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Pancakes and Power Companies Financial Performance of Power Companies 25 May 2011

Pancakes and Power Companies Financial Performance of Power Companies 25 May 2011. One man’s opinion on how the 5 main power companies compare against each other and against values in an “optimal” market Interactive discussion (tell me what I have done wrong) Interrupt and debate as we go.

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Pancakes and Power Companies Financial Performance of Power Companies 25 May 2011

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  1. Pancakes and Power CompaniesFinancial Performance of Power Companies25 May 2011 One man’s opinion on how the 5 main power companies compare against each other and against values in an “optimal” market Interactive discussion (tell me what I have done wrong) Interrupt and debate as we go

  2. Covering • Acknowledgements • Summary of results • Derive like for like asset values against “optimal market” • Benchmark derived values against recent asset transfer values • Table of returns on like for like basis • Comparison with currently traded value • Factors that drive historical returns • Possible drivers for future returns “optimal market” • Derivation of “optimal market asset values” • Discounted cash flows for different types of generation • Forward price curve (The challenges of price forecasting) • Price duration curve (Rewards different types of generation differently) • Discount rate (Based on WACC for typical generation company (pinched from Macquarie)) • Implications • SOE performance vs private performance – implications for SOE sales • Thermal vs renewable performance – past is not a good indicator of future • What I am buying (Contact vs Trustpower) • What I would buy if they partially float SOEs (Genesis vs Meridian)

  3. Acknowledgements Brian Bull – For EC 2010 SOO Revenue Adequate Price Forecast and underlying PDC Basis for optimal asset values as use PDC and fixed and variable cost assumptions to derive cash flow for each generator type All assumptions about what constitutes an “optimal” market development derived from 2010 SOO market development scenarios (plus assume retail margin of 2% as per EC retail reform analysis) Stephen Gale – Overview and critical review The good bits are theirs the mistakes are mine

  4. Summary Like for like asset values against an “optimal market” value Benchmark against recent asset transfer values Returns on a like for like basis Comparison with traded share value

  5. Factors that drive historical returnsComparison Between CompaniesType of Generation – Renewables vs Thermals Renewables out performing thermals – Capacity and Scarcity Pricing Issues

  6. Factors that drive historical returnsComparison Between CompaniesRetail vs Wholesale Profit Net retailers outperforming net generators – Capacity and Scarcity Pricing and Retail Competition Issues (retail margins higher for renewable generators)

  7. Factors that drive historical returnsComparison Between CompaniesSOEs vs Private Private companies outperforming SOE’s could be argument for partial SOE privitisation.

  8. Derivation of “Optimal Market” Asset Values • Derive asset value based on discounted cash flows • Generator discounted cash flows derived from earnings less operating costs • Earnings based on forward price curve and price duration curve (PDC) shape • Both forward price curve and PDC shape derived from EC 2010 SOO • Retail value just based on 2% profit margin assumption • Discount rate based on typical power company WACC (from 2010 Macquarie SOE valuations for COMU)

  9. Discounted Cash Flows Based on Forward Price Curve • EC 2010 SOO Revenue Adequate Forward Price Curve • Derives from EC estimate of optimal generation investment to meet demand under 5 different possible market development scenarios • Adjusted back to align with 2011 – 2013 hedge prices (Hedge disclosure website, weighted average price) • Assumes prices just reach minimum level to call forth right mix of investment to meet security of supply standards, hence “optimal” market

  10. Forward Price Path

  11. Price Duration Curve (PDC) Shape Determines Earnings by Generator Type • When price above costs (SRMC) then generate and earn revenue, when not don’t generate • Recognises some generation (thermal) primarily there to provide back when no rain or wind • PDC Derivation • 5 load blocks per season • Weighted to pick up peak slice and low load slice • 4 seasons • 72 hydro inflow sequences • 5 scenarios • Fitting generation to PDC • Hydro shape available energy (typical inflows to PDC but assume certain degree of inflexibility (price is highest when inflows lowest) • Use average capacity factors then de-rate at peak price as per EC assessment of correlation of dry and still periods (10% peak de-rating)

  12. Discount Rate • Discount rate 6.81% real post tax (tax 28%, inflation 1.75%) • Discount rate based on WACC for typical SOE power companies • As calculated by Macquarie (2010 valuations for COMU) • Overall results for optimal valuations sensitive to discount rate, but relative valuations constant • Rational for a single discount rate (based on WACC) is that all companies should be striving towards optimal leverage and lowest possible WACC. So should trend in that overall direction over time

  13. Implications • See merit in privitisation of SOEs to raise overall return for tax payer • Thermal generator performance likely to improve over time as market evolves towards “optimal” • I prefer Contact over Trustpower • I would buy shares in any of the SOE power companies if floated at current book value • But favourite would be Genesis

  14. SOE Privitisation • SOE privitisation has potential to raise overall return for taxpayer • Ideally raise rate of return on 51% retained to equivalent private rate of return • Alternative may be tax payer subsidisation of large industrial and commercial consumers (through inefficient investment) • Possible example West Wind – 2010 ED estimated LRMC of $101/MWh and build in 2030, seems to have been built before economic • Issue will be trying to ensure float price reflects earnings potential not history

  15. Thermal Generator Performance • Historically thermal generators have earned less than renewables, relative to an “optimal” market • EC analysed as lack of market incentive to value security of supply (led to several public savings campaigns) • Proposed capacity and scarcity pricing market changes • Market should evolve towards “optimal” mix over time • Modelers delusion that reality should change to match my model

  16. Contact vs Trustpower • Current market has favoured renewable over thermal generators and net retailers over net generators (Trustpower winner on both counts) • If believe reform agenda for EA then balance likely to move back towards thermal generators (valuing security of supply via capacity and scarcity pricing) and net generators (reducing retail margins through higher retail competition) • These changes likely to move balance back in favour of Contact (or more closely align with “optimal” market) • However, huge respect for Trustpower management team’s ability to adapt to regulatory and market changes

  17. SOE Values • I would buy any of the SOEs at book value • But favourite would be Genesis (most potential to gain from market changes) • Big issue for Genesis is future of Huntly • “Optimal” market design still shows significant value • Genesis having trouble extracting that value in current market

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