HMTF Understanding PLF August 31, 2015 Kevin Harris, ColumbiaGrid TEPPC\Hydro Modeling Work Group - Chair

Outline Background Is Hydro generation proportional to load? Change in Hydro Operations on Columbia River Understanding PLF K Factor Developing K Values for PLF Hydro Dispatch Against Load – Wind Summary of Findings Hydro Thermal Co-Optimization (HTC) Proposed GridView Improvements 2

Background 3

Objective of Current Hydro Modeling Review Review the modeling of Core Columbia River projects: – What does it mean when you change a modeling coefficients for PLF or HTC? – Determine if existing modeling represents current operations? – Make recommendations to correct any operational issues – Develop tools/method to determine appropriate Hydro modeling parameters/coefficients for in GridView 4

Hydro Background The Northwest represents 74% of the Hydro generation in WECC US System The Core Columbia River projects represents (Coulee – Bonneville): – 19,810 MW of capacity (8,905 aMW of generation ) – The Core is 61% of the Northwest Hydro generation – The Core is 45% of the Hydro generation in WECC US System WECC current Hydro modeling assumptions were created for use in Promod with calendar year 2010 data for the PNW 5 Focus first round of Hydro review on Core Columbia River

The Core Columbia The Core Columbia River is used to evaluate Hydro modeling in GridView Current Modeling: – Fixed Hourly Shape, 5 Projects which represents 23% of the Capacity – PLF/HTC, 6 Projects which represents 77% of the Capacity 6 Upper Columbia: Coulee - Priest Rapids Lower Columbia: McNary - Bonneville

Compare Operations Created spreadsheet to compare operation on the Columbia River by project or by aggregated sets (~65 MB) Contains hourly Hydro and load for: 2001, 2002 and It capable of comparing (all tables and/or charts): – Compare monthly operation: min, avg min, avg, avg max, and max – Compare average weekday peak hour for both load and generation – Compare average weekday operations (hour ending 1-24) – Calculate K Factor based on hourly data by month – Calculate K Factor based on monthly stats – Calculate resulting Hydro generation based on K Factor – Compare daily allocation generation vs. load and (Load-Wind) – Calc Polynomial for daily min and max generation – Compare daily operation by year: min, average and max gen 7

Is Hydro Generation Proportional to Load? 8

Example Historic Operations Example operation for January 2010 through Per unit of generation the operating range of Upper Columbia is greater than the Lower Columbia Load Used:= 100% of BPA + 100% of MidC + 6% of CAISO Aggregated and some individual projects Hydro generation are proportional to load

Change in Hydro Operations on Columbia River

Operational Change Starting in 2011 Starting in 2011 the annual average daily operating range decrease by 2,224 MW (38%) – During the spring run-off (Apr-Jul) an average reduction of 3,619 MW (65%) – Balance of year (Jan-Mar & Aug-Dec) an average reduction of 1,527 MW (25%) Any forecast run should reflect this reduction in operational flexibility 11

Operational Change Starting in Note the polynomial for 2011, 2012, and 2013 for operational Min and Max rating over-lap Date Points Spring Run-Off: 122/yr Balance of year: 243/yr

Understanding PLF K Factor 13

Proportional Load Following (PLF) How PLF works – The reference frame for PLF is the average monthly load and Hydro generation – Hourly Hydro generation is equal to the hourly percent change in load, from average load, multiplied by K Factor and applied to average monthly Hydro generation – Min and Max rating is enforced on Calc Hydro generation – K=0 results in a flat monthly shape equal to the average monthly Hydro generation 14

Measuring Success What’s the Criteria to measure reasonable Hydro operations? Used Criteria Confirm that Hydro generation is proportional to load Average Weekday Operating Range: Focus on keeping the average weekday operating range within reasonable historic limits (Avg WKD Max-Avg WKD Min) – Weekday Max set to the a verage of the maximum 3-4 hours – Weekday Min set to the average of minimum 3-4 hours Error Check: Compare calculated average weekday generation shape with actual operations 15

K Factor - Hourly Shape (PLF) Positive K Factor result in Hydro generation proportional to load – K Factor 0> and < 1, results in a contraction of the daily operating range in Hydro generation relative to the load shape – K Factor > 1, results in expanding the daily operating range in Hydro generation relative to the load shape 16 Negative K Factor result in Hydro generation inversely proportional to load Note: Daily average is equal to monthly average

