FORM 2
THE PATENTS ACT, 1970
(39 of 1970)
As amended by the Patents (Amendment) Act, 2005
&
The Patents Rules, 2003
As amended by the Patents (Amendment) Rules, 2006
COMPLETE SPECIFICATION
(See section 10 and rule 13)
TITLE OF THE INVENTION
A system and method for security oriented optimal placement of phasor measurement units in a power system.
APPLICANT(S)
Crompton Greaves Limited, CG House, Dr Annie Besant Road, Worli, Mumbai 400 030, Maharashtra, India, an Indian Company
INVENTOR(S)
Bhimasingu Ravikumar and Patel Jashavant; both are from Crompton Greaves Ltd., CG Global R&D Center, Bhaskara Building, Kanjur Marg (East), Mumbai - 400042, Maharashtra, India; Rokkam Venkatesh of National Institute of Technology, Warangal-506004, Andhra Pradesh, India; and Dhadbanjan Thukaram of Department of Electrical Engg., Indian Institute of Science (IISc), Bangalore-560012, Karnataka, India; all Indian Nationals.
PREAMBLE TO THE DESCRIPTION:
The following specification particularly describes the nature of this invention and the manner in which it is to be performed:

FIELD OF THE INVENTION:
This invention relates to the field of control systems, analytics' systems, and computational systems.
Particularly, this invention relates to a system and method for security oriented optimal placement of phasor measurement units in a power system.
BACKGROUND OF THE INVENTION:
In an electrical grid or a power grid, relays may be used in order to obtain phasor values of current and / or voltage. Phasor Measurement Units (PMU) are used to obtain instantaneous time-stamped phasor values of current and / or voltage. A phasor measurement unit (PMU) is a device which measures the electrical waves on an electricity grid, using a common time source for synchronization. Time synchronization allows synchronized real-time measurements of multiple remote measurement points on the grid.
Sychronised phasor measurements available from Phasor Measurement Units (PMU) facilitate innovative solutions in power system monitoring, protection, analysis and control. PMUs are majorly important depending on their applications as power system stability, monitoring, protection and control. The advantage of referring phasor angle to a global reference time is helpful in capturing the wide area snap shot of the power system. Effective utilization of this technology is very useful in mitigating blackouts and learning the real time behavior of the power system,
One of the most important issues that need to be addressed is the system applications that influence the required number of installations. The cost of PMUs limits the number that will be installed; although an increased demand in the future is expected to bring down the cost. The placement sites are also limited by the available

communication facilities, the cost of which may be higher than that of the PMUs. The problem has been around for a long time and has been examined under various research areas, such as in operational research, systems theory and control, and combinatorial optimization.
In recent years, there has been significant research activity on the problem of finding the minimum number of PMUs and their optimal locations. Optimal placement of PMUs for the purpose of power system observation using topology based algorithms is formulated in a prior art document, entitled, "Optimal Placement of PMUs for Power System Observability Using Topology Based Formulated Algorithms", by B. Mohammadi-Ivatloo, published in Journal of Applied Sciences, 9: 2463-2468, 2009. Topology-based algorithm using branch and bound and genetic algorithm (GA) optimization methods are selected to solve the problem.
In prior art document, entitled, "A simple and efficient approach for Optimal Placement of PMUs-A Case Study for Eastern Regional Grid", by P. Pentayya, P. Mukhopadhyay, S. Banerjee, M. K. Thakur, published in 16th National Power Systems Conference, 15th-17th Dec, 2010, Graph theory is developed from characteristics of PMU as they give bus voltage phasors and branch current phasors and considering the topology of the system network.
When the measurements will include conventional power flows and injections as well as phasor measurements for voltages and line currents provided by PMUs, the analysis of network observability and PMU placement problem by using these mixed measurement sets are discussed in prior art document, entitled, "Observability analysis and measurement placement for systems with PMUs", by Bei Xu and Ali Abur, published in Proc. 2004 IEEE PES conf. and Expo, vol.2, pp.943-946, Oct. 10-13, 2004. PMU placement analysis by using integer linear programming,

