Catalyzing emerging business models through STAKEHOLDER ENGAGEMENT | CONSULTING | RESEARCH OCTOBER 2012 Input-Based Power Distribution Franchisee Market In India This document contains information and data that pManifold considers confidential. Any disclosure of Confidential Information to, or use of it by any other party, will be damaging to pManifold. Ownership of all Confidential Information, no matter in what media it resides, remains with pManifold.
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Catalyzing emerging business models through
STAKEHOLDER ENGAGEMENT | CONSULTING | RESEARCH
OCTOBER 2012
Input-Based Power Distribution Franchisee
Market In India
This document contains information and data that pManifold considers confidential. Any disclosure of Confidential Information to, or use of it by anyother party, will be damaging to pManifold. Ownership of all Confidential Information, no matter in what media it resides, remains with pManifold.
– Comparative Review of RFPs, Bidder Preferences & Outlook
• Analysis of Bids in Maharashtra
– Connections And Asset Information From RFPs
– Customer Segmentation
– Winning Bid Comparison
– Projected Contribution Of Winning Bid to Utility
• Analysis of Bids in Madhya Pradesh
– Bids Quick Characterization
– Attractiveness Matrix
– Connections And Asset Information From RFPs
– Customer Segmentation
– Winning Bid Comparison
• Analysis of Bids in Jharkhand & SAIL
– Connections And Asset Information From RFPs
– Customer Segmentation
• SAIL Distribution Franchisee bids – 4 Townships
• IBDF Investment Model
– Base Case (Input) - Key Assumptions
– Base Case (Input) - Bid Price and Loss Reduction Trajectories
– Base Case (Input) - Capex Assumption
– Base Case (Output) - Estimated Returns
– Case 1: Sensitivity of Equity IRR to Levelized Input Price
– Case 2: Sensitivity of Equity IRR to Capex
– Case 3: Sensitivity of Equity IRR to Opex
– Case 4: Sensitivity of Equity IRR to Tariff Growth Rate
– Case 5: Sensitivity of Equity IRR to Load Growth Rate
– Case 6: Sensitivity of Equity IRR to Input price shape/curve
• Case Studies
– IBDF Case Study 1: Torrent Power Ltd. (TPL) @ Bhiwandi
• Comparison of Torrent Power at Agra and Bhiwandi by Reuters
– IBDF Case Study 2: SPANCO @ Nagpur
• Conclusions
• References
• Appendix
– 255 towns suggested by Shunglu Report for IBDF implementation
– List of Unbundled States in India (in Chronological Order)
– List of Pilot Smart Grid Projects
– Lists & Links of Distribution Companies, SEB’s in India
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• Missing information on DISCOM asset & real performance (cost & revenue) has challenged creation of good baseline date and basing improved design & structuring of win-win IBDF contract, both for DISCOM and private operator. The resulting bid process delays & litigations has slowed down uptake. (More the delays, more the losses)• Evolving electricity market structure, its commoditization (pricing, trading), distributed generation etc. has created uncertainties to firm long term standing and exit options of the IBDF model.
• DISCOMs in India are facing huge burden of approx Rs. 1,00,000 Cr. fiscal deficit, avg. 13% peak shortage in supply and high avg. 28+% AT&C losses. • While privatization is perceived to improve DISCOM overall financial conditions and improve reliability & customer services, a search for scalable model continues through various pilots. • Input Based Distribution Franchisee (IBDF) is an emerging model with its core foundation in Energy Efficiency (EE) and has potential to address this problem. (Focus of this Research study)
• Power Distribution Infra & services, because of its B2C characteristics and regular cash flows has attracted almost all major Power sector corporate, and also other big and medium size Technology Infra, IT, Telecom, Media companies. Competition is further expected to increase. •The current growth phase will attract many new players from cross-sectors, bringing best practices and innovation in the DF market. More pilots with gestation of 1-2 yrs. will start consolidation at urban level. A further big rural market will continue accommodating new players.
• Currently, 8 Indian cities have distribution of electricity through ‘Input Based Distribution Franchisee’ model, including 3 new contracts that have been awarded recently and are in the handover phase in Madhya Pradesh. The overall market confidence on DF model is low mainly because of reported contractual non-performance at Nagpur & Aurangabad DFs, and slow progress on Agra. inspite operated by experienced co. like Torrent• The Shunglu Committee recommended another 255 cities to be privatized in next 5 years to improve the financial stability of power distribution companies of the country, indicating the growth and opportunity in the DF market. Market size from AT&C loss reduction is Rs. 55K cr. per yr.
