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Wind Energy Honors Course Spring 2011 Iowa State University. James D. McCalley Harpole Professor of Electrical & Computer Engineering. Wind Power and Power Balance in the Grid. Outline. Basic problems, potential solutions Wind power equation Variability

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wind energy honors course spring 2011 iowa state university

Wind Energy Honors CourseSpring 2011Iowa State University

James D. McCalley

Harpole Professor of Electrical & Computer Engineering

Wind Power and Power Balance in the Grid

outline

Outline

Basic problems, potential solutions

Wind power equation

Variability

System Control

Comments on potential solutions

basic problems with wind power balance

Basic problems with wind & power balance

Wind is a variable resource when maximizing energy production

Definition: NETLOAD.MW=LOAD.MW-WIND.MW

Fact: Wind increases NETLOAD.MW variability in grid

Fact: Grid requires GEN.MW=NETLOAD.MW always

Fact: “Expensive” gens move (ramp) quickly, “cheap” gens don’t, some gens do not ramp at all.

Problem: Increasing wind increases need for more and “faster” resources to meet variability, increasing cost of wind.

Wind is an uncertain resource

Fact: Market makes day-ahead decisions for “unit commitment” (UC) based on NETLOAD.MW forecast.

Fact: Large forecast error requires available units compensate.

Problem: Too many (under-forecast) or too few (over-forecast) units may be available, increasing the cost of wind.

solutions to variability uncertainty

Groups of 2-3, 10 minutes

  • Identify your preferred approach to the variability problem
  • Consider the below solutions, one, or combination, or other
  • Identify reasons (e.g., economics, effectiveness, sustainability) and have one person report to class at end of 10 minutes

Solutions to variability & uncertainty

We have always dealt with variability and uncertainty in the load, so no changes are needed.

Increase MW control capability during periods of expected high variability via control of the wind power.

Increase MW control capability during periods of expected high variability via more conventional generation.

Increase MW control capability during periods of expected high variability using demand control.

Increase MW control capability during periods of expected high variability using storage.

slide5

Power production

Wind power equation

Mass flow rate is the mass of substance which passes through a given surface per unit time.

Swept area At of turbine blades:

  • The disks have larger cross sectional area from left to right because
  • v1 > vt > v2 and
  • the mass flow rate must be the same everywhere within the streamtube:
  • ρ=air density (kg/m3)
  • Therefore, A 1 < At < A 2

v1

vt

v2

v

x

slide6

Power production

Wind power equation

2. Air mass flowing:

1. Wind velocity:

3. Mass flow rate at swept area:

4b. Force on turbine blades:

4a. Kinetic energy change:

5b. Power extracted:

5a. Power extracted:

6b. Substitute (3) into (5b):

6a. Substitute (3) into (5a):

7. Equate

8. Substitute (7) into (6b):

9. Factor out v13:

slide7

Power production

Wind power equation

10. Define wind stream speed ratio, a:

This ratio is fixed for a given turbine & control condition.

11. Substitute a into power expression of (9):

12. Differentiate and find a which maximizes function:

13. Find the maximum power by substituting a=1/3 into (11):

slide8

Power production

Wind power equation

14. Define Cp, the power (or performance) coefficient, which gives the ratio of the power extracted by the converter, P, to the power of the air stream, Pin.

power extracted

by the converter

power of the

air stream

15. The maximum value of Cp occurs when its numerator is maximum, i.e., when a=1/3:

The Betz Limit!

slide9

Power production

Cp vs. λ and θ

u: tangential velocity of blade tip

Tip-speed ratio:

ω: rotational velocity of blade

R: rotor radius

v1: wind speed

Pitch: θ

GE SLE 1.5 MW

slide10

Power production

Wind Power Equation

  • So power extracted depends on
  • Design factors:
    • Swept area, At
  • Environmental factors:
    • Air density, ρ (~1.225kg/m3 at sea level)
    • Wind speed v3
  • 2. Control factors:
    • Tip speed ratio through the rotor speed ω
    • Pitch θ
slide11

Power production

Cp vs. λ and θ

u: tangential velocity of blade tip

Tip-speed ratio:

