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ISSN: 2277 – 9043

International Journal of Advanced Research in Computer Science and Electronics Engineering

Volume 1, Issue 2, April 2012

50

All Rights Reserved © 2012 IJARCSEE

Abstract— Due to the rapid technological progress, the

consumption of electric energy increases continuously. But the

transmission systems are not extended to the same extent because

building of new lines is difficult for environmental as well as

political reasons. Hence, the systems are driven closer to their limits

resulting in congestions and critical situations endangering the

system security.Power Flow Control devices such as Flexible AC

Transmission Systems (FACTS) provide the opportunity to

influence power flows and voltages and therefore to enhance system

security, e.g. by resolving congestions and improving the voltage

profile. Even though the focus lies on Static Var Compensators

(SVC), Thyristor-Controlled Series Compensators (TCSC) and

Thyristor-Controlled Phase Shifting Transformers (TCPST), the

developed methods can also be applied to any arbitrary controllable

devices. In order to benefit from these devices, an appropriate

control is necessary. In this thesis, an Optimal Power Flow problem

is formulated and solved to find the optimal device settings. Two

types of FACTS devices, SVC and TCSC, can be installed on buses

and transmission lines to enhance the transmission loadability (TL)

of power systems, respectively through injecting reactive power and

changing line reactance. In this paper, there are three main steps in

the FACTS devices installation strategy proposed. In step 1, based

on the peak-load state, the CPF technique is used to formulate the

maximum transmission loadability (MTL) problem to maximize the

TL increased from the peak-load through installation of the FACTS

devices. Here, the MTL without FACTS device installed is first

calculated. While in step 2, based on the power flow solution for the

MTL obtained in step 1, the positions proper to place SVCs and

TCSCs are determined using the tangent vector technique and real

power flow performance index (PI) sensitivity factors, respectively.

Various FACTS devices installation schemes are then built with

these candidate positions and, for each scheme, the MTL is solved

by determining the ratings for the SVCs and TCSCs installed.

Finally in step 3, by comparing the ratios of the investment costs to

the TLs increased between various schemes, a correspondingly most

advantageous scheme is suggested. Also, to further validate the

effectiveness of the proposed method, a static voltage stability

analysis is given.

Index Terms— FACTS Devices, Transmission Loadability,

Continuation Power Flow, Tangent Vector Technique, Real

Power Flow Performance Index Sensitivity Factor.

I. INTRODUCTION

The evolution of power systems began at the end of the 19th

century when the first transmission lines were built. Over the years,

the systems were extended and a growing number of generators and

loads were connected. Due to the rapidly increased consumption,

the need to transmit larger amounts of electric power over longer

distances emerged which was met by raising the voltage levels of

the power lines. Furthermore, in order to enable exchanges between

different utilities and to improve security, neighboring systems

were connected. Hence, power systems are the products of a long

lasting building process resulting in very large and complex

systems. Outages in a power system affect everyday’s life severely

and may paralyze entire countries. Moreover, extensive failures

cause enormous economical losses. The blackouts in the past years

have shown this impressively In August 2003, the blackout in the

United States and Canada left around 50 million people without

electricity for more than four days in some areas and the costs are

estimated to 4 to 10 billion U.S. dollars . In September of the same

year, a line trip between Switzerland and Italy initiated a major

blackout in Italy affecting 56 million people. Therefore, a secure

and reliable operation of power systems is crucial. But the electrical

energy demand increases continuously leading to an augmented

stress on the transmission system and higher risks for outages. In

addition, electric power trades across borders have enhanced due to

the liberalization of electricity markets. The resulting regularly

changing load-flow patterns require a transmission grid which is

able to cope with daily modified generation and load distributions.

In several areas in Europe, the grid is not able to meet these demands

any more and as a consequence, particular lines are often driven

close to or even beyond their limits. But the extension of the system

required to further guarantee secure transmission is difficult for

environmental and political reasons. A promising and competitive

alternative option is the usage of FACTS devices. These devices are

able to influence power flows and voltages and therefore provide the

possibility to enhance the security of the system in manifold ways:

increase of the transfer capacity, resolution of congestions by

relieving overloaded lines, improvement of the voltage profile,

reduction of power losses, enhancement of damping, etc.. In order to

benefit from such devices, their control settings have to be chosen

appropriately. Nowadays, the determination of these values is

generally based on local objectives. The effects of the FACTS

devices on the rest of the power system are not taken into account.

This may lead to mutual influences among multiple FACTS devices

or other control devices and to a deteriorated control performance.

