On-Line TSA and Control at EMS Control Centers for Large Power Grids

Transcription

1 On-Line TSA and Control at EMS Control Centers for Large Power Grids Dr. Hsiao-Dong Chiang (i) Prof. of School of Electrical and Computer Engineering, Cornell University, Ithaca, NY (ii) President of BSI, Ithaca, NY Cornell University In co-operation with PJM Interconnection LLC. The 12th International Workshop on Electric Power Control Centers, June 2-5, 2013 Bedford Springs, PA USA

2 Key Stages of Research and Development Stage I: Theoretical Foundation ( at U.C. Berkeley) Stage II: Design of Solution Algorithm (BCU method, at Cornell University, group-based BCU method with TEPCO) Stage III: Numerical Methods (TEPCO, BSI) Stage IV: Implementations and Industrial User Interactions Stage V: Practical system installations and developments

3 Contingencies Short-circuit by lightening Demand Variation Generator tripping Short-circuit by non-lightening

4 Contingencies cause limits on power systems Hard Limits Transient (angle) instability Voltage instability Small Signal Stability

5 Joint Development Between TEPCO and BSI (1997-Present) Tokyo Electric Power Company R&D Center Bigwood Systems, Inc. R&D 28 Research Reports TEPCO-BCU Packages U.S. Patents, 3 Japan Patents and 1 China Patent are awarded.

6 Time-Domain Approach: Numerical Integration method Speed: too slow for on-line applications Degree of Stability: no knowledge of degree of stability (critical contingencies vs highly stable contingencies) Control : do not provide information regarding how to derive effective control Direct Stability Assessment Methods (1947, the first PhD thesis)

7 Time-Domain Approach Direct Methods (Energy Function) Pre-Fault System (Pre-fault s.e.p.) (Pre-fault s.e.p.) x(t) end point of fault-on trajectory x(t) end point of fault-on trajectory Fault-On System. x = f F (x,y) t 0 < t < t cl fault-on trajectory fault-on trajectory t = t 0 t = t cl t Numerical integration t = t 0 t = t cl t Numerical integration Post-Fault System. x = f(x,y) t cl < t < t x(t) initial point of post-fault trajectory t = t cl Numerical integration post-fault trajectory t 1. The post-fault trajectory x(t) is not required 2. If v(x(t cl ))< v cr, x(t) is stable. Otherwise, x(t) may be unstable. Direct stability assessment is based on an energy function and the associated critical energy

8 Important Implications CUEP method is the only direct method that works for practical power systems models. The task of directly computing CUEP of the original power system model is impossible. Our analytical results serve to explain why previous direct methods developed in the 1970s and 1980s did not work

9 On-line TSA&C Requirements 12,000 plus buses in system model 1,300 generators 3000 contingencies Look-ahead operating condition (30 ahead for PJM) 15-minute cycle for real-time EMS data 5 minutes in cycle allocated for contingency screening TEPCO-BCU screening performance target is 1.5 seconds to 2 seconds per contingency

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11 PJM Evaluation Results on 5.29 million contingencies (1) Reliability measure: TEPCO-BCU consistently gave conservative stability assessments for each contingency during the three-month evaluation time. TEPCO-BCU did not give overestimated stability assessment for any contingency.

12 Each Contingency

13 (optional service) BSI Online TSA (TEPCO-BCU) Function Data T = 0 min. T = 3 min. Input S.E. Snapshot (CIM, PSSE, PSLF) Contingency List Dynamic Data (i) TEPCO-BCU Method (ii) TEPCO-BCU Classifiers (iii) BCU Control (a) (b) (c) Base-case Dynamic Screening Reliability Efficiency On-line Computation (i) Time-Domain Simulation (ii) BCU-Guided Time-Domain Simulation Critical Contingencies (with estimated CCTs) Base-case Simulation Base-case Time Domain Simulation T = 8 min. Detaile d Output Report BCU (optimal) Preventative Control BCU (optimal) Enhancement Control Insecure Contingencie s Critically Stable Contingenci es Swing Curves Base-case TSA Summary Table Ranking Contingenc y Assessm ent Normalize d Energy Margin Estimate d CCTs Insecure cycles Critically Stable cycles Stable cycles

