2. The SRM has becoming an attractive alternative in variable speed drives, due to
its advantages such as structural simplicity, high reliability, and low cost.
An important characteristic of the SRM is that the inductance of the magnetic
circuit is a nonlinear function of the phase current and rotor position.
So, for the control and optimization of this drive, a precise magnetic model is
necessary.
To obtain this model is not an easy task, because the magnetic circuit operates at
varying levels of saturation under operating conditions.
Further, the nonlinear characteristic of this plant represents a challenge to
classical control.
To overcome this drawback, some alternatives have been suggested in using
fuzzy and neuronal systems.
It proposes to control SR drives using FLC, which is mainly applied to complex
plants, where it is difficult to obtain accurate mathematical model or when the
model is severely nonlinear.
3. FLC has the ability to handle numeric and linguistic knowledge simultaneously.
In this section we present a study by simulation of the use of an FLC for SR drive.
The SRM simulated has a structure of six poles on the stator and four on the rotor
and power of 1HP.
The nonlinear model of this motor was simulated with the Matlab Simulink
package and two tables were used to represent the nonlinearities: I(θ, λ), current in
function of rotor position and flux, and τ (θ, I), torque in function of rotor position
and current.
The objective of the FLC is to present a good performance, even if the two tables
for a given motor were not accurately determined.
The proposed control can be divided into two parts. The first employs FLC and
will generate current reference variations, based on speed error and its change.
The second one has the function of selecting the phase that should be fed to
optimize the torque, based on rotor position.
4. A. Motor:
In a SRM, both stator and rotor have different magnetic reluctance among
various radial axis.
Figure shows the controlled SRM, which has six poles on the stator and
four on the rotor.
Fig: SRM with six poles on the stator and four poles on the rotor
5. SRM electromechanical model can be represented by the following equations:
where V is the stator voltage, R resistance in the winding, λ leakage magnetic flux,
τe electromechanical torque, τL load torque, θ rotor position, ω speed, and J
momentum of inertia.
6. B. Motor Simulation:
Matlab Simulink package was used to simulate the SRM.
This choice was taken because this software has a good performance and satisfies
all features required.
Simulation was based on equations and the tables of torque in function of angle
and current, τ (θ, I) and current in function of angle and flux linkage, I(θ, λ).
These tables, extracted from the numeric data of the motor design by a finite
elements program, were used to avoid the time consuming due to partial derivatives
equations solution.
See in Figure the block diagram used.
10. Both antecedents and consequent linguistic variables are represented by seven
triangular membership functions as shown in Figure. The rule database formed with
the given inputs to obtain the output is as shown in Table.
Finally to conclude, to get dynamics performance predictions of SRMs,
including its control, a simulating model has been shown.
The nonlinear modeling has been represented by look-up tables to obtain torque
and current. A control has been developed for the SRM speed.
This control has two parts. Part 1 determines the reference current, and so
electromechanical torque.
Part 2 chooses which phase should be fed, based on θ and speed, and is
responsible for imposing speed direction.
It was shown that inverting speed direction by energizing the phase with
decreasing inductance to deaccelerate the motor provided speed overshoot, while the
use of load torque on deacceleration made the speed response more smooth.
The FLC has demonstrated a good accuracy and has performed well for the
speed control of the SRM, surpassing its nonlinearities.
12. One of the important operating requirements of a reliable power system is to
maintain the voltage within the permissible ranges to ensure a high quality of
customer service.
In modern bulk power system, voltage instability would lead to blackout which
is of major concern in planning and operation of power system.
Voltage instability is characterized by variation in voltage magnitude which
gradually decreases to a sharp value accompany with simultaneous decrease in
power transfer to load end from the source.
Prior to voltage instability, bus angle and frequency remain constant but after
the occurrence of voltage instability the reactive power absorbed by the
Transmission line increases to such an extent that becomes difficult to maintain the
voltage magnitude within the limit.
Hence it may be rightly said that voltage instability occurs due to the inability
of the system to supply reactive power to the load.
It may also occur due to the network disturbance such as loss of an important
transmission line, transformer or generator may also occur due to the line fault or
bus fault, heavy HVDC power flow without adequate shunt capacitance and
inverters.
