Mapping costs for early coal decommissioning in India
The study has been authored by Vaibhav Pratap Singh and Nikhil Sharma.
To stop the further acceleration of the climate crisis, the world needs to transition to clean energy sources. To realise this transition, countries world over need to direct considerable investment flows to decarbonisation activities; as per Organisation for Economic Cooperation and Development (OECD) estimates, the world needs $6.9 trillion ( ₹5.04 crore crore) annually to meet its 2030 nationally determined contribution targets alon . Given that developing countries have limited economic resources, prioritising decarbonisation efforts on the basis of impact is needed.
In India, the electricity sector accounts for 40% of all greenhouse gas (GHG) emissions in the country (as of 2016) and thus presents one such decarbonisation pathway (MoEFCC 2021). Recognising this need, India has set a target of achieving 450 GW of renewable energy (RE) by 2030 (over 4.5 times the current installed capacity). However, due to the build-up of coal-based assets over the last two decades, India also has around 10% (208 GW) of the world’s installed coal capacity (MOP 2021). Though coal supplies over 70% of the total electricity in the country, these coal-based assets are a significant contributor to the total GHG emissions by the electricity sector. Under the National Electricity Plan (NEP) 2018, the Central Electricity Authority (CEA) has identified over 25 GW of excess coal-based capacity for retirement by 2027. However, the retirement process continues to be slow, even for the list of earlier identified plants.
The slow retirement of old inefficient assets combined with low demand growth, improving RE economics, and increasing penetration has resulted in a high share of inefficient plants in the system, putting pressure on the coal assets with system-wide low utilisation (Lolla 2021; Zeniewski and Singh 2021). Currently, India’s coal assets are significantly under-utilised (53 per cent in FY21) compared to at the start of the decade (above 70% in FY11). The slower than anticipated growth of power demand and, of late, the increasing contribution of renewables drives this under-utilisation. Low utilisation also poses a risk to the financial sector—as of September 2020, 11% of Indian power sector loans were classified as non-performing assets (NPAs), and most of these were loans extended to coal-based assets.
To improve the coal plant mix towards new and efficient plants and accommodate the transition from coal-based assets to RE technologies, the country can opt for early decommissioning of some excess coal capacity. The economically draining capacity, which is pollution-intensive and whose absence would not adversely affect the regional demand-supply balance are ideal for piloting this solution, as already identified by the Central Electricity Authority under the National Electricity Plan, 2018. Such a step could help prepare for decommissioning other assets that may continue to function until RE technologies become viable in line with India’s decarbonisation goals. In addition, this move could help improve utilisation rates and reduce the financial stress on the banking system by ensuring improved cash flows for coal assets. This step is also crucial because, as multiple sectors work towards decarbonisation, they will increasingly rely on electricity rather than fossil fuels. This step can also help unlock the capital in coal-based assets to finance India’s RE transition. The costs, drivers and savings of an early decommissioning As a first step to ascertain the costs associated with such a process, we looked at 130 plants (see Table 4) with 95 GW of installed capacity, representing 45 per cent of the total 208 GW of installed coal capacity in the country.
In the absence of plant-level financials, we used tariff orders of the individual plants to calculate the costs associated as per the methodology discussed later. The calculations allowed us to uncover the payables towards equity and debt holders and the workforce in the face of transition.
Based on the analysis, amortising the total cost associated with decommissioning would lead to an average yearly cost ₹0.37 crore/MW/year ($ 50,550/MW/year) for decommissioning a plant a year earlier than envisaged; this represents savings of around 23% over the annual capacity charges.
1. We find that decommissioning the 130 plants today would cost between ₹2.31 lakh crore ($ 32 billion) and ₹3.50 lakh crore ($ 48 billion), including payouts to promoters and debt holders. These costs, on average, are between ₹2.3 crore/MW ($ 0.33 million/MW) and ₹3.7 crore/MW ($ 0.51 million/MW).
2. Payouts to the workforce contribute another ₹57,490 crore ($ 7.8 billion) to the cost. On average, workforce-related payouts for early decommissioning add ₹0.61 crore/MW ($ 0.08 million/MW).
3. The reduced payouts towards capacity charges, especially under the cost heads of O&M (operation and maintenance) and ‘other’ charges in the event of early decommissioning, could help save ₹1.24 lakh crore ($ 17 billion) for the 130 plants.
