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Hydro Generator Simulator
Final Project Report
Team Ironwood
Angel Barahona-Sanchez
Craig Bjorklund
Matt Colby
David Fugate
Yonas Woldemichael
EE 416
Washington State University
Team Sponsor: Avista Utilities
Mentor: Kristina Newhouse
Instructor: Scott Campbell
Submitted on: November 16th, 2007
Table of Contents:
I. Introduction ………………………………………………….…2
II. Marketing 5
i) Market Analysis …………………………………….….5
ii) Marketing Features ……………………………….……5
iii) Competition …………………………………………….6
iv) Documentation …………………………………………6
III. Engineering …………………………………………………...7
i) Introduction …………………………………………….7
ii) Generator Model ……………………………………….7
iii) Governor/Turbine Model ………………………………13
iv) Excitation Model ………………………………………18
v) Protection Model ………………………………………23
vi) Phase II ………………………………………………...27
IV. Quality ………………………………………………………..32
i) Quality in Software …………………………………….32
ii) Reliability ……………………………………………....33
V. Manufacturing …………………………………………………34
i) Producing a Deliverable ………………………………..34
ii) Product Validation ……………………………………..34
iii) Estimate of Other Production Costs ……………………34
VI. References …………………………………………………….36
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I. Introduction:
The purpose of this senior design project is to design and build a test simulator of
a generic hydro generator unit for Avista Utilities. The simulator is controlled by a master
computer which provides simulated feedback of the generation system. Along with the
simulator, a general layout has been developed for an interface panel capable of accepting
inputs from various control devices so proper settings can be tested and control schemes
developed. A Basler DECS300 Voltage Regulator, Woodward 505H Governor, and a
Schweitzer 300G Protection Relay are the control devices that the simulator is designed
to communicate with. The interface panel will have a modular design in order to
incorporate other control elements aside from those listed above.
The final objective of this project is to provide Avista Utilities with a software
environment that provides an accurate representation of a hydro generation system. The
software must accurately reflect real world responses to system disturbances, load
requirements, and control device settings. Plans have also been developed containing the
general specifications of the interface panel, which is to be constructed by Avista. These
design plans offer a starting point for Avista to begin piecing together what is needed for
the interface panel. The given information contains material lists, inputs and outputs for
the control devices stated above, and a general layout of how the control elements
interface with the system. Documentation provided with the software contains installation
procedures, operating instructions, and a list of conditions the generator will be able to
simulate.
The hydro generator simulator encompasses the capabilities of National
Instrument’s (NI) Labview graphical development software and incorporates it to develop
the simulator models. Modeled to reflect a real world hydro generation plant, these
models are designed to follow IEEE standards. The foundation of the simulator is
designed around a Francis turbine and a salient pole generator. Generic control devices
have been developed to control, monitor and protect the generator/turbine unit. These
devices operate similarly to the Basler DECS300, Woodward 505H, and SEL 300G,
containing common functions and I/O’s.
The capability of modeling to a specific type of control device from a generic
base model gives the hydro generator simulator a robust design. The simulator is also a
flexible engineering tool because it can develop with variations in a particular model,
such as upgrades or revisions. National Instrument’s data acquisition cards (DAQ) and a
programmable logic controller (PLC) will allow the simulator to interface with various
control devices.
The hydro generator simulator is designed specifically for Avista Utilities. A safe
testing environment is needed to verify control settings without risking damage to
expensive equipment. Other primary markets include different power generation utilities
that use hydroelectric dams to generate electricity. As reliability standards continue to
improve, control devices must be able to accurately monitor and control generation units
to meet these standards. The simulator is designed to save power generation utilities
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money and time by giving them the option to test their equipment in house. A possible
secondary market includes schools and training environments, where operators and
technicians can learn from a hands-on learning tool.
One major revision to this project has taken place between the two semesters of
this senior design course. At the end of the first semester (EE415), it was this group’s
intent to have both a software simulator (Phase I) and a physical interface panel (Phase
II) completed by the end of the second semester (EE416). However, realizations from
both the group and Avista determined that completing both phases of the project would
be too cumbersome. Therefore, the hydro generator software simulator (Phase I) is the
final object to be presented to Avista at the end of EE416. The interface panel, Phase II of
the project, will not be completed by this design team but a starting point for its
integration with the simulator will be provided.
The five students responsible for the design and implementation of the hydro
generator simulator remain unchanged from last semester and are known as team
Ironwood. This team consists of five electrical engineering students, Angel BarahonaSanchez, Craig Bjorklund, Matt Colby, David Fugate, and Yonas Woldemichael, all in
their senior year at Washington State University.
Each member will contribute evenly to the efforts of the group, but to maximize
efficiency, the project has been broken into different parts and assigned to group
members. There are four main portions that define the following project plan: Marketing,
Quality, Engineering, and Manufacturing. The following list shows the division of roles
within these portions as shown in table 1:
Table 1. Divisional Roles
Marketing
Matt
Quality
Angel
Engineering
Intro
David
Generator
Angel
Governor/Turbine
Matt
Protection
Yonas
Excitation System
David
HMI & Simulator
Matt & Craig
Phase II
Craig & Matt
Manufacturing
Craig & Yonas
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II. Marketing:
Market Analysis:
The primary customer of the hydro simulator is Avista Utilities. Avista desires the
ability to test control device settings in a safe environment without risking damage to
expensive equipment such as a generator. In the past, engineers from Avista had to travel
to Colorado to test a governor on a Woodward generator simulator. Although this
simulator provided an adequate testing environment, resources were spent on traveling to
Colorado from Spokane, WA. The governor was also damaged in shipping resulting in
unnecessary downtime. An in house generator simulator would provide Avista with a
cost effective solution.
The market for the hydro generator simulator is primarily suited towards power
utilities that use hydro electric dams to generate power. Since few hydro generator
simulators exist in the U.S, the primary market for the generator simulator is fairly large.
The Federal Energy Regulatory Commission (FERC) regulates more than 1,500 hydro
electric dams in the U.S. alone [1]. Power generation utilities must provide a cheap,
reliable source of power as efficiently as possible with minimum downtime. Failure to do
so could result in power outages, loss of money, and wasted resources. In order to meet
standards, adequate control schemes will need to be developed and tested. A hydro
generator simulator provides an effective solution for testing device settings.
A possible secondary market could be trade schools and training for power
generation control operators. It is essential for power generation operators to have hands
on experience before working in an actual control room. The hydro generator simulator
could provide the means to meet this end. In a class room or lab environment students
would have the opportunity to apply theoretical knowledge to a simulation of an actual
hydropower plant. This would allow students to make changes to different system
parameters without worrying about damaging expensive equipment in the event of
unexpected performance.
Marketing Features:
The hydro generator simulator is developed in National Instrument’s Labview 8.2.
