National Council of Applied Economic Research
Opinion: Chetna Choudhuri and Sanjib Pohit.
Capturing regional disparities is crucial.
In COP29, the focus was on finance since countries require significant funding for energy transition. According to International Energy Agency, clean energy investment needs to reach $4.5 trillion a year by 2030 to limit global warming to 1.5°C. The share of renewables in gross electricity generation at the global level must reach 91 per cent by2050 from 28 per cent in 2020.
This calls for significant mobilisation of resources. The requirement of funds is estimated based on various kinds of models. But a major fallacy of the Indian models is that almost all of them are national models, and do not capture regional disparities in energy demand, resources, and policies. In India, with huge disparity in geography, topology, culture, socio-economic condition, and demography across regions, it is quite difficult to capture all the aspects in one macro-economic or energy system model for the nation.
For example, some States are endowed with various fossil fuel resources and that provides jobs to a significant number of workers, some with longer hours of sunshine suitable for development for solar energy, and some have long coastal areas suitable for development of wind or ocean energy. State-level modelling and planning are necessary to understand the challenges and assess the investment requirement.
Regional modelling
Many countries are using multi-regional models for understanding the optimum way to arrive at green energy transition to meet emission targets. For example, even though the EU is a community, each nation in the bloc has devised its own energy transition plan based on strength/weakness of resource endowment and in sync with the overall EU’s target. Large countries like the US, China and Brazil have invested into building multi-sector (100-500 sectors), multi regional models (all major regions as separate entities) for effective policy analysis including that of energy transition.
Resource diversity in the EU or other countries are probably less than that of India. Yet, our pathway is based on a national plan without taking into account the regional diversity. Ideally, a bottom-up approach should have been the right one in our case and national plan should have been derived by aggregating the regional ones and examining whether these are in sync with the national one. Though data availability is an issue in India, it is necessary to capture the regional diversity.
NITI Aayog, in collaboration with the Ministry of Power and the Ministry of New and Renewable Energy, launched the ASSET (Accelerating Sustainable Solutions for Energy.
Transition) platform to assist in formulating State energy transition blueprints and implementation, identifying bankable projects, best practices, innovations in critical sectors like BESSs (battery energy storage systems), green hydrogen, energy efficiency, e-mobility, offshore wind, etc., in line with Viksit Bharat 2047.
An NCAER study, featuring State-level Integrated Assessment Model (IAM) based on soft-linking of macroeconomic CGE model and MESSAGEix model, finds that, for Kerala, $230.75 billion is required cumulatively between 2025 and 2050 to finance low carbon transition for mitigation without hampering economic growth, with an assumption of 2.5 per cent improvement in energy efficiency and 1 per cent productivity growth per annum. For Odisha, the requirement of investment is $395.33 billion cumulatively between 2025 and 2050.
These estimates do not include the loss-and-damage cost, and the finances required for adaptation. To support low-carbon, climate-resilient solutions in energy, transport and agriculture, there is a significant need to invest in the renewable energy sector, and that needs to be captured by the ‘bottom-up’ State-level models and planning. To address this issue, NCAER is developing multi-sector (147 sector) multi-regional model (30+regions) covering all the States.
Chetana is Fellow, and Sanjib is Professor, NCAER. Views are personal.