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The central government has enforced a nation-wide lockdown between March 25 and May 3 as part of its measures to contain the spread of COVID-19. During the lockdown, several restrictions have been placed on the movement of individuals and economic activities have come to a halt barring the activities related to essential goods and services. The restrictions are being relaxed in less affected areas in a limited manner since April 20. In this blog, we look at how the lockdown has impacted the demand and supply of electricity and what possible repercussions its prolonged effect may have on the power sector.
Power supply saw a decrease of 25% during the lockdown (year-on-year)
As electricity cannot be stored in large amount, the power generation and supply for a given day are planned based on the forecast for demand. The months of January and February in 2020 had seen an increase of 3% and 7% in power supply, respectively as compared to 2019 (year-on-year). In comparison, the power supply saw a decrease of 3% between March 1 and March 24. During the lockdown between March 24 and April 19, the total power supply saw a decrease of about 25% (year-on-year).
Figure 1: % change in power supply position between March 1 and April 19 (Y-o-Y from 2019 to 2020)
Sources: Daily Reports; POSOCO; PRS.
If we look at the consumption pattern by consumer category, in 2018-19, 41% of total electricity consumption was for industrial purposes, followed by 25% for domestic and 18% for agricultural purposes. As the lockdown has severely reduced the industrial and commercial activities in the country, these segments would have seen a considerable decline in demand for electricity. However, note that the domestic demand may have seen an uptick as people are staying indoors.
Figure 2: Power consumption by consumer segment in 2018-19
Sources: Central Electricity Authority; PRS.
Electricity demand may continue to be subdued over the next few months. At this point, it is unclear that when lockdown restrictions are eased, how soon will economic activities return to pre COVID-19 levels. India’s growth projections also highlight a slowdown in the economy in 2020 which will further impact the demand for electricity. On April 16, the International Monetary Fund has slashed its projection for India’s GDP growth in 2020 from 5.8% to 1.9%.
A nominal increase in energy and peak deficit levels
As power sector related operations have been classified as essential services, the plant operations and availability of fuel (primarily coal) have not been significantly constrained. This can be observed with the energy deficit and peak deficit levels during the lockdown period which have remained at a nominal level. Energy deficit indicates the shortfall in energy supply against the demand during the day. The average energy deficit between March 25 and April 19 has been 0.42% while the corresponding figure was 0.33% between March 1 and March 24. Similarly, the average peak deficit between March 25 and April 19 has been 0.56% as compared to 0.41% between March 1 and March 24. Peak deficit indicates the shortfall in supply against demand during highest consumption period in a day.
Figure 3: Energy deficit and peak deficit between March 1, 2020 and April 19, 2020 (in %)
Sources: Daily Reports; POSOCO; PRS.
Coal stock with power plants increases
Coal is the primary source of power generation in the country (~71% in March 2020). During the lockdown period, the coal stock with coal power plants has seen an increase. As of April 19, total coal-stock with the power plants in the country (in days) has risen to 29 days as compared to 24 days on March 24. This indicates that the supply of coal has not been constrained during the lockdown, at least to the extent of meeting the requirements of power plants.
Energy mix changes during the lockdown, power generation from coal impacted
During the lockdown, power generation has been adjusted to compensate for reduced consumption, Most of this reduction in consumption has been adjusted by reduced coal power generation. As can be seen in Table 1, coal power generation reduced from an average of 2,511 MU between March 1 and March 24 to 1,873 MU between March 25 and April 19 (about 25%). As a result, the contribution of coal in total power generation reduced from an average of 72.5% to 65.6% between these two periods.
Table 1: Energy Mix during March 1-April 19, 2020
Sources: Daily Reports; POSOCO; PRS.
This shift may be happening due to various reasons including: (i) renewable energy sources (solar, wind, and small hydro) have MUST RUN status, i.e., the power generated by them has to be given the highest priority by distribution companies, and (ii) running cost of renewable power plants is lower as compared to thermal power plants.