Labview provides the software interface that can be used both to manipulate inputs to the
simulator and monitor the system. Using this software the simulator is modeled to reflect
the necessary equipment for the control and operation of a hydro power generation
system. A hydro turbine, generator, excitation system, governor, and protection element
are programmed to reflect a real world system. These models respond according to the
specifications given in the WECC and IEEE standards.
The ingenuity of the simulator is that with Labview’s simulation module the user
can interact with the simulation during its real time operation. Control inputs can be
adjusted while the software is running and the responses can be readily seen. The user no
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longer has to re-run the simulation to view the output response every time a parameter is
modified as you would have to do with other software.
Labview provides an effective human-machine interface and is capable of
handling multiple analog and digital inputs if necessary. Due to this benefit the simulator
is also developed to allow for a future expansion of an interface panel. This will include a
Data Acquisition card (DAQ) and Programmable Logic Controller (PLC). After the
interface panel is implemented, the simulator will be able to accept numerous inputs from
the control devices while in turn providing a feedback response that replicates an actual
system output. Current control devices which are compatible with the simulator are a
Basler DECS300 voltage regulator, a Woodward 505H governor and a SEL 300G. After
the interface panel is complete the simulator is designed so the respective software
models can be disabled when the physical device is attached. Using this interface system,
an engineer will be able to connect various control elements and perform the various
simulations so control settings can be tested.
Competition:
There are not many hydro generator simulators available for power utilities that
can be used to test control devices in a safe environment. The main competitor is the
Woodward generator simulator in Colorado. Since this is a not a distributed product,
engineers from power utilities bring their control devices to be tested.
One thing that separates our product from the Woodward simulator is the fact that
power utilities do not have to travel to test their control schemes. Instead they can test
control settings in house, saving time and resources. The Woodward simulator also lacks
the ability to simulate control devices, but requires the physical devices in question to be
plugged into the system. The developed simulator represents other control devices in
software and generates response signals that reflect a corresponding physical device.
What makes the designed product excel is its ease of use compared to other
products. Various components can be tested simultaneously and their effects on the
simulated system can be observed. For example, if the load on the generator increases,
the response of the governor can be observed to see if it correctly increases the flow rate
to the turbine. Without a fail safe testing environment it can be difficult to predict the
response of a control device or generation system.
Documentation:
Documentation for the simulator covers detailed information on the models and
how to use the simulator. Default parameters, I/O locations, valid data ranges, and how
the models work are some examples of information contained in the documentation.
Details on the overall simulation explain how the simulator works and how to perform
various tests.
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Documentation necessary to get started implementing the interface panel is also
provided. Being that this is a custom designed panel for each customer’s specifications,
the layout of the product will vary slightly from product to product. To aid in any
confusion that may exist because of this, documentation for the panel will be included on
the same disk as the simulator software. This documentation includes mappings of what
control device signals attach to the DAQ modules and which attach to the PLC.
III. Engineering:
Introduction:
The development of the hydro generator simulator was broken into two phases.
Phase I was to develop a virtual simulator while Phase II was to gather information on
how to interface real devices with the simulator. Phase I was further broken down into
five sections which makes up the simulator: the generator, governor/turbine, excitation
system, protection device, and the human machine interface (HMI). In each section the
process used to develop the model is explained. First, an explanation of what the model
represents in the real world is covered. Next is a description of the different parts of each
model and how they interact with each other. Following this is an explanation of how the
model was programmed and validated using Labview. Problems that were encountered
when developing the particular Labview model are explained.
3.1 Generator Model:
Background:
Synchronous generators form the principle source of electrical energy in today’s
power systems and are the core component of the generator simulator. In producing such
a model for the generator, an understanding of its characteristics and accurately modeling
the dynamics are of fundamental importance. Described below is a brief description of
the synchronous generator and its function, followed by the research done in order to
chose an appropriate model.
The synchronous generator consists of a round or salient rotor. Its type depends
on the rated rotational speed of the turbine. For example, at higher speeds, typically
around 1800 rpms and greater, a round rotor is used; and at lower speeds, a salient pole
rotor is used. Typically round rotor generators are found on steam powered units, and
salient pole rotors on hydro powered units.
Another important part of a generator is the stator, which consists of armature
windings that are distributed 120° apart in space. This is done in order to produce
uniform rotation of the magnetic field when excitation current is applied to the field
winding of the rotor. Because of this, the three phase voltages in the armature windings
are displaced by 120° in time.
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The production of three phase voltage is the result of the total net magnetomotive
force produced by the field and armature windings and there relation according to
Faraday’s Law which is shown below.
(1)
(2)
In the above equations, see Equation (1) and Equation (2), ei is the induced
voltage, ψ the instantaneous value of flux linkage at time t, L the inductance, R the
resistance of the conducting wire, and i the per unit current entering the circuit in Figure
1. Because of the large amounts of circuits, like Figure 1, that are involved in the
synchronous machine, and “the fact that the mutual and self inductance of the stator
circuits vary with rotor position” synchronous generator equations are complicated [2].
This complication poses a problem when describing the electrical performance of
synchronous machines, or when modeling a synchronous generator. Historically this has
been always a challenge.
Figure 1. Single-excited magnetic circuit [2]
In the past, to simplify the modeling and analysis of transients for a synchronous
generator, two axes were defined. The direct axis, or d-axis, was centered magnetically
on the north pole of the rotor, and the quadrature axis, or q-axis, was 90 electrical degrees
ahead of the d-axis, as shown in Figure 2. The d and q axis were further developed by
mathematically transforming the 3 phase stator quantities into corresponding two axis
quantities. These transforms developed by R.H. Park, are the widely known Park’s
transformations. The effects of such transformations are to move all the machine timevarying inductance coefficients from the machine flux linkage equations. The widespread
use of the direct axis and quadrature axis equations has been developed from these
concepts. These can also be visualized in terms of d and q axis equivalent circuits. The
order can be defined simply as the number of rotor circuits in either the d or q axis;
depending upon the number of inductance/resistance series combinations representing the
field and direct axis equivalent rotor circuits, or the number representing quadrature axis
equivalent circuits [3].
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Figure 2. Stator and rotor circuits of a synchronous machine [2]
Choosing a Model:
The basic approach taken in generating or finding a model was to first locate
historical work done in this area. The IEEE Xplorer library was the primary source that
provided information relating to model parameters and test procedures of synchronous
generators. Specifically the IEEE standards 1110-1991 and 115-1995 provided a basic
understanding of this subject. After reading through the IEEE standards, many concepts
related to properly modeling the synchronous generator were still unclear
These modeling uncertainties created difficulties in finding the correct model for
the generator. Even though much work has been done historically on modeling dynamics
in a synchronous generator for stability studies, assistance was needed to put this
information into some context. Individuals like Larry Long [16], Professor Tomsovic
[18], and Professor Mani [19] provided assistance in understanding the concepts needed
to find the correct model for the synchronous generator and its relating equations.
