Sunday, July 9, 2017

Air India privatization is not a "reform"

(Published in the EPW issue of 8th July 2017)

The government appears to be on the fast track to privatise Air India (AI), the country’s flag carrier airline with the union cabinet giving its approval soon after a recommendation from the Niti Aayog. The chief executive officer (CEO) of the NITI Aayog revealed that it took only 15 days to come up with the report recommending total privatisation of the carrier. The Aayog did not see any need to consult the stakeholders of AI—employees, management or even the Ministry of Civil Aviation (MCA).
The last time a plan for privatisation of India’s public sector airlines had been mooted—only to be quickly abandoned—was during the tenure of the National Democratic Alliance (NDA) government of 2000–04 (PAC 2014: 154). The years following this were extremely traumatic ones for both the Indian Airlines and AI and after their merger in 2007, also for the merged entity, with a rapid deterioration of its finances.
In April 2012, the government signed a 10-year restructuring plan with the AI. Since then, as required by the plan, it has been continuously monitoring the performance of the airline. Repeated statements by the MCA in Parliament over the years, the last as recently as on 9 March, have testified that the government is largely satisfied that the AI is progressing as per the turnaround plan (MCA 2017a). Against this backdrop, the Minister of Finance Arun Jaitley’s highlighting of AI’s debt and market share as reasons to proceed with its privatisation, is to say the least, curious.
So what caused AI’s finances to deteriorate rapidly till 2012?
The Making of a Crisis
AI and Indian Airlines had been running profitably till 2005–06. However, their future had already been compromised by then.
During the period 1998–2004, no new planes were ordered for AI or Indian Airlines. This was at a time when competition was increasing from private airlines which were rapidly expanding their fleet. The NDA government was keen on privatising Indian Airlines and did not take decisions on the proposals for fleet expansion by Indian Airlines and AI (PAC 2014: 141, 154).
Fleet expansion proposals were finally approved by the government (now of the United Progressive Alliance—UPA) in 2005–06. The orders for new aircraft would have been large ones considering that they came after a long interval. However, even here, the government interfered with the erstwhile AI to its detriment. An AI (pre-merger) board approved proposal for 28 aircraft in January 2004 which was revised to 68 aircraft by November 2004! The total estimated cost of the aircraft on order by the two airlines was over ₹41,000 crore and the only equity infusion planned was ₹325 crore for Indian Airlines. The acquisition was to be funded by debt to be repaid through revenue generation (CAG 2011: viii).
With the two airlines in a precarious situation, the government in its wisdom carried out their merger in 2007 at one stroke. The unions representing airline workers and staff were not consulted. From all accounts, it appears that it was an ill-thought-out act for it would have been difficult to find synergy in the two organisations. The two airlines flew different types of planes and hence the skills of pilots and engineers were different. They had different ticketing systems, and a different organisational culture. The merger imposed huge immediate financial costs and severely affected the morale of the employees.
Between 2007–08 and 2012, AI chalked up increasing losses each year. This along with loans taken to pay for the 111 planes on order added up to a huge debt. By April 2012, when the government finally signed on a turnaround plan for AI, the annual operational loss of the airline had increased to around ₹5,000 crore and its accumulated debt had reached nearly ₹43,500 crore. It was then operating on a capital base of ₹3,345 crore (AI 2012).
Even while the AI was struggling with aircraft shortage, the government went ahead and increased bilateral entitlements (including interior points of call in India) with West Asian countries much beyond the dictates of mutual traffic. At that time, the AI was not even able to utilise its existing quota on what were its most profitable routes. The West Asian carriers used sixth freedom traffic rights (the right to fly from one foreign country to another foreign country after stopping in one’s own country) to transport people from India to Europe and the United States (US) via their West Asian hubs, eating into AI’s share of passenger traffic in/out of India to these countries (CAG 2011: xii). The lack of planes to fly within India resulting from the delay in ordering new aircraft also had an effect on the AI’s passenger share within the country. The national carrier’s share of domestic passengers dropped from 23.1% in 2005–06 to 13% in 2011–12 (DGCA 2017).
Work in Progress
As part of the turnaround plan, the government agreed to restructure some of AI’s debt to reduce the interest burden and also infuse capital to cover the cost of new aircraft. This was however conditional on AI meeting specific performance targets every year. The infusion of capital, had it happened immediately, would have helped it in its turnaround initiatives. Instead, the government went for piecemeal recapitalisation on an uncertain schedule.
Subsidiaries were created for maintenance repair and overhaul (MRO) and ground handling services. An old criticism of AI was that it employed too many people and hence was inefficient. With the creation of the subsidiaries, the manpower employed per aircraft became comparable to other private airlines.
Between 2011–12 and 2015–16 (financial years), the last year for which official financial results are available, the airline showed a steady improvement in terms of its operational profit/loss as well as passenger load factor—the percentage of seats on offer that were filled. In 2015–16, the airline made a small operational profit, two years in advance of the turnaround milestone. Its low cost international airline subsidiary, Air India Express and its ground and cargo handling services company, AISATS also made profits (Table 1).

