Energy and Ancillary Services Design Stream Working Group Meeting 6 New modelling results – Impact of Net Demand Variability

Background – Dispatching to Net Demand The system is dispatched to meet “net demand” – defined as the demand net of variable resources (on the transmission and distribution system) that effectively self dispatch The variability of net demand can pose challenges on the system. Current system operation practices and tools may need to evolve in order to manage the variability (Net Demand Variability) introduced by increased variable generation The AESO is modelling the expected range of variability as well as considering scenarios related to future asset mix, market rules or products to evaluate the impact of NDV and if needed mitigation options At the WG2 meeting, based on the preliminary analysis, we indicated that; The “current market practices and behaviour” may create performance issues above 3,000 MW of variable generation (VG) (compared to current 1450 MW on line) Early modelling results indicate that the 3,000MW VG threshold may be reached by 2022/23

Further Analysis – Simulation methodology Early results were modelled based on the system as a single block and using inputs from the 2016 LTO New Analysis: Two models were developed to simulate; Market functions – Market simulation model Operations functions – System dispatch simulation model Simulated merit orders from the Market simulation model are input into the System dispatch simulation model to simulate operational behaviour Historic behaviour observations will form the foundation of the models Historic data used to validate the models Assumptions of future changes to system are considered The validated model is then used to simulate the future Alternate sensitivity and/or mitigation scenarios will be simulated based on initial observations from the base case simulation

Further Analysis: Key Assumptions Load Forecast Load forecasts for tested years are based on the 2017 LTO Future generation scenarios Generation forecasts (and generation cases) for tested years are based on the 2017 LTO Future variable generation profile Wind/solar profiles and simulations are based on 200 sites extrapolated to future Profiles are also based on 2014, 2015 and 2016 weather years extrapolated to future Operation practices are based on historic observed behaviour At system level (dispatch interval) Based on observed behaviour and related rules Parametric, validated / tuned by simulation (Historical backcast) At asset level Based on observed and expected behaviour (market and operation)

Metrics The metrics will demonstrate impacts on market and system operations as a result of changing supply and system characteristics between now and 2030 # Focus Metric Description 1 Market Supply surplus/shortfall situations To Identify impact of unit commitment on supply surplus and shortfall situations 2 Merit order / market asset characteristics To identify merit order characteristics under different generation mixes such as quantity of $0, Minimum Stable Generation (MSG) and ramp capability 3 Unit cycling Quantify cycling of different types of thermal generation units (CC, SC, CTG and coal for some years) 4 Operations Impact/expected changes to Control Performance Standard 2 (CPS2) violations To measure the10 minute ACE (Area Control Error – Balancing authority MW imbalance) performance at or above the 90% of the time within required threshold A Balancing Authority is the area operator that is responsible for: Matching generation and load. Maintaining the scheduled interchange with other Balancing Authorities. Maintaining the frequency in real-time of the electric power system

Metrics cont. # Focus Metric Description 5* Operations System Operating Limit (SOL) violation (TOP-007-AB-0) To measure the 30 minute or longer ACE performance benchmark and resultant SOL violation. i.e. to measure the SOL violation that exceeds the tie line Total Transfer Capability (TTC) for more than 30 minutes or longer 6* Area Control Error (ACE) events. Related to impact on interties and neighboring systems To measure the 30 minute or longer ACE performance benchmark. i.e. to measure when the intertie flow exceeds the schedule by more than the Transmission Reliability Margin (TRM) of 65MW for more than 30 minutes, but not exceeding TTC 7 Variable energy spill due to power management tool activations Potential spill of variable energy due to using the AESO’s wind power management tool (how often and how much) *The difference between high ACE and SOL is based on how high the BC tie is scheduled during the event. If tie is scheduled near full ATC, then it may cause an SOL; if tie is scheduled low, then it may cause high ACE events.

Study Results – Based on Reference Case The metrics will demonstrate impacts on market and system operations as a result of changing supply and system characteristics between now and 2030 # Focus Metric Results 1 Market Supply surplus/shortfall situations Supply surplus hours exceed historical values around 2026 Model results show no concerns of supply shortfall due to unit commitment 2 Merit order / market asset characteristic Preliminary work shows that future assets will individually have enhanced ramp capability; however, further work required to test the overall system impact of the expected merit order to manage NDV. 3 Unit cycling Future generation, including coal-fired replacements, is anticipated to increase in cycling – from monthly to weekly on average 4 Operations Impact/expected changes to Control Performance Standard 2 (CPS2) violations CPS2 is always above the required 90% (so not an issue) A Balancing Authority is the area operator that is responsible for: Matching generation and load. Maintaining the scheduled interchange with other Balancing Authorities. Maintaining the frequency in real-time of the electric power system

Study Results – Based on Reference Case # Focus Metric Results 5* Operations System Operating Limit (SOL) violation (TOP-007-AB-0) The 1st simulated SOL violation is at 2021 (2,645MW of wind), but it is during the period when the tie line is out of service With the tie line in service, the 1st simulated SOL violation is at 2022 (3,045MW of wind) 6* Area Control Error (ACE) events. Related to impact on interties and neighboring systems There are more big ACE events with the increased variable generation level, from a low of 10 instances per year up-to ~150 7 Variable energy spill due to power management tool activations Both the limited hours and energy are small numbers, with limited energy less than 0.1% of wind power generation Even less (~10 times) if only considering the non supply surplus periods

Summary Impact Based on further analysis, the NDV impact is measured at approximately 3000 MW of variability on the system; however, the estimated date for when the system impact is felt differs depending on the metric, starting in the original timeline of 2022 The impact varies significantly based on availability of intertie No expected system performance issues; however, increased hours of supply surplus which will impact assets and dispatch. Enhanced system flexibility important in managing variability AESO Internal