When choosing a model for the synchronous generator the main consideration
was keeping to the specifications of Avista. The model desired was a salient pole
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generator. Being that most salient pole generators are constructed with laminate rotors,
the rotors usually include copper damper bars located in the pole faces. The purpose of
the damper windings is to reduce the mechanical oscillations of the rotor about
synchronous speed [4]. These damper bars tend to form a squirrel-cage amortisseur
circuit that is effective both in the direct and quadrature axes because they are connected
at their pole faces with continuous end-rings. Since this amortisseur is the only physical
circuit present in the q-axis, a first-order model can describe it adequately. Hence, Model
2.1 is recommended for most salient pole generators [3].
The model chosen was the “gensal” model from the WECC approved model
library because it represents a salient pole synchronous generator. This model is shown in
Figure 3 and is represented as model 2.1 in Figure 4. The main reason it differs from the
round rotor model is that throughout each revolution of the rotor, the self inductances of
the stator, and the mutual inductances between them, are not constant. These values vary
as a function of the rotor angular displacement θ, which is shown in Figure 2 [4]. The
angle θ, is the angle between the axis of phase a and the d-axis [2]. Also, the salient-pole
model doesn’t saturate significantly in the quadrature axis as it does in the round rotor
model, and thus no quadrature axis saturation is present for Figure 3. As a result, the
equations for the flux linkages of the salient-pole machine are more difficult to use than
their round-rotor counterparts [4]. Fortunately, the equations that pertain to the a, b, and c
phases can be transformed by using Park’s transformations.
Efd +
+
-
-
+
-
+
+
-
d-axis
+ + +
id
iq
q-axis
-
+
-
-
Figure 3. Linearized synchronous generator block diagram of a salient pole, ‘gensal’
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Ll
Lf1d
Rfd
R1d
Lad
Lfd
L1d
Ll
R1q
Laq
L1q
Figure 4. Model 2.1
Model Description:
The model shown above in Figure 3 has been the standard salient-pole model
used in recent years for small-disturbances. The direct axis sub transient open circuit time
constant, T`d0, and the direct axis sub transient open circuit time constant, T``d0, are used
to account for time responses of faults that might occur. For example, if a terminal fault
was simulated from an open circuit, the stator currents would be inversely proportional to
Xd0 (for the sub transient period) and inversely proportional to X’d, (for the transient
period) during the fault [3]. These time constants are normally between 0.01 and 9.0
seconds, depending on the type of generator[2].
When the terminal voltage and three-phase currents of the machine change, so
does the field voltage of the rotor windings. This typically causes saturation in the d-axis
of the rotor. The generator open-circuit saturation curve in the model shows this
saturation relationship and is used to determine the saturation factors in this axis. An
internal voltage “behind some specified reactance” is used to locate the operating point
on the open-circuit saturation curve to calculate a saturation factor K (or a saturation
correction ∆E) [3]. Thus, the internal excitation Xadu·ifd, (or Ladu·ifd) is then the sum of
several components [3]. This form of excitation determination has had widespread use
since the early 1960’s [3]. Equation (3) shows this relationship to Figure 3 in per unit.
X ad  i fd  EI  Eq`  I d ( X d  X d` )  E
(3)
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Programming in Labview:
Using the simulation module in Labview made programming of the synchronous
generator model rather straightforward. A snapshot of the synchronous generator is in
Figure 5 below illustrating the manner this was done. The complications that did arise
occurred during the verification stage of the model.
Figure 5. Screenshot of salient-pole model in Labview.
Due to the fact that the generator is part of an integrated system which includes
various controls, the synchronous generator, by itself, could only be verified to a limited
extent. These tests included responses to changes in field voltage inputs and changes to
the respective input axis currents. The results were used to verify that a particular change
in input resulted in the correct output from the model. After these basic tests were
completed, the generator model was connected to the excitation model of the simulator.
Once connected with the excitation model, a general test was conducted to insure
that it worked properly. This was accomplished by changing the reference voltage in the
exciter model and observing if the terminal voltage of the generator responsded correctly.
After this, the synchronous generator model was incorporated into the simulator with a
load and circuit breaker so validation tests could done. Tests were evaluated by
comparing the synchronous generator outputs from the Noxon report [5] to the simulator
synchronous generator outputs. The only discrepancy between the simulator and the
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Noxon report was that a round rotor synchronous generator was modeled for the Noxon
testing rather than a salient-pole generator.
3.2 Governor/Turbine Model:
Background:
Speed governors are used to regulate the output torque and rotational speed of the
prime mover, in this case the hydro turbine. By controlling the energy input to the
turbine, the governor can effectively regulate the MW load on the generator in a
continual effort to match the generation to the load. By controlling the rotational speed of
the turbine the governor can control the electrical frequency of the generator. To
accomplish these two tasks the governor adjusts the turbine wicket gates, which affects
the amount of water that flows into the guide vanes of the turbine.
It was desired by Avista for the governor model to represent an electro-hydraulic
governor. This type of governor uses solid state electronics to implement feedback
control. It senses the speed of the turbine using a frequency transducer and converts this
signal into a DC voltage using a frequency to voltage converter. This signal is compared
with reference DC voltage that represents the desired operating frequency. The error
between these signals is fed into the PID controller. The output of the governor is an
analog signal that operates the control mechanism necessary to adjust the wicket gate
position. For example, if the measured electrical frequency is lower than the desired
frequency the governor gives a raise signal to open the wicket gates. This increases the
shaft speed and therefore the electrical frequency.
It was also necessary for the model to include speed droop. Speed droop opens the
control valve a specified amount for a given disturbance. By definition droop is the
percent difference between the no-load and full load speeds of the unit. [6] It is necessary
for generators to operate with stability in parallel with other generators in interconnected
systems. In operation, droop causes the generation unit to decrease speed for an
increasing power output so that it doesn’t continually work to maintain a constant speed
under different loading conditions. This allows for generators to share a load increase in
proportion to the different ratings of the generators in the system.
Most electronic governors implement droop that receives feedback directly from a
power (watt) transducer from the generator potential transformers (PTs) and current
transformers (CTs), instead of the control gate position. This is known as speed
regulation [6]. Speed regulation is preferred over droop with gate position feedback
because it is not affected by the nonlinear relationship between the gate position and the
water flow. Electro-hydraulic governors also include a speed reference signal. Using this
input signal an operator or an automatic control system can increase the desired rotational
speed of the unit. The speed reference signal can be used to set the individual loading of a
unit.
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Governor/turbine models also include representation of the hydraulic system
which is used to position the wicket gates. In the real world this is usually a pressurized
oil system. A pilot valve is used to direct pressurized oil to the prime mover actuators as
controlled by the PID controller. The pressurized oil is relayed to servo motors that
transmit this hydraulic pressure to a rotating gate ring which is attached to the wicket
gates of the turbine. The rate at which the gate opens and closes as well as the time
constants of the pilot value and servo motors need to modeled in order for an accurate
simulator.
