Quantifying the Full Value of Hyypdropower in the ...mydocs.epri.com/docs/corporatedocuments/sectorpages... · TASK 3: Evaluate National Hydropower Participation in Ancillary Services

Quantifying the Full Value of Hydropower in the y pTransmission Grid

Tom KeyP j t MProject ManagerIndustry Review at NHA Annual MeetingApril 6, 2011

Quantifying the Full Value of Hydropower in the Transmission Grid

Industry Review Meeting Wednesday April 6, 2011, 1-4 PM New York Roomdust y e e eet g ed esday p 6, 0 , e o oo

Time Topic Presenter

1:00 p.m. Welcome, Meeting Objectives Introductions

Tom Key, EPRI

1:10 p.m. Project Update Progress in year 1 Deliverable status Plans for year 2

Lindsey Rogers, EPRI

Plans for year 2

1:30 p.m. Defining the Value of Hydropower Strategy for defining hydropower value Modeling overview and insights so far

Tom Key, EPRIDaniel Brooks, EPRI

Insights from case studies so far Input on Hydro in US Markets Input on Hydro in European Markets

Pat March, HPPiBrendan Kirby, Kirby ConsultingDick Fisher, Consultant/Voith

3:00 p.m. Industry Round Table: Defining Value Getting beyond a “cost-basis” approach. Reconciling power market differences. Affecting choices for capacity expansion.

All

2© 2011 Electric Power Research Institute, Inc. All rights reserved.

Others..

4:00 p.m. Adjourn

Industry Cost Share and Case Study Commitmentsy


Project Team

DOE Contracts ManagerDOE Technical Program Manager

Alejandro Moreno

EPRI Contracts Manager

David Morrisony

EPRI Project Manager

Thomas Key

Principal Investigator

Patrick March, HPPi

G id M d li d St di

Principal Investigator

Daniel Brooks, EPRI

DOE FFRDC Support

ORNL – Hydrologic Constraints

Grid Modeling and Studies

LCG Consulting

Sidart Deb

S i i J i

Hydropower Operation, Cost and Markets

HDR|DTA

Dr. Brennan Smith

Dr. Michael R. Starke

SNLA – Grids and MarketsSrinivas Jampani

Cascade Consulting

Charlie Clark, Tom Guardino

EPRI

Robert Rittase

Steve Brown

Brendan Kirby, Consultant

Markets

Dr. Abraham Ellis

Dr. Verne Loose

Dr Mark Ehlen


EPRI

Aidan Tuohy

Matt Rylander

Consultant Dr. Mark Ehlen

Project Update

2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1

Month 13 - 24Month 1 - 12PROJECT GANTT CHART

CONTRACT START

Confidential Studies

TASK 3 E l t N ti l H d P ti i ti i A ill S i M k t

TASK 2: Establish Wide-Area Modeling Approach and Policy Scenarios

CONTRACT START

TASK 1: Prepare Industry Case Studies

2a

1a 1b 1c

2b

3a 3b 3cTASK 3: Evaluate National Hydropower Participation in Ancillary Services Markets

TASK 5: Develop Data Base of Cost Elements for Development Options

TASK 4: Analyze Systemic Operating Constraints on Hydropower Resources

TASK 6: Develop and Compute Scenario Simulations for WECC Projects

4b

5b

3a 3b

4a 4c

6b

5a 5c

6a

3c

5d

TASK 7: Determine Effects of Alternative Policy Scenarios on Value of Hydropower


TASK 8: Define Strategies for Planning and Applying Hydropower Assets

TASK 9: Documentation and Dissemination of Results (See Project Milestones/Deliverables)

7b

8a

7a

ES Final

PROJECT MILESTONES/DELIVERABLESProject Review MeetingsIndustry Review Meetings

Internal Report Industry Review/Public Report



Progress so far

Public Reports– Task 3a- Role of Hydropower in Existing Markets (11/30/2010) y p g ( )

http://prod.sandia.gov/techlib/access-control.cgi/2011/111009.pdf– Task 2b- Modeling Approach and Base Case Scenario (12/30/2010)

Internal ReportsIndustry Review Task Report on plan for documenting scheduling and operating– Industry Review Task Report on plan for documenting scheduling and operating practices- LCG (10/31/2010)

– Detailed plan for the scope and content of the hydropower cost database-HDR|DTA (12/31/2010)I l T k R h i d l ORNL (3/14/2011)– Internal Task Report on the water operations model- ORNL (3/14/2011)

– Industry Review Task Report on description of technologies and preliminary cost elements for team review and input - HDR|DTA (3/31/2011)

– Industry Review Task Report providing detailed definition and modeling plans for all y p p g g pscenarios including specifications of inputs and expected outputs- LCG (3/31/2011)

Other Milestones First Quarter 2011– Site Visits & Plant Case Studies (TVA, Ameren, NYPA, Exelon)

M h 14 & 15 M d li W k h f WECC


– March 14 & 15 Modeling Workshop for WECC– NHA Industry Review Meeting

Project Update

2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1

Month 13 - 24Month 1 - 12PROJECT GANTT CHART

CONTRACT START

Confidential Studies

TASK 3 E l t N ti l H d P ti i ti i A ill S i M k t

TASK 2: Establish Wide-Area Modeling Approach and Policy Scenarios

CONTRACT START

TASK 1: Prepare Industry Case Studies

2a

1a 1b 1c

2b

3a 3b 3cTASK 3: Evaluate National Hydropower Participation in Ancillary Services Markets

TASK 5: Develop Data Base of Cost Elements for Development Options

TASK 4: Analyze Systemic Operating Constraints on Hydropower Resources


4b

5b

3a 3b

4a 4c

6b

5a 5c

6a

3c

5d

TASK 7: Determine Effects of Alternative Policy Scenarios on Value of Hydropower

p p j

TASK 8: Define Strategies for Planning and Applying Hydropower Assets

TASK 9: Documentation and Dissemination of Results (See Project Milestones/Deliverables)

7b

8a

7a

ES Final

PROJECT MILESTONES/DELIVERABLESProject Review MeetingsIndustry Review Meetings




Year 2 Reports & Project Milestone

Public Reports– Task 5c- Plant Cost Elements (5/30/2011)– Task 3b- Opportunities in Future Markets (6/30/2011)– Task 4c- Systemic Plant Operating Constraints (9/30/2011) – Task 6b- Modeling Results for Future Scenarios (9/30/2011)

