Outline Background & Motivation Reserve Modeling Framework - - PowerPoint PPT Presentation

SLIDE 1

SLIDE 2

Outline

• Background & Motivation
• Reserve Modeling Framework
• Types of improvements
• COMPETES simulations
• Results

SLIDE 3

Challenges Arising from Wind

Source: Flexibility in 21st Century Power Systems, NREL Report

Quack!

Source: CAISO

SLIDE 4

Reserve

• Opera

rating Re Reserve ve is extra capacity (MW) needed in case of contingency

• Loss of a generator
• Loss of a transmission line
• Sudden change in load
• Now: change in renewable energy

40 60 80 100 120 1 6 11 16 21

MW Hour

Expected Demand Reserve+Expected Demand

Frequency restoration (mFRR), not automatic frequency response

SLIDE 5

Operational Reserve

1. Size / Procure

• How much do we need?
• E.g., extra 30 MW on-line in every hour

2. Allocate

• Who will be scheduled?
• Generator B & C will each provide 15

MW

3. Activate

• Who will provide the energy if actually

needed?

• Deliverability in real time market

SLIDE 6

Procurement

• How much do we need?
• Often called ’reserve requirement’
• Examples
• Capacity of largest generator or

transmission line

• X% of demand and Y% of renewables for …
• One day
• One season

20 40 60 80 100 120 1 6 11 16 21

MW Hour

Expected Demand Reserve Ex % Reserve Ex Fixed

SLIDE 7

Allocation Who will be scheduled?

• Most US markets
• Market based
• Primary
• Secondary
• Tertiary
• Determined in zones
• Most European markets
• Long-term contracts
• Portfolio based
• Unit based
• Some dispatch
• Determined by country

Source: ENTSO-E

SLIDE 8

Activation

• Who will actually provide reserves if needed?
• Generators change energy output level in

balancing

• Contract-based
• TSO can call on contracted generators to

provide reserve in real time

• Market-based (US)
• System operator calls on generators

selected in the day-ahead for reserve

• Energy must be deliverable
• Transmission constraints might limit

deliverability within and between countries

SLIDE 9

ECN-JHU Current Research Question What changes to market design will most enhance efficiency in procuring/allocating/activating reserve?

SLIDE 10

Types of Improvements

• Reserve r

requirement p procurement p period

• Seasonal

§ Current practice, four seasonal periods assessed

• Enhancement: Daily

§ Requirement determined daily

• Allocation t

type

• Contract-based

§ Current practice § Bi-lateral contracts between TSO and generators

• Enhancement: Market-based

§ Procured through co-optimization with energy market

• Amount o
• f c

coordination

• Independently determined, current practice
• Enhancement: Northwest Europe coordinates

Example requirement: 3% of demand and 5% of renewable generation

SLIDE 11

Efficiency of Reserve

• Each axis shows

a different improvement to reserve

• Increasing

complexity and efficiency moving away from origin

• Star =

hypothetical ideal

• Dot =

worst case

Reserve R Requirement Co Coordinati tion

DA & Balancing No Coordination Seasonal Daily

Increasing complexity, efficiency à Thanks to Qingyu Xu

SLIDE 12

COMPETES Network

• 33 node pan-European network
• Transmission mimics integrated EU

network with capacity limited by NTC

• Future generation +

potential energy storage

• Renewable scenario

based on ENSTO-E 2030 Vision 4 of “European Green Revolution”

SLIDE 13

Model Formulation: Unit Commitment

• Min Operating Cost
• Subject to
• Generator min & max capacity
• Ramp limits
• Min up & down times
• Transmission line capacity & flow (Net

Transfer Capacity)

• Startup & no-load binary constraints /

relaxed formulation

SLIDE 14

Operational Markets

• Day Ahead
• Schedules generation for the following day
• Inputs: bids & offers, forecast for load and wind
• Outputs: prices, schedule (on/off), dispatch
• à Reserve allocation phase
• Balancing
• Updates schedule to reflect new information
• Inputs: new bids & offers, updated forecast
• Outputs: prices, fast start schedule, dispatch
• à Reserve activation phase
• Was the right amount procured?
• Was it allocated to those who could deliver it?