Table 1: Operational Parameters of Air India
                   Operational                      Passenger Load
                   Profit (` crore)                   Factor (%)
2011–12       -4,901                               67.9
2012–13       -3,806                               72.4
2013–14       -3,978                               73.3
2014–15       -2,636                               73.7
2015–16           105                               75.6
2016–17        1,086*                              76.4**

*Provisional estimate (MCA 2016a). **Estimate (MCA 2017b).
Source: Air India Annual Reports at

AI’s financial results for 2016–17 are not officially available but indications are that there will be a significant improvement over the previous financial year in EBITDA (Earnings Before Interest, Tax, Depreciation, and Amortization) (Ghosh and Ghosh 2017). In answers to questions raised in the Lok Sabha, the MCA stated that AI was expected to improve its revenues in 2016–17 by 10%, revenue passenger km (RPKM) by 6.8% and passenger load factor by 6.2% (MCA 2017b). The provisional estimate for 2016–17 (financial year) was an operational profit of ₹1,086 crore and a net loss of 1,989 crore (MCA 2016a). Though AI continues to make a net loss because of interest outgo on debt which in 2015–16 was about ₹4,000 crore, the secretary, civil aviation, went on record in October 2016 to state that he expected a net profit by 2018–19, ahead of the turnaround plan which projects net profits only by 2021–22 (Mishra 2016). All information available publicly points to a continuing improvement in performance.
However, for AI to remain competitive in the longer term, steps need to be taken about its huge debt that has been a drag on the airline. Leaving aside low interest aircraft loans, the outstanding debt is around ₹30,000 crore, 90% of it is from public sector banks and financial institutions (MCA 2016b). The airline has prime real estate assets which it has found difficult to sell because of bureaucratic delays. If the government were to provide assistance in restructuring the debt, selling AI’s real estate assets and speed up infusion of the remaining capital of about ₹6,000 crore promised as part of the turnaround plan, the airline should be on a good wicket.
Chequered History
The basic credo of supporters of privatisation is that the state should withdraw from the provision of all services (and production of all goods) which private corporations are able and interested in providing (producing). The only exception to this would be a “market failure” which render private players incapable of providing (or unwilling to provide) these services. The argument in support of such a belief is that state-controlled enterprises cannot function as efficiently as private corporations.
How does this argument stand up against the actual performance of India’s airlines over the last two decades?
Several early players such as Damania, Modiluft, Natural Energy Processing Company (NEPC) and EastWest folded up, some under a cloud. Air Deccan, the second largest airline in India in 2007, ran into losses and was ultimately taken over by Kingfisher Airlines. Kingfisher became defunct after borrowing ₹7,000 crore from public sector banks. Sahara was taken over by Jet Airways. Spicejet went close to bankruptcy in 2014–15 stopping operations and stranding passengers without notice and has come back only after a large equity infusion from a promoter.
In 2003–04, before the emergence of competition from low cost carriers, Jet Airways accounted for 44% and the public sector airlines together 43% of domestic passenger shares (DGCA 2017). An IMRB survey in October 2004 rated the Indian Airlines as the “most preferred airline”, above Jet (Sen 2009). The low cost carriers had a huge effect on the full service carriers of that period—IA (AI), Jet and Kingfisher. Kingfisher became bankrupt in 2012. Jet was able to survive only after equity infusion by Etihad of Abu Dhabi in 2013. The government appears to have played a role in the rescue by increasing the bilateral entitlements of Abu Dhabi (the number of passenger seats each way between India and Abu Dhabi), which coincided with the Jet–Etihad deal (Phadnis 2013). In 2017 till May end, Jet’s share of domestic passengers was 15.4% and AI’s was 13.3%, the rest being taken by low cost carriers (DGCA 2017). Jet and Indian Airlines (now Air India) have had a similar fall in share of passenger traffic within India after the entry of low cost carriers.
The finance minister has used the low passenger share to deride AI publicly to create public opinion in favour of its privatisation. The fact is that in 2015–16 compared to 2012–13, AI has flown 29% more passengers within India and increased its passenger load to 78.9% from 68.3%. During this period, the AI’s “available seat kilometres” increased only by 6% (DGCA 2017). What this points to is that its passenger share has been limited by the number of aircraft it has available to fly. As the MCA itself revealed in Parliament, there has been no capacity induction into the AI while private airlines have added substantial capacity. Between 2013–14 and 2015–16, AI’s capacity share in the domestic market came down from 17% to 15% (MCA 2016c). Its market share has come down because of decreasing capacity share. The government must own its share of responsibility for this situation.
If the measure of “efficiency” of an airline includes efficient use of capital and labour and providing services without disruption, then looking at the two decades of turmoil in the airline industry, it is hard to accept that private airlines in general have been necessarily managed efficiently.