K Factor - Daily Allocation (PLF) High K Factors leads to greater operational flexibility that historic operations Lower K Factor reduce the Hydro generation daily volatility 17 Modeling Objective: Lower K Factor reduce the Hydro generation daily volatility K Factor for Avg – Grand Coulee: 2.44 – Core Columbia: 1.44 Develop K Factor for aggregated projects versus individual project Desired new feature: A means to set daily upper and lower limits to bound daily allocation by month

Calculating K Factor The reference frame for PLF is the average monthly load and Hydro generation K Factor:= Slope of – Y= Hydro Gen(Hr i)/Avg Mo Hydro Gen – X:= Load(Hr i)/Avg Mo Load – Example K:= Is their a simpler way to calculate K?

Alternative Method for Calc K Factor You only need two data points to calculate a slope: – Lower Point: The average weekday minimum Hydro and load – Higher Point: The average weekday maximum Hydro and load The dark red line uses the weekday daily min and max 19 Observation: There can be significant volatility in min generation Consider using a multi hour average for min and max (The Green Line use the avg min and max 3 hour) The avg WKD min/max do not set operational min/max rating

Two Point K Factor If Slope is all we need: = Delta(Y Axis)/Delta(X Axis) Delta(Y Axis) and Delta(X Axis) can be independently calculated K Factor can be split into two components: – Hydro K’ [Delta(Y Axis)]: Is tailored to the desired average weekday operating range – Load K’ [Delta(X Axis)]: Is based on the load Hydro is to be dispatched to Formula: Feedback loop: Calculate resulting hourly Hydro generation based on K to determine if its hourly shape mimic desired historic behavior 20

Need Spin? Maximum operational may be lower than physical capability – Typically the available energy runs out serving load/obligation prior to meeting maximum physical capability If the desired maximum operating rating limits a projects ability to provide spin, consider modeling a spinning reserve unit: 21 – Model a second unit representing this project ability to provide spinning reserves: Max Rating: Spin capability Min Rating: Zero Cost: High >= $50,000/MWh – For simplicity set spin reserve capability to zero on original Hydro project

Developing K Values for PLF 22

Develop Modeling Hydro Coefficient Split Columbia River Projects into two groups: – Upper Columbia: Coulee through Priest Rapids (7 projects) – Lower Columbia: McNary through Bonneville (4 projects) – Note: The operating range per unit of generation for Upper Columbia is greater than Lower Columbia – Projects that are not proportional to load are modeled as a flat monthly shape (Previously modeled as hourly shapes) Split the calendar year into two seasons: – Spring Run-Off: Apr-Jul – Balance of year: Jan-Mar, and Aug-Dec Based Hydro operation on average operating from : – Calculate coefficient for each year then average resulting values 23

Summary of Modeling Change Split the 11 projects into upper and lower Columbia River to calculate PLF coefficients and compare to expected operations – Upper Columbia: Coulee through Priest Rapids – Lower Columbia: McNary through Bonneville 24 Use a flat monthly generation shape for previously hourly shapes K:=0 Objective Take a desired operating year and have it’s monthly operation conform to operation from

Min/Max Polynomial and Hydro K’ Polynomial used to determine min and max ratings assume: – Daily max is based on the average of the maximum 3 to 4 hours – Daily min is based on the average of the minimum 3 to 4 hours – Weekdays only (Weekend data is excluded from the poly) 25 Calc Hydro K’: Use target average monthly generation with the appropriate seasonal curve to calculate min and max rating used in calculating Hydro K’

Calculate Operational Min/Max Ratings Calc operational min and max rating based on historic operations – Base min rating on min gen curve at a 15% probability and max on the max gen curve at 85% probability – Use the target average monthly generation for the average – The StDev is based on: Backcast use actual StDev Forecast use calc StDev based on operations 26

Adjustments Calc min rating is greater than or equal to 0 Calc min rating is less than or equal to physical max Using polynomial: Adjustment are made to Outlier data points (outside the operating range of the polynomial) – This is driven by high spring run-off during – The adjustments are: – Operating range was locked at the limiting bounds (upper or lower operating range of the polynomial) – The relative location of operating range is applied to the target operating Min Rating:= (Target Gen aMW)*bound[(Avg – Min)/(Max – Min) 27