14 BSI Online Transfer Limit Determination T = 8 min. Data Input S.E. Snapshot (CIM, PSSE, PSLF) Dynamic Data Definition of Interface #1 Definition of Interface #n Contingency List for Each Interface (i) TEPCO-BCU Method (ii) TEPCO-BCU Classifiers (iii) Continuation Power Flow (iv) BCU Limiters Dynamic Screening for Power Transfers (a) (b) (c) Reliability Efficiency On-line Computation Critical Contingencies with Estimated Transfer Limit for # 1 Critical Contingencies with Estimated Transfer Limit for # 2 Critical Contingencies with Estimated Transfer Limit for # n (i) Time-Domain Simulation (ii) BCU-Guided Time-Domain Simulation Time Domain Simulation to Determine Exact Transfer Limits for Each Interface T = 15 min. Detailed Output Report BCU Control for Increasing Transfer Limits for Each Interface (optional Power Transfer Limits Correlating with Top 5 Binding Constraints for Interface # 1 Power Transfer Limits Correlating with Top 5 Binding Constraints for Transfer Limit for Each Interface Transfe Binding r Limit Contingenc y MW MW MW 1122

15 High-level Overview Solution for PJM on-line Transient Stability Assessments TEPCO-BCU (BSI) EMS Data Bridge To Provide Real Time Data (BSI) Information exchange Result Depository and Visualization (BSI & PLI) DSA Manager & TSAT (PLI) Data Bridge contains common fixed data for both TEPCO-BCU/TSAT and local data required only by TEPCO-BCU or TSAT

16 PJM Evaluation Results For a total of 5.29 million contingencies, TEPCO-BCU captures all the unstable contingencies. Table 1.Reliability Measure Total No. of contingency Percentage of capturing unstable contingencies %

17 Speed: TEPCO-BCU consumes a total of CPU seconds. Hence, on average, TEPCO-BCU consumes about second for each contingency. Table 2. Speed Assessment Total No. of contingency Computation Time Time/per contingency seconds second

18 Screening measure: Depending on the loading conditions and network topologies, the screening rate ranges from 92% to 99.5% Table 3. Screening Percentage Assessment Total No. of contingency Percentage Range % to 99.5 %

19 A summary The overall performance indicates that TEPCO-BCU is an excellent screening tool These unstable contingencies exhibit firstswing instability as well as multi-swing instability. Table 4. Overall performance of TEPCO-BCU for on-line dynamic contingency screening Reliability measure Screening measurement Computation speed on-line computation 100% 92% to 99.5% 1.3 second Yes

20 Spirits of BCU Method Explores the special structure of the underlying model so as to define an artificial, reduced-state model which captures all the equilibrium points on the stability boundary of the original model, and then Computes the controlling u.e.p. of the original model via computing the controlling u.e.p. of the reduced-state, which can be efficiently computed without resorting to an iterative time-domain procedure.

21 Static and Dynamic Relationships? 0 = -----U u + g u 1 u 0 = U u + g w 2 u TxÝ = -----U u + g x 3 u yý = -----U u + g y 4 u (Step 7) 1 uý = -----U u + g u 1 u 2 wý = U u + g w 2 u TxÝ = -----U u + g x 3 u yý = z MzÝ = Dz -----U u + g y 4 u (Step 1) 1 uý = -----U u + g u 1 u 2 wý = U u + g w 2 u TxÝ = -----U u + g x 3 u yý = -----U u + g y 4 u 1 uý = -----U u u 2 wý = U u w TxÝ = -----U u x yý = z MzÝ = Dz -----U u y (Step 6) 1 uý = -----U u u 2 wý = U u w TxÝ = -----U u x yý = -----U u y (Step 2) (Step 5) 1 uý = -----U u u 2 wý = U u w T xý = -----U u x yý = 1 z y -----U u w x y MzÝ = Dz 1 z -----U u y (Step 4) 1 uý = -----U u u 2 wý = U u w TxÝ = -----U u x yý = -----U u y MzÝ = Dz (Step 3) 4/22/96 HDC

