A method in madness: An integrated approach to Case 1 and Case 2 bidding Yasir Altaf and Amit Sharma
The article examines the development prospects and future potential of Case 1 and Case 2 bidding within an integrated power market approach. The article identifies the key components and structural concepts that comprise the bidding and should form the basis of an intelligent decision making process. The article also explores how market trends and infrastructure bottlenecks are influencing the development of bidding and identifies how bidding can be integrated into the system. It also provides an estimate of capacity allocations under Case 1 and Case 2 development and compares how buyers and sellers should position themselves in response to the recent trends.
The Indian power sector is in a state of rapid flux with both buyers and sellers of electricity struggling with uncertainty around decision making. The stakeholders warrant an objective view about understanding how current trends in regulation, economics and markets create unwanted risks and influence the decision making process. Earlier, a developer had an option to enter into long term PPA with discoms under cost plus tariff norms. With the 2006 amendment to the National Tariff Policy (NTP), all future power requirements are to be met compulsorily through bidding route for private players. As a result of this a large number of thermal plants announced by private sector have little knowledge about the perspective buyers and a competitive sales strategy. In this scenario, application for an integrated power market analysis seems limitless. A comprehensive power market analysis can facilitate this assessment and can be seamlessly extended to procurement of power under a competitive bidding process. Both buyers and sellers of electricity can build bidding strategies around a baseline forecast of future market conditions and test alternative scenarios to understand the strategic implications. As per the NTP guidelines, procurement of power can be through the following two mechanisms: •
Case 1: General bid for power where location, technology or fuel is not specified.
•
Case 2: Location specific projects where government assists the developer in securing land, clearances, fuel etc.
In case of competitively bid project, a long-term PPA is signed between the discom and the wining bidder, who offers the lowest levelized tariff. Hence, private players are compelled to offer competitive tariff quotes. This would bring clear benefits to the system such as increased transparency, more choice, competition, efficiency and reduced risk. However, a private developer at the same time has to consider potential negative consequences that competitive bidding may introduce. The inherent risk profile of competitively bid projects exceeds those with traditional cost-plus tariff structures. Even though there may be a technical pre-qualification process, the emphasis on transparency and public accountability is likely to favor projects that simply offer the lowest prices. It may be difficult for the government to accept projects that are more robust over
the longer-term but not the lowest cost. Lastly, a private player would have to wait till a particular state decides to invite tender for its power procurement. It is only after the tender is floated that they can bid and once bids are finalized, financial closure can be facilitated and plants set up. Last few years have seen tremendous response from private sector to the creation of generation capacities under various initiatives and routes (i) Case 1 e.g. Procurement bids by distribution utilities (ii) Case 2 e.g. Ultra Mega Power Project (UMPP) bidding, and (iii) Creation of merchant capacities and power trading. Table 1: Bidding outcomes for Case 2 State
Plant Name
Capacity (MW)
Bid (Rs/kWh)
Winner
Bara
1,980
3.02000
JP Associates
Madhya Pradesh
Sasan
4,000
1.19616
Reliance Power
Gujarat
Mudra
4,000
2.26367
Tata Power
Krishnapattam
4,000
2.33296
Reliance Power
Tiliaya
4,000
1.77000
Reliance Power
Uttar Pradesh
Andhra Pradesh Jharkhand Haryana
Jhajjar
1,320
2.99600
CLP
Talwandi Sabo
1,200
2.86400
Sterlite Energy Limited
Chhattisgarh
Bhaiyathan
1,600
0.81000
India Bulls Power Generation
Uttar Pradesh
Karchana
1,320
2.97000
JP Associates
Maharashtra
Dhopave
1,600
3.66000
Lanco Infratech
Punjab
Reliance Power’s Sasan with a levelised tariff of 1.19616 Rs/kWh and later on India Bulls Bhaiyathan with a tariff of 0.81 Rs/kWh created the lowest ever benchmarks under Case 2 category. With PPA’s being signed at such aggressive tariffs which are well below the cost of generation or maybe even irrational, the strategy adopted by the developers is to cover up through merchant sales apart from vertical integration in terms of taking over captive mines. In some cases, the risks are being passed on to the public (IPO investors), since the private sector initiatives are being well supported by the capital markets with the risk capital being provided in the form of IPOs and private equity. Gujarat was the first state to formalize power purchase agreements under the Case 1 route and has so far tied up 3,200 MW of power capacity under long term purchase agreements, making it the highest in India by any state under this category. Gujarat has been able to get very competitive rates - 2.35 Rs/kWh (Adani Power), 2.40 Rs/kWh (Essar Power) and 2.25 Rs/kWh (Aryan Coal) in its power procurement drive. It has now sought to procure another 3,000 MW (±20 percent) on long-term basis.