Executive Summary
Market
Problem
Challenges
Regulations
Competition
• IBDF is a leasing model, wherein DISCOM lease its assets to DF, and DF takes care of all O&M. In this role, the Regulatory structure continues to be the same (in favor of IBDF model), with DISCOM doing all liasoning, including Tariff petition. • A more accessible Regulator, clear & measurable Standards of Performance (SOPs) and independent performance and customer monitoring for DF will create good governance, which will be key to scaling IBDF model.
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None Difficulty level of Privatization Highest
Parameters SEBs DISCOM R-APDRP enabled DISCOM Distribution Franchisee (Input based DF)
Full Privatization Model
Operational Model
Bundled StateUtility with generation, transmission and distribution
State companies that handle the distribution function only post unbundling
Central funded loans to DISCOMs with part conversion to grants based on performancePART A: IT enabled baseliningPART B: Distribution systemstrengthening
Fixed input price power purchase from DISCOM, Capex investments, O&M, improve metering, billing, collections, reduce AT&C loss
In addition to DF responsibilities, also does own power procurement & management, file ARR and tariff petition
Number of deployments (operational)
3 SEBs still unbundled Kerala, Jharkhand and Bihar
Currently, 37 Discomsfunctioningindependently and 6 state power depts.
PART – A: 1400 towns across 47 discoms in 29 states PART – B: 1240 towns eligible.
• PSU organizational constraints, and poor management• Financial constraints to continue investing in network to match growing loads
• Non-ownership of reforms by utilities with missing incentives• Missing Change Management and capacity building with utility for effective benefit realization.
• Non ownership of assets, leads to problems with securitisation and hence funds procurement by DF operator• High dependence on Distribution Licensee for initial operational support and regular regulatory liaising.
• Revaluation of assets for transfer of ownership• Hike in tariffs because of new procured capital assets. Necessitates high govt. subsidy to avoid big tariff hike.• Low political will.• Lack of govt. (or low cost) funds
Operating Models in use to turnaround loss making Utilities
Trends • 5 Operational IBDF models in last 5 years (2007-
2012) across 2 states. 3 new contracts recently signed in MP, and currently in handover phase.
• Maturity of model is still building with most new players into their first year of operations only.
• 2 years gestation for new state utility to pilot and accept IBDF model’s applicability, and to really get ready to scale it
• Progressive increasing winning bid prices is indication of evolving market correction, that favors DISCOM’s expedited IBDF takeup
• Shunglu committee has recommended IBDF model for 255 R-APDRP Phase-A (urban) towns (including their peripherals) in the 12th Five Year Plan (2012-2017)
– These towns have either input energy more than 100MUs or more than 3 lakh human population
– They together contribute 22% out of overall 40% consumption in 1400 growing towns
– With already invested investments, there exist better IT systems to collect baseline information to build viable business case for IBDF.
– Shunglu committee made recommendations to give bail out package to utilities, only when they would have executed their targeted IBDF numbers
Future Projections
1226
55
119
255
0
50
100
150
200
250
300
2012-13 2013-14 2014-15 2015-16 2016-17
Projected uptake of IBDF projects
• Various states had proposed to adopt the franchisee model –including MadhyaPradesh, Haryana, Chhattisgarh, Jharkhand, Rajasthan, Bihar, etc.
• Optimistic scenario: 100+% CAGR to meet targets of 255 IBDFs in next 5 years (potential 12 new IBDFs in 2012-13)
• Conservative scenario: A study conducted by CRISIL Research in July 2011 expects IBDF in 20 circles (concentrated primarily in MS, UP and MP) over the next 3 years entailing an investment opportunity of Rs. 140-170 billion
Source: pManifold Analysis based on qualitative review of market progression and literature, 2012
For Discom (DL)
• Dilution of identity
• Business discontinuity from non-performance of DF operator and in-between termination
• Difficulties in WCM with delayed payments from DF, slow cycle of tariff revisions, and continuing increasing fuel/electricity price
• Mis-handling of measurements and records by DF
• Any mis-treatment (or its perception) of DL deputed employees with DF, leading to aggression
• DFA and/or Regulatory non-compliance by DF, including in-sufficient capex investment, non-meeting AT&C loss reduction targets etc.
• DFA does not have any amendment provision to address any future corrections.
For Franchisee (DF)
• Incomplete, missing or wrong baseline information, that lead to high input price bid
• Non ownership of assets, leads to problems with securitisation and hence finding investors
• Non co-operation from DL –employees deputation, power procurement, asset & stock sharing, regulator liasoning, capex approval etc.
• Load growth faster than expected and/or DL not able to supply & meet the demand
• Non-payment of terminal depreciated value by DL
• Any Force majeure that affects asset, load & customer mix
• Misled customer /employee agitations. Ex. Attributing power hike to DF privatization.