considering with and without conventional power flow and injection measurements becomes a nonlinear integer programming.
Prior art document, entitled, "Optimal Placement of PMUs by Integer Linear Programming", by Bei Gou published in IEEE Transactions on Power Systems, Vol. 23, No. 3, Aug, 2008 has proposed linear programming with these measurements.
In prior art document, entitled, "Optimal PMU placement and observability of power system using PSAT", published by G. Venugopal, R. Veilumuthu, and P. Avila Theresa, in Int. Joint Journal Conf. on Engineering and Technology, pp.67-71, 2010, Power System Analysis Toolbox (PSAT) is used for power system analysis and control. PSAT is used to solve the PMU placement problem using different methods such as depth first, annealing, direct spanning tree and graph theoretic procedure.
Method for placing PMU in power systems is based on power system intrinsic characteristics, such as major load areas, major control systems, critical equipments and power plants in the power system as disclosed in prior art document, entitled, "PMU Placement Based on Power System Characteristics", by Song Yunting, M A Shiying, W U Lihua, Wang Quan, HE Hailei in Int. Joint Journal Conf. on Sustainable Power Generation and Supply, pp. 1-6, 2009.
In prior art document, entitled, "Placement of synchronized measurements for power system observability", by S. Chakrabarti, E. Kyriakides, D. G. Eliades, in IEEE Transactions on power delivery, vol. 24, no. 1, pp. 12-19, Jan, 2009, integer quadratic programming is used to achieve dual objectives such as to minimize the required number of PMUs and to maximize the measurement redundancy. The constraints are formulated in such a way that the system remains observable as a single island even in the case of outage of a single transmission line or a PMU.

Considering the same, the positions of these measurements are rearranged by a heuristic algorithm in order to minimize the number of PMU placement sites as disclosed in prior art document, entitled, "An Optimal PMU Placement Method against Measurement Loss and Branch Outage", by C. Rakpenthai, P. Suttichai, S. Uatrongjit, N. R. Watson in IEEE Transactions on Power Delivery, Vol. 22, No. 1, Jan, 2007.
In prior art document, entitled, "Optimal Multistage Scheduling of PMU Placement: An ILP Approach", by S. A. Soman, D. Dua, S. Dambhare, G. Rajeev Kumar, in IEEE Transactions On Power Delivery, Vol. 23, No. 4, Oct, 2008, there is disclosed an optimization (ILP approach) for staging/phasing of PMU placement over a given time horizon. In this, maximization of number of observed buses at each stage as an objective during phasing such that at the end of phasing, the final solution is identical to optimal solution obtained without phasing.
In prior art document, entitled, "Optimal PMU Placement to Ensure System Observability under Contingencies", by S. C. Srivastava, S. N. Singh, Ranjana Sodhi, in Int. Joint Journal Conf. on Power & Energy society, pp. 1-6, 2009. They presented a method for optimal placement of PMUs considering critical contingencies. A voltage stability based contingency screening method has been utilized to select critical contingency cases. The contingencies considered are the branch outages of the system.
For PMU placement, prior art document, entitled, "Real-time monitoring of critical nodes with Minimal number of Phasor Measurement Units", by Thukaram, B. Ravikumr, V. Seshadri Sravan Kumar, Y. Prasad Rao, S. Surendra in Third International Conference on Power Systems, Kharagpur, INDIA Dec, 27-29, 2009,

Thukaram.et.al considered critical buses obtained from transient stability analysis considering maximum angular deviation as the major criteria. Integer Linear Programming (ILP) is carried out to find the observability of the system.
In prior art document, entitled, "An approach for optimal PMU placement using binary particle swarm optimization with conventional measurements", by Charu Sharma, B. Tyagi, in International Journal of Engineering, Science and Technology, Vol. 3, No. 3, pp. 56-63, 2011, complete observability various systems is computed by Binary Particle Swarm Optimization.
An optimal PMU placement method based on the nondominated sorting GA is proposed in prior art document, entitled, "Nondominated sorting genetic algorithm for optimal phasor measurement placement", by B. Milosevic and M. Begovic in IEEE Transactions on. Power Systems, vol. 18, no. 1, pp. 69-75, Feb, 2003. The problem is to find the placement of minimum PMUs set so that the system is still observable during its normal operation and any single-branch contingency.
OBJECTS OF THE INVENTION:
An object of the invention is to provide a system and method for determining critical buses in a power grid.
Another object of the invention is to provide a system and method for determining placement of phasor measurement units (PMU) considering PMUs placed at critical buses in a power grid.
Another object of the invention is to provide a system and method for determining placement of phasor measurement units (PMU) considering twice observability of critical buses in a power grid.