Table 2: Bidding outcomes for Case 1 State
Capacity (MW)
Bid (Rs/kWh)
Winner
Gujarat
1,000
2.34950
Adani Power Pvt. Ltd
Gujarat
1,000
2.89000
Adani Power Pvt. Ltd
Gujarat
1,000
2.40060
Essar Power Ltd
Gujarat
200
2.24980
Aryan Power Ltd
Madhya Pradesh
660
2.34000
Lanco
Madhya Pradesh
1,241
2.64000
Reliance Power
Haryana
300
2.86000
GMR
Haryana
1,424
2.96000
Adani Power Pvt. Ltd
Maharashtra
2x660
2.64000
Adani Power Pvt. Ltd
Maharashtra
1X600
2.70000
Lanco Kondapalli Power Ltd
Some other states such as Haryana, Madhya Pradesh, Maharashtra, Punjab, Rajasthan and Uttar Pradesh are also in the process of concluding similar agreements. However, some other states such as West Bengal have been less enthusiastic in allowing private sector to set up generation capacities despite having energy resources. Inspite of all this, the general theme of competitive bidding has advanced in the past one year with some concrete examples visible on ground to substantiate it. Going forward, with the inclusion of Hydro and CPSU, Case 1 and Case 2 bidding is expected to manifest on a much wider scale 1 . A quick comparison shows that the tariff bid and hence return would be usually lower in Case 2 vis-à-vis the Case 1 bidding. Further, under Case 1, the developer is free to sell power above the portion contracted with discoms in the merchant market and hence the return upsides could be higher. Under Case 2, typically, the discom procures the entire power generated from the plant. In order to incentivise developers, even under Case 2, several states such as Chattisgarh and UP, have allowed the L1 bidder to sell a defined portion of the capacity as merchant power. The returns in Case 2 depend upon the bidding strategy adopted by the developer and upsides are by way of capital cost efficiencies, shorter construction periods, right project structuring, right EPC price, competitive financing terms etc. To date, tariffs established through competitive bids are far lower than short term tariffs. Apart from Case 1 and Case 2, the other options for private developers is that of selling in the merchant market by entering into short term PPAs with traders, discoms and end-customers or through power exchanges. In the short to medium term with supply more or less stagnant the returns for pure merchant power plants are expected to be significantly higher than the long-term supply agreements. The other factor for the peak power or short-term merchant power to be expensive in the short term has been attributed to uncertainty of capacity utilization and need to recover capital costs over a shorter period of time. 1
The Central Power Sector Utilities (CPSU) and states are exempted from bidding till 2011 or alternately to a time frame when the regulatory commission assumes that the situation is ripe for competitive bidding.