Task 1c Case Studies on Plant Operations and Utilization (9/30/2011)– Task 1c- Case Studies on Plant Operations and Utilization (9/30/2011)– Task 8a- Planning and Operating Strategies (executive summary) (11/30/2011)– Task 9- Quantifying the Value of Hydropower in the Electric Grid: Final Report

(1/31/2012)I t l R tInternal Reports

– Internal Task Report with plant owners on Columbia (WECC) water operations model and verification of UPLAN hydro model- ORNL (6/30/2011)

– Internal Reports summarizing results after conducting site visits, completing data l i d i b k h d d li d kanalysis and reporting back to operators to support hydro modeling and market

participation reports- HPPi (8/31/2011)Other Milestones

– July 18: Industry Review meeting in conjunction with Hydrovision 2011- Sacramento, CA


– September-October: East Hydropower Modeling Workshop- Review hydro participation eastern interconnect- Date and Location TBD


Project Approach/Strategy for Defining Hydropower Valuey p

Year One:• Conduct specific plant studies to determine operation (HPPi)Conduct specific plant studies to determine operation (HPPi)• Model WECC electric sector to determine value of (LCG):

– Energy arbitrage value with LMP– Ancillary ServicesAncillary Services – Consider CO2, RPS, and future generation mix

• Determine cost of future hydro technology/assets (HDR|DTA)• Evaluate today’s market rules (Sandia)• Evaluate today s market rules (Sandia)

Year Two:• Run scenarios to determine future value (LCG)• Consider other values e g freq regulation reliability energy security (All)• Consider other values e.g. freq. regulation, reliability energy security (All)• Factor in systemic constraints and ways to minimize (ORNL)• Synthesis into valuing/methods report comparing alternatives (All)


Challenges Ahead….Identified at WECC Workshop March 14-15, 2011p ,

• Define metrics/methods that will best quantify value of hydropowerhydropower

• Address questions about “cost-based” modeling and consider exogenous or other societal value basisg

• Better engage WECC, plant owners and balancing authorities to confirm plant modeling assumptionsC id th f t t f t d li• Consider other factors to energy futures modeling– Include potential limits on gas transmission– Define higher future NG cost scenarios– Define higher future NG cost scenarios – Adjust reserve requirements for future wind and solar

variability/uncertainty


– Consider higher RPS…..and look out to 2030

Capacity Expansion Modeling to Define Future Generation Mix in WECC

• The Business As Usual scenario, with reference values and trends (e.g. moderate demand growth, existing renewable Reference Case ( g g genergy mandates)

Reference Case

• This scenario will model a fast, high growth recovery in demand from the economic downturn

High Demand/Energy* from the economic downturnDemand/Energy

• Requires 20% renewable energy for entire WECC• 33% RPS in CaliforniaFederal RPS*

• Models a cap on future CO2 emissions• Waxman-Markey bill for guidance

Carbon Constrained*Constrained

• Combine the impact of two future policy scenarios into one future

• Federal RPS + Carbon ConstrainedCombined Policy*


* EPRI's NESSIE model shall be used to develop the expansion plan for these scenarios.

Scenario Planning Energy Futures

Reference Case High Demand/Energy Federal RPS Carbon Constrained Combined Policy

LCG PLATO Reference Values

Variable Unit Low (L) Mid (M) High (H)

Existing state Renewable Penetration as a Percentage of Total Energy Delivered*

Proposed Futures

• California RPS: 33% of energy

• WECC Mandate: 15% of energy

California RPS % - requirements in California - 33% RPS

-

WECC Mandate %Existing state requirements

20% by 2020 -

energy

• Average natural gas price: $7.1/MMBtu

Natural Gas ($/MMBtu)LCG PLATO Ref. -

20%LCG PLATO Ref.

LCG PLATO Ref. + 20%

Coal ($/MMBtu)LCG PLATO Ref. -

20%LCG PLATO Ref.


Fuel Cost

• Emissions• CO2 price: $0/ton• SO2 price: $58/ton• NOx price:

$3,000/ton (NOx season)$1 500/ton (Non NOx

Uranium ($/MMBtu)LCG PLATO Ref. -

20%LCG PLATO Ref.


SO2 ($/ton) LCG PLATO Ref.NOx ($/ton) LCG PLATO Ref.

Emissions Costs


$1,500/ton (Non-NOxseason)

($ )CO2 ($/ton) 0 34

LCG PLATO - Plants, Loads, Assets, Transmission and Operations

EIA (AEO) Natural Gas Price Estimates


NG Infrastructure


Reference Case Inputs: Commodity Prices

Our intention is to determine “non controversial” commodity prices for the reference case and then investigate different prices in Task 6.

• 2020 Commodity Prices ($/MMBtu)

12 0

Natural Gas Prices $/MMBtu (2008‐2020)

– Natural Gas = 7.1

– Light Oil = 10

– Heavy Oil = 8

10.3

8.2

5 5 5.9 6.2 6.5 6.8 7.1

6 0

8.0

10.0

12.0

/MMBtu

– Heavy Oil = 8

– Coal = 1.5

– Uranium = 0.6

4.7 4.54.9 5.1 5.3 5.5

2.0

4.0

6.0$/

• CO2 emission allowances = $0/ton (reference case)

0.0

2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020


( )

• Sources: EIA, NYMEX Futures

EIA Data on WECC PS Utilization

W E C C P u m p in g

5000000

6000000

W addellG ianelli

3000000

4000000

Pum

ped

Therm alitoO neillM t E lbertM orm on F latE as twood

2000000

3000000

Annu

al M

Wh Hors e M es a

Helm sG rand CouleeF lat ironE dward Hy att

0

1000000

1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

Cas taicCabin Creek


1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

Ye a r

Capacity Additons by Decade Thru 2007

300,000 120%

250,000 100%

150,000

200,000

60%

80%

100,000 40%

‐

50,000

0%

20%

1890 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000

Coal Oil

Gas NuclearHydro Bio


Geo WindSolar Percent capacity built since year

Hydro-related databases and data (Verne Loose, Sandia), )

Operational data and databases

•2010 ISO/RTO Metrics Report - hydro use by ISOs for all ISOs

•Bureau of Reclamation website @ http://www.usbr.gov/power/data/data.html

•1995-2007 capacity, gross generation, net generation; service records all facilitiesp y g g g

•Facility generation by Month (rolling for last 10 years)

•2007 Reclamation Data book has operational data on all facilities (might be new?)