This suggests that if growth in electricity demand were to remain weak, the adverse impact on the coal power plants could be more as compared to other power generation sources. This will also translate into weak demand for coal in the country as almost 87% of the domestic coal production is used by the power sector. Note that the plant load factor (PLF) of the thermal power plants has seen a considerable decline over the years, decreasing from 77.5% in 2009-10 to 56.4% in 2019-20. Low PLF implies that coal plants have been lying idle. Coal power plants require significant fixed costs, and they incur such costs even when the plant is lying idle. The declining capacity utilisation augmented by a weaker demand will undermine the financial viability of these plants further.
Figure 4: Power generation from coal between March 1, 2020 and April 19, 2020 (in MU)
Sources: Daily Reports; POSOCO; PRS.
Finances of the power sector to be severely impacted
Power distribution companies (discoms) buy power from generation companies and supply it to consumers. In India, most of the discoms are state-owned utilities. One of the key concerns in the Indian power sector has been the poor financial health of its discoms. The discoms have had high levels of debt and have been running losses. The debt problem was partly addressed under the UDAY scheme as state governments took over 75% of the debt of state-run discoms (around 2.1 lakh crore in two years 2015-16 and 2016-17). However, discoms have continued to register losses owing to underpricing of electricity tariff for some consumer segments, and other forms of technical and commercial losses. Outstanding dues of discoms towards power generation companies have also been increasing, indicating financial stress in some discoms. At the end of February 2020, the total outstanding dues of discoms to generation companies stood at Rs 92,602 crore.
Due to the lockdown and its further impact in the near term, the financial situation of discoms is likely to be aggravated. This will also impact other entities in the value chain including generation companies and their fuel suppliers. This may lead to reduced availability of working capital for these entities and an increase in the risk of NPAs in the sector. Note that, as of February 2020, the power sector has the largest share in the deployment of domestic bank credit among industries (Rs 5.4 lakh crore, 19.3% of total).
Following are some of the factors which have impacted the financial situation during the lockdown:
Reduced cross-subsidy: In most states, the electricity tariff for domestic and agriculture consumers is lower than the actual cost of supply. Along with the subsidy by the state governments, this gap in revenue is partly compensated by charging industrial and commercial consumers at a higher rate. Hence, industrial and commercial segments cross-subsidise the power consumption by domestic and agricultural consumers.
The lockdown has led to a halt on commercial and industrial activities while people are staying indoors. This has led to a situation where the demand from the consumer segments who cross-subsidise has decreased while the demand from consumer segments who are cross-subsidised has increased. Due to this, the gap between revenue realised by discoms and cost of supply will widen, leading to further losses for discoms. States may choose to bridge this gap by providing a higher subsidy.
Moratorium to consumers: To mitigate the financial hardship of citizens due to COVID-19, some states such as Rajasthan, Uttar Pradesh, and Goa, among others, have provided consumers with a moratorium for payment of electricity bills. At the same time, the discoms are required to continue supplying electricity. This will mean that the return for the supply made in March and April will be delayed, leading to lesser cash in hand for discoms.
Some state governments such as Bihar also announced a reduction in tariff for domestic and agricultural consumers. Although, the reduction in tariff will be compensated to discoms by government subsidy.
Constraints with government finances: The revenue collection of states has been severely impacted as economic activities have come to a halt. Further, the state governments are directing their resources for funding relief measures such as food distribution, direct cash transfers, and healthcare. This may adversely affect or delay the subsidy transfer to discoms.
The UDAY scheme also requires states to progressively fund greater share in losses of discoms from their budgetary resources (10% in 2018-19, 25% in 2019-20, and 50% in 2020-21). As losses of discoms may widen due to the above-mentioned factors, the state government’s financial burden is likely to increase.
Capacity addition may be adversely impacted
As per the National Electricity Plan, India’s total capacity addition target is around 176 GW for 2017-2022. This comprises of 118 GW from renewable sources, 6.8 GW from hydro sources, and 6.4 GW from coal (apart from 47.8 GW of coal-based power projects already in various stages of production as of January 2018).
