Given the significant untapped RE potential in the state, there is a need for careful planning of capacity addition of generation sources. The plans need to be in line with demand trends in the medium term, especially considering the impacts of COVID-19, retirement of generation assets, plant load factors (PLFs), efficiency levels, and policy targets.

This paper develops combination of supply and demand scenarios for Tamil Nadu's electricity sector through 2030-31. Scenario analyses can aid the state in integrated resource planning, capital investments, infrastructure planning, budgets, and multiyear tariff orders.

Key Findings

  • Achieving a balance between electricity demand and supply is more feasible under an ambitious energy transition scenario, aligning with the state’s nine-gigawatt solar target set for 2023.
  • If the state decides to adopt an ambitious renewables pathway, it should plan to integrate storage to absorb renewable energy generation and avoid any potential curtailments or spillage.
  • With the current financial health of TANGEDCO and the delay in tariff revisions, Tamil Nadu should carefully plan for future power purchases, keeping possible demand growth scenarios in mind.


Given the indebtedness of Tamil Nadu’s electricity distribution company, it is important that the state consider the role of demand—and its implications on costs and the energy balance—in its long-term capacity planning.

To assist with this, this paper develops three demand and four supply scenarios through 2030–31 to yield 12 combinations for the state’s future energy balance.

Such analyses can aid in the state’s integrated resource planning processes and financial investment decisions, and they can be adapted for use across states nationally.

This analysis was conducted during the peak of COVID-19. However, variables impacting supply and demand can be dynamically altered based on plausible scenarios in the short, medium, and long term to show different effects of COVID-19, recovery pathways, and the respective needs of the user in the modeling tool.