•Power performance data sliced by size of unit and region•Power performance data sliced by size of unit and region

•WECC TEPPC website @ www.wecc.biz detailed navigation and credentials required

•USACE website @ http://www.nwd-wc.usace.army.mil/perl/dataquery.pl?k=id:GCL

•Has some operational data including hourly generation, pumped water, power produced, etc. however access to data is awkward and would be tedious

•Chelan and Grant Counties sites have bid data but only in aggregate terms


•http://www.chelanpud.org/power-auction-product-description.html

Hydro data and databases, cont’d.

Operational data and databases

•EIA http://www.eia.doe.gov/cneaf/electricity/epm/table1_1.html

•aggregate hydro data that can be broken down by state, sector, type of owner

Other data and databases

•http://www.nwd-wc.usace.army.mil/tmt/

•stream flow and water quality for Columbia River.

•http://www nwrfc noaa gov/http://www.nwrfc.noaa.gov/

•contains detailed hydrological data

•http://www.nwd-wc.usace.army.mil/report/total.html

•mostly water quality

•http://waterwatch.usgs.gov/new/index.php?r=17&id=real

•stream flow data


Synthesizing Results

Task 7 - Determine Effects of Alternative Policy, Market Rules & Scenarios on Value of Hydropower OutlineRules & Scenarios on Value of Hydropower Outline

• Market treatment of ancillary services– Current treatment and potential changes in ancillaryCurrent treatment and potential changes in ancillary

services- Kirby Consulting– Enhancements in plant utilization and optimization-

HPPiHPPi– Gaps in regulatory, market and scheduling structures-

Sandia• Future Scenario analysis of energy policy- LCG• Constraints on water usage- ORNL


Synthesizing Results to Define Value

Current operations and optimizing plant performance (HPPi)

Modeling of current role of hydro (LCG)

p ( )

Recommendations Modeling Future

Scenarios of hydro Valuebased on gaps in reg, market and scheduling

structures (Sandia)

(LCG)

Today’s Market treatment oftreatment of

ancillary services (Kirby)


Also considering future hydro costs (HDR|DTA) & water constraints (ORNL)

WECC Production Cost Model

Necessary Model Components• Transmission network

Detailed WECC Grid Simulation Model Needed to Quantify Hydro ValueTransmission network

– Associated physical constraints

• Conventional generation– Physical & economic characteristics

Needed to Quantify Hydro Value

– Fuel Prices– Participation in A/S

• Conventional & Pumped Storage Model– Conventional parameters

Markets&

TransmissionGeneration

– Conventional parameters– Water availability– Non-power constraints

• Wind and PV

&Physics

Temporal– Spatial and temporal characteristics

• Energy and A/S Markets– Relative economics and market rules

TemporalConstraints


– A/S Requirements

LCG UPLAN Network Power Model (NPM)

• LCG’s UPLAN NPM platform– Security Constrained Unit Commit &Security Constrained Unit Commit &

Econ Dispatch (SCUC/SCED)– Co-optimized Energy & A/S Markets– Hourly Resolution

• A/S Provision– Reg Up/Dn, Spin, Non-Spin,

Replacement• Hydro ModelHydro Model

– Plant constraints– Schedules to accommodate variable

generation– Respond to price signals

• Pumped Storage Model– Price-driven logic

C id ffi i t


– Considers energy efficiency, storage limits, and transmission limitations

Study Footprint and BA Interaction

• Model spans all of WECC– 37 BAs individual BAs37 BAs individual BAs– Modeled as 12 coordinated sub-

regions

• Day-Ahead Unit Commitment– Commits generation to meet

area load – UC without regard to cost of– UC without regard to cost of

neighboring generation

• Real-Time Dispatchp– Available generation transferred to

surrounding BAs if economic – Transmission losses and hurdle rates

respected


respected

Study Year(s) and Scenarios/Sensitivities

• 2010 Reference CaseU d f d l lid ti / fid– Used for model validation/confidence

• 2020 Reference Case– 2019 WECC TEPPC transmission network– Generator characteristic data from LCG PLATO database

• EIA FERC 714 WECC et al• EIA, FERC 714, WECC, et. al.– Wind/PV build out to meet existing state RES for 2020– Existing plus Planned New Pumped Storage Plants

• Water Availability from EIA data

• 2020 Sensitivity Cases


• 2020 Sensitivity Cases

2010 Generation Resource Mix

WECC has a diverse mix of resources in 2010. Gas and Hydro provide much of the capacity followed by coal.

40,000

45,000

50,000

Others

Oil PetroleumHydro29%

Nuclear4%

WECC Capacity by Fuel Type : 2010

Hydro29%

Nuclear4%

WECC Capacity by Fuel Type : 2010 Generation 2,437 Units

D t il d t

25 000

30,000

35,000

,

Gas Based

Wind

l

29%

Oil Petroleum0%

Others2%

Solar1%

29%

Oil Petroleum0%

Others2%

Solar1%

Detailed parameters Economic Operational

Loads Historical BA loads scaled to the

15,000

20,000

25,000 Solar

Hydro

Nuclear

Coal Based17%

Gas Based41%

Wind6%

Coal Based17%

Gas Based41%

Wind6%

Historical BA loads scaled to the study years

Distributed to nodal level using load flow cases

‐

5,000

10,000 Coal Based

Annual Peak Demand (MW)


Comparison of 2010 & 2020 Installed Capacity

CC and CT technology additions to compensate for increasing demand and renewables

Category Diff (MW) Diff %Biomass 579 50%C l 460 1%

WECC Total100,000

120,000

Hydro

Solar

Wi d Coal 460 1%Combined Cycle 4,430 9%CT 5,131 25%CT Oil 2 0%Geothermal 2,253 76%Hydro 741 1%40,000

