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Coal Power’s Trilemma Variable Cost, Efficiency and Financial Solvency

Coal Power’s Trilemma Variable Cost, Efficiency and Financial Solvency

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This study examines the thermal, financial and operational performance of the Indian coal fleet with a capacity of 194 GW over the course of 30 months (September 2017 – February 2020) leading up to the COVID-19 pandemic. It explores factors leading to under-utilisation of some of the new and efficient assets.

The study assesses the factors driving the efficiency and variable costs of the coal fleet and proposes a counterfactual scenario which prioritises efficiency over variable costs in the dispatch mechanism. It goes on to estimate the efficiency improvements and cost savings achieved in the counterfactual scenario.

The study, then assesses several ramifications of the proposed counterfactual scenario such as variation in states’ generation capacity, avoided investment in pollution retrofits, technical operations of the grid, inter-regional transmission, system flexibilities and meeting future demand.

It provides some key recommendations that could potentially destress the sector and make room for fresh investments to enable financially solvent discoms that could cater to the future economy.

Despite having low variable cost, the PLF of 5- to 10- year group is low

Despite having low variable cost, the PLF of 5- to 10- year group is low

Key Findings

  • Around 65 per cent of the total coal power generation capacity as of March 2020 was installed in the previous 10-year period. As much as 33 per cent of these came from the private sector.
  • Variable costs of electricity generation from coal-based plants are distorted by fuel costs, fuel supply contracts and lop-sided fuel availability. Older plants receive cheaper coal and as a result, they outcompete younger ones in variable costs along with fixed costs.
  • Based on a parametric estimation, the study finds that the station heat rate is determined by factors like age of the unit, capacity, plant load factor and share of imported coal, while variable cost is driven by delivered coal price, station heat rate, auxiliary consumption, age and capacity size.
  • On reassignment of generation in a counterfactual scenario to utilise efficient assets on priority, and improve the system efficiency, the study determines that 50 GW of the total coal capacity are surplus to the needs of the system.
  • In the counterfactual scenario in which the efficient assets are dispatched on priority, the coal fleet consumed 42 MT lesser coal than in the actual scenario to generate the average daily power demand met by coal – 2722 MUs. The overall efficiency of the fleet improved by 6 per cent from 29.7 to 31.6 per cent.
  • The total variable cost savings amount to around INR 8,944 crore annually along with a one-time saving of INR 10,250 crore by avoiding pollution control retrofits to the surplus capacity.
  • The overall generation changes in the counterfactual scenario within the state boundaries remain within +/-20 per cent except in West Bengal, Odisha, Karnataka and Haryana.
  • A dip in the ramping capabilities of the system of upto 26 per cent was observed, but the last year saw only 5 per cent of the total ramping capacity being used.
  • The limited active generation capacity after decommissioning could cater to 108 per cent of the average supply expected from all-coal assets in 2022 and 77 per cent of the supply expected from all-coal assets in 2030.

Key Recommendations

  • The 30 GW surplus capacity, identified in this study and which also finds a place in the CEA’s assessment for decommissioning in the National Electricity Plan 2018, must be considered for accelerated decommissioning to realise the financial benefits.
  • Temporarily mothball the remaining 20 GW capacity and requisition it only during periods where their need is expected
  • Prioritise efficiency for electricity dispatch as variable costs are distorted.
  • Take up the reallocation exercise officially using data with higher temporal granularity to detail the challenges in achieving the performance improvements.
  • Establish a set of key performance indicators (KPIs) for the thermal generation fleet, among which environmental footprint associated with thermal power generation (as represented by thermal efficiency) should be accorded priority.

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Anand Gupta Editor - EQ Int'l Media Network