EPOC Winter Workshop 2008: New Zealand Wind Integration Study Goran Strbac, Danny Pudjianto, Anser Shakoor, Manuel J Castro Imperial College London Guy Waipara, Grant Telfar Meridian Energy Limited Sep 2008 - PowerPoint PPT Presentation

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EPOC Winter Workshop 2008: New Zealand Wind Integration Study Goran Strbac, Danny Pudjianto, Anser Shakoor, Manuel J Castro Imperial College London Guy Waipara, Grant Telfar Meridian Energy Limited Sep 2008

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Title: EPOC Winter Workshop 2008: New Zealand Wind Integration Study Goran Strbac, Danny Pudjianto, Anser Shakoor, Manuel J Castro Imperial College London Guy Waipara, Grant Telfar Meridian Energy Limited Sep 2008


1
EPOC Winter Workshop 2008New Zealand Wind
Integration StudyGoran Strbac, Danny
Pudjianto, Anser Shakoor, Manuel J
CastroImperial College LondonGuy Waipara,
Grant TelfarMeridian Energy LimitedSep 2008
  • Version 1.0

2
Background motivation for NZ wind study
1
  • Anecdotes are not data
  • Assertion is not analysis
  • Worldwide the rise of wind power has in the past
    and will continue into the future to present
    unique challenges to power system planning
  • Motivation for NZ study was to inform and shape
    the debate in NZ to move beyond gut reaction and
    anecdote to develop methodologies and quantify
    from first principals what unique costs wind
    generation brings to the system
  • Work first mooted in late 2005 and begun in
    earnest in May 2006 having first identified Prof
    Strbac as a expert in the integration of
    distribution generation into power systems.
  • A desire to learn sometimes hard won lessons from
    other jurisdictions
  • Explicit intent to focus on additional system
    operation costs due to wind NOT to focus on
    issues of market pricing, dynamic efficiency,
  • Place wind intermittency within the context of an
    imperfect power system

3
Challenges of integrating wind generation
2
  • Generation capacity adequacy
  • How reliable is wind generation as a source?
    How much conventional capacity can it displace?
    What are the system integration capacity costs
    and benefits?
  • Wind generation is primarily an energy source
    with limited ability to provide reliable
    generation capacity at times of peak demand.
  • Real time system balancing
  • What are the needs for flexibility and reserve?
    What are the costs? What is the role of storage,
    demand side participation and inter-connectors?
  • Additional requirements for instantaneous and
    frequency keeping reserves.
  • Additional requirements for scheduling reserve.
  • Transmission network requirements
  • How much new transmission capacity is required to
    efficiently transport wind power?
  • System stability
  • What is stability performance of the system with
    new forms of generation? Can this technology
    contribute to improving stability?
  • Role of enabling technologies
  • Can storage and responsive demand have a role in
    facilitating integration of wind generation? Are
    these solutions competitive? What are the drivers
    of value? What new tools are required to support
    system management with wind generation?
  • Technical, commercial and regulatory framework
  • Are the technical, commercial and regulatory
    arrangements appropriate for a system with
    significant contribution of wind? Are the Grid
    Codes and Standards appropriate? Are the
    arrangements for access to transmission networks
    appropriate? Are non-network solutions to network
    problems competitive? Does the market reward
    flexibility adequately?

4
Future Generation Scenarios
5
NZ Electricity System Future Scenarios
3
  • Three scenarios corresponding to future
    generation snapshots in 2010, 2020 and 2030 were
    constructed to represent increasing levels of
    wind penetration
  • High Wind 2010 2,100GWh (4.5)
  • NI 432 MW
  • SI 203 MW
  • NZ 634 MW
  • Very High Wind 2020 6,700GWh (12.5)
  • NI 1,434 MW
  • SI 632 MW
  • NZ 2,066 MW
  • Very High Wind 2030 10,700GWh (17.7)
  • NI 2,215 MW
  • SI 1,197 MW
  • NZ 3,412 MW
  • Explicit intent to focus on system operation with
    and without wind at various points in time NOT to
    focus on issues of dynamic efficiency, etc
  • Of course not really that black and white in
    choice of scenario and implied counterfactual