60,000

80,000 Wind

Pumped Storage

Geothermal

Biomass

NuclearMW

Hydro 741 1%IC ‐ 0%Nuclear ‐ 0%Pumped Storage ‐ 0%Solar 11,799 2469%Steam (1 812) ‐9%

‐

20,000

,Steam

IC

CT Oil

CT

Combined Cycle Steam (1,812) 9%Wind 11,860 105%

Figure: Installed Capacity in 2010 and 2020 by WECC sub‐region (MW)

2010 2020 2010 2020 2010 2020 2010 2020

AZ‐NM‐SNV CA‐MX US NWPP RMPA

Coal

WECC sub‐region


gu e: sta ed Capac ty 0 0 a d 0 0 by CC sub eg o ( )

2020 Reference Case Renewable Additions

2020 RPS Targets for WECC States and ProvincesAs a Percent of Energy Sales Subject to RPS

IdahoColoradoCalifornia

British ColumbiaArizona

Texas EPEOregon

New MexicoNevada

MontanaMexico (CFE)

0 5 10 15 20 25 30 35

AlbertaWyoming

WashingtonUtah

Texas‐EPE

% Breakdown of Renewables by Type ‐ WECC wide

0 5 10 15 20 25 30 35


Wind Solar Geothermal Biomass Small HydroBy Capacity 55.3% 25.7% 10.4% 4.3% 4.3%By Energy 43.7% 19.6% 22.7% 8.9% 5.1%

Characterization of Hydropower

• Conventional Hydro2006 EIA hi t i l thl it f t– 2006 EIA historical monthly capacity factors

– A/S capability Regulation, Spin, Non-Spin– Ramp rate (MW/Hr) – full load in 10 minutes

• Pumped Storage– Storage capacity (GWh): Weekly– Average Pumping size (MW)/Generating size = 0.8– Efficiency: 75%– A/S capability Regulation (only Gen mode existing; PlantA/S capability Regulation (only Gen mode existing; Plant

specific for expansion), Spin, Non-Spin– Ramp rate (MW/Hr) – full load in 10 minutes


• Non-power constraints incorporated only to extent reflected in monthly EIA data

UPLAN NPM Temporal Resolution

• Hourly-resolution simulation

• Intra-hour flexibility represented by including intra-hour A/S requirements procured through DA marketA/S requirements procured through DA market– Reg Up & Reg Dn– Spin & Non-Spin

• Model does not represent individual unit efficiency (heat rate or water efficiency) impacts of intra-hr variabilityrate or water efficiency) impacts of intra hr variability


Short-term Wind Forecast Error

• Used for fast schedulingscheduling

• Based on 10 minute wind data

• Forecast is 10• Forecast is 10 minute persistence

• Need to cover variability betweenvariability between the forecast and actual


Hour-ahead wind forecast error

• For intra-hour scheduling– Can effect reserves by non-optimum unit commitment when the forecast isCan effect reserves by non optimum unit commitment when the forecast is

high– A way to insure enough capacity is committed– Using the same procedure as the short-term forecast error calculationg p

• For hourly scheduling – Predicts additional regulation required for the hour


Incremental Operating Reserves for Wind

• Method for requiring additional operating reserves to maintain CPS1/CPS2 at similar pre wind levelsmaintain CPS1/CPS2 at similar pre-wind levels– regulating reserve based on short-term forecast error– regulating, spin, & supplemental reserve based onregulating, spin, & supplemental reserve based on

hour-ahead forecast error

• NREL Western Interconnect wind and wind forecast 10-min data

• 8760 reserve requirement time series developed for each sub-region incorporating additional reserve requirements


for variability and uncertainty of VG in sub-region

Remaining Modeling Improvements/Questions

• Validation of 2010 reference case against historical hydro data

• Include incremental intra-hr reserve requirements to cover variability/uncertainty of wind/PV

• 2020 Transmission Upgrades beyond TEPPC to allow utilization of existing and future pumped storage plants

• Review treatment of existing hydro plants– Non-Power constraints– Availability

• Gas prices and impact of limited gas line flexibility


Gas prices and impact of limited gas line flexibility

INSIGHTS FROM CASE STUDIESPat MarchPat MarchHPPi


Case Studies Task: Purpose and Project Integration

Knowledge gaps that this task addresses:● Understanding market-related and non-market operational

patterns● Quantifying suboptimization due to these operational patterns● Quantifying suboptimization due to these operational patterns● Comparing near-real-time operations with hourly averages

Integration of task results into overall HGS Project:Integration of task results into overall HGS Project:● Assisting the verification of the UPLAN model for WECC● Providing “rules of thumb” for market-related suboptimization to

inform model assumptions for future scenarios● Providing recommendations for further investigation


Technical Approach for Case Studies

Procedure:N ti t tilit ti i ti d d t fid ti lit t● Negotiate utility participation and data confidentiality agreements

● Conduct site visits, collect operational data, collect market data

● Conduct detailed performance analyses for each plant p y p

● Segregate data by operational pattern, conduct performance analyses

● Prepare confidential reports to utilities and HGS summary report using non-confidential resultsU i tUnique aspects:

● Utilization of optimization engine and automated data analysis engine to perform quantitative performance analyses

● Comparison of one-minute results with hourly averages

● Evaluation of multiple owner/operators, multiple market regions (and non-market regions), and multiple plant and unit types


multiple plant and unit types

Case Study Locations for Hydro Grid Services Project

New York Power Auth.Blenheim-Gilboa

NYISO


NYISO


NYISO


NYISO

USACE

SWPA MISO

USACEHarry S. Truman

AmerenUEOsageMISO

AmerenUEOsageMISO

AmerenUETaum Sauk

MISO

AmerenUETaum Sauk

MISO

Chelan County PUDRocky Reach

WECC


WECC


WECC


WECC

AmerenUEOsageMISO

AmerenUEOsageMISO

AmerenUETaum Sauk

MISO

AmerenUETaum Sauk

MISO

New York Power Auth.Bl h i Gilb

New York Power Auth.Blenheim-GilboaNew York Power Auth.

