1. OPERATIONS and DISPATCH
GE Energy
Asia Development Bank
Wind Energy Grid Integration Workshop:
OPERATIONS and DISPATCH
Nicholas W. Miller
GE Energy Consulting
Beijing
September 22-23, 2013
This lecture is closely related to the economics discussion: operation and economics are interrelated. In the end, the system must be dispatched both economically and reliably.
Disclaimer:
The views expressed in this document are those of the author, and do not necessarily reflect the views and policies of the Asian Development Bank (ADB), its Board of Directors, or the governments they represent. ADB does not guarantee the accuracy of the data included in this document, and accept no responsibility for any consequence of their use. By making any designation or reference to a particular territory or geographical area, or by using the term “country” in this document, ADB does not intend to make any judgments as to the legal or other status of any territory or area.

2. ADB topic list
Wind energy dispatching methodology ( International Expert) • Wind farm as Capacity source or Energy source • Policies for scheduling wind energy • Policies for curtailing wind energy • Comparison different methods • Software and other tools, processes for scheduling wind energy • Role of Wind energy forecasting

3. Time Scales for System Planning and Operation Processes
The system needs to be run, i.e. dispatched, to cover all the time scales within a few days…. The system needs to be PLANNED to have the right equipment in place to allow successful – economic and reliable – dispatch.

4. System Operation Process - Overview
Day Ahead
Prepare load forecast (Total MW load for each hour of the day)
Commit units that will run to serve the load (accounts for uncertainty)
Preliminary dispatch schedule for each unit (by hour)
Units with long startup times are “committed” for operation during the next day
Hour Ahead
Perform hour-ahead load forecast
Adjust hourly dispatch for committed units as required to match actual load
Real Time
Load-following (typically, dispatch is adjusted at 5-minute intervals)
Adjustments based on “economic dispatch”, using marginal costs or competitive bids
Regulation (fast adjustments of MW to regulate frequency and intertie power flows)

5. For grid operations, wind is “similar” to load .
Like load, wind can be forecast a day ahead
Grid operators can plan day-ahead operations base on a load forecast and a wind generation forecast
Dispatchable generation is allocated to serve the net of the forecast load minus the forecast wind
Uncertainty in the wind forecast adds to the uncertainty in the load forecast
Adjustments are made using hour-ahead forecasts and real-time data
Dispatchable Generation Serves “Net Load”
Net Load
= Load Minus Wind
(This is what must be served by other types of generation)
Departure from “net load” approach is usually very expensive.

6. Overview Temporal/Spatial Patterns Variability in Wind and Load MW
Uncertainty
Forecasting for Wind Power

7. Monthly Energy GWh from Wind & Solar for Years 2004–2006 (30% Wind Energy - In Area Scenario)
‘06
‘05
‘04
Notable difference in Wind & Solar energy across the months and over the years

8. 55% of energy from wind and solar
Monthly Energy % from Wind & Solar for Years 2004–2006 (30% Wind Energy - In Area Scenario) 06
55% of energy from wind and solar
‘06
30% is not always 30%
‘05
‘04
Policy people think “% energy” on an annual basis.
Dispatch people think % power on an instantaneous basis
There is huge difference in perspective.
2006 percent monthly energy ranges from 18% (July) to 55% (April) in study footprint

9. Study Footprint Total Load, Wind and Solar Variation Over Month of July (30% Wind Energy in Footprint)
LP Scenario
Wind may or may not exhibit daily cycles.
Under high load conditions with low wind, load dominates

10. Study Footprint Total Load, Wind and Solar Variation Over Month of April (30% Wind Energy in Footprint)
LP Scenario
But when it is very windy, like in the spring (april)
And, the load is low, the wind variability dominates
This is what operators worry about

11. Study Footprint 2006 Net Load Duration – In Area Scenario
% % % % % % % % % % Deciles of Year
Min load MW
Below existing min load ~57% of year, for 30% scenario
EVERY system worries first about light load, high wind…. The minimum load condition is the most difficult
Being about to shutdown and dispatch down baseload generation becomes ABSOLUTELY critical

12. What Does 30% Penetration Mean?
At the 30% annual energy, some hours might approach 100%

13. Overview Temporal/Spatial Patterns Variability in Wind and Load MW
Uncertainty
Forecasting for Wind Power

14. Variability Analysis - Deltas
Statistics used to characterize variability:
Delta (∆) – The difference between successive data points in a series, or period-to-period ramp rate.
Positive delta is a rise or up-ramp
Negative delta is a drop or down-ramp
Mean () – The average of the deltas (typically zero within a diurnal cycle)
Sigma (σ) – The standard deviation of the deltas; measures spread about the mean
For a normal distribution of deltas, σ is related to the percentage of deltas within a certain distance of the mean