6
Wind Profiles
4
  • Wind data profiles derived from
  • 10 minute real wind readings mostly metering
    towers at 40m
  • 11 actual or proposed sites
  • Continuous 2 year period (Jan2005-Dec2006)

2005 wind profiles for 2010 scenario
Very High Wind 2030
High Wind 2010
Very High Wind 2020
Wind (GWh) NI SI Total
Annual 1,653 631 2,285
Weekly maximum 49 24 72
Weekly minimum 15 2 20
Weekly average 32 12 44
Wind (GWh) NI SI Total
Annual 4,906 1,819 6,724
Weekly maximum 145 72 199
Weekly minimum 47 5 57
Weekly average 94 35 129
Wind (GWh) NI SI Total
Annual 7,442 3,354 10,797
Weekly maximum 228 140 320
Weekly minimum 77 8 94
Weekly average 143 65 208
7
5
Initial Electricity Generation and Demand
Scenarios
Scenario gtgt High Wind 2010 (4.9) High Wind 2010 (4.9) High Wind 2010 (4.9) Very High Wind 2020 (12.5) Very High Wind 2020 (12.5) Very High Wind 2020 (12.5) Very High Wind 2030 (17.9) Very High Wind 2030 (17.9) Very High Wind 2030 (17.9)
Region gtgt NI SI NZ NI SI NZ NI SI NZ
Auxiliary 1,017 37 1,054 1,166 37 1,203 1,205 37 1,242
Wind 432 203 634 1,434 632 2,066 2,215 1,197 3,412
Hydro 1,873 3,557 5,430 1,873 3,557 5,430 1,873 3,557 5,430
Coal 972 - 972 972 - 972 972 - 972
Gas 1,500 - 1,500 1,570 - 1,570 1,810 - 1,810
Oil - - - - - - - - -
Distillate 156 - 156 156 - 156 156 - 156
Total capacity (MW) 5,949 3,797 9,747 7,171 4,226 11,397 8,230 4,791 13,022
Hydro energy (GWh) 6,919 17,929 24,848 6,919 17,929 24,848 6,919 17,929 24,848
Wind energy (GWh) 1,653 631 2,285 4,906 1,819 6,724 7,442 3,354 10,797

Peak demand (MW) 4,842 2,455 7,297 5,598 2,845 8,443 6,273 3,197 9,469
Energy demand (GWh) 28,952 17,041 45,993 33,644 19,812 53,456 37,907 22,351 60,258
  • Key Assumptions
  • Load generation are defined at the station
    gate (including embedded)
  • Annual demand growth is approximately 700GWh
    (110MW at peak)
  • No decommissioning of existing assets (except New
    Plymouth PS)
  • Status quo fuel prices in perpetuity gas
    6.5-7.5/GJ, coal 4/GJ, distillate 25/GJ

8
Capacity Value and Additional Capacity Cost of
Wind Generation in the NZ Electricity System
9
Capacity Assessment Objectives
6
  • Assessment of optimal overall generation
    capacity requirements in each future wind
    scenario
  • Capacity credit evaluation of wind generation
  • Evaluation of additional capacity cost of wind
    generation
  • Sensitivity Studies
  • Wind forecasting errors
  • Impact of hydro conditions (Dry/Average/Wet)
  • Impact of inter-connector size and its
    reliability
  • Impact of wind diversity

Wind-Hydro-Thermal System
10
Capacity Assessment Formulation
7
  • The system reliability criterion for capacity
    adequacy applied in this study is Loss of Load
    Expectation (LOLE) with a conservative target of
    8 hours/year.
  • Hydro is used to minimize overall thermal
    capacity requirements (ie the objective function)
  • Hydro is aggregated at the island level (with key
    catchment level constraints maintained)
  • Hydro is modelled as a fully reliable generation
  • Weekly reservoir energy releases (from Spectra)
    are used water cannot be shared between weeks
  • Spare hydro capacity is available to contribute
    to system reliability
  • Main constraints include
  • Aggregated (wind hydro thermal) production
    must meet demand in each time period
  • Minimization of wind and hydro energy curtailment
  • The aggregated reservoir size of each island for
    hydro energy storage
  • Minimum reservoir levels (10 of reservoir size)
  • 99 reliability of the DC inter-connector

2030 With Wind
2030 Without Wind
11
System Capacity Margin Requirements the
Capacity Credit of Wind
8
  • Key assumptions
  • Conservative system reliability criterion LOLE lt
    8 hours/year
  • Availability of conventional generation 85
    (planning time horizons)
  • NI-SI Inter-connector reliability 99
  • Wind forecasting approach is conservative
    accommodates 99 of the wind variations across 4
    to 6 hours time horizon.