Bl h i GilbExelon Generation

Muddy Run-SWPA, MISO Blenheim-GilboaNYISO

Blenheim-GilboaNYISOBlenheim-Gilboa

NYISOMuddy Run-

PJM


WECC


WECC


WECC

Exelon GenerationConowingo

PJM

Pacific Gas & ElectricHelms

CAISO, WECC

Pacific Gas & ElectricHelms

CAISO, WECC

Duke EnergyBad CreekSoutheast




New York Power Auth.New York Power Auth.BlenheimGilboaNew York Power Auth.TVARaccoon Mountain


Blenheim-GilboaNYISO

Blenheim-GilboaNYISOBlenheim-Gilboa

NYISORaccoon Mountain-

SoutheastConventional HydroPumped-Storage

Example of Market Effects on Plant Operation


Typical Operational Patterns for Generation and Pumping

Generation Energy vs Hour of Day

9,000

10,000Jan-Hourly Generation EnergyFeb Hourly Generation Energy

5,000

6,000

7,000

8,000

9,000

rgy

(MW

h)

Feb-Hourly Generation EnergyMar-Hourly Generation EnergyApr-Hourly Generation EnergyMay-Hourly Generation EnergyJun-Hourly Generation EnergyJul-Hourly Generation EnergyAug-Hourly Generation EnergySep-Hourly Generation Energy

0

1,000

2,000

3,000

4,000

0 5 10 15 20 25

Ener Oct-Hourly Generation Energy

Nov-Hourly Generation EnergyDec-Hourly Generation Energy

0 5 10 15 20 25

HourScroll Data '

Show AllSelect Series 'X-Axis Scale 'Pump Energy vs Hour of Day

20,000

25,000Jan-Hourly Pump Energy

Feb-Hourly Pump Energy

Mar-Hourly Pump Energy

10,000

15,000

Ener

gy (M

Wh)

Apr-Hourly Pump Energy

May-Hourly Pump Energy

Jun-Hourly Pump Energy

Jul-Hourly Pump Energy

Aug-Hourly Pump Energy

Sep-Hourly Pump Energy


0

5,000

0 5 10 15 20 25

Hour

Oct-Hourly Pump Energy

Nov-Hourly Pump Energy

Dec-Hourly Pump Energy

Sc oll Data ' Select Se ies 'X A is Scale '

Process for Performance Analyses

OHPI Data Analysis ScriptOHPI Data Analysis ScriptOHPI Data Analysis ScriptOHPI Data Analysis ScriptOHPI Data Analysis ScriptOHPI Data Analysis ScriptOHPI Data Analysis Script

Archival Data (WaterView)

Time, Flow, Power, Gate, Blade, Head

OHPI Data Analysis Script















DataWolff (Automated Data A l i S t )

Unit Characteristics File (WaterView)

Expected Flow, Power for Given HeadDataWolff

(Automated Data A l i S t )














Expected Flow, Power for Given Head

Analysis System)

Calculation Libraries

•Optimization Module (WaterView)•Averaging, Segmenting, Integration Routines

Analysis System)



Analysis System)



Analysis System)



Analysis System)



Analysis System)


•Optimization Module (WaterView)•Averaging, Segmenting, Integration Routines g g, g g, g(DataWolff)

Analysis Results

Indicators - LEO, LRO, WCO for l d i id if i

g g, g g, g(DataWolff)

Analysis Results


Note:LEO = Lost Energy OpportunityLRO = Lost Revenue Opportunity


Analysis Results



Analysis Results



Analysis Results



Analysis Results


Note:LEO = Lost Energy OpportunityLRO = Lost Revenue Opportunity


system, plants, and units, identifying major energy losses within system.system, plants, and units, identifying major energy losses within system.

LRO = Lost Revenue OpportunityWCO = Water Conservation Opportunity

system, plants, and units, identifying major energy losses within system.system, plants, and units, identifying major energy losses within system.system, plants, and units, identifying major energy losses within system.system, plants, and units, identifying major energy losses within system.

LRO = Lost Revenue OpportunityWCO = Water Conservation Opportunity

Typical Plant CharacteristicsOverall Plant Efficiency versus Head and Power

Efficiency vs. Power100

95

1140 ft

1200 ft

1260 ft

90

95

ency

(%)

85

90

Effic

ie

85


800 500 1,000 1,500 2,000 2,500 3,000 3,500

Power (MW)

Example of Sampling Interval Analyses

Calculated Improvement versus Sampling Interval3.5

P t I t P t Ch i I t

2

2.5

3

)

Percent Improvement Percent Change in Improvement

0.5

1

1.5(%

-0.5

01 Min Snapshot 5 Min Snapshot 15 Min Snapshot 30 Min Snapshot Hourly Snapshot Hourly Avg


Non-Market Example 1 ( Scheduling Analysis)

Actual vs Optimized Energy, Head 1175

7000 100

5000

6000

7000

d 11

75

94

96

98

100

ency

(%)

3000

4000

2010

-Ene

rgy

Hea

d

86

88

90

92

miz

ed P

lant

Effi

cie

0

1000

2000

0 200 400 600 800 1000 1200 1400 1600 1800

Apr

il

80

82

84

86

Opt

im

0 200 400 600 800 1000 1200 1400 1600 1800

Power (MW)

Scroll Data 'Show A

Select Series 'X-Axis Scale '


Non-Market Example 2 (Operational Efficiency Analysis)

Load and Eff Improvement vs Time

500.0

600.0

4.00

4.50

5.00

200.0

300.0

400.0

Uni

t Pow

er (M

W)

1.50

2.00

2.50

3.00

3.50

ency

Impr

ovem

ent (

%)

0.0

100.0

04/03/09 09:09 04/03/09 10:21 04/03/09 11:33 04/03/09 12:45 04/03/09 13:57 04/03/09 15:09 04/03/09 16:21 04/03/09 17:33 04/03/09 18:45 04/03/09 19:57

Time

U

0.00

0.50

1.00 Effic

ie

Scroll Data ' Select Series 'X Axis Scale ' TimeScroll Data Show All

Select Series X-Axis Scale


Market Example 1 ( Scheduling Analysis)

Actual vs Optimized Energy8000 95

6000

7000

8000

90

95

)

4000

5000

nerg

y H

ead

860

85

ant E

ffici

ency

(%)

2000

3000

July

2010

-E

80 Opt

imiz

ed P

la

0

1000

-100 0 100 200 300 400 500 600 700

P (MW)

