WÄRTSILÄ. Dan Johnson

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1 WÄRTSILÄ Dan Johnson

2 California and the West as a whole Expectations for 2020 in WECC? WA: 15% x 2020* OR: 25%x 2025* (large utilities) CA: 33% x 2020 NV: 25% x 2025* Renewable Portfolio Standard Policies / March 2015 UT: 20% x 2025* AZ: 15% x 2025* MT: 15% x 2015 CO: 30% by 2020 (IOUs) * NM: 20%x 2020 (IOUs) ND: 10% x 2015 SD: 10% x 2015 KS: 20% x 2020 OK: 15% x 2015 MN:26.5% x 2025 (IOUs) 31.5% x 2020 (Xcel) IA: 105 MW MO:15% x 2021 WI: 10% 2015 IL: 25% x 2026 MI: 10% x 2015* IN: OH: 12.5% 10% x x NY: 29% x 2015 VA: 15% x 2025 DC NC: 12.5% x 2021 (IOUs) SC: 2% 2021 ME: 40% x 2017 NH: 24.8 x 2025 VT: 20% x 2017 MA: 15% x 2020(new resources) 6.03% x 2016 (existing resources) RI: 14.5% x 2019 CT: 27% x 2020 NJ: 20.38% RE x % solar by 2027 PA: 18% x 2021 DE: 25% x 2026 MD: 20% x 2022 DC: 20% x 2020 TX: 5,880 MW x 2015* 2 Wärtsilä HI: 40% x 2030 Renewable portfolio standard Renewable portfolio goal U.S. Territories NMI: 20% x 2016 Guam: 25% x 2035 PR: 20% x 2035 USVI: 30% x States + Washington DC + 2 territories have a Renewable Portfolio Standard (8 states and 2 territories have renewable portfolio goals)

3 WECC System with 13% Energy from Wind/Solar * GTCC deep turndown, cycling Coal cycling 3 Wärtsilä

4 What happens in WECC dependent on CA 4 Wärtsilä

5 CAISO has 23% MWh from Wind/Solar 23% of CAISO energy from Renewables in GW ramp from 23% renewables This chart shows overgeneration risk in 2020, but already started in 2014! Several hours with up to 1100 MW wind/solar curtailed 5 Wärtsilä

6 Infamous Duck Chart CA Flexible Capacity Markets Indexed to 3 hour Net Load Ramp when CA 23% renewable GWh But CAISO knows they could see very large net load ramps at shorter time scales! 2 GW in 15 min! Fig ES-7 from 6 Wärtsilä

7 Modeling CAISO system (Using LTPP WECC Model) Future challenges CPUC announced (2012 LTPP**) to invest 5.6 GW in new GTCC and GT capacity Future scenarios Base scenario: 5.6 GW of GTCC & GT Flexible scenario: 5.6 GW of Internal Combustion Engines (ICEs) System modeling focus * Modeling Operations Study by Wärtsilä and Energy Exemplar Energy & AS Co-optimized Results isolated for CAISO Results for CAISO 7 Wärtsilä

8 Setup of CAISO System Analysis CAISO (2012) wind & solar (33% RPS) Retirements New GT, GTCC 10 Year Horizon CAISO GW new GTs, GTCCs CAISO GW of Wärtsilä capacity instead of GTs/GTCCs Of the two future systems, which has - Lowest annual Operations Cost (OPEX)? - Lowest annual CO 2 generation? 8 Wärtsilä

9 Why explore ICE options as alternatives to GTs? ICEs are more Flexible, and More Efficient 10% less fuel (per MWh) than the most advanced Aero GT 2 5 minute start times 5 minute minimum down time No defined minimum up time Start multiple times per day, no maintenance impact or added cost Minimum load 30-40% (soon to be 10%) Ramp rates (MSL to full load) 40s or less Modular buildout 40 to 500 MW+ (10 or 20 MW increments) Capex ($/kw) less than or equal to Aero GTs 9 Wärtsilä

10 What does this Flexibility do at the System Level? Energy + AS Base Flex Savings Gross savings at marginal cost (BUSD/a) 1, 2) $9.46 $ % In CAISO System, in % of capacity were flexible gas engines instead of gas turbines. 6.0% decrease in annual ratepayer costs Existing Combined Cycle starts ($) reduced by 20% Existing Combined Cycle capacity factor increases (from 50% to 53%) System Efficiency increases, CO 2 generation reduced 1.1% 1) All $15k/MWh, acc to 2) $50k/MWh acc to and other acc to 1) 10 Wärtsilä

11 Results: Wärtsilä Flexibility Optimizes the Fleet 22 GW Fleet of GTCCs with 5.6 GW of new GTs/GTCCs (Base Case) 22 GW Fleet of GTCCs with 5.6 GW of new Wärtsilä (Flex Case) Wärtsilä as Smart Power Generation - Individual Units cycle w/o added cost - Part Load Efficiency ~ Full Load - Take over ancillary service provision (ramping, load following, regulation) - Portfolio Optimization: influences dispatch of entire fleet of assets to minimize operational cost! 11 Wärtsilä

12 Long Term Planning (Utility Scale) - Installed capacity of ~ 30 GW - Significant build out of renewables (~ 30% of energy, ~ 50% of capacity) - Reliance on gas-fired thermal - Retirement of 6GW steam boiler plants in next 10 years - Transmission capacity of 9 GW - Demand response of 1.8 GW - Capacity reserve margin 15% 12 Wärtsilä

13 This Utility will see Large Net Load Ramps 7 GW net load ramp In 1 hour! Dispatchable (Thermal) generation Source: 2012 LTPP WECC Model data (for year 2022) What if you do capacity expansion plan with 2 options? - The usual lineup of new built options, GTs & GTCCs - Flex alternative- same lineup of GTs & GTCCs, plus Wärtsilä 13 Wärtsilä

14 Simply adding Wärtsilä capacity as another new-build option MUSD NPV savings over 10 years (Capex + Opex) - 10% less capacity needed to meet obligations Key Metrics Reduce Optimize Optimize Fuel Diversity Operational Expenditure s Capital Expenditure s Fuel Burn Sensitivities Fuel Prices CO 2 costs Portfolios Reduce 1.5% Water Use CO 2 Emissions Externalities Hydro / Weather Chrono, Gas- Turbine- Centric Chrono w/ Flexible ICE Capacity Wärtsilä Optimizes Outcomes from Long Term Capacity Planning 14 Wärtsilä

15 Summary Flexibility Needed Value of Flexibility (Wärtsilä ICEs) How to Get Flexibility - Renewables - Retirements - Wärtsilä = best gas-fired option Significant ratepayer savings (system scale) Optimization of Resource Planning (Utility Scale) Include ICEs in resource/system plans Use state of the art capacity expansion models Market Evolution (From 1-3 hour products to real time (5 minute)! 15 Wärtsilä

16 Thank You Dan Johnson Business Development Manager Wartsila North America, Inc. Please visit White Papers available at under Commercial Publications -> White Papers tab, - Incorporating Flexibility in Utility Resource Planning - Power System Optimization by Increased Flexibility

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