Unsustainable Debt
Extending the discussion of efficiency to India’s private corporate sector as a whole, it is useful to delve into what has been termed the “twin balance sheet problem.”
Over the years, India’s private corporations have borrowed heavily from banks to grow their businesses. Some of these businesses have failed and others are not generating enough revenue to service their debt. The banks who have lent them money have lost interest income and are in danger of having to write off their debts. It is estimated that three-fourths of all corporate lending could be from public sector banks (Chakravarty 2016).Public sector banks bear the brunt of the bad loan problem.
The government has stonewalled attempts to get the banks to name the bad debtors among private corporations. However, piecing together information from different sources, one finds that more or less all of India’s large industrial houses are involved.
A 2012 Credit Suisse report featured 10 large manufacturing houses—Lanco, Jaypee, GMR, Videocon, GVK, Essar, Adani, Reliance (Anil Ambani), JSW and Vedanta—with high levels of debt that they would find hard to service. A follow-up by Credit Suisse in 2015 found that the financial condition of these groups had deteriorated despite their attempts to sell assets to pare debts. These groups accounted for 27% of all corporate loans from the banking system (Sanjay 2015). In August 2016, the government stated in Parliament that the top 10 corporate groups owed public sector banks and financial institutions ₹5.7 lakh crore (PTI 2016). The businesses of these groups span areas extending from military hardware to steel, coal, power, oil and gas, roads, airports, railways and ports.
In June 2017, the Reserve Bank of India (RBI) identified companies of three groups from the list—Lanco, Essar and Jaypee—and nine other companies which together owed ₹1.75 lakh crore to banks to be dealt with under the bankruptcy code. It is estimated that at least half the debt will have to be written off by the banks.
In the telecom sector, the debt of India’s top seven telecom companies—Bharti Airtel, Vodafone, Idea, Reliance Communications, Reliance Jio and Tata Teleservices—increased by 20% in 2016–17 to ₹3.6 lakh crore and all the companies (except for the new entrant Reliance Jio) have problems servicing their debt (Sarkar 2017). The State Bank of India has the largest exposure to the industry and its chairperson has pleaded with the government to help the industry by deferring spectrum payments, providing duty waivers and reducing the goods and services tax (GST) rate in order to prevent its loans from imminently becoming non-performing assets (NPAs) (TNN 2017). While the incumbent operators blame Reliance Jio for their debt servicing problems, the latter points out that these companies were working with insufficient equity, relying too much on debt financing (PTI 2017).
A recent example from the power sector involves three large corporate houses—Tata, Adani and Essar. All of them won competitive bids based on tariff and set up power plants in Gujarat using imported coal. Their contracts have no provisions to link tariff with coal prices and the companies are running at a loss after coal prices increased and are unable to service their debt. The government is reportedly putting together a rescue package where the companies will be brought under state ownership (Dutta 2017).
The above examples do not capture the enormity of the bad debt problem. During the period 2013–15, public sector banks wrote off ₹1.14 lakh crore of debt (Mathew and Narayan 2016). Several additional lakh crore will likely be written off in the coming years. Eventually, the banks will have to be “bailed out” by the government through capital infusion.
The unsustainable debt of so many private corporations across a swathe of sectors periodically requiring government rescue—including debt write-off by public sector creditors—hardly speaks well about the innate superior efficiency of the private sector.
Timing of Privatisation Decision
Why has the government announced the decision to privatise AI—a decision taken in great haste—just at a time when the airline is on the verge of becoming profitable?
The decision comes at a time when the government’s “reform” credentials are coming under question. These “reforms” which were eagerly anticipated by business leaders and foreign investors have got derailed and include making land acquisition easy, relaxing labour regulations for large factories and doing away with the obligations of banks to lend to the “priority sector” (farmers, small businesses, etc). The government’s inability to make a major dent in the “twin balance sheet problem” has severely affected new lending by banks to the private corporate sector. All this has affected the sentiment of business towards the government.
The announcement of the privatisation of the AI, considered a “soft target” by the government, is perhaps aimed at reversing this state of affairs. As a business newspaper editorialised,
(T)he privatization of Air India will boost investor sentiment in a big way as it demonstrates the government’s willingness and ability to take the reforms process forward. (Mint 2017)
Case against Privatisation
Private investors are interested in the AI because it is an operationally profitable airline with a large fleet of mainly new aircraft, a profitable low cost international carrier like Air India Express, a profitable ground handling services venture, valuable immovable assets in land, offices, hotels and hangers; skilled human resources in the form of a large number of pilots and engineers; the only MRO set-up in India, prime slots at airports in the country and around the world, membership of Star Alliance, etc. The AI is also the largest Indian carrier of passengers across the country’s borders.
