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J. McCalley

J. McCalley. Wind Power Variability in the Grid: Regulation & Load Following. Outline. AGC AGC and wind Control performance standards (CPS) Effect of AGC on CPS. 2. BA 1. BA 2. P 12. X. Two Area System. Stiffness coefficient:.

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J. McCalley

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  1. J. McCalley Wind Power Variability in the Grid: Regulation & Load Following

  2. Outline AGC AGC and wind Control performance standards (CPS) Effect of AGC on CPS 2

  3. BA 1 BA 2 P12 X Two Area System Stiffness coefficient: And if the two areas are operating with only primary control, then their “slow” dynamics are represented by the following block diagram. 3

  4. Two area system with primary control dynamics only See http://home.eng.iastate.edu/~jdm/ee553/AGC1.pdf 4

  5. State equations for this system Form of equations is the same, except for sign of ΔPtie term in 3rd equation of each set. 5

  6. For a load change in area 1, we desire: ∆ Pm1∞=∆PNL1 ∆Pm2∞=0 ∆ω∞=0 ∆Ptie∞=0 Each BA compensates for its own load change. Will this work? Steady-state values The system of the previous two slides consists of just primary control, and as we have seen will distribute the generation imbalance to all units, leaving a non-zero steady-state frequency error. Thus, ΔPm2∞≠0; Δω∞≠0, and ΔPtie∞≠0. We need an additional control loop. 6

  7. ACE1=-B1∆ω-∆Ptie, ACE2=-B2∆ω+∆Ptie Introduce Area Control Error PNL1 The additional loop is an integral control loop, which provides the ability to zero the steady-state error of the system output (frequency) in response to a unit step disturbance. PNL2 See http://home.eng.iastate.edu/~jdm/ee553/AGC1.pdf 7

  8. State equations for this system 8

  9. ACE, being a measure of how much the total system generation needs to change, is allocated to the various units that comprise the balancing area via participation factors. The participation factors are obtained by linearizing the economic (market) dispatch about the last base point solution (see Wood & Wollenberg, section 3.8). AGC and participation factors Base point calculation is performed by the real-time market every 5 mins. See http://home.eng.iastate.edu/~jdm/ee553/AGC1.pdf 9

  10. Summary of power balance control levels We are addressing the system’s ability to control steady-state frequency. Why consider the real-time market? The real-time market has a secondary influence on the system’s ability to control steady-state frequency because it computes base points based on a net load forecast. The accuracy of this forecast determines how much the units will be moved by AGC and as a result, how much frequency variability is present. So let’s take a look at how the real time market uses a net load forecast.

  11. ADS: automatic dispatch system DOT: dispatch operating target Focus on interval 2, { t+5, t+10}. For interval 2, a short-term net load forecast is made 7.5 min before interval 2 begins, at t-2.5, and generation set points are computed accordingly. At t+2.5, which is 2.5 minutes before interval 2 begins, the units start to move. The units are ramped at a rate which provides that they reach the desired base point at t+7.5 min, which is 2.5 min after the interval begins. Base point calculation via real-time market Key point: The base point is computed from a net load forecast. There is error in this forecast, which typically increases as wind penetration increases. This error contributes to frequency deviation. Source: Y. Makarov, C. Loutan, J. Ma, and P. de Mello, “Operational impacts of wind generation on California power systems,” IEEE Trans on Power Systems, Vol. 24, No. 2, May 2009. 11

  12. Wind farm participation in AGC PNL1 Most windfarms do not participate in AGC today. However, windfarms do affect the net load seen by AGC, as indicated here. PNL2 12

  13. Control performance standards Control Performance Standards CPS1 and CPS2 evolved from earlier metrics and were enacted by NERC in 1997 to evaluate a balancing area’s frequency control performance in normal interconnected power system operations. The motivation underlying CPS is to ensure a targeted long term frequency control performance of the entire interconnection. CPS measures each balancing area’s frequency control performance in achieving control objectives. N.Jaleeli and ,L.VanSlyck, “Control performance standards and procedures for interconnected operation,” Electric Power Research Institute, Dublin, Ohio, Tech.Rep. TR-107813, Apr.1997. N.Jaleeli and L.S.Vanslyk, “NERC’s new control performance standards. IEEE Trans. Power Syst.,” vol.14, pp.1092-1099, Aug.1999.

  14. Control performance standards CPS1 CPS2 NERC Standard BAL-001-0.1a — “Real power balancing control performance,” http://www.nerc.com/files/BAL-001-0_1a.pdf.