75


Power (MW)Scroll Data '

Show AlSelect Series '

Example Showing Volumetrically Derived Unit Characteristics

Flow vs Power6,000

Corrected Flow

2,000

3,000

4,000

5,000

Flow

(cfs

)

Expected FlowFlow - Curve Fit (cfs)

0

1,000

,

100 120 140 160 180 200 220 240 260 280 300

Power (MW)

Efficiency vs Power

85

90

95

100Volumetric Efficiency (cfs)Expected EfficiencyEfficiency-Curve Fit

60

65

70

75

80

Eff (

%)


60100 120 140 160 180 200 220 240 260 280 300

Power (MW)

Market Example 2 (Scheduling Analysis)

Actual vs Optimized Energy

4000

4500

ad

95

cy

2000

2500

3000

3500

010-

Ener

gy H

ea11

00 85

90

d Pl

ant E

ffici

enc

(%)

500

1000

1500

Sept

embe

r2

80

Opt

imiz

ed

0-200 0 200 400 600 800 1000 1200 1400 1600

Power (MW)

75

Scroll Data 'Show All

Select Series 'X-Axis Scale '


Market Example 2 (Operational Efficiency Analysis)

Load and Eff Improvement vs Time

300

350

400

16.0

18.0

20.0

%)

150

200

250

nit1

-Act

Uni

tPow

er

8.0

10.0

12.0

14.0

ency

Impr

ovem

ent (

%

0

50

100

11/10/08 07:37 11/10/08 08:49 11/10/08 10:01 11/10/08 11:13 11/10/08 12:25

U

0.0

2.0

4.0

6.0

Effic

ie

TimeScroll Data '

Show AllSelect Series 'X-Axis Scale '


Market Example 3 (Scheduling Analysis, 95 ft GH, Non-aerating Operation in May)Non aerating Operation in May)

9516000


9012000

14000

Non-aerating Operation

858000

10000

ant E

ffici

ency

(%)

Hea

d 95

804000

6000

Opt

imiz

ed P

la

May

2010

-Ene

rgy

H

75

80

0

2000

4000


750-50 0 50 100 150 200 250 300 350 400

Power (MW)

Market Example 3 (Scheduling Analysis, 95 ft GH, Aerating Operation in July)g p y)

9516000


Aerating Operation

9012000

14000

Aerating Operation

858000

10000

Plan

t Effi

cien

cy (%

)

gy H

ead

95

804000

6000

Opt

imiz

ed

July

2010

-Ene

r g

750

2000

-50 0 50 100 150 200 250 300 350 400


50 0 50 100 150 200 250 300 350 400

Power (MW)

Preliminary Results from Case Studies

● Markets (particularly ancillary services markets) can lead to significant energy suboptimization of hydro assets at the unit level and the plant level suboptimization of hydro assets at the unit level and the plant level

● Profitability increases, but

● Quantitative maintenance cost increases are unknown

● Environmental operations can lead to significant energy suboptimization of hydro assets at the unit and plant levels

● Markets can lead to significant suboptimization of multiple hydro projects sharing a water resource

● “Smart” markets sho ld better address energ limited reso rces incl ding ● “Smart” markets should better address energy limited resources, including pumped-storage

● Opportunities for low-cost production improvement exist in both market and


pp p pnon-market environments

OPERATIONS IN US MARKETS

Brendan KirbyBrendan KirbyKirby Consulting


Power Systems Economics & Markets Define The “Need” For Energy Storage

• Pumped storage is an ideal power system resource– Flexible in both directions

gy g

– Fast and accurate• Wind and solar add variability and uncertainty to the power

system• Storage can help mitigate both variability and uncertaintyThe “need” for storage is an economic choice among

competing alternatives– Demand response– Transmission– Flexible generation– Improved operational practices

• Storage should (almost) always be used as a system resource rather than balancing wind or solar


Changed System Conditions

• Energy arbitrage less attractive than in 1980s– Dramatic drop in gas price– Increased efficiency of CCGTs and CTs

Reduced capital cost for CCGTs and CTs– Reduced capital cost for CCGTs and CTs• (Increased capital cost of pumped storage)

– Gas is often on the margin at nightGas is often on the margin at night• Wind and solar increase variability• Response valued through ancillary services and

hourly/sub-hourly energy markets• Markets/reliability rules may not appropriately consider

inter-temporal storage constraints


inter-temporal storage constraints

Power System Values Response to Variability and Uncertainty

• Ancillary services– Regulation: minute-to-minute AGC response

y

Regulation: minute to minute AGC response– Spinning reserve: On line, full response in 10 min– Non-spin: Full response in 10 min– Supplemental: Full response in 30 min

• Energy markets– Bilateral– Day-ahead hourly

Markets provide transparencyWholesale energy and ancillary

– Hour-ahead hourly– Subhourly

• Other servicesCapacity

service markets cover >½ of the U.S. load

Same needs exist in non-– Capacity– Blackstart– Voltage support and dynamic reactive– T&D deferral

Same needs exist in nonmarket areas


– T&D deferral

Maximize Pumped Storage Profits With Energy & Ancillary Service Markets

• Power system values flexibility

Energy & Ancillary Service Markets

Power system values flexibility– Hour-ahead energy markets are more volatile than day-

ahead• 5 minute markets are even more volatile

– Regulation costs more than spinning reserve which costs more than non spincosts more than non-spin

– Prices change hourly• Maximize profits by selling the most profitable mix each p y g p

hour


2002 2003 2004 2005 2006 2007 2008 2009 2010

Ancillary Services Show a

Annual Average $/MW-hr California (Reg = up + dn)

Regulation 26.9 35.5 28.7 35.2 38.5 26.1 33.4 12.6 10.6 Spin 4.3 6.4 7.9 9.9 8.4 4.5 6.0 3.9 4.1

Non Spin 1 8 3 6 4 7 3 2 2 5 2 8 1 3 1 4 0 6Show a Consistent

Pattern

Non-Spin 1.8 3.6 4.7 3.2 2.5 2.8 1.3 1.4 0.6 Replacement 0.90 2.9 2.5 1.9 1.5 2.0 1.4