15. Average Daily Profile of Deltas Over Year (30% Wind Energy in Footprint – LP Scenario) (Avg. +/- sigma, Minimum, Maximum)
5644 MW (Nov 14)
Load and Net Load Delta (MW)
Total Load and Net Load (MW)
The net load variability from wind increases
But not uniformly…. In this system, more reserves are needed especially around hour 1600.
Economic operation requires good data… do not add reserves uniformly across all hours.
-4931 MW (Jun 7)
Hour of Day

16. Overview Temporal/Spatial Patterns Variability in Wind and Load MW
Uncertainty
Forecasting for Wind Power

17. Standard Deviations of Day-Ahead Forecast Errors
33,000 MW Peak Annual Load
3,300 MW Total Wind Plant Rating
950 MW
With Wind
800 MW Without Wind
Load forecasts AND wind forecasts are always wrong.
It is the total error that is a problem for dispatch

18. Overview Temporal/Spatial Patterns Variability in Wind and Load MW
Uncertainty
Forecasting for Wind Power

19. Forecasting Wind forecasting is absolutely essential
Forecasting increases economic value of wind power by >25% or more
Wide-spread extreme wind events are predictable (e.g. widely publicized Texas events were predicted)
Texas February 24, 2007 event
Arrival of such fronts is generally forecastable, several hours ahead within a 30-minute window
Extreme Thirty-Minute Wind Drops
~1600 MW
Multiple system studies (NY, Ontario, Colorado, Minnesota, Idaho, California, Alberta,…) have all reached the conclusion that maintaining and developing a portfolio that includes substantial (and increasing) levels of flexible generation is critical to enabling high levels of wind penetration
Systems with limited hydro resources will need to rely on the latest technology thermal plants to meet these requirements. Existing hydro resources need to maintain their flexibility against encroachment (bank erosion, fish kill, irrigation, etc.)
The value of flexible generation to resource owners (and grid operators) is rapidly becoming as critical as heat rate and other more traditional measures of value; flexibility is a competitive advantage
Each MW of flexible generation will enable successful integration of many MWs of additional wind generation (exact level is system dependent)
~1.5hours

20. Reserve Requirements

21. Large System Net Load Variability : Separating Wind and Load Effects (30% case)
10-minute Ds
Net load variability increases with wind
Implied reserve requirement is 3 x Ds
Requirement is a function of both load level and wind level
Wind Level
Distillation of 3Ds to Simple Rule: X% of Load plus Y% of Wind Production with a max
The industry is still experimenting with different ways to specify additional reserves.
This is one example from recent research.
The plot looks complex, but the end result can be simple rules for dispatchers to add reserves based on the wind forecast.
Load Level

22. Can’t lean on the Neighbors
Wind Power Data: Extrema More Important in Small Systems Provided by AWS Truewind (2 years of 10-min for each plant)
500 MW Wind case (inc 2 x 200MW remote island plants
Can’t lean on the Neighbors
Small systems that have little or no connection to neighbors need to be more conservative with their reserves
New Reserve = Spin + Up Regulation = 185MW + f (Wind)

23. Flexible Generation

24. Dealing with Variability
Balance of generation portfolio (dispatchable generation) must have the capability to respond to variations in net load
Net load = (Load MW) – (Wind MW)
Generators must have room to maneuver up or down
Ramp RANGE up and down
Generators must be capable to maneuver fast enough to follow changes in net load
Ramp RATE (MW/minute)
The following slides show how Ramp Range and Ramp Rate for an operating area are affected by increasing penetration of wind generation

25. Grid maneuverability decreases as wind penetration increases
10% Wind Energy
20% Wind Energy
Week of April 10, Spring Season
Load levels are typically low
Wind generation is typically higher in spring than other seasons
Wind plant output is typically greater at night
Grid has difficulty operating at “minimum load”
30% Wind Energy
This is a detail of the minimum load problem.
Wind plants can be selectively curtailed to eliminate this problem.
Dispatchers MUST have the right and capability to occasionally curtail wind plants.
There MUST be a penalty assigned to system operation, NOT just the wind plants, for curtailment. Market mechanisms are one way to do this.