In addition to the governor and hydraulic system it was also necessary for a prime
mover to be modeled. The prime mover converts kinetic energy from rushing water into
mechanical energy necessary to rotate the shaft of the generator. A Francis turbine is
modeled as the prime mover. A Francis turbine is a reaction turbine that is used at dams
with larger head levels, usually 50 to 2400 feet [7]. How the Francis turbine performs is
influenced by several characteristics of the turbine as well as the water column behind the
turbine. Several non-ideal characteristics of the water column include water inertia and
water compressibility as well as the elasticity of the penstock walls. Head level, flow rate,
and penstock length are also factors that should be accounted for. These factors are
usually modeled into the water starting time. The water starting time is defined as the
time required for water flow to in the penstock to accelerate from zero to no load water
velocity given some initial head level. [2]
The turbine’s relationship between the ideal gate opening and real gate opening
was also necessary to be modeled. This is modeled as an overall turbine gain. This can be
found by inverting the difference between the full load gate position and the no load gate
position. Finally the non-linear relationship between the gate position and power at the
turbine must be modeled. This relationship is measured during the real time operation of
the turbine and modeled using a lookup table.
Choosing a Model:
The process of researching and finding an appropriate governor/turbine model
was fairly difficult. Initially, during the research process, the main source of information
was the IEEE Xplorer. The IEEE Xplorer is a library of IEEE documents that cover a
wide range of technical subjects which includes power system control modeling. Many of
the governor models found were designed to represent the older mechanical governors
which included transient and permanent droop instead of PID control and speed
regulation.
The initial model chosen for the simulator was the PID governor model “gpwscc”
as recommended by Larry Long [16]. This is an accepted model of the Western
Electricity Coordinating Council (WECC) and can be used in most steady state and
transient analysis studies. The only drawback is that the turbine depicted in this model
was an ideal lossless turbine represented by a single transfer function. For simulations
involving large variations in power output and frequency this ideal turbine model is not
appropriate [2]. It was preferred to have a more accurate turbine model that accounts for
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non-ideal properties such as an inelastic water column as well as flow rate and head level.
After contacting Kristina Newhouse [17], the model Avista provided was the hyg3 model
as shown in Figure 6. This model is used to represent the governor/turbine for Unit 1 at
Noxon Rapids generation station.
Governor
Hydraulic system
Francis Turbine
Figure 6. Hyg3 Model
Model Description:
As seen from Figure 6 the desired governor characteristics (droop, PID control,
etc.) are incorporated into this model. Droop is shown as ‘relec’ while the PID controller
gains are ‘ki’, ‘k1’ and ‘k2’. Transducer delay effects are also modeled using first order
transfer functions. The inputs to the model are electrical power, reference power (or
speed setpoint) and the speed deviation. The resulting outputs are the mechanical power
and the gate valve position.
It should be noted that the model shown in Figure 6 has been modified from the
original Hyg3 model. The model shown in Figure 6 neglects the option of using gate
droop feedback from the control value. Instead this model only allows for electrical droop
(speed regulation) because it is more frequently used. Although deadband is shown in
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Figure 6 it is usually not modeled because it is difficult to get the necessary data to model
it [2].
A hydraulic system and detailed turbine model representing a Francis turbine are
also shown in hyg3. For the hydraulic system, the first transfer function represents the
pilot valve and servo motors. This transfer function is limited by the maximum rate at
which the gate can open and close. The gate position is modeled by the integrator block
and is limited by the maximum and minimum gate positions. The output of the hydraulic
system in the model is the gate valve position.
The value of the gate value position is fed into the non-linear lookup table that
converts the gate position to the power at the gate valve. This value is then fed into the
turbine model which calculates running values of the head level and flow rate. The water
time constant, as discussed earlier, is modeled as ‘Tw.’ The block labeled ‘At’ is used to
account for the difference between the ideal gate opening and real gate opening.
Programming in Labview:
Programming the hyg3 model into Labview using the simulation toolkit was fairly
straightforward. Since the simulation toolkit supports linear and non-linear functions such
as transfer functions and saturation limiters, the block diagram shown in Figure 6 was
programmed in a few hours. A screen capture of the governor/turbine model is shown in
Figure 7 below.
Figure 7. Screenshot of the governor/turbine model in Labview
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Difficulty arose during the debugging and verification stages. Even if the model
could be programmed into Labview fairly quickly, there was no way to tell if the model
was functioning correctly unless there was data to compare it with. In order to determine
if the model was functioning as desired, different scenarios were simulated. By
connecting the output of the model, Pmech, back to the input, Pelec, it was possible to
simulate feedback control. After running the simulation, the output had a steady state
value of the reference input. This showed that the PID controller was functioning
correctly.
Other tests included varying the speed deviation, dW, and the reference speed,
Pref. Since the inputs are in per unit, Pref has a range from 0-0.04 per unit assuming the
droop is set to four percent. By adjusting this value to 0.03 for example the output power
of the system was verified to level off at 0.75 per unit. To test the dW input, the
frequency was adjusted by -0.01 per unit. A one percent drop in frequency should result
in a 25% increase in the power output if the unit is set to four percent droop. See
Equation (4) for this calculation. The model response was verified for this test as shown
in Figure 8.
Ppu  Pref 
1
 .01
f  0 
 0.25 pu
R
.04
(4)
Figure 8. Model response for 1% frequency drop
During simulation, probes were used to measure various points in the system. As
a result of this testing several problems in the system were discovered. It was noted that
the integrators of the system had to be limited to prevent them from going to infinity in
certain cases.
Another problem with the model dealt with initial conditions. Due to the feedback
loop shown in the turbine model Labview was unable simulate hyg3. Without initial
conditions this created what is called a cycle. A cycle is where one calculation point, say
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node 1, is waiting for the output of another node, node 2 for example. Node 2 is also
waiting for the output from node 1. If neither of these nodes are initialized with presimulation conditions, the results are NaN (not a number). This problem was resolved by
creating a simple initial conditions function.
3.3 Excitation Model:
Background:
The primary function of an excitation system is to provide direct current to the
field winding of a synchronous generator so voltage can be induced in the armature
winding. It also regulates the generator’s terminal voltage and reactive power output by
controlling the DC current that is applied to the field windings. A typical excitation
system contains five subsystems; an exciter, voltage regulator, terminal voltage
transducer and load compensator, power system stabilizer, and limiters and protective
circuits, Figure 9.
Figure 9. Excitation block diagram [2]
The first subsystem of the excitation system is the exciter. The exciter provides
the necessary DC power to the synchronous machine's field windings to maintain a
desired terminal voltage. It was desired to model a DC excitation system as apposed to
newer AC and static excitation systems because this is what Avista has in place at Noxon
Rapids Unit 1. A DC excitation system uses a DC generator with a commutator to provide
power.
The next major subsystem is the voltage regulator. The voltage regulator controls
the amount of excitation that is applied by the exciter. It receives voltage signals from the
generator(s) as well as the operator set voltage reference. The error between these two
signals is used for the excitation control. This is known as feedback control. Depending
on the excitation type, proportional, integral, and differential (PID) controls are used to
improve voltage profile and the regulator's dynamic response.
