IEEE Power & Energy Magazine - May/June 2014 - 48

Power plant models are key components
of power grid models, which are used by the power industry
as planning and operating tools.

recordings. The approach proposed by the UW team uses
pattern recognition to find relationships between power
plant model parameters and the dynamic performance of the
power plant, as measured by a PMU. Then an expert engineer can tune the power plant model parameters to obtain the
best match between the model and the disturbance recordings. This collaboration strengthened the techniques so that
they could be applied to other types of power plants. following these successes, the bPa made a request to the DOe for
additional funding support to begin to prove the concepts
and develop a version of the process that could be transferred
and used throughout the western United States. The DOe
tasked the consortium for electric reliability Technology
Solutions (cerTS) to continue the work with UW and the
bPa to initiate these enhancements.
Using the newly developed methods and tools developed
in conjunction with cerTS, the bPa applied the approach
to the columbia generating Station (cgS), a 1,150-MW
nuclear power plant near richland, Washington. initially,
the cgS power plant was not accurately modeled, and the
model was not able to reproduce the disturbance recordings,
as shown in figure 5(a). Such a mismatch would usually

control inspection by the plant operator confirmed that
the plant's PSS had an internal failure that could only be
detected by using disturbance recordings from line PMUs
near the generating unit.
To date, the bPa has installed PMUs at 15 power plants
that account for approximately 70 generators, totaling more
than 18,000 MW of generating capacity. The types of generators being measured include hydroelectric, natural gas,
coal, nuclear, and wind.

The DOE/BPA Generator
Model Calibration Project

Before

1,300

1,100
Blue = Actual
Red = Model
900

25

40
Time (s)

55

Active Power (MW)

Active Power (MW)

building on these successful efforts, the bPa sought to
continue expanding this work for power plant model validation as well as to involve others in the industry in further
improving the technique. Through its Technology innovation program, the bPa announced opportunities for other
organizations to work with the bPa on these efforts. a team
at the University of Wisconsin-Madison (UW) applied to
work with the bPa under a cost-sharing agreement.
The UW team developed analytical methods for calibrating dynamic power plant models using a set of disturbance

After

1,300

1,100

900

25

40
Time (s)

55

40
Time (s)

55

-180

-280

-380
25

40
Time (s)

55

Reactive Power (vars)

Reactive Power (vars)

(a)
-180

-280
Blue = Actual
Red = Model
-380
25

(b)

figure 5. (a) The disparity between the responses from two actual disturbance recordings (blue) and the response from
the CGS model (red) before the CERTS-developed calibration technique was applied. (b) The same two disturbance
recordings (blue), but the CGS model (red) has now been calibrated to more accurately reflect the actual response.
48

ieee power & energy magazine

may/june 2014



Table of Contents for the Digital Edition of IEEE Power & Energy Magazine - May/June 2014

IEEE Power & Energy Magazine - May/June 2014 - Cover1
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