1. It s architecturally unique 2. It has unique features

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4 1. It s architecturally unique 2. It has unique features

5 1. Transparent 2. Customisable 3. Integrated

6 Architecturally unique

7 Architecturally unique

8 Architecturally unique

9 1. Time 2. Stochastic Optimisation 3. Risk management

10 Time Time Works in a Unique Way 1. The Long Term 2. Granularity 3. Interleaved Mode

11 Time

12 Generation (MW) Time 1 Week dispatch ST GT1 GT2 GT3

13 Expected Cost ($Billions) 31,7 Efficient Frontier (Costs) Time 31,68 31,66 31,64 31,62 31,6 31,58 31,56 31,54 Each point represents the outcome of one PLEXOS risk-constrained stochastic LT Plan optimization with a unique level of risk input. These solutions have lower risk but higher expected total cost. Stochastic Optimal Solution. This is the optimal solution ignoring the decision maker's risk appetite. 31,52 31,5 39,2 39,25 39,3 39,35 39,4 39,45 39,5 39,55 39,6 39,65 39,7 Cost 10th percentile ($Billions)

14 Time

15 High Granularity Time

16 Generation (MW) Interleaved Time Kelar on 21-May Day ahead plan Actual

17 Stochastic Optimization 1. Stochastic Unit Commitment 2. Stochastic Hydro

18 Stochastic Optimisation CAPACITY TECHNICAL LIMITATIONS MINIMUM PRODUCTION PRODUCTION COST 2x100 [MW] -12hrs off -8hrs on [65] MW 10$/MWh 100 [MW] -4hrs on -2hrs off [10] MW 50$/MWh [MW] uncertain Must-run! - 0$/MWh How to efficiently schedule thermal power plants with technical restrictions if we don t know how much wind (and/or load) is going to be available?

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20 Stochastic Optimisation Stochastic Unit Commitment

21 Stochastic Hydro Stochastic Optimisation

22 Risk Management 1. New storage technologies (for supply) 2. Demand Response (for Demand) 3. Reliability and Resource Management (for supply and demand)

23 New Storage Technologies Risk management

24 Risk Management PLEXOS can model any storage technology. Most popular are: Concentrated Solar Power (CSP) Compressed Air Energy System (CAES) Batteries Pumped Storage (PS) Electric Vehicles (EV).

25 Risk Management Example: Concentrated Solar Power (CSP) Solar Radiation Heat Storage Electrical generator Resource profiles Max heat Min heat Heat loss Max capacity Min Stable Level Ramps MDT/MUT Number of starts per day Startup cost

26 Risk Management Example: Compressed Air Energy System (CAES) Compressing mode: Storage Generating mode: Storage Storage capacity Cycle efficiency Compressor load Max capacity Min stable level Variable heat rate Ramp Max capacity

27 Risk Management Example: Batteries Capacity (MWh) Max SoC (%) Min SoC (%) Max Input Power (MW) Max Ramp Up/Down (MW/min) Charge Efficiency (%) Discharge Efficiency (%) Max Cycles: Hour/Day/Week/Month/Year Capacity degradation

28 Risk Management Example: Pumped Storage Generator Mode 75% efficiency pump Pumped Mode Pumped Head - 1 MW Pumped Tail MWh +1 MW - 1 MW Pumped Tail +1 MW Pumped Head MWh

29 Risk Management Example: Electric Vehicles Discharge Charge Ancillary Services

30 Output from DR resource (MW) Risk Management Demand Response DR _gen maximum generation* (MW) DR _gen response time (min) DR _gen minimum generation* (MW) DR _gen ramp up (MW/min) DR _gen ramp down (MW/min) DR _gen maximum duration (min) Minutes (1440 minutes/day)

31 Risk Management Reliability & Resource Management Example: CAISO 2000 out of 8050 scenarios (161 x 5 x 10) PG&E Model Random Draw SDGE Model Random Draw Simulation 161 Random Draw Weather SCE Model 10 5 Load Sample Pool Wind Sample Pool Solar Sample Pool

32 LOLP Risk Management Reliability & Resource Management 0,18% Loss of Load Probability Convergence 0,16% 0,14% 0,12% 0,10% 0,08% 0,06% 0,04% 0,02% 0,00% Number of Samples

33 Unique 1. Time Works in a Unique Way 2. Stochastic Optimization 3. Risk Management

34 Thank you