Hence, a coordination of the control is essential.

Optimal set values for any controllable devices in a system with

An approach towards FACTS Devices

Installation Strategy for Transmission

Loadability Enhancement Using Fuzzy Logic

Controller

Dr. K.T. Chaturvedi, Assistant Professor Dept. of Electrical Engineering UIT RGPV Bhopal,

Rohit Kumar Gupta UIT RGPV Bhopal

ISSN: 2277 – 9043



51


respect to various objectives can be obtained by formulating and

solving an optimization problem. In the area of power systems, this

optimization problem corresponds to an Optimal Power Flow

problem. Typical objective functions include the minimization of

active power losses, the minimization of active power generation

costs, the maximization of transfer capacity, etc.. An Optimal Power

Flow problem can also be formulated in order to determine the

optimal control settings of FACTS devices in a power system with

the objective to enhance the security of the system reducing the risk

for system outages.

THE power systems are complex non-linear systems, which are

often subjected to low frequency oscillations. The application of

power system stabilizers for improving dynamic stability of

power systems and damping out the low frequency oscillations due

to disturbances has received much attention. Power system is a

highly nonlinear system and it is difficult to obtain exact

mathematical model of the system. In recent years, adaptive

self tuning, variable structure, artificial neural network based

PSS, fuzzy logic based PSS have been proposed to provide

optimum damping to the system oscillations under wide variations

in operating conditions and system parameters. Recently, fuzzy

logic power system stabilizers have been proposed for effective

damping of power system oscillations due to their robustness. Fuzzy

logic controllers (FLC) are suitable for systems that are structurally

difficult to model due to naturally existing non-linearities and other

model complexities. Exact mathematical model is not required in

designing a fuzzy logic controller. In contrast to conventional

power system stabilizer, which is designed in frequency domain, a

fuzzy logic power system stabilizer is designed in the time domain.

Fuzzy logic controllers have successfully applied in control

applications, they are subjective and heuristic. Although, fuzzy

logic control introduces a good tool to deal with complex,

non-linear and ill-defined systems, it suffers from the drawback of

tuning of parameters of FLPSS. The generation of membership

functions (MFs) and the tuning of scaling factors for FLC are done

either iteratively by trial and error or by human expert. Therefore,

the tuning of the FLPSS parameters is a time consuming task. It

necessitates the need for an effective method for tuning the

parameters of FLPSS.

II. PROBLEM FORMULATION

A SVC can be installed on a bus through providing reactive power

to control the magnitudes of bus voltages, while a TCSC can be

installed on a transmission line through regulating the line reactance

to control the power flows on the grid. To maintain system operating

in security as well as stability states, the two FACTS devices are

adopted in the FACTS devices installation strategy proposed.

Let xij be a regulable reactance for the TCSC installed on

transmission line i-j. The range of xij is set within compensation

levels: -0.8xij < xij < 0.2 xij, where xij is the line reactance. Then,

the real and reactive power flows can be

and let Qci be a regulable reactive power for the SVC

installed on bus i and its rating is set within limits:

-Qc < Qci < Qc . Employing the CPF technique to formulate

the MTL problem, let λ , λ > 0 , be the loading factor, λ = 0

for the base load, and involving in (1) and (2) the real and

reactive power balance equations on bus i can be expressed as:

where Pio Pgio Plio and Qio Qgio Qlio are the real and

reactive power injections for the base peak-load, ∆Pli and ∆Qli the

real and reactive power increments for load i to increase, control

variable ∆Pgi the increment of the real power generation for

generator i to increase; as bus i has a SVC on, the rating Qci 0 . The balance equations of the power system can be expressed in a

functional vector as follows:

f (x,v) 0

In (5), vector x denotes the state variables including all buses

voltage magnitudes and phase angles, vector v the control variables

including the reactive powers and reactance compensation levels

provided by the installed SVCs and TCSCs, the settings of the shunt

capacitors (SC), the on load tap changing (OLTC) transformers and

the automatic voltage regulators (AVR), and the generation

increments and loading factor. In addition, the security constraints

considered in system operating are represented by a functional

vector as:

g(x,v) 0

Equation (6) includes all generation limits, for generator i,

Pgio = Pgio +λ∆Pgi < Pgi and Qgi < Qgi ; line flow limits, if for real

power, for line i-j, Pij < Pij ; bus voltage magnitudes, for bus i,

0.9pu. < Vi < 1.1pu. and for all installed SVCs and TCSCs and the

loading factor shown above. Besides, the investment cost [12] for

the FACTS devices to install is limited by:

h(v) C

Finally, the MTL problem with both technical and economic

concerns is shown as follows:

Min λ

III. DETERMINATION OF INSTALLATION POSITIONS

In order for the installed FACTS devices to obtain high utilization

performance, as specified by the ratio of the increased TL to the

investment cost, it is necessary to install the FACTS devices on

proper positions with appropriate ratings. In the proposed method,

the positions for SVCs and TCSCs to install are first determined and

by solving the MTL problem the ratings of the installed devices are

then determined.