4. On average, an annual saving of ₹0.11 crore/MW/ year ($ 15,450/MW/year) is potentially possible through early decommissioning of the sample.5
5. Decommissioning the asset today, on average, will allow a capital unlocking of equity and debt worth ₹1.3 crore/MW ($ 0.17 million/MW) and ₹2.4 crore/MW ($ 0.33 million/MW) each.
Given the scale of the task at hand, multiple complexities may arise, including challenges in balancing the regional power supply and demand and adapting grid infrastructure. Thus, the decommissioning process needs to be split into multiple stages to address these technical constraints and to optimise the viability of decommissioning financially. Therefore, in addition to a plant-level economic assessment of each of the 130 units, we have categorised them based on age, variable costs of power, station heat rate, etc., to understand the relationship of cost to these parameters. These benchmarks could help establish the most financially prudent path to early decommissioning among several different pathways, including those not analysed in the report.
Based on the criteria of age (one of the preferred criteria for decommissioning coal assets the world over), the assessments produced the following significant findings. For plants above 25 years of age, the assumed remaining life of the contract is five years. We estimate the average annual cost of decommissioning (including debt, equity, and workforce-related payouts) for these plants to be ₹0.2 crore/MW/year ($ 6,320/MW/year). For the 47 plants that meet these criteria, with an aggregate capacity of 35 GW and an average age of 34 years, it would cost ₹21,474 crore ($ 2.9 billion) to pay off the debt and equity holders; workforce payouts would contribute another ₹11,700 crore ($ 1.6 billion). It would cost a total of ₹33,170 crore ($ 4.5 billion) to decommission these plants early and pay the stakeholders for the five-year worth of contract value.6 However, the avoided portion of the annual payouts worth ₹7,550 crore to these assets, primarily operations and maintenance, and working capital amount to ₹37,750 crore ($ 5.2 billion). That is an early decommissioning could be paid for itself over the next five to six years.
Interestingly, there is significant scope to reduce high equity-related payouts worth 29% of the total cost of decommissioning the 95 GW capacity analysed. As is visible in Germany’s latest rounds of auctions to decommission its coal assets provide evidence of how a law on phasing out coal, coal-based generation, and the auction mechanism can help reduce the costs associated with decommissioning— particularly the payouts due to equity holders—to 40% of the auction caps (Wehrmann 2020).
For its next steps, India would need to ascertain how to remove coal assets from the grid through decommissioning, mothballing, or repurposing for storage or RE. All these and other options need careful assessment to choose the right option viable for different sets of plants. Another essential step in the process is mapping the potential fallouts, significantly impacting the workforce, and building strategies to make the transition just for all the concerned stakeholders. Ensuring a smooth transition, especially for the people in the workforce, a mix of strategies would be needed, including voluntary retirement schemes (as used in nationalised banks in India when the core banking solution was introduced in the 1900’s) and retraining and absorbing workers into alternative jobs. Adequate compensation must be paid to coal mine owners and workers for the early closure of existing contracts to supply coal.
This is important since electricity generation is one of the most significant drivers of coal demand in India and directly employs close to 5 lakh people (IEA 2020). However, the process would need further deliberations as residents of over 50 districts, across 13 states in India are reliant to a varying degree on the coal-based activities to earn a livelihood and transition will impact that (Sandeep Pai and Hishman Zerrefi 2021). Otherwise, by continuously delaying the process, the country may be stuck with excess coal capacity that would continue hurting financiers as has been the case with the power sector’s NPAs, which may ultimately delay RE growth by locking in the much-needed capital.
Based on the economics of the decision, we found that decommissioning may not be a viable option for most of the new plants but make sense for a number of the older plants above 20 years, as shown later in the analysis. The age, when combined with the variable cost factor, we found that around 16 GW of the 95GW could be feasibly retired at almost 40% of the yearly costs at ₹0.15 crore/MW/year ($ 19,960 / MW/year) vs ₹0.37 crore/MW/year ($ 50,550/MW/ year) of the sample analysed. Decommissioning these plants would be a cost-efficient way of decarbonising the power sector as the payouts are lesser, and discoms can save on the high variable costs associated with purchasing power from these generators.
(The study has been authored by Vaibhav Pratap Singh and Nikhil Sharma)