The privatisation of AI is only possible if the government writes off a significant part of its debt. This debt accumulated for the large part until 2012 has acted as a millstone around the airline’s neck and delayed its return to profitability. There are various proposals being mooted to once again restructure AI to make its main business—that of flying passengers—attractive to potential buyers. Whatever restructuring is done, there is no getting away from the fact that its debt has to be written off.
The responsibility for this debt rests squarely with the government and is due to its many omissions and commissions in the past—delayed acquisition of aircraft, late capitalisation of the airline, interference in decisions related to aircraft acquisition, the ill-thought-out merger of the AI and Indian Airlines and not providing a level playing field to the national carrier on international routes.
If the government extends the same benefits to the public sector airline (that it wants to for a possible private owner by writing off part of its debt), it will be able to forge ahead. However, given that the airline is close to becoming profitable, it appears that even assistance with restructuring of its debt to public sector banks and sale of its properties will help it to reach profitability and manageable levels of debt.
Publicly owned airlines can also be run efficiently. Singapore Airlines is an example. An efficiently run public carrier can bring stability to air transport services and provide the right competition to private airlines. It can also fulfil objectives that are not dictated by the exigencies of maximising profit—like providing essential coverage to underserved areas or unscheduled services to the Indian diaspora during an emergency— as it does now.
The corporate business press is lauding the government’s privatisation decision, hailing it as the resumption of “reforms” which will consist of more disinvestment and privatisation. It is hard to understand how mismanaging public assets and then selling them is “reform.” Only those who see opportunities for profit in such sales can pretend that these are reforms.
The real reform that India needs is in the manner that public sector enterprises are managed. This reform must ensure at a minimum that there are well-defined policy guidelines for these enterprises available in the public domain, that the enterprises are compensated for costs incurred in implementing specific government policies not in line with their commercial objectives, that there is professional management in place and that this management is shielded from interference from politicians and bureaucrats.
The present government came with the claim of providing “good governance.” There is no reason why this should not extend to the management of public sector enterprises.
AI (2012): “Air India Balance Sheet 2011–12,” Air India,
CAG (2011): “Performance Audit Report on Civil Aviation in India,” Comptroller and Auditor General of India, August,
Chakravarty, Praveen (2016): “The Half-truth of Prudent Private Sector Lending,” BloombergQuint, 18 August,
DGCA (2017): “Domestic Air Traffic Reports,” Directorate General of Civil Aviation,
Dutta, Sanjay (2017): “Government Stitches Rescue Plan for Tata, Adani Power Plants,” Times of India, 28 June,
Ghosh, Shayan and Malyaban Ghosh (2017): “Setback for Air India, RBI Refuses Concession for Debt Restructuring,” Financial Express, 17 May,
Mathew, George and Khushboo Narayan (2016): “Write-offs a Scam, Small Loans Rarely in It, Says Former RBI Deputy Governor,” Indian Express, 11 February, bad-loan-rti-write-offs-a-scam-small-loans-rarely-in-it-says-former-rbi-deputy-governor/.
MCA (2017a): “Financial Performance of Air India, 16th Lok Sabha, Unstarred Question No 1566,” Ministry of Civil Aviation, 9 March,
— (2017b): “Air India Revenues, 16th Lok Sabha, Unstarred Question No 1424,” Ministry of Civil Aviation, 9 March,
— (2016a): “Losses Incurred by Air India, 16th Lok Sabha, Unstarred Question No 353,” Ministry of Civil Aviation, 17 November,
— (2016b): “Outstanding Loan on Air India, 16th Lok Sabha, Starred Question No 321,” Ministry of Civil Aviation, 8 December,
— (2016c): “Privatisation of Air India, 16th Lok Sabha, Unstarred Question No 789,” Ministry of Civil Aviation, 28 April,
Mint (2017): “Maharaja’s Abdication,” Mint, 30 June.
Mishra, Mihir (2016): “After Posting an Operational Profit of 105 Crore, Air India Expected to Soar Higher,” Economic Times, 27 October,
PAC (2014): “93rd Report of PAC: Performance of Civil Aviation in India,” Public accounts Committee (2013–14) Fifteenth Lok Sabha, February, Lok Sabha Secretariat, New Delhi.
Phadnis, Aneesh (2013): “All You Need to Know about Jet–Etihad Deal,” Business Standard, 20 November,
PTI (2016): “Top 10 Corporate Groups Owe ₹5.73 Lakh Crore to Lenders,” Times of India, 2 August,₹-5-73-lakh-crore-to-lenders/articleshow /53507056.cms.
— (2017): “Reliance Jio vs Airtel: Who Is Saying What on Telecom Sector Debts?,” Business Today, 23 June,
Sanjay, P R (2015): “Debt Continues to Weigh Down India’s Top Conglomerates,” Livemint, 22 October,
Sarkar, Saumeet (2017) “The Indian Telecom Industry’s Debt Problem in Three Charts,” BloombergQuint, 4 June,
Sen, Probir (2009): “Air India’s Bailout: Is There Light at the End of the Tunnel?,” Hindu, 19 August, /tp-opinion/Air-Indiarsquos-bailout-is-there-light-at-the-end-of-the-tunnel/article16536689.ece.
TNN (2017): “Telecom Industry’s Debt at Unsustainable Level: SBI,” Times of India, 2 Jun,