India has set a goal of installing 175 GW of Renewable Power Capacity by 2022 as part of its climate change commitments (86 GW has been installed as of January 2020). In January 2020, the Parliamentary Standing Committee on Energy observed that India could only install 82% and 55% of its annual renewable energy capacity addition targets in 2017-18 and 2018-19. As of January 2020, 67% of the target has been achieved for 2019-20.
Due to the impact of COVID-19, the capacity addition targets for various sources is likely to be adversely impacted in the short run as:
construction activities were stopped during the lockdown and will take some time to return to normal,
disruption in the global supply chain may lead to difficulties with the availability of key components leading to delay in execution of projects, for instance, for solar power plants, solar PV modules are mainly imported from China, and
reduced revenue for companies due to weak demand will leave companies with less capacity left for capital expenditure.
Key reforms likely to be delayed
Following are some of the important reforms anticipated in 2020-21 which may get delayed due to the developing situation:
The real-time market for electricity: The real-time market for electricity was to be operationalised from April 1, 2020. However, the lockdown has led to delay in completion of testing and trial runs. The revised date for implementation is now June 1, 2020.
UDAY 2.0/ADITYA: A new scheme for the financial turnaround of discoms was likely to come this year. The scheme would have provided for the installation of smart meters and incentives for rationalisation of the tariff, among other things. It remains to be seen what this scheme would be like since the situation with government finances is also going to worsen due to anticipated economic slowdown.
Auction of coal blocks for commercial mining: The Coal Ministry has been considering auction of coal mines for commercial mining this year. 100% FDI has been allowed in the coal mining activity for commercial sale of coal to attract foreign players. However, the global economic slowdown may mean that the auctions may not generate enough interest from foreign as well as domestic players.
For a detailed analysis of the Indian Power Sector, please see here. For details on the number of daily COVID-19 cases in the country and across states, please see here. For details on the major COVID-19 related notifications released by the centre and the states, please see here.
Recently, the Supreme Court collegium reiterated its recommendations for the appointment of 11 judges to certain High Courts. It had first recommended these names earlier this year and in August last year, but these appointments were not made. The Indian judiciary faces high vacancies across all levels (the Supreme Court, High Courts, and subordinate courts). Vacancy of judges in courts is one of the reasons for delays and a rising number of pending cases, as there are not enough judges to hear and decide cases. As of today, more than four crore cases are pending across all courts in India. In this blog post, we discuss vacancies across courts over the years, delays in appointment of judges, and methods to determine the adequate judge strength required to handle the caseload courts face.
High vacancy of judges across courts
Vacancies in courts keep on arising periodically due to retirement, resignation, demise, or elevation of judges. Over the years, the sanctioned strength of judges in both High Courts and subordinate courts has been increased gradually. However, vacancies persist due to insufficient appointments (see Figures 1 and 2). Between 2010 and 2020, vacancies increased from 18% to 21% across all levels of courts (from 6% to 12% in the Supreme Court, from 33% to 38% in High Courts, and from 18% to 20% in subordinate courts).
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Figure 1: Vacancy of judges in High Courts |
Figure 2: Vacancy of judges in subordinate courts |
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Sources: Court News 2010-2018; Vacancy Statement, and Rajya Sabha replies, Part I, Budget Session (2021), Department of Justice; PRS. |
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As on November 1, 2021, the Supreme Court had a vacancy of one judge (out of a sanctioned strength of 34). Vacancy in High Courts stood at 37% (406 posts vacant out of a sanctioned strength of 1,098). Since May, 2021, the Supreme Court collegium has recommended more than 130 names for appointment as High Court judges. In three High Courts (Telangana, Patna, and Calcutta), at least half of the posts are vacant (see Figure 3). The Standing Committee on Personnel, Public Grievances, Law and Justice (2020) noted that every year, 35-40% of posts of High Court judges remain unfilled.