Calculate K Calc Load K’ based on modeled load: Calculate: 28 Example K Values

Error Check 2013 Backcast 29 Compare calculated hourly weekday generation shape with historic operation for accuracy in duplicating hourly shape (hour ending 1-24) 2013 backcast matches actual operations

Error Check 2010 Backcast 30 Compare calculated hourly weekday generation shape with historic operation for accuracy in duplicating hourly shape (hour ending 1-24) 2010 backcast matches actual operations

Error Check 2010 Forecast 31 Compare calculated hourly weekday generation shape with historic operation for accuracy in duplicating hourly shape (hour ending 1-24) Reduced operating range can be seen in the above chart

Hydro Dispatch Against Load – Wind 32

Hydro Dispatch Load - Wind Relative to load, wind generation serves up to 64% of BPA daily load in 2014 or 20% of annual load Changing from “Load” to “Load – Wind” increases the deviation in daily a factor of 2.7 The expanded daily StDev directly impacts the daily allocation of Hydro generation. This impact can be amplified when K is > 1 33 Installed Wind Capacity in BPA for ,515 MW

Hydro Dispatch Load - Wind The top right chart BPA load vs Core Columbia gen (R^2=0.616) The bottom right chart: BPA Load – Wind vs Core Columbia gen (R^2:= 0.252) Bottom chart show daily Hydro generation tracking BPA load 34

Hydro Dispatch Load - Wind Compare backcasting April 2013 Hydro operation: – Against Load: A better match against actual Hydro operation – Against Load-Wind: When wind comes on and off for a couple of days the result Hydro diverges from actual Hydro generation 35

Hydro Dispatch Load – Wind What we want: – Daily Hydro allocation to reflect historical operations There is no one clean answer when determining monthly Hydro allocation – Intra day Hydro generation to take into account generation from non- dispatchable supply (Wind and Solar) when dispatching Competing issues: – K values based on Load has a tendency to be higher, resulting in increase volatility in daily Hydro allocation – K values based on Load –Wind tend to be lower while the volatility in load increases: resulting mixed results, i.e. volatility daily Hydro allocation may increase or may decrease K based on Load is more predictable while Load – Wind increase volatility in monthly allocation 36

Summary of Findings 37

Summary of Findings Current modeling does not reflect operational changes on the Columbia River which starting in 2011 – Base Hydro operating on year for any forecast year Individual project Hydro generation are not always proportional to load but Net Columbia, Upper Columbia and Lower Columbia are proportional to load Individual project that are not proportional to load are modeled as a flat monthly profile (Base Load) Calculating coefficients for two aggregated systems: – Upper Columbia: Coulee to Priest Rapids – Lower Columbia: McNary to Bonneville 38

Summary of Findings The use of high K values result in inappropriate intra monthly allocation of daily Hydro generation – Develop K factors in a manor to minimize its value (Consider develop K Factors on an aggregate basis instead of individual) – The use of HTC can lower K value: For example: Splitting 50% of the dispatch range to HTC reduces K value by 50% Dispatching Hydro against “Load – Wind – Solar” – K based on “Load” is more predictable while “Load –Wind” increase volatility in monthly allocation 39

Hydro-Thermal Co-optimization (HTC) 40

HTC reshapes a share of PLF Hydro generation based on LMP The original equation for HTC – Where: C – Plant Capacity A – Range of plant generation (Plant Operating Range) This assumes a 50/50 split between PLF/HTC hence ½*A Re-writing where – HTC(Share) + PLF(Share) = 1 (Share of operating range) – A:= Range of Plant Gen:= C*OpRange(%) – ½:= HTC(Share) 41

Proposed GridView Improvements 42

Proposed GridView Improvements Load – Wind – Solar: Add two new dimensions that control how Load – Wind – Solar is set: – The ability to set Load – Wind – Solar by area/region – The ability to set a percentage (0% to 100%) of wind and solar that is subtracted from the load – Example: BPA: 20% Wind and 100% Solar CAISO: 100% Wind and 100% Solar A means to limit daily allocation of Hydro generation when K Factors is high – Example: Weekday limit between 110% and 90% of average daily generation. Weekend would allow a lower limit? 43

44 Kevin Harris (503)