Saturday, February 11, 2017

Modi government's solar policy - 2 :

Is the government’s overly aggressive solar thrust in public interest?

(This piece appeared in the Feb 11th issue of EPW ; reproduced below)

Shortly after coming to power the Modi government declared a fivefold increase in the 2022 target for solar generation capacity in the country to an eye popping 100 GW. Less than a year earlier, India’s electricity establishment had estimated 100GW to be India’s solar potential till 2032 (MoP 2014:22)! To see the numbers in perspective, India’s current solar capacity is less than 8 GW.

The target has been set without reference to the coal-fired capacity addition in progress and at a time when capacity utilization of existing thermal plants is very low and there is a large uncertainty on how electricity demand will develop in the next few years (Singh 2016, Tongia 2016:6).

The only argument the government has offered in favour of its aggressive solar thrust is that this would help India meet its international commitments on carbon emissions (GOI, 2015a). There have been questions raised about whether such a rapid build-up of non-fossil fuel capacity is indeed necessary to meet these commitments (Tongia 2016:17). These have remained unanswered.

The government estimates the investment requirement for 100 GW of solar generation to be of the order of Rs 6 lakh crores. Globally, RE is a favourite of investors and the government’s solar program has been enthusiastically received. Foreign investors such as SunEdison, SkyPower, Fortum India and SoftBank and Indian business houses including Adani, Tata and Mahindra have aggressively participated in the large solar tenders. Competition is fierce and the Ministry of New and Renewable Energy has had to hire large halls to accommodate all interested players during pre-bid meetings (Kenning 2015)!

How will such an aggressive solar program impact India’s electricity distribution companies? How will it affect the cost, availability and quality of electricity for consumers? Is the pace of solar adoption pushed by the government in public interest? These are some questions that this paper attempts to answer.

1.    Challenges of renewable energy on the grid

The thrust of the government is entirely on grid connected solar energy. A little background is useful to understand the challenge this poses for electricity distribution.

Electricity demand typically varies round the clock. For example, the all India average pattern shows a higher demand during the day than at night with a sharp late evening peak (PGCIL 2012: 57). It is a basic requirement of a stable electricity grid that demand and supply be “balanced”, or in other words, matched at all times and over different time scales.

Balancing demand and supply

There are several options for balancing. On the supply side, the output of power plants can be controlled to follow demand. On the demand side, the options can be to store energy when there is excess supply and to curtail demand forcibly or through economic disincentives when there is a deficit.

Conventional power plants – such as coal, gas-fired and reservoir based hydro power - are amenable to output control to varying extents. Their use in balancing is determined by their operational “flexibility” - the range over which their output can be changed and the rate at which the change can be made. The capacity available for flexible use is termed “balancing capacity”.

The output of gas-fired and hydro power plants with reservoirs can be changed rapidly and over a large range to handle changing load. These plants are high in flexibility. The old (“subcritical”) coal-fired plants were designed to provide a steady output. Output changes in these plants happen relatively slowly and over a smaller range and frequent output changes can lead to wear and tear with attendant costs. These plants are low on flexibility. Newer “supercritical” coal-fired plants are by design more flexible and resilient than the older subcritical plants (PGCIL 2012: 120-124).

Currently, demand is typically assessed from load profiles from the past (previous day, same day previous week or year) which can give an indication of the load variations to be expected. Conventional generators are scheduled to match the expected load.

The intra-day variation in demand is addressed mainly by varying output of reservoir based hydro plants. Coal plants provide the “base load” and their output is varied only in a small range (PGCIL 2012:125). In recent years, this range has been expanding steadily indicating need for increasing balancing capacity (MoP 2016b: 28). The use of gas-fired plants in balancing has been discouraged by non-availability of gas and high price.

When there is insufficient supply, “load shedding” is resorted to. The Indian grid has hardly any storage capacity available as the need for storage solutions has not been acutely felt in the past.

Implications of renewable energy for balancing

The presence of solar energy generators on the grid makes balancing more challenging for several reasons. One is that electricity regulation in India incentivizes solar energy by conferring a “must run” status on solar generators; their entire output must be accepted into the grid. This makes solar power plants “inflexible” from a balancing standpoint.