The third subsystem is the terminal voltage transducer and load compensator. This
senses the generator's terminal voltage, VT, and line current, CT, and can use them to
18
calculate a compounded terminal voltage. With load compensation, the excitation system
can be used to regulate voltage at a set point out in the system. Although currently not
relevant for the hydro simulator, some excitation systems include an automatic voltage
regulator, AVR, which uses inputs from other local synchronous machines to control the
machine's terminal voltage since they share a common load.
The fourth subsystem is the power system stabilizer, or PSS. The PSS provides an
additional signal to the regulator to enhance damping of power system oscillations.
Commonly used input signals are terminal voltage, accelerating power, rotor speed, and
frequency deviation. Although the power system stabilizer is an important part is system
stability it is not implemented at Noxon unit 1 therefore is not necessary to be modeled.
The fifth subsystem is the protective circuits and limiters. Various control and
protective features work to ensure that the limits of the both the exciter and the generator
are not exceeded. If they are exceeded, some of these functions can also take emergency
action and signal the breaker to take the generator offline. Some of the commonly used
functions are over/under excitation, field-current limiter, terminal voltage limiter, and
volts/hertz limiter.
Excitation systems need to be able to control the generator’s operation not only
during steady state conditions, but during transient, and post disturbance conditions.
Failure to due so could result in power outages and equipment damage. The ceiling
voltage and the response rate are the main factors that determine how well an excitation
system can respond to sudden changes during disturbances.
The ceiling voltage is the maximum field voltage the exciter can operate at [7]. It
usually ranges from 1.5 to 6 times the field voltage during full load conditions. The
response rates deals with how fast the excitation system can respond to changes in
voltage. It is defined as the time required for the exciter to go from open circuit voltage to
the ceiling voltage when then generator is at full load field voltage [7]. These conditions
are necessary to be incorporated into the model.
Choosing a Model:
The excitation model to be used in the hydro simulator is EXAC8B, an approved
WECC model, which is also known as the AC8B by IEEE. This model is shown in Figure
10, with the colored blocks representing the different sections of the model. The
EXAC8B was chosen after Larry Long [16] suggested using this model due to the fact
that it reflects the digital PID controls that are similar to the Basler DECS300. The
EXAC8B models an AC excitation system which uses an AC alternator and either
stationary or rotating rectifiers to produce the DC field. Although this model was
developed for brushless AC exciters, it can be used to model a DC exciter simply by
settings the gains of Kc and Kd to zero.
19
Figure 10. AC8b/EXAC8B Model
The “AC” type models are not valid for frequency deviations of +- 5% from the
rated frequency, 60Hz and oscillation frequencies up to about 3 Hz [8]. This is because
the model does not account for regulator modulation as a function of the system
frequency. Hence this model should not be used to study sub-synchronous resonance or
other shaft torsional interaction problems. The synchronous machine's field current must
be supplied back to the model in order for it to represent loading effect accurately.
Model Description:
EXAC8B receives the following inputs from the synchronous generator:
compound terminal voltage ‘Vcomp (or ‘Vc’), generator field current ‘Ifd’, and ‘Vs’ from
the power systems stabilizer, if in use. Section A in Figure 10 is the PID voltage regulator.
This takes the sum of ‘Vsig, ‘Vc’, and ‘Vref’, and amplifies the signal in block B. The
time constant, ‘Tdr’ represents lag from the PID controls and ‘Ta’ is the lag from the
voltage amplifier. The constant ‘Ka’ represents the voltage regulator’s set gain. The
output of the voltage regulator is now a regulated voltage, ‘Vr.’ This signal is used to
control the excitation system, which is modeled in blocks C and D.
Section C uses ‘Vr’ in a feedback loop and also receives the generator field
current, ‘Ifd’. The time constant in the integration block is the lag associated with the
exciter. The output from this block is the exciter voltage, ‘Ve’. This voltage is multiplied
with ‘Fex’ to represent ‘Efd’, the exciter field voltage that is fed to the generator. The
exciter voltage is used to calculate a voltage, ‘Vx’, which is proportional to exciter
saturation between the field current and field voltage as the load increases.
Section D models rectifier regulation. Rectifier regulation is a non-linear effect
that decreases the rectifier output voltage as the load current increases. The expression for
'Fex' is determined by the value of 'In.' There are three specific modes of operation, as
shown in Table 2.
Table 2. Rectifier regulation effect
20
Mode 1
f(In)=1.0+0.577In
In  0.433
Mode 2
f(In)= 0.75 - In 2
0.433 < In < 0.75
Mode 3
f(In)=1.732(1.0-In)
0.75  In  1.0
It should be noted that although DC exciters ignore effects of rectifier regulation and field
current feedback, these features were still modeled incase a user desired to simulate an
AC excitation system.
Programming in Labview:
By using Labview’s simulation toolkit, programming the excitation system took
only a couple of hours. Once EXAC8B was programmed into Labview, a few basic tests
were performed to validate that the model worked as expected. Model parameters from
the Noxon report [5], specifically unit 1, were programmed into the model and set as the
models default parameters. Figure 11 shows a screen capture of the programmed
excitation system model.
Figure 11. Screenshot of the excitation system in Labview
To perform the test, the output ‘Efd’ was fed back to the input, ‘Vc’. Normally the
compound terminal voltage, ‘Vt’ from the generator would be fed into ‘Vc’, but since
‘Efd’ and ‘Vt’ are proportional it can be done. The gains Kc and Kd were set to zero for
this to model a DC excitation system. The additional voltage signal, ‘Vsig’ was set to
zero because this input is from a PSS and this component is not needed for modeling unit
1 of the Noxon plant. For the first test, the reference voltage, ‘Vref,’ was initially set to
0.1 per unit (pu) and speed to 1 pu. When ‘Vref’ was increased to 0.8 pu, ‘Efd’ also
increased. When ‘Vref’ was decreased back to 0.1 pu, ‘Efd’ decreased, see Figure 12.
This test demonstrated that when the reference voltage is increased or decreased, the PID
controller drives the field voltage to this same reference value.
21
Figure 12. Resulting field voltage after changing the input, Vref
For the next test ‘Vref’ was held at 0.5 pu and the speed signal was changed.
When “speed” was decreased from 1 pu to 0.8 pu, ‘Efd’ initially decreased. The voltage
regulator amplified this error and the PID controller brought the level of the field voltage
back up to the reference value. Likewise, when the speed signal was increased, ‘Efd’
increased and then automatically decreased to the set level, as shown in Figure 13. These
results follow what should be expected. If the speed of the generator decreases, power
output and terminal voltage will decrease as well. To stay at the desired voltage the
excitation system compensates for the decrease in speed by increasing ‘Efd’. The same
response is seen if the speed increases, but instead ‘Efd’ is decreased to maintain the
reference voltage.