ERCOT (Reg = up + dn) Regulation 16.9 22.6 38.6 25.2 21.4 43.1 17.0 18.1 Responsive 7.3 8.3 16.6 14.6 12.6 27.2 10.0 9.1

Year to Year R i t

Non-Spin 3.2 1.9 6.1 4.2 3.0 4.4 2.3 4.3 New York (east)

Regulation 18.6 28.3 22.6 39.6 55.7 56.3 59.5 37.2 28.8 Spin 3.0 4.3 2.4 7.6 8.4 6.8 10.1 5.1 6.2

Non Spin 1.5 1.0 0.3 1.5 2.3 2.7 3.1 2.5 2.3– Region to Region

Non Spin 1.5 1.0 0.3 1.5 2.3 2.7 3.1 2.5 2.3 30 Minute 1.2 1.0 0.3 0.4 0.6 0.9 1.1 0.5 0.1

MISO (day ahead) Regulation 12.3 12.2

Spin 4.0 4.0 N S i 0 3 1 5

Quicker Pays More

Non Spin 0.3 1.5 New England (Reg +”mileage”)

Regulation 54.64 30.22 22.26 12.65 13.75 9.26 7.07 Spin 0.27 0.41 1.67 0.71 1.75

10 Minute 0.13 0.34 1.21 0.47 1.15


30 Minute 0.01 0.09 0.06 0.08 0.42

Energy Only PS Net Income & CyclingEnergy Only PS Net Income & Cycling


MISO 2009

Power System Values Flexibility


Preliminary Energy & Ancillary Service Results:

$/KW/Yr Total Energy Regulation Spin

MISO 2009 $40.63 $40.63

Energy & AS$49.89122%

$28.6672%

$9.4222%

$11.8129%122% 72% 22% 29%

NYISO 2009 $26.73 $26.73

Energy & AS$60.25 $10.27 $33.80 $16.18

Energy & AS 225% 38% 126% 61%

NYISO 2008 $49.39 $49.39

$97 15 $19 56 $54 30 $23 29Energy & AS

$97.15197%

$19.5640%

$54.30110%

$23.2947%

•Ancillary Services during generation only


•$5/MWH minimum spread – 80% round trip efficiency

•16 hr storage

5 Minute Energy Markets May Offer Additional Profit Potential

• 2010 NYISO annual average energy prices:$ /– $42.05/MWH Day-ahead

– $42.82/MWH Hour-ahead$41 81/MWH 5 minute– $41.81/MWH 5-minute

• Average within-hour price range for 5-minute energy: $39.99/MWH

• NYISO settles on 5 minute prices– Other markets settle on hourly average


Hydropower inHydropower in European M k tMarketsRICHARD FISHER & JIRI KOUTNIKVOITH HYDROVOITH HYDRO


Comparisons, Europe to US

CanadaCanada

US



Wind Power Production in the EU – TWH

Share of consumption according to the NREAPS


IEWA:EU Energy Policy To 2050



Comparisons, Europe to US ?


Source: US Department of Energy

Total Generation Comparisons, Europe to US

US % Europe %

Carbon awareness Low HighFeed in Tariff Policy Some Yes

% renewabes 2000 9.4 13.9% renewables 2010 10.0 19.0% renewables 2020 13.7 32.0

% wind 2000 0 2 0 7% wind 2000 0.2 0.7% wind 2010 2.2 5.0% wind 2020 3.5 14.0

% Hydro 2000 7.0 10.6% Hydro 2010 6.0 10.2% Hydro 2020 5.9 10.0


IEWA:EU Energy Policy To 2050

EIA: International Energy Outlook 2010, 2011

Volatility of wind & solar generation - 2010


Source: REW: New Technologies 10-26-2010

Forecast wind power – next hours

Wind power

put i

n M

WO

utp


Source: RWTH, Prof. Sauer

Feb 3 Mar 2

Grid requirements – grid code 2000 in Europe

• UCPTE (DVG) requirements– Primary control (second reserve (Power Quality) ) – ensures stable powerPrimary control (second reserve (Power Quality) ) ensures stable power

supply; (5% power increase in 30 s / 2,5% power increase in 5s)– Secondary control (minutes reserve (Bridging Power) ) – frequency error

compensation– Tertiary control (Energy Management) – covering of large power

differences (seasonal changes)

• 5-step-plan– step 1 49,8Hz Alarm, Usage of existing power, pump shut-off– step 2 49,0Hz 15-20% load rejection of the system load– step 3 48,7Hz the next 15-20% load rejection of the system load– step 4 48,4Hz the next 15-20% load rejection of the system load– step 5 47,5Hz Disconnection of the power plants from the grid


4696e

Speed of Response of Different Conventional Solutions

Minimum Load Ramp Rate Type Minimum Load

Generating [% power per minute]

CCGT ~50% 2.5%

Gas Turbines >25% 4%

Coal >25% 1%

Nuclear ~50% 1.5%

Pumped Storage(conventional hydro) > 40% 100%

N t S i i t t diti f P d St H t t t diti f th


Notes: Spinning reserve start condition for Pumped Storage, Hot start condition for others

Grid power control needs and pumped storage solutionsp p g

5% power increase

European i tms s minµs hours days

Power Quality Bridging Power Energy Management

requirement

Renewables - intermittency

Scheduling / economics / emissions

Transmission bottlenecks

Grid harmonics

Grid faults / stability

Conventional PS Units

Variable Speed & Ternary PS Units

Advanced Conventional PS Units

time scale


time scale

Possible PS Unit Configurations Depending on Regulation Responsiveness and Grid Needsg p

– Conventional reversible unit & f

SlowerLess Flexible– Fast & frequent response reversible unit

– Conventional units in short circuit arrangementVariable Speed reversible unit

Less Flexible

– Variable Speed reversible unit– Ternary unit arrangement (Francis or Pelton) Faster

More Flexible


Conventional Reversible Unit

– Typical of older fleet in world todaytoday

– Regulating in turbine modeRegulating in turbine mode only

– Load range for generation: • 50-100% power.