When system load increased, the SVCs can provide reactive power

to maintain bus voltage in security. Therefore, evaluated by the

tangent vector technique, if voltage security of a bus being violated

in a larger degree, it is considered necessary to install a SVC on the

bus. On the other hand, by changing the lines reactance with the

TCSCs installed, the transmission congestion can be released; the PI

sensitivity factor calculated being negative for a TCSC installed on

a line indicates that the transmission congestion can be released due

to the installed TCSC. Therefore, a line can be more proper to install

a TCSC as the PI sensitivity factor obtained is more negative than a

TCSC installed on some other lines.

The following criteria are used to determine the positions proper to

install SVCs and TCSCs from technical concerns.

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Determination of proper buses for SVCs to install

First, solve (8) to obtain the MTL state without FACTS installed,

and based on the Jacobian matrix obtained, the tangent vector

technique is then used to evaluate the changes of the state variables

due to the increased system load [13]:

In (9), vectors ΔPg , ΔPl and ΔQl include all real and reactive

increments of the PV and PQ buses; vectors Δθg , Δθl and ΔVl

represent all changes of the system bus angles and voltage

magnitudes. Generally, the changes of the voltage magnitudes

should be negative due to system load increases.

The ratio ∆Vi /Vi is used to evaluate how proper bus i is to

install a SVC. In principle, the more the ratio ∆Vi /Vi is negative, the

more the bus i can be a proper position.

Determination of proper lines for TCSCs to install

Based on the MTL state without FACTS device installed,

the congestion level of the transmission system can be

evaluated by index PI as below [14]:

where PL is the real power flow on line L and PL the capacity; wL is

a weight to reflect the importance of the line, in the paper wL = 2 PL

/ PL for line L ; exponent n is set to 2.

As a TCSC installed on line k, the PI sensitivity factor can

be calculated by:

where Xk > 0 is the value of the reactance -Xk , as provided by the

TCSC installed on line k.

Equation (11) indicates that the more the PI sensitivity factor is

negative, the more the chance to reduce transmission congestion by

the installed TCSC has, and thus, the TL can be increased by the

installation. Accordingly, by calculating the PI sensitivity factor in

turn for each line individually installed with a TCSC, the lines with

more negative PI sensitivity factors when installed with TCSCs can

be proper choices to install TCSCs.

Various installation schemes are then built by the combination of

the proper positions for installing SVCs and TCSCs determined, and

then the MTL problem is solved in turn for each scheme. The

scheme with larger utilization performance derived from the MTL

solutions is considered to be the correspondingly most

advantageous scheme for the installation.

IV. SOLUTION METHOD AND INSTALLATION STRATEGY

A particle swarm optimization (PSO) based OPF method is

used to solve the MTL problem. In the population, each particle

represents a candidate solution for the control variables, as denoted

in vector form, for the ith particle:

where particle xi includes the vectors of all generation increments

iΔPg , all reactive power injections icQ for the installed SVCs and

all compensation reactances ikX for the installed TCSC.

Neglecting the controls to the SCs, OLTCs and AVRs, as

been set for the MTL state without FACTS devices installed,

the strategy proposed to suggest a correspondingly most

advantageous FACTS devices installation scheme is shown in

Fig. 1.

The utilization performance (up) of the installed FACTS

devices for scheme i is defined as:

upi (TL increased) /(Investment Cost)

The scheme with the minimum up is considered as the

correspondingly most advantageous scheme.

V. TEST RESULTS AND DISCUSSION

A modified IEEE-14bus system shown in Fig. 2 is used to test the

proposed method. The existing control units include: four sets of

AVRs respectively on buses 1, 2, 3 and 8, one SC on bus 9 and three

OLTCs on lines 8, 9 and 10 respectively.

The base case power flow for the base peak-load is shown in Table

1. As shown in Table 1, the loading level is set as the real and

reactive powers of the peak-load.