Figure 13. Resulting field voltage after change in speed
A few problems were encountered while working on the excitation model. The
first problem with the model was that the original diagram provided by Larry Long was
incorrect. Highlighted in Figure 14, block A has two inputs but no outputs. This problem
was thought to be solved by looking at other documentation of the EXAC8B [9]; which
22
shows that the output of the block A connects directly to block B and that the only input
to block A was from ‘Ladifd’, not from block C.
Figure 14. Exac8b model with labeled blocks
Eventually, while looking at the two different sources, it was discovered that
block A actually received inputs from block C and ‘Ladifd’, [2],[8],. It was also verified
that block A output was the input to block B. The rest of the model was verified to be
correct. The other problem with the EXAC8B model was some confusion in what block
B represented. It was later discovered that the output from block A, representing the
rectifier current, which is used to determine which equation should be used to calculate
Fex, see Table 2.
3.4 Protection Model:
Background:
A protection model was also necessary be included in the simulator. This model
was developed using several features from the Schweitzer 300G protection relay. The
300G provides protection for the generator by controlling the current, voltage, and
frequency outputs from the generator. Some of the key features of the 300G relay include
current differential protection, out-of-step protection, over excitation detection,
directional power protection, volts/hertz Protection.
Even though the relay provides numerous protection features, only a handful of
features were chosen to be incorporated into the simulation design due to the design of
the generator model. For example, in the simulator, the generator output is simply a per
unit value for the magnitude of the terminal voltage. Since many of the protection
elements use a three phase input for their calculations, only the over and under voltage,
over and under current and frequency protection elements were chosen to be modeled.
23
Over and Under Voltage:
Phase over voltage protection operates by measuring the output voltage at the
generator terminals and compares this with a reference maximum value. In an actual unit
the voltage is simply measured with potential transformers (PTs). If the measured
secondary voltage is higher than the maximum reference voltage, the under voltage
protection element is activated. This element will open the circuit after a certain amount
of time proportional to the magnitude of the measured voltage, if it is greater than the
reference voltage. Phase under voltage protection uses this same concept.
Over and Undercurrent:
Phase overcurrent protection operates using the maximum of the measured phase
current magnitudes. Phase undercurrent protection operates using the maximum of the
measured phase current magnitudes. There are many types of overcurrent elements which
the 300G relay provides for protection of the generator. Some of the typical elements of
protection are definite time overcurrent, neutral time overcurrent, residual time
overcurrent, and voltage controlled definite time overcurrent protection.
Frequency Protection:
Over frequency conditions usually occur during dramatic load variations. In order
to provide protection during these situations frequency protection is provided. The relay
provides six bands of over/under frequency protection. The pickup settings for the under
and over frequency elements are 59.5 Hz and 60.5 Hz respectively. When the frequency
deviates below 59.5 Hz it will fall in one of the six protection bands. The greater the
frequency deviation the fast the relay will operate. Figure 15 shown below provides a
more detailed description of how under frequency protection works in the 300G relay.
Figure 15. Under frequency operation [10]
The band between 60 and 59.5 Hz is the area of unrestricted time operating
frequency, while the dotted areas below 59.5 Hz are areas of restricted time operating.
Table 3 shows a more detailed description of the different operating conditions.
24
Table 3. Under frequency operation description [11]
Frequency Band (Hz)
Time delay
Comments
60-59.5
No action, generator can
operate
59.5 and below
1.5 s
Continuous under frequency
alarm
59.5–58.8
50 min
Alarm “under frequency
58.8- 58.0
9 min
limit exceeded.” These
58-57.5
1.7min
bands may trip or alarm
57.5-57
14 sec
depending on individual
57 - 56.5
2.4 sec
utilities’ practices.
56.5 and blow
1.0 sec
Programming in Labview:
As with the other models, Labview’s simulation toolkit was used to implement
the protection model. One challenge during programming the model was making the
correct timer from the simulation toolkit for the frequency and overcurrent elements.
Initially, the frequency and current protection models failed in situations when the
simulation speed was increased because the timer used in the while loop and simulation
loop were mismatched. The simulation loop timer ran faster than the while loop timer.
Therefore, a different approach was used where the timing from one loop was linked to
the other.
Over and Under Voltage Labview Model:
The function of the under and over voltage model is to read the terminal voltage
from the generator and feed this value to a comparator with respect to the voltage
reference. The comparator then checks if the given voltage is below or above the
reference voltage. A Boolean value is returned to determine if the relay is to trip the
circuit breaker. Figure 16 shows the Labview screenshot for the under and over voltage
model.
Figure 16.
Under
Over
voltage
model
25
Overcurrent Labview Model:
The overcurrent element was programmed using the U.S Inverse curve U2. This
equation can be used to calculate the operating time of the relay see Equation (5).
5.95 

tp  TD * 0.180  2 
(5)
M  1

The time dial (TD) settings are used to control the slope of the inverse curve. The
more inverse the slope, the faster the relay will operate for a given current. The operating
time (tp) is the time which the relay will operate for a given current input. Multiples of
pickup current (M) are given by the ratio of the input current to pickup setting. In this
model ‘Ipickup’ is set to 5A secondary current. Current input (Iinput) is the output
current from the generator. A screen capture of this model is shown in Figure 17.
Figure 17. Screenshot of the Overcurrent model in Labview
Under Frequency Labview Model:
The under frequency model monitors the generators operating frequency to
make sure it is within the acceptable bounds of 60 Hz. If the generator's frequency is
below a certain limit frequency, then this model determines if the generator is
disconnected from the grid. A screen capture of the under frequency model is shown in
Figure 18.
26
Figure 18. Screenshot of the under frequency model in Labview
For the Labview model, this is done by monitoring the generators, operating
frequency and comparing it to a set “trip frequency”, in this case 59.5 Hz. If the operating
frequency is below 59.5 Hz then the case structure, which holds the current simulation
time, turns false and captures the time at which the operating frequency entered the
“restricted operation” zone. To calculate the elapsed time the generator is in “restricted
operation” zone, the captured time is subtracted from the simulation time. To determine if
the generator is disconnected from the grid, the elapsed time is compared against
different time bands as shown in Figure 15. If the time exceeds one of the time bands for
a given frequency range then the generator is disconnected from the grid.
3.5 Phase II:
As mentioned earlier in this report, the Phase II stage of this project is not a major
part of this groups work. Instead, team Ironwood has assembled the beginning portions of
the work needed to be done for the physical interfacing with the generator simulator. To
recap, Phase II consists of integrating the software simulator with the physical control
devices being modeled within the software. Therefore, if the user/utility wanted to use an
27
actual Woodward 505H governor in the simulation, the software model for the governor
would be deactivated and the physical device’s inputs and outputs would be connected to
the simulator via a PLC and DAQ. The simulation would then run as it normally would,
only the governor control signals are given from the actual governor. Figure 19 is shown
to give a general schematic of how the physical system would be interconnected.