Yet another object of the invention is to provide a system and method for determining optimum placement of phasor measurement units (PMU) without considering critical buses in a power grid.
Still another object of the invention is to provide a system and method for determining placement of phasor measurement units (PMU) in a power grid such that the cost of the PMU is considered and proportional to number of lines connected to the bus.
An additional object of the invention is to provide a system and method for determining placement of phasor measurement units (PMU) in a power grid such that the system is still observable even though one of the PMU's data is lost or equipment lost, we can still ensure that the critical buses are observed, without bothering overall system observability.
SUMMARY OF THE INVENTION:
According to this invention, there is provided a system for security oriented optimal placement of phasor measurement units in a power system, said system comprises:
a. transient stability analysis module adapted to obtain observed parameter
values for pre-defined contingencies for said power system;
b. fuzzy logic controller module adapted to identify the critical buses in said
power system; and
c. integer linear programming module adapted to identify minimum number of
phasor measurement unit placement sites, where, critical buses are observed

either for at least two times or by ensuring placement of phasor measurement unit at the critical bus location.
Typically, said transient stability analysis module comprises means to read power system data based on load flow for a base case.
Typically, said transient stability analysis module comprises means to read dynamic data of said power system.
Typically, said transient stability analysis module comprises contingency application means adapted to apply pre-defined contingency parameters to said power system.
Typically, said transient stability analysis module comprises contingency application means adapted to apply pre-defined contingency parameters to said power system, said contingency parameters being selected from, a group of parameters relating contingencies consisting of line outage contingency, 3-phasor fault contingency, load decrement contingency, load increment contingency, and generator tripping contingency.
Typically, said transient stability analysis module comprises angle deviation reading means to read maximum angle deviation values from said power system upon application of each contingency to said power system.
Typically, said transient stability analysis module comprises initial angle reading means to read initial angle values from said power system upon application of each contingency to said power system.

Typically, said transient stability analysis module comprises time reading means to read time values, for load angle to attain tolerance limits, from said power system upon application of each contingency to said power system.
Typically, said fuzzy logic controller module comprises input means to input said observed parameter values to said fuzzy logic controller module.
Typically, said fuzzy logic controller module comprises severity index computation means adapted to compute severity index for each bus, for each contingency, of said power system based on said observed parameter values, said computation being carried out by pre-defined rules and formulae.
Typically, said fuzzy logic controller module comprises overall severity index computation means adapted to compute overall severity index for each bus considering all contingencies.
Typically, said integer linear programming module comprises identification means
adapted to identify minimum number of phasor measurement units placement sites,
where, critical buses are observed for at least two times.
Alternatively, said integer linear programming module comprises identification
means adapted to identify minimum number of phasor measurement unit placement
sites, where, critical buses are observed by ensuring phasor monitoring unit at that
location.
Typically, said integer linear programming module comprises identification means adapted to identify minimum number of phasor measurement units' placement sites, where, complete power system values are observed without considering critical buses.

