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Overview of PRM Study Overview of PRM Study Nova Scotia Power Inc. August 7, 2019 Zach Ming, Sr. Managing Consultant Study Objectives The Planning Reserve Margin (PRM) study provides an update to several assumptions to be used by Nova Scotia Power Inc. (NSPI) in the integrated resource planning (IRP) process PRM study outline • Background + jurisdictional review of industry best practices • Overview of analytical approach & assumptions: E3 RECAP model • Calculation of required PRM for NSPI to meet target reliability standard – Loss of Load Expectation (LOLE) of 1 day in 10 years (0.1 days/yr) • Calculation of existing and potential effective load carrying capability (ELCC) for various dispatch-limited resources – Wind – Solar – Storage – Demand Response 2 Planning Reserve Margin (PRM) Planning reserves are resources held by the utility above the forecasted median peak load that help maintain reliability even in the event of: • Unplanned forced generator outages • Higher than normal peak loads (very cold weather) • Operating reserve requirements PRM is a convention that is typically based on: • Installed capacity of traditional generation vs. 1-in-2 median peak load (e.g. half of the years experience a peak load higher than this and half lower) PRMs vary by utility but typically range from 12%- 20+% depending on system characteristics • Larger systems with more load and resource diversity can MW generally maintain lower PRMs PRM • Islanded systems with limited interconnections and load and Traditional resource diversity such as Hawaii must maintain a PRM Generation 1-in-2 Nameplate around 40% Capacity Peak Step 1 Step 2 Load Reliability Target Planning Planning Reliability Standard Traditional (1-day-in-10-years) Reserve Margin Process System 3 Renewable/Storage Contribution to PRM In systems with high penetrations of renewable energy and storage, utilities must still maintain acceptable reliability through a planning reserve margin Effective load carrying capability (ELCC) measures a resource’s ability to contribute to PRM ELCC is the quantity of “perfect capacity” that could be replaced or avoided with 90% renewables or storage while providing equivalent system reliability • A value of 50% means that the addition of 100 MW of that resource could displace the need for 50 MW of firm capacity without compromising reliability Calculating ELCC requires computationally intensive models that can accurately 18% account for the correlation and probability 5% of production between load and renewables Wind Solar Storage 4 Diminishing Marginal ELCC and Diversity Benefits of Renewables/Storage The ELCC of renewables or storage depends on the other resources on the system The diminishing marginal peak load impact of solar PV is illustrative of this concept There are also diversity benefits between resources such that the total contribution of a portfolio of resources may be more than the sum of their parts 60 6 50 5 40 4 30 3 Load (GW) Load 20 2 10 (GW) Load Peak Reduction 1 0 0 1 2 3 4 5 6 7 8 9 101112131415161718192021222324 0 6 12 18 Hour Installed Solar PV Capacity (GW) 5 Jurisdictional Review Overview of Jurisdictional Review E3 conducted a review of reliability standards and planning practices mainly across several North American electric jurisdictions • Reliability metrics and targets used for planning • How reliability metrics are converted into planning practices e.g. PRM values • PRM metric conventions i.e. de-ratings for forced outages Ultimate conclusion was that NSPI is in-line with industry best practices for reliability planning • NSPI plans to a 1-day-in-10 year standard or 0.1 days/yr loss of load expectation (LOLE) 7 Jurisdictional Summary Jurisdiction / Utility Reliability Metric Metric Value Notes 800 MWh/year AESO monitors capacity and can take action if modeled EUE exceeds threshold; 34% AESO EUE (0.0014%) PRM achieved in 2017 w/o imports CAISO PRM 15% No explicit reliability standard Tracks PRM for information purposes; “Purely information” PRM of 13.75% achieves ERCOT N/A N/A 0.1 events/yr; Economically optimal = 9.0%; Market equilibrium = 10.25% Florida LOLE 0.1 days/year 15% PRM required in addition to ensuring LOLE is met 0.2/0.1/0.01 ISO-NE LOLE Multiple LOLE targets are used to establish demand curve for capacity market days/year MISO LOLE 0.1 days/year 7.9% UCAP PRM; 16.8% ICAP PRM Nova Scotia LOLE 0.1 days/year 20% PRM to meet 0.1 LOLE standard LOLE is used to set capacity market demand curve; Minimum Installed Reserve Margin NYISO LOLE 0.1 days/year (IRM) is 16.8%; Achieved IRM in 2019 is 27.0% PacifiCorp N/A N/A 13% PRM selected by balancing cost and reliability; Meets 0.1 LOLE Hawaii (Oahu) LOLE 0.22 days/yr Relatively small system size and no interconnection results in 45% PRM PJM LOLE 0.1 