A second is that solar power is variable. Solar power plants produce power only in daylight hours and their output varies with the movement of the sun, peaking at midday. Balancing now needs to be carried out for load as well as supply variability.

A third reason is that solar output is dependent on weather. Cloudy or foggy conditions lower output and introduce intermittency into the variations. The expected output under such conditions, obtained from models using weather forecasting data, has to be available sufficiently in advance to enable scheduling of conventional generators for balancing. Since weather is not entirely predictable, actual generation will show deviations from forecasts and these have to be handled in real time.

Wind mills are the other major source of renewable energy (RE) in the Indian context. Together with solar, they account for over 90% (160 GW) of the RE target for 2022. These plants also have a “must run” status and produce output that is variable and influenced by weather conditions. From a balancing perspective, they have issues similar to solar.

Balancing areas in India’s federal electricity setup

There is another dimension to balancing that derives from India’s federal electricity setup - electricity provisioning is a state government responsibility. Each state has to maintain the supply-demand balance in its own grid which becomes the “balancing area”. Access to balancing capacity commensurate with the RE capacity planned is required in each balancing area, that is, at the level of every state.

The RE potential of a state depends on various factors like the level of solar irradiation and wind conditions. Seven states – Tamil Nadu, Karnataka, Andhra Pradesh, Maharashtra, Gujarat, Madhya Pradesh and Rajasthan – are suitable for both wind and solar generation and account for 70% of the aggregate wind and solar capacity planned across India (MNRE 2016). These have been termed “RE rich” states.

As to generation, historically, states have had their own dedicated power plants or shares in the capacity of central public sector power plants. State distribution utilities procure a bulk of their power requirements (89% in 2011-12) through long term power purchase agreements (PPA’s) with these state owned plants and some private plants (NTPC 2012). The remaining comes from generators with ‘untied’ capacity that are either recently commissioned private plants that have not found long term customers or private plants operating as merchant producers.

Long term PPA’s pretty much fix the generation resources and balancing capacity in the portfolio of a state. They also come in the way of states pooling their balancing resources. A state looking for additional balancing capacity outside of its fixed portfolio has to find it from the limited pool of ‘untied’ generators.
For these reasons, there can be a wide mismatch between the balancing capacity in different states and the RE capacity planned for them.  

The experience of Tamil Nadu:

Tamil Nadu currently has the highest RE capacity penetration among all states with RE (largely from wind mills) accounting for 56% of its overall generation capacity. Its balancing capacity is inadequate for this level of penetration (GIZ 2015: 54, 63-65). Use of its limited reservoir-based hydro capacity for balancing is restricted by irrigation release schedules and periods of high inflows into reservoirs when hydro power generation cannot be curtailed. Neighbouring Karnataka and Telangana, which are part of the Southern Electricity Region, are rich in hydro power resources, but these are not available to Tamil Nadu. The state has no flexible gas-fired plants and limited flexibility available in its old coal-fired plants (CEA 2013:13).

Till early 2016, in the absence of capability for wind power forecasting, short term power purchases were planned after making assumptions about wind generation. If wind power generation was greater than expected, after exhausting its limited balancing options, the state utility would have only two options - either back down power from private coal plants contracted for short term power or cut off wind power plants from the grid.

Either option has been problematic for the utility - violating contract provisions in one case and not respecting the “must-run” status accorded to wind generators in the other. The dispute involving the state utility, coal-fired plants and the wind power producers is now in the courts (Vaitheeswaran 2015). Legal issues aside, there are negative economic consequences either way. Varying power from coal plants means underutilization of capacity and higher costs related to wear and tear. Backing down wind power means wasted energy.

2.    Preparations for RE

The central government’s massive RE targets require a commensurate increase in balancing capability at least in the RE rich states. Balancing resources can be augmented by dedicated transmission corridors distributing RE across states, grid storage and additional flexible generation – all long gestation infrastructure (PGCIL 2012:116). Besides resources, accurate forecasting of RE generation is essential for balancing. What follows is an assessment of the central government’s preparatory work in each of these areas.

Grid Storage

Pumped storage is not only the most widely deployed grid level energy storage technology, it also the most flexible and competitive one (GIZ 2015: 80). Pumped storage hydro electric plants store and generate electricity by moving water between reservoirs at two different heights. While India has a very limited capacity of operational pumped storage, the electricity establishment has identified a number of hydropower projects that can be developed to support pumped storage (CEA 2013: 39-43). The government however has just woken up to the need to identify concrete projects and there is talk of setting up 10GW of pumped storage (ET Bureau 2016).

Grid level battery storage technologies are evolving and in one estimate 3-8 times more expensive than pumped storage (GIZ 2015:80). There are several vested interests active in promoting these technologies including the US – India business council and the government seems to have fallen for the hype created around them. The public sector Solar Energy Corporation of India has put out tenders for solar capacity with storage components potentially driving up the cost of solar electricity (Clover 2016). The storage component is miniscule as of now and nowhere near the scale needed to be practically useful to the distribution companies (DISCOMS).