  15. CPS1:a measure of a balancing area’s long term (12 mo) frequency performance. • Control objective - bound excursions of 1-minute average frequency error over 12 months in the interconnection. • Measures control performance by comparing how well a balancing area’s ACE performs in conjunction with the frequency error of the interconnection. Ref: M. Terbrueggen, “Control Performance Standards” 2002 Average ACE, ΔF over 1 min to compute: 10B to give units of Hz. ΔF is an interconnection measure. ΔPtie is a balancing area measure. When ΔF<0, the interconnection needs generation, so desire BA to make ΔPtie large  ACE>0 (helping). If ACE<0, it means BA is undergenerating  “hurting.” So we want to see CP negative, large in mag.

  16. CPS1:a measure of a balancing area’s long term (12 mo) frequency performance. • Control objective - bound excursions of 1-minute average frequency error over 12 months in the interconnection. • Measures control performance by comparing how well a balancing area’s ACE performs in conjunction with the frequency error of the interconnection. Ref: M. Terbrueggen, “Control Performance Standards” 2002 Average ACE, ΔF over 1 min to compute: Average CP 1min over 12 mo to compute: ε1 =target bound for 12 month of 1min avg freq error. e.g., 0.018Hz in EI, 0.228Hz in WECC, 0.020 Hz for ERCOT. Must be squared to normalize Hz2 in numerator.

  17. CPS1:a measure of a balancing area’s long term (12 mo) frequency performance. • Control objective - bound excursions of 1-minute average frequency error over 12 months in the interconnection. • Measures control performance by comparing how well a balancing area’s ACE performs in conjunction with the frequency error of the interconnection. Ref: M. Terbrueggen, “Control Performance Standards” 2002 Average ACE, ΔF over 1 min to compute: Average CP 1min over 12 mo to compute: Problem: balancing area can grossly over- or under-generate (as long as it is opposite frequency error) and get very good CPS1, yet impact its neighbors with excessive flows (large ACEPtie,a>>Ptie,s).

  18. CPS2: measure of a balancing area’s ACE over all 10-minute periods in a month. • Control objective – limit ACE variations & bound unscheduled power flows between balancing areas. • Developed to address “problem” of previous slide. Requirement: |ACE10min |< CPS2=100%-(Percent of 10 min periods in violation)>90% • L10 is max value within which ACE10min must be controlled • BS=sum of B values for all control areas. • ε10 =target bound for 12 mo RMS of10-min avg freq error: e.g., 0.0057Hz in EI, 0.0073 for the WI and ERCOT. • In 2003, the 10Bs were ~ -5692 mw/0.1hz for EI, -1825 mw/0.1hz for WEEC, -920 mw/0.1Hz for ERCOT.

  19. Simulation System • Two Area System (Area A and Area B) • Wind power is assumed in area A • Each area consists of 10 conventional units, with inertia and with speed governing • Based points are computed from net load forecast made 7.5 min ahead, with an assumed error of 1% for load and 4.5% for wind. • Wind penetration levels- 6%, 10%, 13%, 17%, 21%, 25% (Pw/Pnw) are considered (by capacity). • Wind is assumed to displace conventional units • Actual sec-by-sec p.u. value of load and of wind power data from one wind farm is used. Con units A B Con units Wind units C. Wang and J. McCalley, “Impact of Wind Power on Control Performance Standards,” under review, IEEE Trans on Pwr Sys.

  20. 2 Area Simulation System C. Wang and J. McCalley, “Impact of Wind Power on Control Performance Standards,” under review, IEEE Trans on Pwr Sys.

  21. Inputs for 2 Area Simulation System Area 2 input Area 1 input The sec-by-sec generation levels in each case (PG1,RTED and PG2,RTED) are determined by linearly interpolating between their respective 5 minute load and wind forecasts. C. Wang and J. McCalley, “Impact of Wind Power on Control Performance Standards,” under review, IEEE Trans on Pwr Sys.

  22. Study results Case A: Area 1, Area 2 have same size. Case B: Area 1 unchanged. Area 2 load and gen scaled up by 10. Normalized CPS1 Conclusions: CPS1 and CPS2 deteriorates with increasing wind penetration. The effect is larger for “smaller” interconnections. Normalized CPS2 C. Wang and J. McCalley, “Impact of Wind Power on Control Performance Standards,” under review, IEEE Trans on Pwr Sys.

  23. Study results • Measures to improve CPS1, CPS2: • M1: Increase primary frequency control capability in Area 1 • M2: Increase the forecast accuracy of wind power • M3: Control wind power output to be no more than a band around forecasted value • M4: Combining control areas. C. Wang and J. McCalley, “Impact of Wind Power on Control Performance Standards,” under review, IEEE Trans on Pwr Sys.

  24. Do nothing: fossil-plants provide reg & LF (and die ). • Improve forecasts (M2) • Increase control of the wind generation • Control wind to band around forecasted value (M3) • 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 (M1): • Conventional generation • Load control • Storage • Expand control areas • Combine control areas (M4) Solutions to variability & uncertainty 24

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