1 Dr.Wang Yingtao Engineer Power System Department CEPRI,China Nov 2006 R&D OF REAL TIME DYNAMIC MONITORING SYSTEM IN CHIHA

2 The interconnected Power Grid in China Northwest South Northeast Central North East 500kv 220kv 330kv Fossil-fuelled power plant power plant Hydraulic Power plant Nuclear power plant substation

3 Large interconnected system has two distinct forms of interarea oscillations: a very low frequency mode involving all the generators and higher frequency modes involving subgroups of generators swinging against other.Large interconnected system has two distinct forms of interarea oscillations: a very low frequency mode involving all the generators and higher frequency modes involving subgroups of generators swinging against other. Increasing number of long distance AC and DC transmission channels, insufficient reactive power reserve,etc. make it difficult to control the voltage.Increasing number of long distance AC and DC transmission channels, insufficient reactive power reserve,etc. make it difficult to control the voltage. Widespread of fault happened in the interline is threatening the stability of the whole power grid.Widespread of fault happened in the interline is threatening the stability of the whole power grid. New types of load, dynamic control devices,etc implemented in power systems make the dynamic characteristic more complex.New types of load, dynamic control devices,etc implemented in power systems make the dynamic characteristic more complex. Dynamic stability problems of the power grid

4 WAMS brings oppotunity to dynamic monitoring  synchronous － measure power system synchronous.  global － observe power system as an entity.  continuous － record power system states continuous several days. WAMS Master station communicatio n substation PMU Data concentrator

5 Infrastructure of real time dynamic monitoring system based on WAMS Phase 2 Data process in master station Power system Mathematics modelling State estimate configure of PMU Phase 3 Phase 4 Stability prediction Synchronous measure Phase 1 Control decision measure control

6 Development of PMU in China  Measurement:phasor 、 power 、 frequency 、 inner potential of generator 、 field voltage and digital signals ， etc.  Synchronous accuracy:1μs  Phasor accuracy:0.1 ～ 1degree  Transmission rate:20-100Hz  Communication delay:10 ～ 20ms

7 Master station of WAMS network EMS MIS firewall Application server history/Web server MODEM Communication server Monitoring work station printer analysis work station WAN E1 2*10/100BaseT

8 Application Basic functions of master station Communication with PMUs Dynamic monitoring Fault analysis Disturbance alarm ……

9 Data process in master station （ 1 ） transfer data received from PMU, using IEEE-1344 and C （ 2 ） Form the topo of the power grid monitored by PMU （ 3 ） detect abnormal data, and smooth it. （ 4 ） rectify error data received from PMU using state estimation. （ 5 ） rectify time synchronous error.

10 Low frequency swing analysis A power swing happened in the interconnecting lines between fujian and huadong network in Based on data sampled byWAMS, CEPRI analysized underlying reason and carry out measures to quench the power swing.

11 Layer and zoning structure of information exchange Huabei power grid Dongbei power grid Substation A1 Huabei master station National dispatch center Dongbei master station Substation A2 Substation A3 Substation B1 Substation B2

12 time data data command command ProvinceDispatchcenter Subgroup dispatch center National dispatch center Information exchange Data transmission Control command

13 Security defense for WAMS Security zone I Security zone II Security zone III SPDNet firewall Safety isolating device WAMS SCADA/EMS

14 Interconnections of WAMS with other systems

15 Configuration of PMU in power grid  Monitor voltage and current phasor, which can form state result of the power grid.  Monitor dynamic of the mechanical-electrical process,which enable the analysis of the interaction of subgroups of the power grid.

16 State measuring methods using WAMS 1.Measure voltage/current phasor of the substation implemented with PMU 2.Calculate phasor of the substation which has no PMU,but next to station installed PMU using resistance between them.

17 Configuration method based on generator synchronism analysis  Time domain simulation Use varying forms of cases including short-circuit 、 break- line 、 trip generator 、 load shedding to derive swing curve of the system.  Synchronism criterion Rotor angle deviation is less than a threshold given during the simulation period.

18 Rules for PMU configuration Considering economical factor,installation of PMU is step by step,a principle is necessary for PMU configuration.  Take advantage of main network.  Power plant with large capacity, or big influence to the stability of the power grid.  Interconnecting line or interface between province and subgroup network.  substation with typical load model.

19 Static state estimate based on WAMS state observe equation State estimate equation

20 Dynamic state estimate based on WAMS  The SE algorithm based on Kalman filter:

21 State estimate based on WAMS and EMS （ 1 ） State estimate for the main network ： with the development of WAMS,more networks over 200kV have installed PMU. The main network of some power grid even can be observed completely. （ 2 ） State estimate for the distribution network: PMU is installed sparsely in distribution networks, it has to estimate the network using RTU. （ 3 ） Mixed estimate ： put the WAMS and EMS state estimate result in the Nonline state estimate algorithm to calculate the state of the whole power grid.

22 Identification technology based on WAMS  devices needed to be identified distributes extensive in space.  use WAMS to monitor and track physics characteristic of model continuously.  The dynamic data with high resolution can be used to validate the dynamic response of control system

23 Mathematics model for identification Take single input-single output state equation as the model Form identification equation based on the WAMS data with same time interval.

24 Identification algorithm Pulse response data series can be measured by WAMS ， based on which, the order of transfer function can be derived from Hankel matrix: parameter identification: 1. least square estimate 2. maximum likelihood estimate

25 Parameter identification of PSS

26 Identification of load model Modeling of static load

27 Verification of mathematics model CEPRI completed the validation of mathematics models of dongbei power grid,based on data monitored by WAMS during a big disturbance test in 2004.

28 Future prospects （ 1 ） software and hardware for high speed data exchanging of WAMS with other system. （ 2 ） on-line stability prediction and control system based on WAMS （ 3 ） on-line software to make decision when the low frequency swing happens in bulk power system. (4) …

29 Research on transient stability fast prediction with Synchronism-based model and WAMS 220kV500/330kV220kV 500/330kV 220kV 500/330kV 220kV 500/330kV 220kV 500/330kV 220kV 500/330kV master station A区A区A区A区 D区D区D区D区 C区C区C区C区 B区B区B区B区 E区E区E区E区

30 Thank you