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CER aggregation – Opportunities and Risks

CER aggregation – Opportunities and Risks March 2006 Background Market situation More than 3.6 million CER’s registered (Source: UNFCCC) Of the 93 CDM projects registered, 23 are from India* Almost 50% of projects in the pipeline are from India*

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CER aggregation – Opportunities and Risks

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  1. CER aggregation – Opportunities and Risks March 2006

  2. Background

  3. Market situation • More than 3.6 million CER’s registered (Source: UNFCCC) • Of the 93 CDM projects registered, 23 are from India* • Almost 50% of projects in the pipeline are from India* • India consistently ranked no.1 on CDM country ranking for the past year (Source: Point Carbon) *Source: CD4CDM.org analysis, Feb 2006

  4. Power Generation Industry Transport India’s potential • Over 75% of India’s CDM potential lies in the energy sector Source: TERI National Strategy Study 2004

  5. Market Players – Buyers • End Users • Energy Utilities (Shell, BP) • Industries (Steel, Small scale users) • Cross Border Funds • PCF (World Bank) • Nation funds (Japan Carbon Fund, Danish Carbon Fund) • Private funds • Banks (BNP, AXA) • Carbon funds (EcoInvest, Trading Plc. Etc) • Aggregators • Consultants (Ecosecurities, Agrienergy etc.) • Trading agencies (Mitsui etc.)

  6. CER Pricing • Difficult to gauge demand as information is closely guarded • Currently a sellers market but sellers unable to utilize market position • CER pricing pushed down by creating a high risk profile for projects originating out of India • Buyers take advantage of fragmented sellers

  7. Market Aggregation

  8. Market Makers - Current • Market fragmentation and lack of risk mitigation drives down prices Cross Border Funds Sellers End Users Project Owners Private Funds CER Prices

  9. Market Makers - Proposed • Higher volume results in better price negotiation and results in increase in prices Cross Border Funds Sellers Seller Side Aggregators End Users Project Owners Private Funds CER Prices

  10. Value Proposition • Risk mitigation • In case of non-delivery of CER’s a safety margin of total CER’s (around 20%) caters to defaults • Larger geographical and sectoral spreads (multiple renewable types, across geographies) reduces project risks • Price Consolidation • Larger volumes command larger pricing; better negotiation power • Market movement • In case of upward price movement, further sale can be initiated from existing CER reserves

  11. Value Proposition • Aggregator provides access to reputed buyers • Aggregator will have the scale to provide access to genuine buyers • Making smaller CDM projects viable • Smaller CDM projects (<15,000 CER) generally have difficulty finding buyers, due to high transaction cost at buyer side • Being part of aggregate makes these projects viable • Aggregator helps develop the CER market • Aggregation attracts sellers with attractive pricing and lower administrative hassles for project owners

  12. Aggregation - Approach • Aggregation approach • Sharing Validation cost • Validation costs can be brought down due to volumes • Project Participant for Aggregator • Aggregator becomes a Project Participant to reduce its project risk. Project participant status helps reduce chances of disputes in case of withdrawal from aggregation • Subsidizing Registration cost • Registration cost can be partially met by aggregator; zero risk investment for aggregator

  13. Aggregation – Sale Strategy • CER sale strategy (long term view) • Buyers based on prices • Select multiple buyer based on geographical demands. Some regions have higher demands • Regulations • Some regions have stiffer penalty requirements. Utilize for more effective pricing • Seasonal Demand • Harsh winters give rise to higher energy demand – more energy output – more GHG emissions – Higher CER demand

  14. Risks and Returns

  15. Aggregation Risks • Project Registration rate is lower than expected (assumed at 75%) • Mitigation 1: Spread projects across multiple sectors like mini hydro, wind, bio mass • Mitigation 2: Spread projects across geographies within and outside India • CER price does not rise as expected • Mitigation 1: Sell only a % of aggregated CER, banking the rest for potential rise later • Mitigation 2: Identify buyers based on demand; driven by regulations, seasonal demand change etc.

  16. Revenue Model • Cost • Administration cost for local and overseas office • Cost is more time related than cash flow • Revenue • Fixed margin. aggregator charges a fixed margin (for example 3%, benchmarked to financial transactions) • Lower administrative overhead for Aggregator

  17. Returns • Assumption • Aggregation of 200,000 CER in 2007 • CER base price of USD 11 in 2007 • Forward contract for a crediting period of 7 years • Overheads assumed at INR 10 lakh per annum • Expected Revenues Model 1 • Fixed margin of 3% on CER revenues • EBITDA of INR 13.6 lakhs from year 2, for 7 years • EBITDA increase to INR 34 lakhs if CER price increases to USD 16

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