Next Steps Further testing of asset scenarios to evaluate any change in impact Examples: enhanced co-generation system, changes in coal to gas assumptions Evaluation of current rules to mitigate system impact Wind power management, forecasting, use of AGC, Evaluation of dispatch protocol / rules related to ramp Examples: Dispatch tolerance, ramp response Evaluation of further market rules / products Pricing to incent more system flexibility, new ancillary services products Efficiency analysis to evaluate mitigation options – impact to system, fleet, costs AESO Internal

Market simulation model finding details Appendix A Market simulation model finding details

Metric 1: Impact of unit commitment on supply shortfall and surplus in 2030 Under the 2017 LTO reference case, the hourly commitment of generation were similar in most hours between runs with forecast wind and runs with actual wind Supply surplus test; because of over commitment due to wind forecast error, there were approximately 50% more hours of surplus in 2030 Supply shortfall test; In situations where a lower number of units committed because of a higher than actual wind forecast, units that were online were able to cover the forecast error In general, changes to flows on the intertie and redispatch of online generation helped to manage error within the wind forecast AESO Internal

Metric 1: Supply surplus events expected to increase by 2030 Under the 2017 LTO reference case, results show supply surplus hours are expected to increase compared to recent experience By 2030, surplus hours may reach 153 (w/ tie) or 1,087 (w/o tie) Over the past few years, supply surplus have not exceeded 58 hours even during years of high hydro-led imports Results are impacted by: $0/MWh offers Intertie assumptions including perfect scheduling and ATC Commitment of generation Key finding: From the market simulation model supply surplus hours exceed historical values around 2026 Model results show no concerns of supply shortfall based on unit commitment model   Total Number of Hours  Reference Case – with intertie Reference Case – w/o Intertie 2016 - 10 2017 2018 2019 2020 2021 2022 1 2023 4 2024 12 2025 46 2026 3 89 2027 121 2028 43 439 2029 84 702 2030 153 1087 Historical Thresholds (2008-2017 YTD) Average Hours 7 Maximum Hours 58 49 hours of surplus when the BC tie was assumed on planned outage During these periods of curtailments: Wind: 4,700 MW Cogen: 3,200 MW Hydro/Other: 500 MW == 8,400 MW must run Demand: 9,400 MW And 2,500 MW of committed generation BC Offline Aug.26 to Sep.9 AESO Internal

Metric 3: Cycling statistics of commitment units A comparison was completed that looked at how large commitment units (>300 MW) currently cycle and are anticipated to cycle in the future Results are impacted by: Unit start up costs, min up/down time Portfolio considerations (no portfolio considerations are assumed) Generation mix Key Finding: Future generation, including coal-fired replacements, is anticipated to increase cycling frequency -- from monthly to weekly on average AESO Internal

System dispatch simulation model details Appendix B System dispatch simulation model details

Metric 4: Impact to CPS2 and supply surplus CPS2 is a Control Performance Standard violation measured when the ACE is above an acceptable threshold, approximately 60 MW, for ten minutes. Each ten minute period counts as one event. On a monthly average, the ISO must operate below this threshold 90% of the time. Key Finding: CPS2 is always above the required 90% The worst case is 93-94% Supply surplus hours pass historical values starting 2025 AESO Internal

Metric 5: SOL violation (TOP-007-AB-0) Key Finding: System Operating Limit (SOL) Violation SOL violation is approximately 2021 / 2022 depending on intertie and level of wind. The 1st simulated SOL violation is at 2021 (2,645MW of wind), but it is during the period when the tie line is out of service With the tie line in service, the 1st simulated SOL violation is at 2022 (3,045MW of wind) AESO Internal

Metric 6: Impact on interties Key Finding: Big Area Control Error (ACE) events There are more big ACE events with the increased variable generation level, from a low of 10 instances per year up-to ~150 Both metrics 5 and 6 measure 30 minute or longer ACE events. However; Metric 5 is for situations when the TTC is exceeded; Metric 6 is for situations when TTC is not exceeded The difference between high ACE and SOL is based on how high the BC tie is scheduled during the event. If tie is scheduled near full ATC then an SOL, if tie is scheduled low then high ACE events. AESO Internal

Metric 7: Variable spill due to WPM Wind power limited hours and energy due to Wind Power Management (WPM) Key Finding: Variable energy spill due to the AESOs WPM is insignificant at less than 0.1% The WPM protocol manages ramp therefore preventing need for further spill Even less (~10 times) if only considering the non supply surplus periods AESO Internal

AESOs Authoritative Document Glossary Definitions AESOs Authoritative Document Glossary

Area Control Error (ACE) means the instantaneous difference between actual interchange and scheduled interchange, taking into account the effects of frequency bias, time error and unilateral inadvertent interchange if automatic correction is part of the automatic generation control of the interconnected electric system, and a correction for metering error

Control Performance Standard (CPS) means the reliability standard that sets the limits of the area control error of a balancing authority over a specified time period.

System Operating Limit (SOL) means the value (MW, MVar, amperes, frequency or volts) that satisfies the most limiting of prescribed operating criteria for a specified system configuration to ensure operation within acceptable reliability criteria; system operating limits are based upon certain operating criteria: (i) facility ratings (applicable pre- and post-contingency equipment or facility ratings); (ii) transient stability ratings (applicable pre- and post-contingency stability limits); (iii) voltage stability ratings (applicable pre- and post-contingency voltage stability); and (iv) system voltage limits (applicable pre- and post-contingency voltage limits).