It seems that storage can be safely discounted as an option for balancing in the run up to 2022.

Forecasting and Dispersing RE

Renewable energy management centres (REMC’s) are to be set up in at least all the RE rich states with the responsibility for state wide forecasting of RE. The costs incurred in managing the uncertainty in predicting renewable generation will not be part of its purchase cost; these costs are to be “socialized” among grid users (CERC 2015). Till mid 2015, there was no centralized forecasting for renewable generation anywhere in India (GIZ 2015:60). Tamil Nadu has inaugurated its REMC recently (Srikanth 2016).

Transmission corridors (termed “Green Energy Corridors”) providing RE clusters in RE rich states access to neighbouring states were a part of the 12th plan. The corridors are under implementation with an enlarged scope to include connectivity to the "ultra mega solar parks" and will enable RE generators to disperse electricity in a wider geography with more balancing resources than available in the RE rich states (MoP 2016b:42).

Both the forecasting and transmission infrastructure are early work in progress and there is no visibility into when they will be ready.

Flexible generation

There is little chance of capacity addition in gas-fired thermal plants in the 2022 time frame with existing gas-fired plants running at partial capacity because of the cost of gas which has to be imported. Hydro power projects totalling over 12 GW are under construction (CEA 2015). Possibly less than half of this capacity will be amenable to flexible use. Most projects are many years behind schedule because of environmental related standoffs and opposition from local populations.

Old coal-fired plants can be made more flexible through retro-fitting. This will require capital expenditure and there are no signs that governments (who own most of these plants) are seriously considering this option. A total of 73 GW of coal capacity is under construction of which supercritical plants account for 50 GW (CEA 2016, MoEFCC 2015:72).

One can conclude that coal-fired plants, in particular super-critical ones, will be the mainstay of RE balancing. With conventional capacity addition far lower than planned RE capacity addition (of 130 GW), India’s overall “balancing potential” – the ratio of balancing capacity to RE capacity – is set to decrease in the run up to 2022.

Market for balancing capacity

The mere existence of flexibility in generation will not translate to flexible operations as the later has negative financial implications for the operator. For instance, in the case of coal-fired plants, these are due to wear and tear reducing the life of the plant, higher maintenance costs and costs associated with capacity underutilization and lower efficiency. The government is therefore moving to incentivize flexible operations. There is already a regulation to compensate generators for holding capacity in reserve for responding to grid management requests in real time. A framework for market based pricing for balancing capacity is just down the line.

Will market based incentives solve the problem of making adequate balancing capacity available in the RE rich states?

There are some constraints. Firstly, the generation capacity available in the electricity market untied to PPA’s is currently limited, though it is slated to rise with the commissioning of new plants. Secondly, inter-regional transmission constraints can come in the way of RE rich states using flexible capacity from regions other than their own.

The later problem is illustrated by the Southern Electricity Region which has been facing a generation capacity deficit for several years. Coal-fired generators in the Western Electricity region are unable to provide power to the Southern Region because of transmission bottlenecks and their capacity lies underutilized. Market based pricing for electricity has not solved the problem of electricity deficit in the southern region in five years; electricity prices at the Indian Electricity Exchange have remained significantly higher for the southern region compared to the western region from 2011 onwards (Kasturi 2016:24).

Two years after announcing massive RE targets, the government still does not have an assessment of the actual balancing capacity available with the RE rich states or how this will grow in future! It appears to believe that the market for balancing capacity will somehow solve all problems.

3.    The real cost of solar

State utilities are generally strained financially and will not be keen to purchase RE as long as it is relatively expensive. To make RE more attractive, the central government has worked out ways of subsidizing it at the cost of public sector companies in the power or fuel sector. Inter-state transmission charges for solar electricity have been waived at the cost of the PGCIL.

NTPC contracts for solar power from producers and sells it to DISCOMS after subsidizing it in the following way. It “bundles” solar power with low cost power from its coal-fired plants and offers utilities power at a rate which is lower than its purchase price for solar electricity (Upadhyay 2015). This bundled price has to approach “grid parity” – the average price of electricity contracted by utilities - for NTPC to be able to find willing buyers.

Of course, even if solar prices reach grid parity it does not mean that solar has become cost effective compared to other sources of energy. The cost of balancing variability in generation through flexible capacity held in reserve must also be attributed to solar power. To this must also be added the cost of infrastructure for forecasting RE and the costs arising from errors in forecasting. The government has not even hazarded a guess at these costs yet.