Figure 19. Phase II layout for connecting a 505H
For purposes of this project, the group has determined the following I/O’s to be
those covered to meet the requirement of physically connecting the governor and
excitation system into the simulation. The information given below is based on the I/O’s
typical for a Woodward 505H digital governor and a Basler DECS300 voltage regulator.
The highlighted items are those covered by the PLC with the remaining to be covered by
the DAQ.
Table 4. I/O Layout between the PLC and DAQ
Governor:
Voltage Regulator:
(6) Analog Inputs (4-20 mA)
(1) Generator Voltage Sensing (~120 V)
(6) Analog Outputs (4-20 mA)
(2) Generator Current Sensing (~1 A)
(1- 2) Speed inputs (1-30 Vrms)
(13) Switching contact inputs (24 Vdc)
(16) Discrete Inputs (18-26 V dc) (1) Remote set point control Input (-10 to 10 V)
(1-2) Actuator Outputs (4-20 mA) (1) Analog output (-10 to 10 volts or 4-20 mA)
(8) Discrete Outputs (form “C”)
(8) Contact outputs
28
In order to handle the various I/O’s required of the PLC, various control cards are
needed. To ensure the correct parts were chosen, the customer service department for the
PLC was contacted and the above list of requirements was given to them. Avista
requested the use of a Modicon Quantum PLC as it is one that they have used in the past.
The company responsible for the Quantum PLC is Schneider Electric, based in Palatine,
IL. The customer service representative (Joe Cyr) was briefed on the requirements of the
PLC for this project and the following parts list was established to do the job. The pricing
for the below PLC parts, shown in Table 5, were quoted on 10/22/2007 from Graybar, the
supplier Avista will most likely be using should they choose to order these parts.
Table 5. PLC Quote
Description
Part Number
10 Slot Backplane
140XBP01000
AC Power Supply 115/230V
140CPS11420
Quantum 434 Controller (High End) 140CPU43412A
Quantum 512K CPU (Mid Range)
140CPU11303
Relay Out 16 x 1 NO
140DRA84000
Analog Out 4ch Current
140ACO02000
Discrete DC Input Module
140DDI35300
Total with High
End CPU:
Total with MidRange CPU:
Price
$481.24
$994.47
$8,615.57
$5,178.24
$740.20
$1,479.61
$740.20
$13,051.29
$9,613.96
While these pieces of equipment cover the requirements of the PLC, there are a
couple of signals that still remain uncovered for the voltage regulator I/O’s. The
generator voltage and current sensing signals are two inputs into the voltage regulator
that require a voltage and current amount that exceeds the rated handling of any PLC and
DAQ card available. A possible solution to this may lie within using an external source
such as a Doble power source to generate these high values required. Being that Phase II
is beyond the scope of this group’s project, the details in solving this issue will be left as
is and remain to be solved by others.
Data Acquisition:
The Labview simulator is designed to also communicate with the physical control
devices using Data Acquisition methods developed by National Instruments, the same
company that develops Labview. These types of equipment are designed to seamlessly
interface directly with any virtual instrument developed in Labview with little additional
programming. DAQ devices can accept a wide range of analog and digital inputs from
the control I/Os that will be hardwired to the device itself.
After deciding which control device I/Os will interface with the PLC and which
will interface with the DAQ, it was desired to find an effective, low cost solution. As
previously discussed the PLC will be handling more of the digital I/Os while the DAQ
will handle much of the analog I/Os such as the actuator signals and the speed signals.
29
National Instruments offers several methods that would work. Figure 20 shows several of
the data busses available.
Figure 20. Bandwidth vs. Latency of various busses [12]
The first option researched was PXI/PCI interface method. This option proved to
be one of the best methods. It could cover most of the required I/Os and also interfaced
with the computer using the PCI slot. Also, the I/O card purchased for this system would
all run on the same clock so there would be no problems with synchronizing the different
I/O modules. Even though this option had the most benefits, they did not outweigh the
cost of this option. After configuring a complete system to handle the necessary analog
I/Os, the PXI method would have run roughly $6000 to $8000.
After further research, the method eventually decided upon was the compact DAQ
system. This system provides a simple means to interface with the computer using USB
2.0. It is much cheaper than the PXI interface method. As it can be seen from Figure 20,
USB 2.0 provides good bandwidth with a fairly low latency. Another benefit in using
USB is that it is designed to take advantage of the plug and play feature of a Windows
computer with no additional hardware necessary, similar to a USB thumb drive. The
computer can automatically detect the new device when it is attached. The only drawback
to this system is that the USB 2.0 bus shares its bandwidth across all the I/O modules.
This means that when all the modules are connected to control devices there may be
some time delay in transferring the data. However according to a National Instruments
engineer, Avinash Harjani [15], this is not a significant problem for this application. A
typical compact DAQ system is shown below in Figure 21.
30
Figure 21. A compact DAQ system attached to a computer [13]
As it can be seen from Figure 21, the compact DAQ uses a chassis where several
I/O modules are connected. The chassis provides power for the signal generation of the
I/O modules. The individual control and measurement modules are designed to interface
with control devices using screw terminals. The process of selecting the appropriate I/O
modules was fairly straightforward. The analog and digital signals from the Woodward
505H and Basler DECS300 not covered by the PLC were matched to the appropriate
modules using the compact DAQ builder on the National Instruments website. After
developing a compact DAQ system a National Instruments applications engineer verified
that the I/O modules selected would be appropriate for this application.
Some of the analog signals created more of a problem. One example is the speed
signal that is fed into the Woodward 505H. This speed signal is of the magnitude 1-30
volts RMS. The I/O modules for the compact DAQ system are only in the range of 0 to
10 volts and 0 to 20 mA. Not only did a DAQ device need to be able to generate this
signal, it had to do so at the appropriate frequency because this signal represents the
signal read from the speed transducer. By working with the applications engineer from
National Instruments the PCI-6624 was chosen as shown below in Figure 22.
Figure 22. The NI-PCI-6624 DAQ card [14]
This card plugs directly into the PCI slot of a standard computer. Although this
card runs at about $1,300, it is able to provide eight channels of frequency controlled
analog voltage. When connected and programmed properly, this DAQ card should be
able to mimic the speed signal from a real hydro plant. After verifying this card, a full
quote was developed by customer service at National Instruments. This quote is shown
below in Figure 23 with the total price for the DAQ system at $4,671.
31
Figure 23. National Instruments DAQ quote
IV. Quality:
Quality in Software:
When looking at the main work that was done for this project, the majority of the
time was spent within the software models. The generator, exciter/voltage regulator,
turbine/governor, and the protection device each have their own Labview software
model. However, the design for each model was based on the general operating principles
of its physical counterpart and the respective standard that it followed. Therefore, the
quality of each developed software model was tested to meet similar specifications.
32
To meet these specifications, each model underwent an end item verification
process throughout the design and upon completion of the finished model. This was done
to reduce any final troubleshooting time as well as to verify that the developed model met
the requirements for its respective device after major programming changes were made.