ω: rotational velocity of blade

R: rotor radius

  • Important concept #1:
  • The control strategy of all US turbines today is to operate turbine at point of maximum energy extraction, as indicated by the locus of points on the black solid line in the figure.
  • Important concepts #2:
  • This strategy maximizes the energy produced by a given wind turbine.
  • Any other strategy “spills” wind !!!
  • Important concepts #3:
  • Cut-in speed>0 because blades need minimum torque to rotate.
  • Generator should not exceed rated power
  • Cut-out speed protects turbine in high winds

v1: wind speed

GE SLE 1.5 MW

slide12

Power production

Usable speed range

STOPPED HERE

Cut-in speed (6.7 mph)

Cut-out speed (55 mph)

slide13

Wind Power Temporal & Spatial Variability

JULY2006

JANUARY2006

Blue~VERY LOW POWER; Red~VERY HIGH POWER

  • Notice the temporal variability:
  • lots of cycling between blue and red;
  • January has a lot more high-wind power (red) than July;
  • Notice the spatial variability
  • “waves” of wind power move through the entire Eastern Interconnection;
  • red occurs more in the Midwest than in the East
mw hz time frames

=

+

Load Following

Regulation

MW-Hz Time Frames

Source: Steve Enyeart, “Large Wind Integration Challenges for Operations / System Reliability,” presentation by Bonneville Power Administration, Feb 12, 2008, available at

http://cialab.ee.washington.edu/nwess/2008/presentations/stephen.ppt.

slide15

How Does Power System Handle Variability

Turbine-Gen N

Turbine-Gen …

Turbine-Gen 2

Turbine-Gen 1

ACE=∆Ptie +B∆f

Primary control provides regulation

Secondary control provides load following

∆f

∆Ptie

slide16

Characterizing Netload Variability

∆T HISTOGRAM

Measure each ∆T variation for 1 yr (∆T=1min, 5min, 1 hr)

Identify “variability bins” in MW

Count # of intervals in each variability bin

Plot # against variability bin

Compute standard deviation σ.

Regulation

Load following

Ref: Growing Wind; Final Report of the NYISO 2010 Wind Generation Study, Sep 2010.

www.nyiso.com/public/webdocs/newsroom/press_releases/2010/GROWING_WIND_-_Final_Report_of_the_NYISO_2010_Wind_Generation_Study.pdf

solutions to variability uncertainty1

Do nothing: fossil-plants provide reg & LF (and die ).

  • Increase control of the wind generation
    • Provide wind with primary control
      • Reg down (4%/sec), but spills wind following the control
      • Reg up, but spills wind continuously
    • Limit wind generation ramp rates
      • Limit of increasing ramp is easy to do
      • Limit of decreasing ramp is harder, but good forecasting can warn of impending decrease and plant can begin decreasing in advance
  • Increase non-wind MW ramping capability during periods of expected high variability using one or more of the below:
    • Conventional generation
    • Load control
    • Storage
    • Expand control areas

Solutions to variability & uncertainty

slide18

Why Does Variability Matter?

  • NERC penalties for poor-performance
  • Consequences of increased frequency variblty:
    • Some loads may lose performance (induction motors)
    • Relays can operate to trip loads (UFLS), and gen (V/Hz)
    • Lifetime reduction of turbine blades
    • Frequency dip may increase for given loss of generation
    • Areas without wind may regulate for windy areas
  • Consequences of increased ACE variability (more frequent MW corrections):
    • Increased inadvertent flows
    • Increase control action of generators
  • Regulation moves “down the stack,” cycling!
slide19

Increasing wind penetration causes cycling

Hydro peaking: http://hydropowerstation.com/?tag=hydropower-peaking-operations

how to decide

First, primary frequency control for over-frequency conditions, which requires generation reduction, can be effectively handled by pitching the blades and thus reducing the power output of the machine. Although this action “spills” wind, it is effective in providing the necessary frequency control.

Second, primary frequency control for under-frequency conditions requires some “headroom” so that the wind turbine can increase its power output. This means that it must be operating below its maximum power production capability on a continuous basis. This also implies a “spilling” of wind.

Question: Should we “spill” wind in order to provide frequency control, in contrast to using all wind energy and relying on some other means to provide the frequency control?

Answer: Need to compare system economics between increased production costs from spilled wind, and increased investment, maint, & production costs from using storage & conventional gen.

How to decide?