Typically, said integer linear programming module comprises identification means adapted to identify minimum number of phasor measurement units' placement sites, where, complete power system values are observed with considering critical buses.
Typically, said integer linear programming module comprises identification means adapted to identify minimum number of phasor measurement unit placement sites, where, complete power system values are observed considering twice observable of critical buses.
Typically, said integer linear programming module comprises identification means adapted to identify minimum number of phasor measurement unit placement sites, where, complete power system values are observed considering complete power system twice observable.
Typically, said integer linear programming module comprises identification means adapted to identify minimum number of phasor measurement units placement sites, where, complete power system values are observed considering cost of phasor measurement units proportional to number of lines connected to the corresponding bus of said power system.
According to this invention, there is also provided a method for security oriented optimal placement of phasor measurement units in a power system, said method comprises the steps of:
A. obtaining observed parameter values for pre-defined contingencies for said
power system, using transient stability analysis module;
B. identifying critical buses in said power system, using fuzzy logic controller
module; and

C. identifying minimum number of phasor monitoring unit placement sites, where, critical buses are observed either for at least two times or by ensuring phasor monitoring unit at their corresponding location, using integer linear programming module.
Typically, said step of obtaining observed parameter values for pre-defined contingencies for said power system, using transient stability analysis module comprises a step of reading power system data based on load flow for a base case.
Typically, said step of obtaining observed parameter values for pre-defined contingencies for said power system, using transient stability analysis module comprises a step of reading dynamic data from a power system.
Typically, said step of obtaining observed parameter values for pre-defined contingencies for said power system, using transient stability analysis module comprises a step of applying pre-defined contingency parameters to said power system, using a contingency application means.
Typically, said step of obtaining observed parameter values for pre-defined contingencies for said power system, using transient stability analysis module comprises a step of applying pre-defined contingency parameters to said system, using a contingency application means, said contingency parameters being selected from a group of parameters relating contingencies consisting of line outage contingency, 3-phasor fault contingency, load decrement contingency, load increment contingency, and generator tripping contingency.
Typically, said step of obtaining observed parameter values for pre-defined contingencies for said power system, using transient stability analysis module comprises a step of reading maximum angle deviation values from said power

system upon application of each contingency to said power system, using angle deviation reading.
Typically, said step of obtaining observed parameter values for pre-defined contingencies for said power system, using transient stability analysis module comprises a step of reading initial angle values from said power system upon application of each contingency to said power system, using initial angle reading means.
Typically, said step of obtaining observed parameter values for pre-defined contingencies for said power system, using transient stability analysis module comprises a step of reading time values, for load angle to attain tolerance limits, from said power system upon application of each contingency to said power system, using time reading means.
Typically, said step of identifying critical buses in said power system, using fuzzy logic controller module comprises a step of inputting said observed parameter values to said fuzzy logic controller module, using input means.
Typically, said step of identifying critical buses in said power system, using fuzzy logic controller module comprises a step of computing severity index for each bus, for each contingency, of said power system based on said observed parameter values, said computation being carried out by pre-defined rules and formulae, using severity index computation means.
Typically, said step of identifying critical buses in said power system, using fuzzy logic controller module comprises a step of computing overall severity index for

each bus considering all contingencies, using overall severity index computation means.
Typically, said step of identifying minirnum number of phasor monitoring unit placement sites, where, critical buses are observed either for at least two times or by ensuring phasor monitoring unit at their corresponding location, using integer linear programming module comprises a step of identifying minimum number of phasor monitoring unit placement sites, where, critical buses are observed for at least two times using overall severity index for each bus, using identification means.
Alternatively, said step of identifying minimum number of phasor monitoring unit placement sites, where, critical buses are observed either for at least two times or by ensuring phasor monitoring unit at their corresponding location, using integer linear programming module comprises a step of identifying minimum number of phasor monitoring unit placement sites, where, critical buses are observed by ensuring phasor monitoring unit at that location using overall severity index for each bus, using integer linear programming module comprising identification means.
Typically, said step of identifying minimum number of phasor monitoring unit placement sites, where, critical buses are observed either for at least two times or by ensuring phasor monitoring unit at their corresponding location, using integer linear programming module comprises a step of identifying minimum number of phasor monitoring unit placement sites, where, complete power system values are observed without considering critical buses, using identification means adapted. Typically, said step of identifying minimum number of phasor monitoring unit placement sites, where, critical buses are observed either for at least two times or by ensuring phasor monitoring unit at their corresponding location, using integer linear programming module comprises a step of identifying minimum number of phasor