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Figure 3: Vacancy of judges across High Courts (in %) (as on November 1, 2021)
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Source: Vacancy Statement, Department of Justice; PRS. |
Appointments of High Court judges are guided by a memorandum of procedure. As per this memorandum, the appointment process is to be initiated by the concerned High Court at least six months before a vacancy occurs. However, the Standing Committee (2021) noted that this timeline is rarely adhered to by High Courts. Further, in the final stage of the process, after receiving recommendations from the Supreme Court collegium, the executive appoints judges to the High Court. No timeline is prescribed for this stage of the appointment process. In 2018 and 2019, the average time taken to appoint High Court judges after receiving the collegium’s recommendations was five to seven months.
As of today, over 3.6 crore cases are pending before subordinate courts in India. As on February 20, 2020, 21% posts for judges were vacant (5,146 posts out of the sanctioned strength of 24,018) in subordinate courts. Subordinate courts in Bihar, Haryana, and Jharkhand (among the states with high population) had a high proportion of vacancies of judges (see Figure 4). Note that the Supreme Court is monitoring the procedure for appointment of judges to subordinate courts.
For an analysis of the data on pendency and vacancies in the Indian judiciary, see here.
Figure 4: Vacancy of judges across subordinate courts (in %) (as on February 20, 2020)
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Source: Report No. 101, Standing Committee on Personnel, Public Grievances, Law and Justice (2020); PRS. |
How many judges do we need?
The Law Commission of India (1987) had noted the importance of manpower planning for the judiciary. Lack of adequate number of judges means a greater workload per judge. Thus, it becomes essential to arrive at an optimal judge strength to deal with pending and new cases in courts. Over the years, different methods of calculating the required judge strength for subordinate courts (where the backlog of cases in the Indian judiciary is concentrated) have been recommended (see Table 1).
Table 1: Methods recommended for calculating the required number of judges for subordinate courts
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Method of calculation |
Recommendation and its status |
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Judge-to-population ratio: optimum number of judges per million population |
The Law Commission of India (1987) had recommended increasing this ratio to 50 judges per million people. This was reiterated by the Supreme Court (2001) and the Standing Committee on Home Affairs (2002). For 2020, the judge-to-population ratio was 21 judges per million population. Note that this figure is calculated based on the sanctioned strength of judges in the Supreme Court, High Courts and subordinate courts. |
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Rate of disposal: number of additional judges required (to clear the existing backlog of cases and ensure that new backlog is not created) based on the average number of cases disposed per judge |
The Law Commission of India (2014) proposed this method. It rejected the judge-to-population ratio method, observing that filing of cases per capita varies substantially across geographic units depending on socio-economic conditions. |
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Weighted case load method: calculating judge strength based on the disposal by judges, taking into account the nature and complexity of cases in local conditions |
The National Court Management Systems Committee (NCMS) (2016) critiqued the rate of disposal method. It proposed, as an interim measure, the weighted case load method, which addresses the existing backlog of cases as well as the new flow of cases every year in subordinate courts. In 2017, the Supreme Court accepted this model. |
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Time-based weighted case load method: calculating the required judge strength taking into account the actual time spent by judges in different types of cases at varying stages based on an empirical study |
Used widely in the United States, this was the long-term method recommended by the NCMS (2016) to assess the required judge strength for subordinate courts. It involves determining the total number of ‘judicial hours’ required for disposing of the case load of each court. The Delhi High Court used this approach in a pilot project (January 2017- December 2018) to calculate the ideal judge strength for disposing of pending cases in certain courts in Delhi. |
Sources: Reports No. 120 (1987) and 245 (2014), Law Commission of India; Report No. 85, Standing Committee on Home Affairs (2002); Note for Calculating Required Judge Strength for Subordinate Courts, National Court Management Systems Committee (NCMS) (2016); Imtiyaz Ahmad vs. State of Uttar Pradesh, Supreme Court (2017); PRS.