12
Summary of Capacity Results
9
  • Additional capacity costs attributed to wind
    generation
  • Fall from 2010 to 2020 due to a larger HVDC size
  • Rise by 2030 due to reserve requirements to
    accommodate larger wind forecasting errors
  • Unlike peak focused thermal based power systems,
    the capacity value of wind in NZ is driven by its
    higher load factor as well as by large variations
    in a relatively small period of time
  • Hydro increases capacity credit of wind however,
    but at higher penetration levels its contribution
    to firming up the wind power reduces
  • Capacity credit of wind generation in the NZs
    hydro dominated system is higher than in the
    other thermal based systems, however, it also
    declines with rise in wind penetration level
  • Capacity values for wind are not effected by
    hydro (dry) conditions although the overall
    capacity requirements increase with low
    availability of hydro energy
  • The low production of wind for several days is
    found not to effect the capacity value of wind as
    this is compensated by the flexible hydro energy
    with presence of large hydro reservoirs
  • Key Assumptions
  • Capacity cost of (OCGT) conventional plant
    100 /kW/yr to 150 /kW/yr
  • The additional costs of wind are relative to a
    base load thermal plant

13
Cost of Wind Power Driven Reserve in the NZ
Electricity System
14
Wind Reserve Requirement Objectives
10
  • Quantify operating reserves needed to deal with
    wind intermittency and wind forecasting errors
  • Instantaneous reserve (up to 30 mins) provided by
    synchronised generators
  • Frequency keeping reserve (up to 1 hour) provided
    by synchronised generators
  • Scheduling reserve (for 4-6 hours) provided by
    synchronised and standing generators
  • Evaluate wind related impact of increased reserve
    requirement on system operating costs
  • Fuel cost, generation start up cost and no-load
    cost
  • Cost of interruptible load
  • Sensitivity analysis
  • Hydro conditions (Dry/Average/Wet)

15
Reserve Requirement Methodology
11
North Island
  • Additional reserves increase operating costs
  • Requires more on-line capacity
  • Use of low merit (expensive) generation
  • Lower efficiency-part loaded plants
  • Increased frequency of start-ups of generators
  • Increased demand of Interruptible load (IL)
  • Increased standing reserve
  • Operating cost is determined using a MILP
    generation scheduling optimisation model for
    energy production and the allocation of reserves
    among synchronised units
  • Objective
  • Minimise the total system generation costs
    (including no load, start up cost and IL costs)
  • Operational constraints
  • Power balance constraints
  • Generation constraints Min stable generation,
    Power rating, Max Instantaneous Reserve, Ramp
    up/down constraints, Min up/down time
    constraints, Load factor constraints for CCGTs
    (minimum 75)
  • Hydro catchment power constraints Daily ROR
    energy constraints, Weekly hydro inflows
    constraints, Reservoir constraints
  • Reserve constraints Min instantaneous and
    frequency keeping reserve provision for each
    island (no reserves sharing)
  • Flow constraints on HVDC
  • Cost of additional operating reserve attributed
    to wind is determined as the difference between
    the operating cost of the system with and without
    wind reserve component
  • Cost of standing reserve is determined by
    calculating the expected energy of standing
    reserve that would be exercised

South Island
Amount of reserve requirements increases with
increased wind output
16
Reserve Requirements Assumptions
12
2010 2010 2010 2020 2020 2020 2030 2030 2030
IR FK Standing IR FK Standing IR FK Standing
Case 1 NI 398 107 124 446 215 312 533 315 503
SI 167 73 65 245 157 174 379 271 326
NZ 565 180 189 691 372 486 912 586 829
Case 2 NI 398 150 81 446 314 272 533 466 352
SI 167 93 31 245 226 105 379 400 214
NZ 565 243 112 691 540 377 912 866 566
Case 3 NI 398 194 37 446 416 170 533 618 200
SI 167 115 9 245 296 35 379 530 67
NZ 565 309 46 691 712 205 912 1148 267
  • Note all units are expressed in MW
  • IR (Instantaneous Reserve)
  • FK (Frequency Keeping)