• Non-flexibility of DFA to address any new uncertainty and associated arbitration delays, if any
For End Consumers
• Initial non-performance from new learning players
• In-accurate metering and billing
• Addition of new service charges
• Strong enforcement against theft, recovery, etc.
• DF not incentivized to help customer save energy
IBDF Model Risks
Key emerging risks for different stakeholders in DF model
Risks
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Comparative Review of RFPs, Bidder Preferences & Outlook
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Parameters Bhiwandi (MS)
Agra(UP)
Aurangabad(MS)
Nagpur(MS)
Jalgaon(MS)
Gwalior(MP)*
Remarks / Recommendations
Contract Period (long contracts preferred by bidders) ◔ ◕ ◑ ◑ ◔ ◑ DF contract tenure has increased from 10 - 20, with most new tenders settling for
15 years. Bidders favor 20 years to meet their reform commitment better.
Asset Health in RFP Baseline (Ageing, Transformer Failure Rate, etc.)
◌ ◌ ◌ ◌ ◌ ◑ RFP baseline needs to further improve with all critical assets details, ageing, R&M cycles, make etc. to allow bidders to develop rational capex plan.
Revenue & Customer Segmentation (Absolute Number & Time Trend)
◔ ◕ ◑ ◑ ◑ ◕ RFP baseline should share detailed customer segmentation - meter types, numbers, consumption, arrears (Live & PD), subsidy, payment, complaints etc.
Performance Guarantee (Inclusion of Electricity Duty) ◌ ◌ ◌ ◌ ◌ ◔ DISCOM's risk is better covered, by adding few months ED towards performance
guarantee.
Minimum Benchmark curve for Price Bid (No benchmark is favored by bidders
◑ ◌ ◌ ◌ ◌ ◑ Setting no min. benchmark curve will allow bidders to be innovative in their price bid structuring. DISCOM should instead share their calculations for viability.
Higher arrear recovery sharing works as good incentive for bidders. Ageing data will allow better analysis if to extend incentive time period to 2-3 yrs. There is risk of public agitation, if arrear recovery is taken up immediately on DF handover.
Deputed Employees Terminal Liability Payment by DF (sharing with DF is fair)
◌ ◌ ◌ ◌ ◌ ◑Sharing part responsibility of deputed employee's terminal liabilities (gratuity/pension) with DF, till service used, is supportive to DISCOM business case for DF (lower HR and O&M costs).
Mandated AT&C Loss Reduction Trajectory (No trajectory is preferred by DF)
◌ ◕ ◕ ◕ ◕ ◌A bulk target of reducing AT&C losses to say 13% in 10 yrs. has higher chances of success over year wise targets and associated penalties. Ground conditions and engaging locals could take good time.
Penalties for Non Achievement of Loss Reduction Targets (Lower is better with bidder)
◔ ◔ ● ● ● ◑ Keeping low penalties and extreme targets could not guarantee compliance. Increased co-creation and sharing between bidders will yield better contract.
Treatment of Subsidy (Bid Price to include subsidy retention by DL. Likely more preferred by DF)
◑ ◑ ◑ ◑ ◑ ◕There is risk for subsidy collection from Govt. and DISCOMs are suffering from it already. The risk is better mitigated with bidder costing it in the bid price itself. (Ideally, subsidy could go away with strong delivery)
Payment of Electricity Duty by DF (Payment Frequency) ◕ ◕ ◕ ◕ ◕ ◑ Allowing ED to be paid in say 6 months could give DF working capital, over paying it
every month. This could incentivize DF.
Quality of supply, SOP, Customer Satisfaction (KPIs & Targets defined in RFP)
◌ ◌ ◌ ◌ ◌ ◑Some core objectives of DF are PQR, customer satisfaction, and most RFPs do not have any metrics to measure and hence set targets & ask focused capex. MP policy makers have made a good start.
Terminal Option to DF (longer visibility preferred by DF) ◌ ◌ ◌ ◌ ◌ ◌ Option like DF extension, conversion to full privatization model, all Buy-out, Exit
etc. needs to be given detailed thoughts, in light of changing electricity market.
◌ Below Average ◔ Average ◑ Good ◕ Very Good ● ExcellentSource: pManifold Analysis * Ujjain and Sagar RFP is same as Gwalior
ANALYSIS OF BIDS IN MADHYA PRADESH
Gwalior, Ujjain and Sagar
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MP Bids Quick Characterization
Volume vs. Opportunity from ATC reduction vs. Risks
All Base assumptions and changing the price bid curve only
• Uniform growth rate:– The price bid is assumed to grow linearly at one rate– It usually has a high start & high end.
• Variable growth rate:– This has lower bid price start– High growth rate in initial 3-4 years. Then lower growth
rate.
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