases (GHGs) should be regulated to slow down the heating of the Earth’s oceans and atmosphere. Energy consumption and CO2 emissions are continuously increasing in different countries, especially developing ones such as India, whose emerging economy and rapid economic development has caught the attention of the world. CO2 emission trading is executed by the various developed countries to alleviate the affect of GHG emissions. In this work, an optimal bidding strategy for a supplier has been developed, considering rival’s bidding behavior, in an hourly day-ahead pool market. Bidding problem has been formulated as a bi-level multi objective optimization problem (BLMOOP), where in the first level generator submit bid strategically to the ISO and in the next level a particle swarm optimization (PSO) approach has been employed for the maximization of social welfare with risk management. It is assumed that each generator should submit bid in sealed auction based on pay-as-bid MCP (market clearing price) mechanism with knowing the rival’s bidding behavior. The practicability of proposed optimization method is examined by an IEEE-30 bus system which consists of six suppliers.
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Acknowledgements
This Publication is an outcome of the R & D work undertaken in the project under the Young Faculty Research Fellowship, Visvesvaraya PhD Scheme of Ministry of Electronics & Information Technology, Government of India, being implemented by Digital India Corporation (formerly Media Lab Asia). We would also like to show our gratitude to Maulana Azad National Institute of Technology, Bhopal for providing us the required facilities during the course of this research.
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Arya, A., Mathur, S.P.S. & Dubey, M. Optimal generator side bidding with carbon emission trading and risk management. CSIT 8, 235–240 (2020). https://doi.org/10.1007/s40012-020-00298-0
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DOI: https://doi.org/10.1007/s40012-020-00298-0