Electricity Baselines for Grid-Connected Renewables: ACM 0002 Issues and Options

1. Electricity Baselines for Grid-Connected Renewables: ACM 0002 Issues and Options Michael Lazarus, SEI Workshop on CDM Methodologies and Technical Issues Associated with Power Generation and Power Saving Project Activities Montreal, December 3, 2005

2. Overview of Presentation • Fundamentals of the combined margin concept • Key issues and recent developments in ACM0002 • Guidance on OM/BM weights • Defining grid boundaries (imports and exports) • Overcoming data constraints • Factoring in other CDM projects • Retrofits • Improving build margin methods • Moving forward • New issues, methods, processes… mechanisms?

3. Context : The Current CDM Pipeline • Over 28 MtCO2e of the 140 MtCO2e/yr (2008-2012) pipeline are renewable electricity projects • 15 MtCO2e are in other categories related to avoided grid electricity (EE and gas) Electricity baseline methodologies have a major impact on CER markets Source: Jane Ellis, Ellina Levina, The Developing CDM Market, OECD/IEA Information Paper (Dec 2005)

4. The challenge of getting it “right” • Power sector projects and CERs depend upon an unknowable counterfactual baseline: there is no “right answer” • CERs = MWhproject x (EFy,baseline– EFy, project) [tCO2e/MWh] • Baseline methodologies must consider • Accuracy/credibility • Feasibility (cost, data availability) • Transparency • Consistency (projects, contexts) ACM0002 reflects a balancing of objectives

5. A CDM electricity project can affect: • The choice and/or timing of new power plants (or life extension of existing ones), i.e. the build margin (BM), and/or • The operation of existing power plants, i.e. the operating margin (OM) • Under ACM0002, the baseline emission factor, EFy(tCO2e/MWh) = wOM*EFOMy + wBM*EFBMy • Weights wOM andwBM, are 50% by default. • “Alternative weights can be used as long as…appropriate evidence justifying the alternative weights is presented. These justifying elements are to be assessed by the Executive Board.” Weights matter: OM and BM can differ by 2x or more; Ambiguity is problematic

6. How to determine appropriate weights? • MP commissioned a paper (Synapse) and reviewed various methodology submissions, and found that: • 50/50 reasonable for the first crediting period. OM impacts dominate until capacity additions can be deferred/modified, then BM dominates. 50/50 OM/BM weighting corresponds to shift midway during 1st crediting period. • Rationale implies 100% BM weighting for 2nd and 3rd CPs [not adopted at EB22] • Increased weight and potential limitations of existing BM methodology (data availability, sample size, volatility, and the possible reliance on unrepresentative historical experience) suggests review of potential improvements.

7. PPs propose quantification methods consistent with guidance; no weight exceeds 75% during first crediting period (suggested) Project- and context-specific guidance

8. Grid Boundaries – the Problem • Boundaries matter: they determine which power plants are included in emission factor calculations • Different choices of boundary lead to more/fewer CERs • Clear grid definitions can be difficult • ACM0002 defines the project electricity system as “the spatial extent of the power plants that can be dispatched without significant transmission constraints”. But what is significant? • Different PPs have used, and DOEs accepted, different grid boundaries in the same country/region Ambiguity is problematic

9. Grid Boundaries – the Solution (for now) • Where grid boundaries are unclear, given country-specific variations in grid management policies: • (a) Use the delineation of grid boundaries as provided by the DNA of the host country, if available; or • (b) In large countries with layered dispatch systems (e.g. state/provincial/regional/national) the regional grid definition should be used. In other countries, the national (or other largest) grid definition should be used by default.

10. Other CDM projects in the Baseline • NM0076-rev is only methodology that accounts for other CDM projects • First come, first served principle (preserves first mover incentives, in principle…) • On a theoretical basis, CDM projects should not be included in baseline (OM or BM calculations). Or should they? • If and when CDM projects become a major contribution to new electricity supply, new approaches may be needed • the “without CDM” baseline may become very hard to detect and measure A problem we should wish for

11. Retrofits (to renewable power plants) • ACM0002 modified to consider (hydro) upgrade projects that increase electricity production • Baseline assumes existing facility would have continued to provide electricity at historical levels (3-5 year average) until the “time at which the generation facility would likely be replaced or retrofitted in the absence of the CDM project activity.” • The date of baseline retrofit/replacement should account for typical equipment lifetime and common practice (in company/sector/country context) Small but important niche market

12. OM and BM methods in ACM0002 ACM0002 currently contains: • 4 operating margin options: • Simple OM: Excludes low-operating cost and must-run power plants • Simple Adjusted OM: Includes some must-run/low-cost resources (e.g. hydro) where they dominate a grid • Average OM • Dispatch data analysis OM: Uses top 10% of dispatch • 1 build margin option: • the average emission factor of recently built plants (5 most recent or most recent 20% of generation, whichever is greater in MWh); • PP can choose either ex ante or ex post analysis Are they sufficient? Are they clear?

13. Fitting the data to the methodology • Defining the build margin cohort • Estimating plant-specific fuel consumption rates • Filling data gaps (e.g. missing plant data) Is ambiguity problematic here?

14. The Build Margin challenge • How to reduce dependence on lumpy, historical data, where • One or two large plants can have disproportionate influence in calculation • BM emission factor can vary considerably year-to-year • BM cohort may be out-dated (particularly if done ex ante) ….while maintaining transparency and feasibility, and limiting bias? • What role for plans, projections, and models?

15. Strengths Relative simplicity and feasibility: low-cost, manageable data and skill requirements Incorporation of both OM and BM effects Relatively consistent and comparable across regions and projects Relatively transparent and credible: data verifiable Weaknesses/challenges Dependence on lumpy, historical data for build margin Applicability to larger investments, lower-emission (e.g. natural gas) projects Implementing project-specific and context-specific OM/BM weights Remaining ambiguities and data constraints Reflection of local market and operational conditions ACM0002: strengths and weaknesses?

16. Moving forward ….in what direction(s)? • Enhancing ACM0002 • Specific algorithms or unambiguous criteria for alternative OM/BM weights? Additional guidance for other conditions? • Standardized methods to fill “data gaps”? • More forward-looking, less volatile build margin methods? • Other issues, e.g. CDM projects in baseline, grid boundaries, etc? • Thinking beyond ACM0002 • Alternatives to ACM0002, simpler or more complex? • Develop new processes for resolving methodology issues? What might they look like? • Complementary approaches and mechanisms to support low-GHG power sector investments and strategies?