days/year LOLE used to set target IRM (16%) which is used in capacity market demand curve PRM assigned to all LSE’s to achieve LOLE target: 12% Non-coincident PRM & 16% SPP LOLE 0.1 days/year Coincident PRM System operator monitors forecasted reliability and can intervene in market if Australia EUE 0.002% necessary 5% (Target PRM 2021/22) Great Britain LOLH 3 hours/year 11.7% (Observed PRM 2018/19) LOLH determines total capacity requirement (10% PRM) which is used to determine Ireland LOLH 8 hours/year total payments to generators (Net-CONE * PRM) 8 RECAP Model Overview & Assumptions E3 Renewable Energy Capacity Planning Model (RECAP) RECAP is a loss-of-load-probability (LOLP) model for evaluating power system reliability for high penetration scenarios Initially developed to support the California ISO with renewable integration modeling more than 10 years ago Has been progressively updated and used by a number of utilities and regulators across North America • CPUC • Portland General Electric • SMUD PNW Nova Scotia Xcel • WECC PGE • LADWP New York CAISO SMUD • Florida Power & Light CPUC • El Paso Electric LADWP El Paso • Pacific Northwest Florida • Nova Scotia Power HECO • Xcel Minnesota • HECO 10 RECAP: E3’s Renewable Energy Capacity Planning Model RECAP is a loss-of-load probability (LOLP) model used to test the resource sufficiency of electricity system portfolios • This study uses a 1-day-in-10-year standard (0.1 days/yr LOLE) to determine the target PRM RECAP evaluates sufficiency through time-sequential simulations over thousands of years of plausible load, renewable, and stochastic forced outage conditions • Captures thermal resource and transmission forced outages • Captures variable availability of renewables & correlations to load • Tracks hydro and storage state of charge 11 RECAP Methodology Step 1 Step 2 Calculate Hourly Calculate Renewable Load Profiles Step 3 Step 4 Calculate Available Hydro Dispatch Dispatchable Generation Step 5 Step 6 Calculate Available Dispatch Storage Transmission Step 7 Step 8 Dispatch Demand Calculate Loss of Load Response 12 Inputs for Load and Renewable Profiles Actual historical NSPI hourly load from 2009 to 2018 Actual historical NSPI wind profiles from 2011 to 2018 Simulated historical NSPI solar profiles from 2008 to 2010 Weather and date information from 1953 to 2018 1953 Timeline 2018 Use historical weather data and artificial neural network regression techniques to create Gather 10 years of recent 2 synthetic load shapes based on extended weather record 1 historical load data Load Use Monte Carlo day-matching algorithm to extend renewable profiles to cover same Gather 8 years of actual 4 span of weather conditions as synthetic load while preserving correlations among load 3 wind profile and 3 years and renewable production of solar profile Wind 2011-2018 Solar 2008-2010 13 Dispatchable Resources in 2020 E3 used the net operating capacity (MW) and DAFOR (%) to stochastically represent the dispatchable generating capability of these resources in the RECAP model Category Fuel/Tech Type Unit Name Operating Capacity (MW) DAFOR (%) Tufts Cove 1 78 36.0% Tufts Cove 2 93 19.1% Tufts Cove 3 147 2.0% HFO/N Gas Tufts Cove 4 49 2.9% Tufts Cove 5 49 5.1% Tufts Cove 6 46 1.6% Pt Aconi 168 1.9% Lingan 1 153 1.7% Lingan 2 0 1.7% Lingan 3 153 4.2% Coal/Petcoke Lingan 4 153 5.0% Trenton 5 150 6.8% Trenton 6 154 4.4% Tupper 2 150 1.9% Burnside 1 33 10.0% ConventionalThermal Burnside 2 33 10.0% Burnside 3 33 10.0% Oil Burnside 4 33 10.0% Victoria Junction 1 33 10.0% Victoria Junction 2 33 10.0% Tusket 33 10.0% Hydro Dispatchable Hydro 162 5% Port Haweksbury 43 1.2% Biomass IPP Biomass 31 1.2% Biogas IPP Biogas 2 1.2% Renewable Total Operating Capacity (MW) 2,012 14 Hydro / Tidal Resources Overview For modeling purposes, hydro is grouped into 3 categories • Dispatchable: hydro units can be dispatched at maximum output with no limit on duration • Tidal: Annapolis is modelled as resource with variable hourly profile similar to wind • Wreck Cove: Can be dispatched under constraints including maximum output, minimum output, and daily maximum energy 15 Hydro and Tidal Resources Maximum Minimum Other Constraints in Hydro Group Resource Name Capacity (MW) Capacity (MW) RECAP Tusket 2.4 0.9 St Margarets 10.8 0 Sheet Harbour 10.8 0.4 Dickie Brook 3.8 0.1 Nictaux 8.3 0 Lequille 11.2 0 Assumed to be available Firm Hydro Avon 6.75 0 at maximum capacity Black River 22.5 6 during peak load hours Paradise 4.7 2 Mersey 42.5 6 Fall River 0.5 0 Sissiboo 24 6 Bear River 13.4 0 Subtotal 162 Tidal Annapolis 19 Annual output profile Daily Energy Budget Subtotal 19 (MWh) Wreck Cove Wreck Cove 212 0 500 - 1100 Subtotal 212 Total 393 16 Transmission Lines No internal transmission constraints assumed within
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