monitoring unit placement sites, where, complete power system values are observed with considering critical buses, using identification means.
Typically, said step of identifying minimum number of phasor monitoring unit placement sites, where, critical buses are observed either for at least two times or by ensuring phasor monitoring unit at their corresponding location, using integer linear programming module comprises a step of identifying minimum number of phasor monitoring unit placement sites, where, complete power system values are observed considering twice observable of critical buses, using identification means adapted to.
Typically, said step of identifying minimum number of phasor monitoring unit placement sites, where, critical buses are observed either for at least two times or by ensuring phasor monitoring unit at their corresponding location, using integer linear programming module comprises a step of identifying minimum number of phasor monitoring unit placement sites, where, complete power system values are observed considering complete power system twice observable, using identification means.
Typically, said step of identifying minimum number of phasor monitoring unit placement sites, where, critical buses are observed either for at least two times or by ensuring phasor monitoring unit at their corresponding location, using integer linear programming module comprises a step of identifying minimum number of phasor monitoring unit placement sites, where, complete power system values are observed considering cost of phasor measurement units proportional to number of lines connected to the corresponding bus of said power system, using identification means.
BRIEF DESCRIPTION OF THE ACCOMPANYING DRAWINGS:
The invention will now be described in relation to the accompanying drawings, in

which:
Figure 1 illustrates a flow diagram of the working of a system for security oriented optimal placement of phasor measurement units in a power system.
DETAILED DESCRIPTION OF THE ACCOMPANYING DRAWINGS:
According to this invention, there is provided a system for security oriented optimal placement of phasor measurement units in a power system.
In accordance with an embodiment of this invention, there is provided a transient stability analysis module for the system and method of this invention. Typically, transient stability of the system is performed for various generating conditions. Reference numeral I refers to the steps performed by the transient stability analysis module.
System data from a power system or an power system such as an electrical grid / network or a power grid or a network is read. Load flow is applied for base case and system data is read. Dynamic data from a power system such as an electrical grid / network or a power grid or a network is read for transient analysis.
For identifying critical buses in a power system such as an electrical grid / network or a power grid or a network, transient analysis of the system is run for different disturbances like 3-phasor line faults, line outage cases, load increments, load decrements and generator tripping. To simulate the transient stability analysis of the system, disturbances are simulated using various systems such as PSS/E system. The dynamic models for generator, excitation system and turbine-governor are

considered as GENROU (Round rotor generator model), ESDC1A (IEEE type DC1A Excitation system), TGOV1 (Turbine-Governor model) respectively. The angular deviation values for all the disturbances are stored correspondingly. Maximum angle deviation value(s), initial angle value(s), and time value(s) for rotor to attain tolerance limits are used as measures to identify the critical buses in the system. Figure 2 shows extraction of these measures from transient stability studies.
In accordance with an embodiment of this invention, there is provided a fuzzy logic controller module for the system and method of this invention. Typically, fuzzy logic controller is designed to identify the critical buses in the system. Reference numeral II refers to the steps performed by the fuzzy logic controller module.
Parameters calculated from transient stability analysis are considered as inputs to the fuzzy logic controller module to obtain severity index of each bus. Fuzzy logic controller module is, typically, designed for 3 inputs and single output. Each input parameter is normalized and expressed in fuzzy set notation before being processed
by the fuzzy reasoning rules. The Gaussian membership function is used in the present method because it holds the advantage of representing smoothness, concise notation and nonzero output at all points. Each input membership function is divided into five categories using fuzzy set notation as Large Positive (LP), Medium Positive (MP), Zero (ZE), Medium Negative (MN) and Large negative (LN). To evaluate the severity, a severity index computation means is used to obtain a severity index for each bus in the system. For severity index, the output membership functions are also divided into five categories as More Severe (MS), Above Severe (AS), Severe (SE), Below Severe (BS) and Less Severe (LS). Fuzzy logic controller defines fuzzy operators on fuzzy sets. The problem in applying fuzzy operations on fuzzy sets is,