Case1 dominated by standing reserve Case2
balanced allocation Case3 dominated by spinning
reserve
  • Key Assumptions
  • Additional operating reserves in each Island
    analysed separately, i.e. (no operating reserve
    sharing across the DC)
  • Power transfers across the DC link are limited by
    MW only (with the max of NI to SI level set to
    60 of SI to NI)
  • All operating spinning reserves quantities for
    instantaneous reserve and frequency keeping are
    unable to meet demand requirements
  • Operating reserve mainly provided by part loaded
    plant along with a contribution from demand side
    (interruptible load)
  • Standing reserve is provided by off-line thermal
    plants which can synchronise and produce
    electricity quickly
  • Levels of operating reserve required cover about
    99.5 of all operating conditions.
  • Reserve from synchronised plant are assessed at
    30 min and 1 hour. Standing reserves deal with
    wind forecasting errors beyond 1 hour
  • Reserve requirements are computed for
    half-hourly.
  • Additional reserve requirements to deal with wind
    variability never exceed expected wind power
    output.
  • Day/night system inertia impacts on operating
    reserve requirements are modelled.
  • CCGTs assumed to operate with minimum load factor
    of 75 irrespective of hydro and wind conditions.

17
Summary of Reserve Requirements Results
13
  • Additional reserves are needed to cover the
    unpredictability of wind power
  • Instantaneous reserve provided by synchronised
    generators
  • Frequency keeping reserve to cover 1 h wind
    variability provided by synchronised reserve
  • Scheduled reserve to cover 4-6 h wind variability
    provided by synchronised standing reserve
  • The quantity of wind reserve component increases
    with rise in wind penetration
  • Provision of scheduling reserve up to 4-6 hour
    time horizon
  • For low wind penetration (2010), hydro will be
    the primary source
  • For high wind penetration (2020 2030), it is
    desirable to use flexible standing power plants
  • The cost of additional reserve to deal with
    forecasting error of wind for several scenarios
    have been quantified
  • For low penetration (4.9 in 2010) , it is around
    0.19 /MWh of wind energy
  • It increases to 2.42 /MWh of wind energy in 2030
    with high wind penetration (17.9)
  • Hydro remains the primary source of synchronized
    reserve, but in the future a greater contribution
    from IL and other thermal plants will be required

Case1 dominated by standing reserve Case2
balanced allocation Case3 dominated by spinning
reserve
18
Summary of Findings
19
Summary of Key Results
14
2010 2020 2030
Installed wind power capacity (MW) 634 2,066 3,412
Wind power (GWh) 2,285 6,724 10,797
Capacity credit of wind () 32 29 15
Max. Instantaneous Reserve (MW) 565 691 912
Max. Frequency Keeping (MW) 309 540 866
Max. Standing Reserve (MW) 46 377 566

Capacity cost (/MWh of wind) 1.7 - 2.5 1.3 - 2.0 6.2 - 9.3
Reserve cost (/MWh of wind) 0.19 0.76 2.42
TOTAL Cost (/MWh of wind) 1.9 - 2.7 2.1 - 2.8 8.6 - 11.7
20
Other Issues
21
Other Wind Related System Issues
15
  • Quality of long-run wind record
  • Single biggest impediment to systematic analysis
    of wind
  • However good correlation (daily energy) between
    synthetic (NIWA weather station) data and actual
    wind farm data
  • Annual wind variation
  • Positive correlation between wind and hydro may
    increase need for hydro-firming plant
  • Not investigated here but likely order of
    magnitude small?
  • A 30 year Spectra run with 8TWh of wind generates
    a total system cost of 25B
  • Removing wind variation decreases market prices
    by 2/MWh (2) and system costs by 63M (0.3)
  • Correlation between demand and wind
  • Positive correlation between extreme peak demand
    and low wind conditions may reduce capacity
    credit of wind and increase need for additional
    firm system MW

2006 Calendar Year
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