– Proven technology


Advanced Conventional Reversible Unit

– Typical of new fixed speed conventional units todaytoday

– Designed for faster & more frequent responseP t k t l t• Penstocks, surge control systems

• Valves• Mode change & control systems• Materials

– Fast & frequent response duty leads to moreFast & frequent response duty leads to more stringent maintenance requirements


Variable Speed Reversible Units

– Power regulation in the pump modemode

– Improved part-load efficiency inImproved part load efficiency in turbine mode

– Wider and more stable operation range in turbine mode


4707e

Example of the Power Regulation Band in Pump Mode for a Variable Speed Machinep p

110

120

Max. Power limit

100

tput

[%]

80

90Ou

7080 85 90 95 100 105 110 115 120

Net Head [%]


Net Head [%]

Ternary Arrangement

– Turbine + Generator +Torque Converter + Multistage pumpConverter Multistage pump

– Regulating in turbine and pump modes with hydraulic “short

Upper reservoir

modes with hydraulic short circuit”

Project Kops (Austria) recently– Project Kops (Austria) recently commissioned is latest version of this flexible arrangement.• No change of rotation direction Lo

wer

es

ervo

ir

• No change of rotation direction • Enables steepest load ramp• Quickest mode changes

r


• Lowest losses4708e

Mode change times for various Unit concepts -“Flexibility”y

Pump Turbine time [seconds]T Mode change A B C D ET Mode change A B C D E

1 90 75 90 90 652 340 160 230 85 80

Standstill TU-Mode

Standstill PU-Mode

5 70 20 60 40 206 70 50 70 30 258 420 470 45 259 190 90 280 60 25

TU-Mode

PU-Mode

PU-Mode

SC-Mode

SC-Mode

PU M d

TU-Mode

9 190 90 280 60 25TU-ModePU-Mode

Reversible PTA – advanced conventional B – extra fast response conventionalp

C – VarSpeed,

Ternary setD – with hydraulic torque converter + hydr. short circuit, horiz, with Francis Turbine


D with hydraulic torque converter hydr. short circuit, horiz, with Francis Turbine

E – same as E but vertical with Pelton Turbine

Revenue optimization - Feedback EoN

Reference: Dr Klaus Engels, Michael Brfuckner, Michaela Harasta and

Dr Tobias MirbachDr. Tobias Mirbach

Energy-Economic Evaluation of Pumped-Storage Plants


Revenue optimization - Feedback Kops II

– Number of mode changes:t 500 th & it– up to 500 per month & unit

– Number of operating hours per unit per month:p g p p– Turbine mode - ~ 200 - 500– Pump mode - ~ 10 - 50– Sync. condens. - ~ 10– Hydraulic circuit - ~ 150 - 400


Pumped storageNumber of NEW projects per Areap j p

• Projects with DoA 2000 – 2011O• Only NEW projects, total 31 projects


Pumped storageNumber of NEW projects per Areap j p

• Projects with DoA 2011 – 2015O• Only NEW projects, total 31 projects


Selected pumped storage projects in bidding / planning stage in Europe and North America todayp g g p y

Niederwartha

Vetaux R h

Atdorf

Kuethai II

Salamonde II

Waldeck 2+

Vetaux Hongrin

Rosshag

Kuethai IIWaldeck 2+????????

Green marked plants are reversible PS


Yellow marked plants are ternary sets

Conclusion

• Renaissance of pumped storage in Europe due to increased wind power installation; load regimes are changedpower installation; load regimes are changed

• often, new pumped storage plants are using existing reservoirs, thus, full load hours of those reservoirs are reducedfull load hours of those reservoirs are reduced

• ternary sets provide more flexibility (faster mode switch times, regulation of pumping power)regulation of pumping power)

• trend with an increase of variable speed units

• waterways are to be designed depending on unit type selection


Europe (Germany) plans

• 30% renewables by 2020%• 80% renewables by 2050

• long time storage necessary• 20 40 TWh might be needed (0 04 TWh available in• 20 – 40 TWh might be needed (0.04 TWh available in

Germany today)




HydroPeak concept

Norway providing storage for Europe with:

Conventional Hydro

Pumped storage


Industry Roundtable: Defining Value

• Getting beyond a “cost-basis” approachff• Reconciling power market differences

• Affecting choices for capacity expansion• Others• Others


Synthesizing Results

Task 7 - Determine Effects of Alternative Policy, Market Rules & Scenarios on Value of Hydropower OutlineRules & Scenarios on Value of Hydropower Outline

• Market treatment of ancillary services– Current treatment and potential changes in ancillaryCurrent treatment and potential changes in ancillary

services- Kirby Consulting– Enhancements in plant utilization and optimization-

HPPiHPPi– Gaps in regulatory, market and scheduling structures-

Sandia• Future Scenario analysis of energy policy- LCG• Constraints on water usage- ORNL


Synthesizing Results to Define Value

Current operations and optimizing plant performance (HPPi)

Modeling of current role of hydro (LCG)

p ( )

Recommendations Modeling Future

Scenarios of hydro ValueEnergy Security?

based on gaps in reg, market and scheduling

structures (Sandia)

(LCG)

Today’s Market treatment oftreatment of

ancillary services (Kirby)

Societal?


Also considering future hydro costs (HDR|DTA) & water constraints (ORNL)

Action Items

• Look into why Europeans are building new PS plants and how they are operating and paying for them. What is driving it? (Dick Fisher,are operating and paying for them. What is driving it? (Dick Fisher, Brennan Smith, Rick Miller)– Understand compensation streams & market structure (Rick

Miller))– Determine if 2.5/30s reserve requirement is the driver in Europe

(Daniel Brooks, LCG, Brendan Kirby)• Follow up with ORNL to review the LCG hydro plant modelingFollow up with ORNL to review the LCG hydro plant modeling

parameters in WECC• Better cost information (Brennan Smith, HDR|DTA)• How do you monetize benefits (Brennan Smith)• How do you monetize benefits (Brennan Smith)

– How do you monetize benefits compared to others• Look into possibility of validating model with WAPA website SCADA

information (http://www wapa gov/crsp/opsmaintcrsp/scada htm)


information (http://www.wapa.gov/crsp/opsmaintcrsp/scada.htm)

Together Shaping the Future of ElectricityTogether…Shaping the Future of Electricity


Documents

Quantifying the Full Value of Hyypdropower in the ...mydocs.epri.com/docs/corporatedocuments/sectorpages... · TASK 3: Evaluate National Hydropower Participation in Ancillary Services