the appropriate fuzzy operator may not be known. For this reason, fuzzy logic usually uses IF-THEN rules. 125 rules are used for evaluation of severity index for each bus for every disturbance with the given input parameters. Some of them are as follows:
If input 1 is LP & input 2 is LP & input 3 is LP then output is MS,
• If input 1 is LP & input 2 is ZE & input 3 is ZE then output is AS, If input 1 is ZE & input 2 is ZE & input 3 is ZE then output is ZE,
• If input 1 is LN & input 2 is ZE & input 3 is ZE then output is BS,
• If input 1 is LN & input 2 is LN & input 3 is LN then output is LS.
For every disturbance considered with the above membership functions and rules, the fuzzy inference engine will generate an output that represents the Severity Index (SI) of each bus. The Overall Severity Index (OSI) of a bus is obtained from the summation of SI of that bus from each disturbance.

where,
i is the bus number,
N is the number of disturbances considered. Order the buses according to OSI. The buses with high OSI are considered as critical buses.
In accordance with an embodiment of this invention, there is provided an integer linear programming module for the system and method of this invention. Typically, integer linear programming module is used to identify minimum number of phasor monitoring unit placement sites, where, critical buses are observed either for two

times or ensuring phasor monitoring unit at that location. Reference numeral II refers to the steps performed by the integer linear programming module.
The formulation of integer linear programming module for the optimal placement of phasor monitoring unit can be viewed as minimizing the objective function (2) according to the constraints (3).

where,
Ci is the cost function of phasor monitoring unit, A is the connectivity matrix
obtained from topology of the system.
A (i,/)=l
Iines connected between buses i and} (4) otherwise
PMU installed at i'h bus otherwise
b(i) = k, where k represents no. of times i lh bus is observed
In case of considering the phasor monitoring unit placement at critical buses, the constraints are reflected in the Aeq and beq matrices. In this system and method, for placing the phasor monitoring units at optimal locations, different cases that have been considered are:
(i) complete system observable without considering critical buses; (ii) considering PMU placed at critical bus; (iii) considering twice observable of critical buses; and

(iv) considering cost of PMU proportional to number of lines connected to that bus.


i is a critical bus otherwise


Acq(i , J) = 0, i=j
PMU installed at fh bus otherwise

(5)

In this system and method, an approach has been provided for placement PMUs to ensure system observability while considering critical buses which are obtained from transient stability analysis of the studied system. Fuzzy logic controller is designed to identify the critical buses in the system. ILP is used to find the location of the PMUs while complete system observable for following cases: I. without considering critical buses, II. considering PMUs placed at critical buses,
III. considering twice observable of critical buses,
IV. considering complete system twice observable and
V. considering cost of PMU proportional to number of lines connected to that bus
While this detailed description has disclosed certain specific embodiments of the present invention for illustrative purposes, various modifications will be apparent to those skilled in the art which do not constitute departures from the spirit and scope of the invention as defined in the following claims, and it is to be distinctly understood that the foregoing descriptive matter is to be interpreted merely as illustrative of the invention and not as a limitation.

We claim,
1. A system for security oriented optimal placement of phasor measurement
units in a power system, said system comprising:
a. transient stability analysis module adapted to obtain observed
parameter values for pre-defined contingencies for said power system;
b. fuzzy logic controller module adapted to identify the critical buses in said
power system; and
c. integer linear programming module adapted to identify minimum number
of phasor measurement unit placement sites, where, critical buses are
observed either for at least two times or by ensuring placement of phasor
measurement unit at the critical bus location.
2. The system as claimed in claim 1, wherein said transient stability analysis module comprising means to read power system data based on load flow for a base case.
3. The system as claimed in claim 1, wherein said transient stability analysis module comprising means to read dynamic data of said power system.
4. The system as claimed in claim 1, wherein said transient stability analysis module comprising contingency application means adapted to apply predefined contingency parameters to said power system.
5. The system as claimed in claim 1, wherein said transient stability analysis module comprising contingency application means adapted to apply predefined contingency parameters to said power system, said contingency parameters being selected from a group of parameters relating contingencies