, reserve sizing

SLIDE 15

Simulations & Sensitivity Analysis

• Simulations
• Simulated one day-ahead forecast
• Followed by 5 real-time ”actual” wind

realizations

• Results show mean of 5 simulations
• Error bars show minimum and

maximum deviations

• Added an extra coordination

component

• Due to results found by K. van den

Bergh in [4], we consider coordination in balancing alone with no coordination in day-ahead

• K. van den Bergh, [4]

Day-Ahead

• Bal. 1
• Bal. 2
• Bal. 5
• Bal. 3
• Bal. 4

SLIDE 16

Efficiency of Reserve

• Each axis shows

a different improvement to reserve

• Increasing

complexity and efficiency moving away from origin

• Star =

hypothetical ideal

• Dot =

worst case

Seasonal Daily

Co Coordinati tion Reserve R Requirement

SLIDE 17

Operating Costs

• Example results comparing
• Star, ‘ideal case’ (DMC)
• Reserve size based on daily average
• Market-based allocation
• Co

Coordinati tion in d day-ahead a and b balancing

• Rectangle (DMN)
• Reserve size based on daily average
• Market-based allocation
• No c

coordination +54.9%

54.0 55.6 0.32

• 0.29

0%

+59.3%

EU

NL

0%

54.9% = DMN op costs − DMC op cost DMC op cost

Deviation of minimum scenario Deviation of maximum scenario 54.9%: 20% load shedding 80% generation deviations

Seasonal Daily Co Coordinati tion Reserve R Requirement

SLIDE 18

Results – operating cost

% deviations from ‘ideal’ case without load shedding

Seasonal Daily

Co Coordinati tion Reserve R Requirement

30.9 33.0

• 0.21

0.51

• 0.23

0.49

+0.12% +0.11% +32.1% +40.9%

39.9 41.7

• 0.30

0.44

+0.05%

0.37

• 0.33

EU

NL

27.7 31.4

+29.1%

• 0.48

2.50

• 0.72

1.62 34.3 37.9

• 0.20

0.91

• 0.66

0.95

+0.67%

• 0.04%

+0.28% +35.7%

0%

0%

SLIDE 19

Daily

Co Coordinati tion Reserve R Requirement

Seasonal

CZE, DEW, FRA, GER, ITA, POR, SKO, SPA, SWE, SWI, NOR, BLK DEN, POL, UKI NED, BLT BEL, FIN, IRE

• Lowest Cost Solution by Country

Where is each country is better off?

SLIDE 20

Results – wind curtailed

% deviations from ‘ideal’ case, NL data in MWh

Seasonal Daily

Co Coordinati tion Reserve R Requirement

1.1 19

• 8.2

9.1

• 5.3

11.4

• 3.5%
• 0.6%

+6.2% +6.6%

1.7 20

• 7.7

10

• 2.7%

13

• 4.8

EU

NL

448 8350

3885 MWh

448 8350

0 MWh 0 MWh 0 MWh 3875 MWh

0%

0 MWh

SLIDE 21

Reserves: Source Fuel

All market based simulations showed similar percentages Storage prod. 59% Coal 2% Lignite 1% Res-e 1% Nuclear 0% Oil 0% Wind 0% Sun 0% Gas 37%

SLIDE 22

Contracted Reserve Cases

Reserve R Requirement Co Coordinati tion

Balancing No Coordination Seasonal Daily

+40.9% +0.17% +32.1% 0% +110% +30.0%

• All contracted cases

showed higher c costs

• Some cases were

double the cost of the market-based cases

§ Some countries faced significant load shedding § Wide difference in

• perating costs

country by country

• Fewer MWh of wi

wind d cu curtailment than ‘ideal’ case when reserves were coordinated in balancing

• Additional plants online

meant lower curtailment

SLIDE 23

Conclusions

Three Suggested Improvements: 1. Difference between daily vs. seasonal requirement is minimal 2. Coordination in balancing achieves almost all benefit,

• r can produce better

solution 3. Naïve contracts for reserves produce least efficient solution compared to market

• Coordination in reserve

allocation & balancing might make up for higher costs

Other Observations ØMore coordination may lead to more wind curtailment

• Possibly due to location of

reserve within country

• Consideration of forecast

uncertainty and wind farm location can reduce curtailment

ØStorage can provide a significant amount of reserve

SLIDE 24

References

[1]

• S. Kasina, S. Wogrin, and B.F. Hobbs, “A comparison of

unit commitment approximations for generation production costing,” Working Paper, Johns Hopkins University, 2014. [2] Ö. Özdemir, F. Munoz, J. Ho, and B.F. Hobbs, “Economic Analysis of Transmission with Demand Response and Quadratic Losses by Successive LP,” IEEE Trans. Power Syst., DOI: 10.1109/TPWRS.2015.2427799, in press. [3]

• J. Cochran, M. Miller, O. Zinaman, M. Milligan, D. Arent,
• B. Palmintier, M. O’Malley, S. Mueller, E. Lannoye, A. Tuohy, B.