Not only was the model checked against requirements of the device, but also verified to
meet the functionality of parameters desired by the customer. With each model passing
its respective tests, the final deliverable (hydro generator simulator) was tested to verify
that each component worked compatibly with one-another.
To ensure the quality of the software models, various test procedures specific to
each model were also developed. These verification procedures were implemented for
each respective model, and for a couple of protection schemes. These tests determined
how accurately the developed software models simulated the operation of the physical
devices they were representing. An example of such a test was the comparison to the
Noxon Report simulation [5], which was done at one of Avista’s current facilities. This
was emulated on the simulator to see if the modeled equipment responded in a similar
way that the Noxon report did. To expand the testing even more, the simulation
parameters were tested to determine the range of the respective parameters the models
could operate in.
With the equipment models being tested in this fashion, certain parameter
boundaries were enabled. The software was made to simulate a hydro generator, so
proper operating boundaries were checked. These boundaries were checked before and
during the simulation. For example, if an actual turbine had a speed limitation of 100
RPMs, then a user input of 200 RPMs would be responded to with an error prompt
notifying the user, telling him to input another value. With these boundaries set and
proper testing complete, the quality of each software model was assured.
Reliability:
Finally, to insure the reliability of the software, all specifications of each
respective model were tested and challenged. This enabled the design team to check
when the software was vulnerable to errors, thus rendering it useless. To further prolong
the life of the software, a modular development approach was taken. This approach
allowed the design of the software models to be easily substituted in and out of the
overall system. This permitted for future device changes and upgrades to be accounted
for. For example, if a company would change their voltage regulator to a new model, the
corresponding block could be changed by simply adding in an updated module in the
place of the current one.
33
V. Manufacturing:
Producing a Deliverable:
As a product that is individually tailored for the client, the hydro generator
simulator is an item that is produced in relatively small numbers. The product is
developed for power utilities that have specific requirements and regulations that their
personalized simulator must adhere to. With the client base of the product being a fairly
narrow one, the client can rest assured that their product will fit their needs. This
personalization and attention to detail therefore means that a large manufacturing facility
for mass production will not be necessary.
The overall manufacturing process for the hydro generator simulator consists of
two parts, the software and the interface panel. The software consists of the hydro
generator simulator along with all of the control device models. This single program runs
using the Labview application on the customer’s computer to form the overall simulation.
The interface panel is the physical device that allows the customer to integrate actual
control elements into the computer simulation. The final design and assembly of the
interface will be done by the customer, but information provided by team Ironwood
offers a starting point and some general information needed to create the interface.
The completed product includes all of the software, interface panel (Phase II)
documentation and a manual covering the details for each model and what conditions the
simulator can model. All of this data is included on a compact disk. This results in a very
simple manufacturing process since all that is needed to be produced is a CD.
Product Validation:
With the final software and documentation loaded onto a compact disk, final
verification procedures were implemented to ensure the disk is ready to be delivered to
the customer. The software was first installed onto a generic computer that met minimum
specifications. Once the software was installed, several basic simulations were run. This
ensures that no essential modules of the software are missing or erroneous. The different
trials place specific stress on individual sub-functions within the software.
Along with the software install validation, the included documentation was
checked to confirm they have been successfully installed on the computer. Since these
procedures simply verify the proper installation of the software and corresponding
materials, minimal time is taken. After the manufacturing tests have been run, the disk
can then be labeled and is ready for delivery to the customer.
Estimate of Other Production Costs:
As was discussed in the Phase II portion of the Engineering section of this paper,
two quotes were obtained covering the costs of the PLC and DAQ equipment. The final
34
pricing for these items are given in Table 6, neglecting the necessary man-hours needed
to assemble the interface panel.
Table 6. Estimated cost of the interface panel
High Cost
Low Cost
Modicon Quantum PLC
$13,051.29
$9,613.96
NI DAQ
$4,671.60
$4,671.60
Total
$17,722.89
$14,285.56
35
VI. References:
[1] Wikipedia, “Hydropower,” www.wikipedia.org, 2007. [Online]. Available:
http://en.wikipedia.org/wiki/Hydropower. [Accessed: April. 9, 2007].
[2] [Kundur] P. Kundur, Power System Stability Control, 1st ed., San Francisco:
McGraw-Hill Inc., 1994.
[3] IEEE Power Engineering Society, Power System and Electrical Machinery
Committees, " IEEE Std 1110-1991," IEEE Guide for Synchronous Generator Modeling
Practices in Stability Analyses, 1991.
[4] J.J. Granger, W.D. Stevenson, Jr., Power System Analyses, 1st ed. , San Francisco:
McGraw-Hill, Inc., 1994.
[5] Hannett, Louis N, “Report to: Avista Corp. for Noxon Rapids 1-4,” 28 April 2005
[6] WECC Control Work Group, WECC Tutorial on Speed Governors, WECC, 1998.
[7] Avista Generation Staff, Introduction to Generation, Avista Utilities, 2001.
[8] IEEE, “IEEE Recommended Practice for Excitation System Models for Power
System Stability Studies,” IEEE Std 421.5-2005 (Revision of IEEE Std 421.5-1992), 21
April 2006.
[9] Pacific Gas and Electric Company, “System Impact Study”, www.energy.ca.gov, 2005.
[Online]. Available:
http://www.energy.ca.gov/sitingcases/humboldt/documents/applicant/afc/Volume_02/App
endix%205/HBRP_Appendix_5B_System_Impact_Study.pdf, pp. 146 [Accessed: Oct.
13, 2007]
[10] Schweitzer Engineering Laboratories Technical Staff, SEL-300G Multifunction
Generator Relay Instruction Manual, Schweitzer Engineering Laboratories, 2006, pp. 299.
[11] IEEE Power Engineering Society, Power System and Electrical Machinery
Committees, ANSI/IEEE C37.106-1987,"An American National Standard IEEE Guide
for Abnormal Frequency for Power Generating Plants, 1987, pp. 19
[12] National Instruments, “Digital What Makes a Bus High Performance,” www.ni.com,
2007. [Online]. Available: http://zone.ni.com/devzone/cda/tut/p/id/4819. [Accessed: Sep.
17, 2007].
[13] National Instruments, “NI Compact DAQ,” www.ni.com, 2007. [Online]. Available:
http://www.ni.com/dataacquisition/compactdaq. [Accessed: Nov. 15, 2007].
36
[14] National Instruments, “NI PCI-6624,” www.ni.com, 2007. [Online]. Available:
http://sine.ni.com/nips/cds/view/p/lang/en/nid/12501. [Accessed: Nov. 15, 2007].
[15] Avinash Harjani (private communication). 2007.
[16] Larry Long (private communication), 2007.
[17] Kristina Newhouse (private communication), 2007.
[18] Kevin Tomsovic (private communication). 2007.
[19] Mani Venkatasubramanian (private communication). 2007.
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