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23 Theoretical Foundations Solution Methods Numerical Methods and Numerical Justification Chapter 3 Stability Regions Chapter 6 Construction of Analysis Chapter 8 Introduction to Direct Methods Chapter 4 Quasi-Stability Regions Chapter 7 Construction of Numerical Energy Functions Chapter 12 Computational Challenges and Numerical Issues Chapter 5 Chapter 9 Energy Function Theory Foundations of the Closed UEP Method Chapter 15 Chapter 17 Numerical Network- Reduction BCU Methods Numerical Network Preserving BCU Methods Chapter 18 Chapter 19 Numerical Asects and Justification of BCU Methods Chapter 10 Foundations of the Closed UEP Method Chapter 22 Chapter 20 BCU-Exit Point Method Chapter 11 Foundations of the Controlling UEP Method Chapter 23 Group-Based BCU Methods Chapter 21 Group Properties of Power System Chapter 13 Chapter 24 Chapter 14 Chapter 16 Network-Reduction BCU Method BCU Methods Network Preserving An overview of the organization and content of the book.

24 Theoretical Foundation Benefits: gain insights and build belief Theory of stability boundary Energy Function Theory (extension of Lyapunov function function) Energy Functions for Transient Stability Models (non-existence of analytical energy function)

25 Theoretical Foundation Benefits: (gain insights and build belief) Theoretical Foundations of Direct Methods CUEP method and Theoretical foundation Theoretical Foundation of BCU method

26 Time-Domain Approach: Numerical Integration method Speed: too slow for on-line applications Degree of Stability: no knowledge of degree of stability (critical contingencies vs highly stable contingencies) Control : do not provide information regarding how to derive effective control

27 sustained fault-on trajectory moves toward the stability boundary intersects it at the exit point. The exit point lies on the stable manifold of the controlling UEP of the fault-on trajectory.

28 If the fault is cleared before the fault-on trajectory reaches the exit point, then the fault-clearing point must lie inside the stability region. Hence, the post-fault trajectory starting from the fault-clearing point must converge to the post-fault SEP.

29 The controlling UEP method approximates the relevant stability boundary, which in this case is the stable manifold of the controlling UEP, by the constant energy surface, which passes through the controlling UEP.

30 The only scenario in which the controlling UEP method gives conservative stability assessments is the situation where the fault is cleared when the fault-on trajectory lies between the connected constant energy surface and the relevant stability boundary which is highlighted in the figure.

31 BCU relevant stability boundary-based framework for enhancement control Use unstable manifold of the CUEP to identify the behavior of the unstable trajectory with clearing time slightly larger than critical clearing time. Use CUEP and its by-product information to compute the sensitivity of CCT (or ATC) with respect to each generator, and rank all machines based on their criticalness (i.e. sensitivity) The dynamics of the post-fault trajectory near the relevant stability boundary is governed by the stable and unstable manifolds of the CUEP.

32 Critical machines The group of machines that loses synchronisms first and separate from the rest of the machines Usually corresponds to machines that are under stress Decreasing MW output of unstable machines is likely to improve transient stability 10 IEEE145 System, Fault bus: 59, Line-tripped: IEEE145 System, Fault bus: 72, Line-tripped: (radian) 4 (radian) Time (sec) Single-machine Loss of synchronism Time (sec) Multiple-machines Loss of synchronism

33 Control Sensitivity Calculation by Controlling UEP method and BCU method Machine Unstable Eigenvector Component Machine Unstable Eigenvector Component (radian) IEEE145 System 145 buses, 50 machines Fault-bus 72, Line-tripped IEEE145 System, Fault bus: 7, Line-tripped: 7-6 Machine 20 Machine Time (sec)

34 Machine Unstable Eigenvector Component Machine Unstable Eigenvector Component E (radian) IEEE145 System 145 buses, 50 machines Fault-bus 72, Line-tripped IEEE145 System, Fault bus: 72, Line-tripped: Time (sec)

35 Identifying critical machines by Controlling Unstable Equilibrium Point Contingency Faultbus: Line Unstable Machines Time domain Unstable eigenvector at CUEP 7: , 26 20, 26 6: , 26 20, 26 59: , 2, 3, 4, 5, 6, 7, 8, 9, 10, 2, 5, 6, 8, 12, 13, 14, 16, 17, 11, 12, 13, 14, 15, 16, 17, 19, 20, 21, 22, 23, 24, 26, 27, 19, 20, 21, 22, 23, 24, 25, 33, 34, 35 72: , 27, 33, 34, : : , 2, 3, 4, 5, 6, 7, 8, 9, 10, 2, 5, 6, 8, 12, 13, 14, 16, 17, 11, 12, 13, 14, 15, 16, 17, 19, 20, 21, 22, 23, 24, 26, 27, 19, 20, 21, 22, 23, 24, 25, 33, 34, 35 72: , 27, 33, 34, : , 2, 3, 4, 5, 6, 7, 8, 9, 10, 2, 5, 6, 8, 12, 13, 14, 16, 17, 11, 12, 13, 14, 15, 16, 17, 19, 20, 21, 22, 23, 24, 26, 27, 19, 20, 21, 22, 23, 24, 25, 33, 34, 35 75: , 27, 33, 34, 35 91: *From 10 different contingencies, the CUEP And its relevant information can accurately identify the critical machines* Ranking by Sensitivity components at CUEP Most critical Least critical (stable) Positive sign critical machines Negative sign stable machines