Kujala, M. Sommer, H. Holttinen, J. Kiviluoma, and S. K. Soonee, “Flexibility in 21st Century Power Systems,” Golden, CO, 2014. [4]

• K. van den Bergh, R. B. Hytowitz, K. Bruninx, E. Delarue, W.

D'haeseleer, and B.F. Hobbs, "Benefits of coordinating sizing, allocation and activation of reserves among market zones," Electric Power Systems Research, 143: 140–148, Feb. 2017.

SLIDE 25

Thank you! Questions?

Email: hytowitz@jhu.edu

SLIDE 26

Backup slides

SLIDE 27

Results – operating cost

% deviations from ‘ideal’ case

Seasonal Daily

Co Coordinati tion Reserve R Requirement

54.3 56.1

• 0.06

0.37

• 0.08

0.36

+0.14% +0.17% +55.4% +54.9%

54.0 55.6

• 0.26

0.39

+0.04%

0.32

• 0.29

EU

NL

57.4 61.1

+58.8%

• 0.28

2.69

• 0.74

1.60 58.0 61.5

• 0.34

0.77

• 0.66

0.95

+0.87%

• 0.05%

+0.14% +59.3%

0%

0%

SLIDE 28

Generation Mix

TWhdifference between (Seasonal/Market/No Coordination) -(Daily/Market/Coordination)

←More in ‘ideal case’ More in S/M/NC case→

Seasonal Daily Co Coordinati tion Reserve R Requirement

SLIDE 29

Net Trade (Imports)

for market based simulations, (+) = fewer imports, (-) = more imports

Daily Requirement Seasonal Requirement Day-ahead & Balancing Coordination No or Only Balancing Coordination Day-ahead & Balancing Coordination No or Only Balancing Coordination BEL

0% 0.07% 0.06%

• 0.01%

CZE

0% 0.15% 0.23% 0.14%

DEN

0% 0.15% 0.07% 0.12%

DEW

0% 0.47% 0.01% 0.64%

FIN

0% 0.34%

• 0.05%

0.04%

FRA

0% 0.16% 0.07% 0.19%

GER

0% 0.03% 0.26% 0.04%

IRE

0% 0.20% 0.26% 0.19%

ITA

0%

• 0.05%
• 0.09%
• 0.02%

NED

0% 1.27%

• 0.08%

1.90%

POL

0%

• 0.06%
• 0.04%
• 0.08%

POR

0% 0.45% 0.60% 0.65%

SKO

0% 0.06%

• 0.58%
• 0.50%

SPA

0%

• 0.21%
• 0.19%
• 0.62%

SWE

0%

• 0.02%

0.13% 0.07%

UKI

0% 0.55%

• 0.04%

0.55%

SWI

0% 0.31% 0.29% 0.34%

NOR

0%

• 0.40%

0.41%

• 0.31%

BLK

0%

• 0.04%
• 0.08%
• 0.19%

BLT

0%

• 0.13%
• 0.09%
• 0.14%

AUS

0% 0.32% 0.09%

• 0.03%

Total Energy Traded 0.15% less trade 0.07% less trade 0.15% less trade

SLIDE 30

Reserve Requirement

5 10 15 20 25

Frequency Bin

Winter

10 20 30 40

Frequency Bin

Spring

5 10 15 20 25 6302 6708 7115 7522 7928 8335 8741 9148 9554 9961

Frequency Bin

Summer

10 20 30

Frequency Bin

Fall

Seasonal: 8675 MW Seasonal: 8032 MW Seasonal: 7625 MW Seasonal: 7870 MW

SLIDE 31

Four different scenarios (A↔D) considered

31

A B C D Si Sizing

• +

Allo Allocation

• +

+ Ac Activation

• +

+ + “+” = coordinated “-” = uncoordinated

SLIDE 32

(3) Activation of reserves (real-time)

32 Allocation, activation and net cost savings relative to scenario A.

SLIDE 33

Conclusions

1) Coordinating real-time reserve activation is always beneficial 2) Coordinating reserve sizing & allocation can lead to suboptimal results (possibly even deteriorated) if network constraints are neglected 3) Further research deals with including network constraints in (deterministic) reserve sizing and allocation rules

33

SLIDE 34

Model Formulation

binary variables

ui

... ...

Commitm tment w t with thin th the N Neth therlands

Day-Ahead

xi

... ...

continuous variables

SLIDE 35

Model Formulation

relaxed binary variables

Commitm tment o t outs tside th the N Neth therlands

Day-Ahead

xi

... ...

continuous variables

ui

... ...

SLIDE 36

binary variables fast start units

ui

... ...

Model Formulation

... ...

continuous variables

Commitm tment o t only with thin th the N Neth therlands

Balancing

xi

... ...

Fixed variables: line flows, slow units

ui

... ...

xi