Minimising Risk Maximising Return. Chanda Kapande Business Development Manager Wind Prospect

Minimising Risk Maximising Return Chanda Kapande Business Development Manager Wind Prospect

Agenda Wind Prospect Wind energy in East Africa Sample Project & Financial model RIsks Wind Conclusions Performance Completion Economics

Built UK s No 2 wind farm in 1992

1GW consented

100 wind farms constructed

Global Presence Vancouver Halifax Denver Ireland UK Paris Warsaw Istanbul Beijing Hong Kong Adelaide Wanaka

East Africa: strong platform for Key Figures: growth in wind business Kenya NW (Marsabit & Turkana districts) + edges of the Rift Valley (average wind speeds above 9m/s at 50 m) The coast (~ 5-7 m/s at 50 m high) Fixed tarriff <9.0 US Cents per kwh wind farms less than 50MW Tarriff applies to the first 150MW of wind developer in the country Tarriff applies for 15 years from commissioning Ethiopia Eastern half of the country including the western escarpment of the Rift Valley (7-10m/s) 97% power from hydro Due to high altitude (2,400 m above sea level) turbine production ~ 25%less Tariff?? Tanzania Spot measurements as high as 12 m/s. Singida region & Makambako in Iringa Region ~8m/s Tariff case 1 (2009) (TZS/kWh) Annual Average 85.49 Dry season (Aug Nov) 102.58 Wet season (Jan-Jul and Dec) 75.94

Current Status Project Capacity (MW) Country Lake Turkana 300 Kenya Ashegoba 120 Ethiopia Singida 210 Tanzania Confidential ~ 200MW Djibouti Various ~ 300MW Kenya Ngong II 10 Kenya Sinohydro/EEPCo 102 Ethiopia Currently under Operating Ngong, Marsabit Ngong 5.1 MW 150kW 600 kw

Project Sensitivity Analysis Assumptions 30MW project 96% average availability $90/MWh FIT fixed for 15 years IRR = 11.3% $60/MWh price of electricity Turbine costs ~$1.5million/MW O&M costs ~$34,000/wtg/year Inflation 4.69% Yield per turbine ~8000GWh

Risks Wind Investment Revenues Performance Risks Wind supply risk Technical performance risk Commercial Risks Completion risk Economic viability risk Organisational risk Country Risk Legal Political Sample Project Delivered CERs CDM Risks Quantity Price Cost

Wind Supply Financial return is directly linked to wind speed at the site Wind studies are undertaken to develop an understanding of that return To have confidence in an investment, you need confidence in the wind study All wind and energy studies carry a degree of uncertainty and potential for error. This financial risk is amplified in the energy prediction due to the relationship between turbine output and wind speed. In a study, all stages of wind measurement, modelling and prediction are based around minimising uncertainty, resulting in a best guess of the wind speeds and yields that the site will see during operation To avoid financial disadvantages, uncertainties must be minimised

The influence of wind speed A change in wind speed, means a change in energy production. A bit of maths: Power available in the wind = 1/2 x air density x Area (of turbine rotor) x Wind speed 3 752kW 841kW 7.5m/s 7.8m/s So in this example, a 0.3m/s (4%) gain in wind speed gives a 90kW (12%) gain in power produced by the turbine Get the annual average wind speed wrong by 4%, and your model could be out by 6-8%

Understanding wind speed In order to reduce financial risk, it is important to fully understand the wind speeds at the site High quality wind resource campaign Mast location and height representative of site and WTGs? Calibrated anemometers, correctly mounted? Measure for at least 12 months - high availability? Long term reference future variability? Flow models, losses, uncertainties.

Technical Performance Risks Operational risks Proven Technology O & M Macroeconomic framework Product quality? Dependence on supplier s know-how? TCMA contracts, alternative vs. reliable providers? Volatility of O&M costs? Loss of licences? Env t monitoring plan? Business interruption? Operational efficiency problems? Exchangeability of currency? Appreciation vs depreciation? Interest rate changes? Cash-sweep?