26. Subhourly Time Simulations
QSS (Quasi Steady-State) Simulations
vs.
LTDS (Long-term Dynamic Simulations)
Provide Validation and Context for Operational and Statistical Analysis
Cases Selected from Statistical Analysis
Boundary Conditions Set by Operational Analysis
Evaluate Impact of Significant Wind Generation
Load Following & Ramp Rate Requirements
Regulation/AGC Requirements
Illustrate Performance Issues
Illustrate Mitigation Measures

27. Unit-Type Dispatch 20% Wind max min 30% Wind 10% Wind
AS combine cycle plants are pushed out, coal plants (steam) must cycle more.
Ramp rate limits on plants can become very important.

28. Dealing with Uncertainty
Basic options are increased reserves or demand response
Increasing reserves
Commit additional generation so that load will never be interrupted
Need to do it 100% of the time, because you do not know the reserves will be required
Demand response
Interrupt or reduce load occasionally, as need arises
A paid ancillary service

29. Using Load to Meet Occasional Extremes
Load Interruption
This shows how occasionally – about 1% of all hours – curtailing a small amount of load (about 1-2%) can avoid the need for ver conservative, and expensive oeration strategies.
Load Energy
PAID
to be interupted

30. Costs are per MWh of energy reduced.
Interruptible loads
are easily cost
justified
The cost benefit of occasionally interupting loads can be huge in high wind systems.
In this example, on the right hand side, curtailing 1 MWH is “worth” $100,000.
Cost of reducing Unserved Energy by discounting wind generation forecasts. (i.e., adding reserves in proportion to forecasted wind generation)
Costs are per MWh of energy reduced.

31. Impact on the Existing Generation Fleet?
Lower capacity factors for base and mid-merit generation
Use of “peakers” at “unusual” times
Pressure to increase hydro maneuverability
Increased combined cycle cycling (today and growing rapidly)
Increased coal cycling (growing rapidly in some places)
Increased O&M, higher outage rates, environmental performance impacts
Credible quantitative data is limited; sensitive
Claims of costs, loss of life, and physical capability are variable
Severity of impacts and the allocation of costs is a topic of intense debate

32. Capacity Value of Wind Generation

33. Effective Capacity or Effective Load Carrying Capability (ELCC)
ELCC is a measure of long-term adequacy
Ability of a plant to serve load
Avoid loss of load by the power grid
Example of a 100 MW thermal plant
If forced outage rate is 10%, and
If forced outages are equally probable at any time, then
ELCC is 90%
How does this measure apply to wind power?
Output of a wind plant is not dispatchable
Wind plant output is a function of available wind, and it is time-dependent
Capacity value is best calculated with Monte Carlo simulations of impact on unserved load.
This method is widely used for conventional generation in the US.
The method works well with wind generation, too. 33
Source: WindLogics

34. 2001 Average Load versus Average Wind
August
July
September

35. Effective Capacity
Based on rigorous LOLP calculations using load and wind profiles for NY State
Inland Wind Sites:
Capacity factors ~ 30%
Effective capacity, UCAP ~ 10%
Offshore Wind Site:
Capacity factors ~ 40%
Effective capacity, UCAP ~ 39%
Developed approximate calculation method:
UCAP ~ On-Peak Capacity Factor for 1:00-5:00pm, June-August
684
358
570
322
400
261
105
600

36. Experience and Lessons LearnedGE
Energy
Experience and Lessons Learned

37. Major Study Results : Get the infrastructure right And use it better
Large interconnected power systems can accommodate variable generation (Wind + Solar) penetration levels exceeding 30% of peak loads
But not by doing more of the same…..
To reach higher levels of wind generation and other renewables:
Get the infrastructure right
And use it better
The debate has changed:
No longer: “Is it possible?”
Now: “How do we get there?”

38. Missing Wind/Solar Target Higher Cost of Electricity
Lessons Learned
Impediments
Lack of transmission
Lack of control area cooperation
Market rules / contracts constraints
Unobservable DG – “behind the fence”
Inflexible operation strategies during light load & high risk periods
System Cost
Unserved Energy
Missing Wind/Solar Target
Higher Cost of Electricity
Renewables (%)
Enablers
System Cost
Impediments
Enablers
Wind Forecasting
Flexible Thermal fleet
Faster quick starts
Deeper turn-down
Faster ramps
More spatial diversity of wind/solar
Grid-friendly wind and solar
Demand response ancillary services
All grid can accommodate substantial levels of wind and solar power … There is never a hard limit