As subsidies alone are not enough to make solar power attractive, the government has also taken recourse to coercion. The new tariff policy calls for high RE purchase obligations for DISCOMS with the target for solar alone being 8% of non-hydro power consumed by every utility by 2022 (MoP 2016a). To make sure that states comply with the RPO targets, such compliance has been made part of the conditions associated with the ‘Ujwal Discom Assurance Yojana’ (UDAY) that provides relief to indebted state DISCOMS (GOI, 2015b).

Negative consequences of force feeding RE

Forcing DISCOMS to absorb RE beyond their ability to handle it will have consequences for the health of the DISCOMS and the cost and quality of electricity supply. A key assumption behind UDAY is that power costs will come down with lower cost of coal and help DISCOM finances. Rapid solar penetration will push up the cost of power.

Utilities are already hard put to handle load variation even today. They lack accurate load forecasting, flexibility in conventional generation, balancing resources such as pumped storage and generation reserves to handle different eventualities on the grid (MoP 2016b: 11). For customers, this has meant a regime of poor quality and unscheduled power cuts. With high RE penetration and an expected further deterioration in balancing potential, this regime is bound to continue in to the future. The government is also preparing to use demand curtailment curtail for balancing by pushing for large scale installation of smart meters that will allow setting time-of-day tariff (MoP, 2016a).

Public interest will be better served if the pace of solar (and wind) capacity build up is compatible with the balancing capacity available with the states and their ability to manage RE variability. The government must pay as much attention to capacity building in inter-regional transmission, pumped storage and highly flexible generation as it is doing to solar generation.

Renewable energy targets based on these considerations rather than impetuous declarations will be sustainable and allow steady decrease of carbon emissions. A slower adoption of solar generation will be beneficial for yet another reason - solar power, as long term trends suggest, will only get cheaper with time.


CEA (2013): “Large scale grid integration of renewable energy sources - Way forward”, Central Electricity Authority, November,

-  (2015): “Hydro electric projects under execution”, Central Electricity Authority, November,

-  (2016): “Monthly report on broad status of thermal projects in the country”, Central Electricity Authority, July,

CERC (2015): “Framework on Forecasting, Scheduling and Imbalance Handling for Variable Renewable Energy Sources (Wind and Solar): Statement of Reasons”, Central Electricity Regulatory Commission,

Clover, Ian (2016): “India: storage to be included in 100 MW tranche of Andhra Pradesh 750 MW solar tender”, PV Magazine, 15 March,

ET Bureau (2016): “India readies plan to improve renewable power storage”, Economic Times, 22 August,

GIZ (2015): “Report on Forecasting, Concept of Renewable Energy Management Centres and Grid Balancing”, Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) 

GOI (2015a): “Revision of cumulative targets under National Solar Mission from 20,000 MW by 2021-22 to 100000 MW”, Government of India, 17 June,

GOI (2015b): “UDAY (Ujwal DISCOM Assurance Yojana) for financial turnaround of Power Distribution Companies”, Government of India, 5 November,

Kasturi, Kannan (2016): “Private Thermal Power in a Liberal Policy Regime”, Economic & Political weekly, Vol 51, No 10, pp 22-26

Kenning Tom (2015): “India’s cutthroat solar auctions – behind the hype”, PVTECH, 22 Dec,

MNRE (2016): “Tentative State wise break-up of Renewable Power target to be achieved by the year 2022 so that cumulative achievement is 175000 MW”, Ministry of New and Renewable Energy, (Sept 21, 2016)

MoEFCC (2015): “First Biennial Update Report to the United Nations Framework Convention on Climate Change”, Ministry of Environment, Forest and Climate Change, December,

MoP (2014): “Perspective Transmission Plan for twenty years (2014-2034)”, Ministry of Power, August,

MoP (2016a): “Resolution, Tariff Policy”, Ministry of Power, Gazette of India, 28 January

MoP (2016b): “Report of the Technical Committee on Large Scale Integration of Renewable energy, Need for Balancing, Deviation Settlement Mechanism and associated issues”, Ministry of Power, April,

NTPC (2012): “Annual Report, 2011-12”, National Thermal Power Corporation,

PGCIL (2012): “Transmission Plan for Envisaged Renewable Capacity, Vol 1”, Power Grid Corporation of India Limited, July,

Singh, Sarita (2016): “Power demand may be lower by 15% for five years starting FY18”, The Economic Times, 25 Apr,

Srikanth, R (2016): “Tangedco sets up centre to tap renewable energy”, The Hindu, 26 March,

Tongia, Rahul (2016): “India’s Updated (2016) Renewable Energy ‘Guidelines’: Bold targets, but can we meet them?”, Brookings India IMPACT Series, No. 082016-2.0

Upadhyay, Anindya (2015): “India's Modi Tells Coal Power Plants to Subsidize Solar”, Bloomberg, 7 September,

Vaitheesvaran, Bharani (2015): “Wind or conventional power? Tamil Nadu power producers battle it out in court”, The Economic Times, 26 August,


India's outdated electricity grid needs major upgrade says expert