consisting of line outage contingency, 3-phasor fault contingency, load decrement contingency, load increment contingency, and generator tripping contingency.
6. The system as claimed in claim 1, wherein said transient stability analysis module comprising angle deviation reading means to read maximum angle deviation values from said power system upon application of each contingency to said power system.
7. The system as claimed in claim 1, wherein said transient stability analysis module comprising initial angle reading means to read initial angle values from said power system upon application of each contingency to said power system.
8. The system as claimed in claim 1, wherein transient stability analysis module comprising time reading means to read time values, for load angle to attain tolerance limits, from said power system upon application of each contingency to said power system.
9. The system as claimed in claim 1, wherein said fuzzy logic controller module comprising input means to input said observed parameter values to said fuzzy logic controller module.
10. The system as claimed in claim 1, wherein said fuzzy logic controller module comprising severity index computation means adapted to compute severity index for each bus, for each contingency, of said power system based on said observed parameter values, said computation being carried out by pre-defined rules and formulae.

11. The system as claimed in claim 1, wherein said fuzzy logic controller module comprising overall severity index computation means adapted to compute overall severity index for each bus considering all contingencies.
12. The system as claimed in claim 1, wherein said integer linear programming module comprising identification means adapted to identify minimum number of phasor measurement units placement sites, where, critical buses are observed for at least two times.
13. The system as claimed in claim 1, wherein said integer linear programming module comprising identification means adapted to identify minimum number of phasor monitoring unit placement sites, where, critical buses are observed by ensuring phasor monitoring unit at that location.
14. The system as claimed in claim 1, wherein said integer linear programming module comprising identification means adapted to identify minimum number of phasor measurement units' placement sites, where, complete power system values are observed without considering critical buses.
15. The system as claimed in claim 1, wherein said integer linear programming module comprising identification means adapted to identify minimum number of phasor measurement units' placement sites, where, complete power system values are observed with considering critical buses.
16. The system as claimed in claim 1, wherein said integer linear programming module comprising identification means adapted to identify minimum number

of phasor measurement unit placement sites, where, complete power system values are observed considering twice observable of critical buses.
17. The system as claimed in claim 1, wherein said integer linear programming module comprising identification means adapted to identify minimum number of phasor measurement unit placement sites, where, complete power system values are observed considering complete power system twice observable.
18. The system as claimed in claim 1, wherein said integer linear programming module comprising identification means adapted to identify minimum number of phasor measurement units placement sites, where, complete power system values are observed considering cost of phasor measurement units proportional to number of lines connected to the corresponding bus of said power system.
19. A method for security oriented optimal placement of phasor measurement units in a power system, said method comprising the steps of:
A. obtaining observed parameter values for pre-defined contingencies for
said power system, using transient stability analysis module;
B. identifying critical buses in said power system, using fuzzy logic
controller module; and
C. identifying minimum number of phasor monitoring unit placement sites,
where, critical buses are observed either for at least two times or by
ensuring phasor monitoring unit at their corresponding location, using
integer linear programming module.
20. The method as claimed in claim 19, wherein said step of obtaining observed
parameter values for pre-defined contingencies for said power system, using

transient stability analysis module comprising a step of reading power system data based on load flow for a base case.
21. The method as claimed in claim 19, wherein said step of obtaining observed parameter values for pre-defined contingencies for said power system, using transient stability analysis module comprising a step of reading dynamic data from a power system.
22. The method as claimed in claim 19, wherein said step of obtaining observed parameter values for pre-defined contingencies for said power system, using transient stability analysis module comprising a step of applying pre-defined contingency parameters to said power system, using a contingency application means.
23. The method as claimed in claim 19, wherein said step of obtaining observed parameter values for pre-defined contingencies for said power system, using transient stability analysis module comprising a step of applying pre-defined contingency parameters to said system, using a contingency application means, said contingency parameters being selected from a group of parameters relating contingencies consisting of line outage contingency, 3-phasor fault contingency, load decrement contingency, load increment contingency, and generator tripping contingency.
24. The method as claimed in claim 19, wherein said step of obtaining observed parameter values for pre-defined contingencies for said power system, using transient stability analysis module comprising a step of reading maximum angle deviation values from said power system upon application of each contingency to said power system, using angle deviation reading.