13. In practice to overcome the above problems, usually controlling devices such
as tap changing transformers are employed.
However they fail to get activated quickly enough to prevent voltage collapse.
Most of the indices developed are system-based or based on bus orientation.
There has not been much research in voltage stability assessment via line
based voltage stability index.
The existing technique is based on a line based voltage stability index which
detects the critical lines for a specific load scenario for monitoring the system prior
to experiencing line outage.
The limitation of the above method is that it does not reach unity under
various power factor operations of a transmission lines.
Particularly, their index show very less value (much less than 1) for high
power factor operation of a transmission line.
A bacterium foraging technique has been implemented for minimizing loss,
taking voltage stability into account.
An analysis of MW and MVAR management for the improvement of
economical dispatch by using participation factors has been derived from the
critical eigenvectors of the Jacobean matrix.
14. A new model for optimal reactive power flow has been designed by the
predictor corrector primal dual interior point method.
A recent work on the stability index has been carried out by the use of
tellegen‟s theorem.
Other works on the stability index have included preventive control of
voltage stability using a new voltage stability index.
Many novel methods have been employed for this voltage stability control
such as the effect of load tap changers in emergency and preventive voltage
stability control.
Nonlinear optimization techniques have been used for voltage stability
analysis by fast computation of voltage stability security margins.
Other applications of the nonlinear programming have included
congestion management problem ensuring voltage stability.
The voltage collapse prediction methodology has been presented based on
line voltage stability index.
It is predicted by estimating the load flow solution and then calculating the
line voltage stability index.
Hence, the lines which are in stressed conditions can be easily identified.
15. This information can be used as a basic tool for security monitoring of the
system.
Most of the indices developed are system-based or based on bus
orientation.
There has not been much research in case of static voltage stability
assessment via line based voltage stability index.
In the existing model, a voltage stability criterion is formulated based on
power transmission concept in a single line.
An interconnected system is reduced to a single line network and then
applied to assess the overall system stability.
Utilizing Fuzzy Logic based Stability Index Power System Voltage
Stability Enhancement the same concept but using it for each line of the network, a
stability criterion is developed which is used to assess the system security.
In this paper, voltage stability assessment via line based stability index is
analyzed using fuzzy based controller and an effective procedure for voltage
stability assessment (nearness of the operating point to voltage collapse point)using
the exact line voltage stability index is developed.
The developed index incorporates correctly the effect of real and reactive
power increase scenario in any direction as against the existing line voltage
stability index.
16. Here the uncertainties in the input parameters would be dealt with the fuzzy sets. Fuzzy
based voltage stability index is calculated in each step after performing Newton-Rap son
load flow study.
The fuzzy voltage stability index clearly indicates the location and status of critical bus
bar.
Therefore, a new method of achieving a reasonable voltage profile for economic and
stable operation of a power system is the need of the hour.
The software based results are provided for the proposed algorithm to validate its
feasibility of operation.
The 18 bus IEEE system was simulated in a stability analysis program developed for
two different disturbance types: short circuit and generation loss.
Four load modeling kinds were studied: constant impedance, constant current, 50%
constant current and 50% constant power (mist 1), and finally 21% constant current and
79% constant power (mist 2).
The fuzzy controller applied here has seven predicates.
Figure shows the terminal voltage at bus bar 7 of the IEEE system for a short circuit
simulation at bus bar 12 lasting 300 ms. The load was modeled as 50% I constant and 50% P
constant.
17. Fig: The 18 bus bar system analysis (terminal voltage Vt in bus bar 7)
18. Figure shows the terminal voltage at the IEEE system bus bar 7 for a generator
loss simulation at bus bar 4 at 2 s.
The load was modeled as 50% constant current and 50% constant power.
Fig: The 18 bus bar system analysis (terminal voltage Vt in bus bar 12)
19. It could be observed for both studies (Matlab simulation and stability program
simulation) an excellent response of the fuzzy controller and with no oscillation,
while the AVR response presented a ripple in both studies and some oscillations
before reaching the steady state operation point.
It is shown that an excellent performance of the fuzzy control over the
conventional one for the excitation control of synchronous machines could be
achieved.
