Indian Institute of Technology Gandhinagar

Prof. Sudhir K. Jain was the Founding Director of IIT Gandhinagar (IITGN) and held this office from June 2009 to January 2022. As the founding head of the institution, Prof. Jain was instrumental in building IIT Gandhinagar into a unique institution with a distinctive culture that is widely recognized within academic circles in India.

The efficient, economic, and reliable operation of power systems is crucial for ensuring reliable electricity supply to the end users. As power system is evolving with increasing renewable energy integration, network complexity, and the need for real-time operational security, there is growing interest in upgrading existing despatch practices such as merit order despatch through advanced optimization techniques. Security constrained economic despatch (SCED) for state load despatch centres (SLDCs) is a complementary approach to support the transition towards smart, secure, and optimized power system operations. SCED incorporates all types of constraints like transmission constraints, generating unit constraints- declared capacity, technical minimum, ramp-up and ramp-down limits, etc. This work describes the SCED implementation for SLDC Gujarat from 15.06.2025-15.07.2025, for day-ahead and first window of real-time generation scheduling to take decision about the amount and price of power to be acquired from the electricity market. The optimization problem is formulated as linear programming to minimize the operational cost, respecting generating unit constraints (declared capacity, technical minimum, ramp-up, and ramp-down). The simulation study is carried out using the CPLEX solver in the GAMS software.

As per the Paris Agreement of the 15th Conference of the Parties (COP 15), nations pledged to set their national decarbonization and Net Zero goals or Nationally Determined Contributions (NDCs) as part of a larger shared goal of preventing the rise of global average temperatures to more than 1.5°C compared to the pre-industrial average as per the recommendations of The Intergovernmental Panel on Climate Change (IPCC), to avoid the possibilities of large scale irreversible climate catastrophes emerging from the effects of global warming. Accordingly, India has also set its ambitions to go Net Zero by 2070. Also, as per India’s NDC, targets have been set for various carbon-intensive industries like Oil & Gas, Power, Cement, Transport, Steel, etc. Amidst these pledges and targets that span across sectors, green hydrogen is emerging as a key technology with a promise to decarbonize several of these end-uses, as a chemical feedstock in some, while as an energy source in others. However, not all end-uses are equal in their technological readiness or maturity to adopt green hydrogen economically and at scale. In this paper, the possibility of sector coupling between green hydrogen and steel is studied and quantified at the most granular detail (site-level), as steel is one of the most carbon-intensive and critical sectors and must be abated if a nation is to fulfill its NDCs. Steel facility level optimization results available in the public domain are referenced, and an in-house Machine Learning (ML) Modeling framework is developed to estimate the Levelized Cost of Steel (LCOS) based on the Renewable Energy (RE) characteristics of specific geolocations. The correlation between the modeled LCOS and the Levelized Cost of Hydrogen (LCOH) at those geolocations is computed, whereby the presence of a moderately positive correlation between the two commodities would establish grounds for sector coupling.