SYGMA lab at SDSC (UCSD)

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Phasor Data for Event Detection, Feedback Control
and On-line Generator Modelling in the SyGMA lab
R.A. de Callafon1, C.H Wells2, Sai Akhil Reddy1
[email protected]
Joint work with H. Ghoudjehbaklou, T. Rahman, S. Sankaran,
at Diego Gas and Electric (SDG&E)
1SyGMA Lab, University of California, San Diego (UCSD)
2OSIsoft
JSIS Talk, April 26-28, 2006
Official Opening
The new SyGMA lab at SDSC, UCSD opened on
March 17, 2016
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Callafon - SyGMA Lab, JSIS Meeting, April 2016
Mission Statement
The SyGMA lab: key player in the emerging
technology on electric grid instrumentation.
 Development of new data processing, modeling
and model validation tools
 Advanced grid monitoring and automatic control
of electric networks
All based on synchrophasor data…
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Real-time Event Detection
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Real-time event detection algorithm is currently being
developed to run on Linux using Python on Raspberry PI.
Automatically detect events in real-time.
Send only the data with events to the data server, which can
drastically reduce data storage on the server.
Real-time data Live on SyGMA website
http://sygma.sdsc.edu/
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Feedback Control with Phasor Data
Funded by CEC
Application to
Anza Borrego
microgrid
PCC
Tom Bialek, Neal Bartek
SDG&E, Main PI
Objective
Control P/Q at
PCC via P/Q of
distributed
smart inverters
(while maintaining
constrains)
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control
See: Borrego Spring Microgrid Demonstration Project
http://www.energy.ca.gov/2014publications/CEC-500-2014-067/CEC-500-2014-067.pdf
Detailed simulations with
Simulink/SimPower Systems
Simulations reveal:
 Typical oscillations
 Coupling between
P/Q at PCC that is
both static and dynamic
 Non-linear P/Q behavior
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Phasor based Feedback Control
Feedback control algorithm uses phasor feedback (V,I, + angles)
Feedback algorithm takes into account:
 Grid dynamics (oscillation response)
 Communication delays (PMU data + actuation)
 Non-linear dynamic coupling (trig. between phasors and P/Q)
 Disturbance rejection + tracking (to follow P/Q references)
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Detailed simulations with
Simulink/SimPower Systems
Simulations reveal:
 Damping of oscillations
 Reduced coupling between
P/Q at PCC that is
both static and dynamic
 Tracking and disturbance
rejection of P/Q at PCC
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Generator Model Validation
𝑇
𝜔



low side high side
𝑉
𝐼
𝑉
𝐼
disturbance
Disturbance (change in f or P/Q) generated by “grid”
Measurements of f, V/I and P/Q at high/low side
In addition to
Koserev/Yang
approach:
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𝑉𝑓 𝐼𝑓
Rotor “phasor” angle 𝜃
and rotor frequency 𝜔
Field 𝑉𝑓 𝐼𝑓
Overview of data

Instrumentation for rotor angle measurements
Rotor phasor angle via
zero-crossing detection
Rotor frequency via timing
measurement
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Typical Rotor Angle Data
Chief Joe Brake Test: 09/17/2015 - 3:00pm - 4:00pm (3:14pm and 3:24pm)
𝜃(𝑘)
𝜃𝑢 𝑘 =
𝑢𝑢(𝜃 𝑘 )
𝜔 𝑘 =
𝜃𝑢 𝑘 − 𝜃𝑢 (𝑘 − 1)
0.03333
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Note: 𝜃 𝑘 constant if rotor frequency = 60Hz (not absolute rotation)
Comparison of rotor angle and frequency
Chief Joe Brake Test: 09/17/2015 (zoom in at 3:24pm)
𝑓(𝑘) = 60+
𝜃𝑢 𝑘 − 𝜃𝑢 (𝑘 − 1)
0.03333 ∙ 2 ∙ 180
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Final Transient Data: Field V,I and P,Q
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Generator Models
More advanced models

(simplified CIGRE or GT1)
Still “simplified” model
Ham et al. “Development and
Experience in Digital Turbine
Control” IEEE Trans. on Energy
Conversion, (1988)
Features:
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Logic for feedback (P/PI/PID)
2nd order model for
gas turbine dynamics
Possibility to model power
output as function of heat/speed
Similar to GGVO1
CIGRE Technical Brochure 238, Modeling of Gas Turbines and Steam Turbines in
Combined-Cycle Power Plants (2003)
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Results
Results of “fitting” measured rotor frequency
Due to simple dynamics between
POI PMU frequency and rotor
frequency and excellent fit
is obtained
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Results
Results of “fitting” Ifield and Vfield
Dynamic effects are captured reasonably well
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Results
Results of “fitting” positive sequence real P and reactive Q
Dynamic effects are captured, but model needs more features
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Wrap Up
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𝑇
𝜔
𝑉𝑓 𝐼𝑓
low side high side
𝑉
𝐼
𝑉
𝐼
disturbance
Additional rotor angle/angular speed 𝜔 allows
characterization of PMU/transformer dynamics
Additional rotor angle, filed current and field voltage
can be exploited distinguish generator dynamics from
PSS dynamics
For more info/pubs see also http://sygma.sdsc.edu/
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SYGMA lab at SDSC (UCSD)

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