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As seen in Table 6, it can be found that the schemes in the shadow

area, which obviously have more increased TLs,involve

simultaneously installing TCSCs on lines 2 and 10 or on lines 2, 9

and 10, no matter on which buses SVCs are installed. While related

to the same area in Table 7, it can be found that 4.71(MUS$) for

scheme 5 is the minimum investment cost of the schemes in the area

and its cost rate (the ratio of investment cost to TL increased) is the

least in all schemes. In other words, scheme 5 has the highest

utilization performance for the FACTS devices installation. It can

also be verified from Fig. 3 through comparison between the eight

schemes with higher utilization performances. As seen in Fig.3,

although scheme 49 can increase TL the most, its investment cost

(9.22MUS$) is also the highest due to need to install FACTS

devices on all candidate positions. Accordingly, scheme 5 is

suggested as the correspondingly most advantageous scheme.

For schemes 5 and 9, as system operating on the MTL states

respectively with the individually installed FACTS devices, the

ratings of the FACTS devices installed for each scheme are

determined and shown in Table 8. It can be seen in Table 8 that, the

ratings of the same FACTS devices (one SVC on bus 12 and two

individual TCSCs on lines 2 and 10 respectively) installed for

schemes 5 and 49, are very close to each other. While for scheme 49,

it needs to extra install two SVCs respectively on buses 13 and 14

with ratings 0.12pu. and 0.13pu. and one TCSC on line 9 with

compensation level of reactance -0.27, the investment cost thus

raises largely.

For scheme 5, while system operating on the MTL state with the

FACTS devices installed, the load flow and power flows on the lines

are shown in Tables 9 and 10, respectively.

Comparing Tables 9 and 2, it can be found that the bus voltage

magnitudes are obviously raised due to the FACTS devices

installed. For examples, the voltage magnitude on bus 14 is raised

from 0.9004pu. to 0.9135pu., and in addition, observed from the

shadow area of Table 10 the flow limits of lines 2, 4, 5 and 6 are all

reached. Obviously, corresponding to the system with no FACTS

device installed, the FACTS devices installed for scheme 5 can

operate effectively in improving transmission network utilization.

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A study of three cases, with no FACTS device installed, schemes 5

and 49, is implemented and the results when system operating on the

MTLs states for the three cases shown in Fig.4 are compared. As

seen in Fig. 4, due to the installed SVCs for the two installation

schemes, the voltage magnitudes are raised, and thus, system

security increased from the case with no FACTS device installed.

Besides, to further validate the proposed strategy, applying the CPF

analysis to the study the P-V curves (as referred to as voltage

stability margin, VSM) for the three cases are shown in Fig. 5. It can

be found from Fig. 5 that the static voltage stabilities for the two

schemes are much larger than the one with no FACTS device

installed. Therefore, if determined based on static voltage stability,

scheme 49 will be the best choice; however, a tradeoff should be

concerned because its investment cost is much higher than scheme

5.

VI. CONCLUSIONS

Under the existing transmission grids, to enhance TL for

power systems while maintaining transmission security and

further more avoiding voltage collapse, to install FACTS

devices on proper positions with appropriate ratings can be a better

substitute for constructing more transmission lines. In the paper, the

proposed FACTS devices installation strategy first determines the

buses and lines suitable for SVCs and TCSCs to install, respectively

evaluated by the tangent vector technique and PI sensitivity factors.

These candidate positions are then combined into various schemes

for installation of FACTS devices. Then, the MTL problem is

solved in turn for each scheme by using the PSO-OPF method

through

determining the ratings of the FACTS devices installed. Comparing

and analyzing the utilization performances of all schemes, the

scheme with the highest utilization performance is then suggested as

the correspondingly most advantageous installation scheme.

Finally, the efficiency of the proposed method is further validated

by a static voltage stability analysis, proven that the VSM can also

be largely improved.

VII FUTURE WORK

There are many types of FACT devices available presently and each

one has their advantages and disadvantages or limitation hence surly

no one is perfect solution for every type of problem in my present

work I tried to compare the performance (peak fluctuation, settling

time, power flow etc.) for each device like (STATCOM, TCSC etc.)

and for different conditions (like earth fault, changing load,

generator fluctuation etc.) and proposed a fuzzy based controller for

the STATCOM to smoothly handle all problems.

Since present approach gives better results than traditional

controllers, in future the hybrid fact devices could be designed and a

neuro-fuzzy approach can also be designed to control the designed

devices. This will definitely improve the stability and voltage

profile of the system.

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[10] H. A. Abdelsalam, G. E. M. Aly, M. Abdelkrim, K. M. Shebl,

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