25. The method as claimed in claim 19, wherein said step of obtaining observed parameter values for pre-defined contingencies for said power system, using transient stability analysis module comprising a step of reading initial angle values from said power system upon application of each contingency to said power system, using initial angle reading means.
26. The method as claimed in claim 19, wherein said step of obtaining observed parameter values for pre-defined contingencies for said power system, using transient stability analysis module comprising a step of reading time values, for load angle to attain tolerance limits, from said power system upon application of each contingency to said power system, using time reading means.
27. The method as claimed in claim 19, wherein said step of identifying critical buses in said power system, using fuzzy logic controller module comprising a step of inputting said observed parameter values to said fuzzy logic controller module, using input means.
28. The method as claimed in claim 19, wherein said step of identifying critical buses in said power system, using fuzzy logic controller module comprising a step of computing severity index for each bus, for each contingency, of said power system based on said observed parameter values, said computation being carried out by pre-defined rules and formulae, using severity index computation means.
29. The method as claimed in claim 19, wherein said step of identifying critical buses in said power system, using fuzzy logic controller module comprising a

step of computing overall severity index for each bus considering all contingencies, using overall severity index computation means.
30. The method as claimed in claim 19, wherein said step of identifying minimum number of phasor monitoring unit placement sites, where, critical buses are observed either for at least two times or by ensuring phasor monitoring unit at their corresponding location, using integer linear programming module comprising a step of identifying minimum number of phasor monitoring unit placement sites, where, critical buses are observed for at least two times using overall severity index for each bus, using identification means.
31. The method as claimed in claim 19, wherein said step of identifying minimum number of phasor monitoring unit placement sites, where, critical buses are observed either for at least two times or by ensuring phasor monitoring unit at their corresponding location, using integer linear programming module comprising a step of identifying minimum number of phasor monitoring unit placement sites, where, critical buses are observed by ensuring phasor monitoring unit at that location using overall severity index for each bus, using integer linear programming module comprising identification means.
32. The method as claimed in claim 19, wherein said step of identifying minimum number of phasor monitoring unit placement sites, where, critical buses are observed either for at least two times or by ensuring phasor monitoring unit at their corresponding location, using integer linear programming module comprising a step of identifying minimum number of phasor monitoring unit placement sites, where, complete power system values are observed without considering critical buses, using identification means adapted.

33. The method as claimed in claim 19, wherein said step of identifying minimum number of phasor monitoring unit placement sites, where, critical buses are observed either for at least two times or by ensuring phasor monitoring unit at their corresponding location, using integer linear programming module comprising a step of identifying minimum number of phasor monitoring unit placement sites, where, complete power system values are observed with considering critical buses, using identification means.
34. The method as claimed in claim 19, wherein said step of identifying minimum number of phasor monitoring unit placement sites, where, critical buses are observed either for at least two times or by ensuring phasor monitoring unit at their corresponding location, using integer linear programming module comprising a step of identifying minimum number of phasor monitoring unit placement sites, where, complete power system values are observed considering twice observable of critical buses, using identification means adapted to.
35. The method as claimed in claim 19, wherein said step of identifying minimum number of phasor monitoring unit placement sites, where, critical buses are observed either for at least two times or by ensuring phasor monitoring unit at their corresponding location, using integer linear programming module comprising a step of identifying minimum number of phasor monitoring unit placement sites, where, complete power system values are observed considering complete power system twice observable, using identification means.
36. The method as claimed in claim 19, wherein said step of identifying minimum number of phasor monitoring unit placement sites, where, critical buses are

observed either for at least two times or by ensuring phasor monitoring unit at their corresponding location, using integer linear programming module comprising a step of identifying minimum number of phasor monitoring unit placement sites, where, complete power system values are observed considering cost of phasor measurement units proportional to number of lines connected to the corresponding bus of said power system, using identification means.