Availability Manufacturer s Availability Warranty: 95% to 97% site availability +/-5% of power curve Availability Calculations exclude periods of: Disconnection from grid Scheduled maintenance Lost communications Extreme weather conditions Yawing Emergency stops Owner s Availability Turbine ready to produce (h) 8760 h = WTG availability Understand all the factors which affect a turbines ability to produce electricty and therefore revenue.

Lost Revenue Turbine User: T4 Turbine Fault and Comms: T5 Maintenance: T6 Grid: T3 1 0.00 22.41 22.95 0.00 Winter 2shutdown approved 0.00 for wind 24.46 farms27.71 0.00 577.99 24.67 September 3 24, 2005 0.00 50.03 22.95 0.00 1305.08 50.04 To reduce 4 bird 0.00 deaths, farm some 1.34 shut 4,000 down 22.95 aging 0.00 wind turbines in California will be 5 0.00 35.66 22.95 0.00 23.51 1.35 7 0.00 24.95 27.15 0.00 8 0.00 0.22 22.95 0.00 9 0.00 20.00 22.95 0.00 10 0.00 18.58 27.14 0.00 11 0.00 24.32 22.95 0.00 12 0.00 21.59 22.95 0.00 13 0.00 38.87 22.95 0.00 All Turbs 0.0 300.8 315.7 0.0 % of Total Downtime 0.00% 48.79% 51.21% 0.00% Cost* (euro) Turbine collapse causes New York wind Time (h) 269.31 22.37 idled temporarily, and some will be scrapped and replaced with newer models. 6 0.00 18.37 27.14 0.00 639.58 35.74 Jesse Broehl, 20 January 2010, 5:08pm 252.43 18.41 1153.11 24.95 18.18 0.24 1062.29 20.03 418.85 18.63 395.22 24.32 684.97 21.62 163.02 38.94 6,964 301 Monthly Downtime per Turbine Monthly Error Log

Completion Risk Construction phase risk Contracting Construction Construction plan & mitigation of commissioning delays, delays in receipt of permissions? Test period defects? Turbine supply alternatives & purchase contract details, performance guarantee, completion guarantees? EPC-Contractor or Multi-Contracting? Subcontractor s clauses? Qualified local workforce?

Unplanned Delay ~30 MW wind farm Financial close August 2008 WTGs delivery dates February 2009 Original energisation date agreed at financial close March 2009 Delay in receiving grid connection wayleaves Actual energisation date July 2009

Consequences of Delay Additional construction insurance 20k Project management costs 40k Temporary generation costs 32k Acceleration payment to DNO 50k Legal fees due to default 80k Maintenance Costs for WTGs 100k Interest on payments to WTG supplier 250k Additional Interest during construction 325k TOTAL 847k

Consequences of Delay Other factors Lost revenue of ~ 1.6 million Total losses ~ 2.5 million Material damage to the WTGs due to moisture (electronic components) Potential deemed take-over of the WTGs A lot of stress for the developer.

Risks Wind Investment Revenues Performance Risks Wind supply risk Technical performance risk Commercial Risks Approval risk Economic viability risk Organisational risk Country Risk Legal Political Sample Project Delivered CERs CDM Risks Quantity Price Cost

Economic Viability Risk Electricity market Electricity output Off-taker Price Is there a wind energy & certificates purchase obligation? With priority access? Grid extension & operation: public or private? Credit-worthiness of the off-taker? Remuneration system (Feed-in, PTCs, Certificates)? How often does the remuneration law change?

Attractive remuneration system, though volatile Remuneration Challenges from a banker s view Electricity price $90/MWh (ca. 9$c/kWh) PPA s: off takers creditworthiness term of the PPA s Green certificates Emission Reduction Unit(CO 2 certificates) CoO max price = substitution fee + annual inflation. CoO until 2012. And afterwards?

Where the money goes Sale of electricity Sale of carbon credits Interest income Insurance proceeds O&M costs Insurance costs Tax Revenues Costs Cash flow available for debt service Payment of interest on loan Debt reserve account Repayment of capital Free cash flows Dividends for equity investors

Conclusion The most critical factors influencing IRR are: Capital cost Load factor Electricity tariffs Profitability of a wind farm is very sensitive to changes in any of the above

Thank You!