12.0
3,000
10.0
2,500
8.0
2,000
6.0
1,500
4.0
1,000
2.0
500
0.0
0 Aug Sep Oct
Nov Dec Jan Feb Mar Apr May Jun
Volume (MU)
Price (Rs/kWh)
Figure 1: Volume and Average Price of traded power for the period Apr ’08 - Jul ’09
Jul
Bilateral Trade (MU)
UI (MU)
P Ex. (MU)
Bilateral Trade Price
P Ex. Price
UI Price
The magnitude of the price wedge is apparent from the weighted average shortterm power price of 7.24 Rs/kWh (Apr ’08 –Jul ‘09) and the levelized tariff quoted by various bidders for coal linkage projects on long term basis to state electricity boards (SEBs) of 2.5 – 3.5 Rs/kWh. But for the load shedding, the short term and peaking power would have been even more costlier. Peaking power price being available on energy only is expected to be high, however round the clock high price of traded power is clear indication of inadequate capacity contracting by the utilities. Thus, the higher short and merchant returns have attracted the private developers to setup both peak and base load plants as merchant plants or alternately, have initiated the current trend of reserving a part of the power plant capacity for merchant transactions. In this scenario, any flawed strategy adopted by the buyers or sellers can negate the advantages. Therefore developers warrant a sales strategy (i.e. an optimum mix of long term, medium term and merchant sale) and distribution utilities an advance planning of generation mix for their power purchases (i.e. procurement under long term and short term). In order to achieve these twin objectives, the key is to have a firm view on short, medium and long term power prices (both peak and off-peak conditions). The power prices in the foreseeable future are expected to be largely driven by how demand – supply equation (forecasted electricity & latent demand, shortages etc.), capacity additions, transmission expansion, fuel availability and prices, environmental concerns, paying capacity of discoms and policy and regulatory developments shape up. But the pressure one parameter has been exerting on the other and the current uncertainty makes it difficult to take any stance on the prices and hence a bid that is appropriate. The fundamental requirement for successful bidding is therefore an integrated market approach with careful consideration of the multiplicity of the above factors and how they are affecting the power markets. Such a proposition would assist both buyers and sellers of electricity in making the choices between types of generation and fuel in a systematic and transparent manner. This would address the concerns of most of the developers and utilities that continue to struggle in
arriving at an efficient price discovery and least cost capacity additions and power procurement. In this scenario, an integrated power market approach with a view on long term horizon would help decision makers in formulating their long term strategies. One such model (refer box 1) uses an integrated power market analysis process to arrive at a comprehensive view on how the capacity additions and power prices could evolve from the today’s starting point. Different risks can then be weighed by adopting a scenario based analysis that would help in valuing each and every risk. This robust methodical analysis would help in framing structured strategy for bidders and power procurers. The power prices and capacity additions for the state of Maharashtra using the model are shown below. The assumption used here are very specific to this case. 8,000
25
7,000
MW
5,000
15
4,000 10
3,000 2,000
GWh
20
6,000
5
1,000 0
0 2012
2013
2014
2015
Case 1 (MW)
2016
2017
Case 2 (MW)
2018
2019
2020
2021
Short term trading (GWh)
Figure 1: Illustrative estimated Case 1 and Case 2 capacity additions for Maharashtra over the period 2012 – 21 using I-IPM® 14 12 Rs/KWh
10 8 6 4 2 0 2009
.
2010
2011
2012
2013
2014 RTC
2015 Peak
2016
2017
2018
2019
2020
2021
Off ‐ Peak
Figure 2: Illustrative forecasted Peak, Off-peak and Round the Clock (RTC) power prices for Maharashtra for the period 2012 – 21 using I-IPM®
The main objective of this type of model is to minimize the long run marginal costs of energy services while balancing the interests of all the stakeholders. Thus the most cost effective among an array of various capacity types and additions can be identified with the cost of generation being compared on a level
playing field. Any capacity additions whether Case 1 or Case 2 would be recommended only if cost is less than or equal to other competing alternatives. Thus the decision regarding the best ways to bridge the supply demand gap by providing rational choices among alternatives (Case 1 and Case 2 additions and merchant power) by a particular state can be forecasted. The end result is a market perspective that delivers a detailed, integrated, consistent and transparent set of medium and long term projections on power prices, Case 1 and Case 2 capacity additions, transmission and fuel resource optimization. Box 1: India - Integrated Planning Model (I-IPM®) India - Integrated Planning Model (I-IPM®) is a detailed bottom up dynamic linear programming model. It takes an integrated view across generation, transmission, fuel and emissions markets along with other system constraints and solves all parameters in an integrated manner. The model typically captures a planning horizon spanning 25 years.
I-IPM® is backed by an extensive database representing the Indian power sector comprising of all the existing and potential – power plants, transmission lines, fuel sources and linkages. The model is anchored by an integrated simulation engine which is used to prepare a long term view on the Indian power markets. The data sources in the model are ably supplemented with expert views on a number of market drivers. From a top down perspective, the current state of the power market at state and regional levels is assessed to determine the impact on the wholesale markets and future power prices. Utilizing model inputs as diverse as power plant capital costs, total transmission capability (TTC), environmental issues, regulatory policy, fuel supply and developmental costs, and projected gas pipeline expansions etc, the capacity additions and power prices can be forecasted over short, medium and long term.