36 Time-domain simulation before preventive control

37 Design of Enhancement Control

38 Time-Domain Simulation after preventive control

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42 Figure 7 Contingency 2:17240 before controls

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44 Time-domain simulation to validate preventive control

45 Figure 10. Contingency 1:20100 before control

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48 Challenges Subject to: hx ( ) 0 gx ( ) 0 min Cx ( ) However, security-constrained OPF can not be expressed as the above analytical form: i. Power balance equations: ii. iii. iv. Voltage limit constraints: Thermal limit constraints: Transient-stability constraints: v. Voltage stability constraints: hx ( ) 0 x x x gx ( ) 0?????? 48

49 Theoretical Developments Voltage Stability Constraints There does not exist an explicit expression for voltage stability constraints of power systems Transient Stability Constraints There does not exist an explicit expression for transient stability constraints of power systems. 49

50 Multiple Optimal Solutions (1)There are multiple feasible components (2)Multiple local optimal solutions in each feasible component X X X X X X X X X X X X X X X X X X 50

51 Architecture of PMU-enhanced Real-Time Stability Monitoring and Control Systems On-line Voltage Stability Assessment and Control (VSA&E) On-line Transient Stability Assessment and Control (TSA&E) Energy Management System (EMS) Assessment & Control Information Phasor Measurement Unit (PMU) Real-Time Network Information Integrated System Real-Time Measurement Information Real-Time Stability Monitoring and Control

52 0 0 Safe margin threshold Safe margin threshold Monitoring of critical angle difference Monitoring of critical power transfer critical bus #i angle P M U Critical bus i i P M U Critical bus j j critical bus #j angle

53 PMU-based Real-Time Voltage Stability Monitoring and Enhancement System Demonstration Project (2011): TEPCO + BSI + TOSHIBA + CRIEPI Copyright 2012 Bigwood Systems, Inc. Ithaca, New York, U.S.A.

54 PMU-based Real-Time Transient Stability Monitoring and Enhancement System Demonstration Project (2012): TEPCO + BSI + TOSHIBA + CRIEPI Copyright 2012 Bigwood Systems, Inc. Ithaca, New York, U.S.A.

55 Monitoring & Analysis Graphical Scheme 50% 100% Voltage Security Threat Key Voltage Violation Type Key Red Orange Yellow Blue Danger of Voltage Collapse Danger of Thermal Limit Danger of Voltage Violation Safe Voltage Collapse Thermal Limit Voltage Violation

56 Monitoring & Analysis (Base-Case) Main Window KMF BED-BLA EAST-X EAST WEST Central APSouth

57 On-line Voltage Stability Assessment and Control Control Actions (user-defined priority) Level one SC, ULTC, and phase-shifter Level two real power rescheduling, voltage setting Level three new SC, loadshedding Control Strategies Priority-based Control Min-Number Control Min-Action Control Sensitivity-based Control

58 CAISO VSA &E System real-time mode on-line study mode look-ahead mode Day-ahead mode (energy market) Operational at CAISO EMS since June 2009 Copyright 2012 Bigwood Systems, Inc. Ithaca, New York, U.S.A.

59 Introduction Meter Details (2) Current Operating Point in MW Margin in MW Safety Margin in MW

60 North Interface Approaching Limit

61 Operator Requests Control Action recommendation result posted in new meter

62 North Interface Recovering South Interface Approaching Limit

63 Operator Requests Control Action recommendation result posted in new meter

64 My Belief solving practical problems efficiently and reliably can be accomplished through a thorough understanding of the underlying theory, in conjunction with exploring the features of the practical problem under study