Claims:We claim:
A method for screening contingencies in an electric grid for time-domain stability analysis, comprising:
obtaining, by a screening system, operation data and contingency data associated with an electric grid;
generating, by the screening system, adjacency matrix of a plurality of buses associated with the electric grid based on the operation data and the contingency data;
grouping, by the screening system, one or more buses from the plurality of buses based on at least one of adjacency of the plurality of buses and sorting of Z-thevenin value of each of the plurality of buses, to form one or more contingency groups;
determining, by the screening system, each of the one or more contingency groups to be one of stable group and unstable group based on an instability index computed for a bus selected from one or more buses in the corresponding one or more contingency group; and
providing, by the screening system, each of the one or more contingency groups, determined to be the unstable group, for time-domain stability analysis of the electric grid.

The method as claimed in claim 1, wherein the grouping of the one or more buses based on sorting of the Z-thevenin value of each of the plurality of buses, comprises:
sorting the Z-thevenin value of each of the plurality of buses in one of a descending order and an ascending order;
determining difference of adjacent Z-thevenin values in the sorted Z-thevenin value of each of the plurality of buses, wherein the determined difference is an absolute value; and
grouping the one or more buses based on the determined difference to form the one or more contingency groups.

The method as claimed in claim 2, wherein the plurality of buses associated with the difference lesser than a first predefined threshold value are grouped together and each of the plurality of buses associated with the difference greater than the first predefined threshold value are grouped independently.

The method as claimed in claim 3, wherein difference of Z-thevenin values between each of the one or more buses associated with a contingency group of the one or more contingency groups is lesser than the first predefined threshold value.

The method as claimed in claim 2, further comprising:
verifying one or more buses in each of the one or more contingency groups to be one of not connected and connected via one of direct connectivity and indirect connectivity, with other one or more buses in the corresponding contingency group; and
forming one or more new contingency groups, in the one or more contingency groups, when the one or more buses are verified to be not connected, wherein each of the one or more new contingency groups comprises the one or more buses verified to be connected via one of the direct connectivity and the indirect connectivity.

The method as claimed in claim 1, wherein grouping of the one or more buses based on the adjacency of the plurality of buses comprises:
determining absolute value of difference of Z-thevenin values for every first bus and second bus from the plurality of buses, wherein the first bus and the second bus are identified to be adjacent to each other from the adjacency matrix; and
grouping the first bus and the second bus together when the difference is lesser than the first predefined threshold value and grouping each of the first bus and the second bus independent to each other when the difference is greater than the first predefined threshold value.

The method as claimed in claim 1, wherein the bus for computing the instability index is selected based on extreme value of one of Z-thevenin values and the operation data associated with the one or more buses of the corresponding one or more contingency groups.

The method as claimed in claim 1, wherein each of the one or more contingency groups is determined to be one of the stable group and unstable group when the corresponding instability index is one of lesser than and greater than a second predefined threshold value respectively.
A screening system for screening contingencies in an electric grid for time-domain stability analysis, comprises:
a processor; and
a memory communicatively coupled to the processor, wherein the memory stores processor-executable instructions, which, on execution, cause the processor to:
obtain operation data and contingency data associated with an electric grid;
generate adjacency matrix of a plurality of buses associated with the electric grid based on the operation data and the contingency data;
group one or more buses from the plurality of buses based on at least one of adjacency of the plurality of buses and sorting of Z-thevenin value of each of the plurality of buses, to form one or more contingency groups;
determine each of the one or more contingency groups to be one of stable group and unstable group based on an instability index computed for a bus selected from one or more buses in the corresponding one or more contingency group; and
provide each of the one or more contingency groups, determined to be the unstable group, for time-domain stability analysis of the electric grid.

The screening system as claimed in claim 9, wherein the grouping of the one or more buses based on sorting of the Z-thevenin value of each of the plurality of buses, comprises:
sorting the Z-thevenin value of each of the plurality of buses in one of a descending order and an ascending order;
determining difference of adjacent Z-thevenin values in the sorted Z-thevenin value of each of the plurality of buses, wherein the determined difference is an absolute value; and
grouping the one or more buses based on the determined difference to form the one or more contingency groups.

The screening system as claimed in claim 10, wherein the plurality of buses associated with the difference lesser than a first predefined threshold value are grouped together and each of the plurality of buses associated with the difference greater than the first predefined threshold value are grouped independently.

The screening system as claimed in claim 11, wherein difference of Z-thevenin values between each of the one or more buses associated with a contingency group of the one or more contingency groups is lesser than the first predefined threshold.

The screening system as claimed in claim 10, further comprises:
verifying one or more buses in each of the one or more contingency groups to be one of not connected and connected via one of direct connectivity and indirect connectivity, with other one or more buses in the corresponding contingency group; and
forming one or more new contingency groups, in the one or more contingency groups, when the one or more buses are verified to be not connected, wherein each of the one or more new contingency groups comprises the one or more buses verified to be connected via one of the direct connectivity and the indirect connectivity.

The screening system as claimed in claim 9, wherein grouping of the one or more buses based on the adjacency of the plurality of buses comprises:
determining absolute value of difference of Z-thevenin values for every first bus and second bus from the plurality of buses, wherein the first bus and the second bus are identified to be adjacent to each other from the adjacency matrix; and
grouping the first bus and the second bus together when the difference is lesser than the first predefined threshold value and grouping each of the first bus and the second bus independent to each other when the difference is greater than the first predefined threshold value.

The screening system as claimed in claim 9, wherein the bus for computing the instability index is selected based on extreme value of one of Z-thevenin values and the operation data associated with the one or more buses of the corresponding one or more contingency groups.

The screening system as claimed in claim 9, wherein each of the one or more contingency groups is determined to be one of the stable group and unstable group when the corresponding instability index is one of lesser than and greater than a second predefined threshold value respectively.

Dated this 28th day of August, 2017
R. Ramya Rao
IN/PA-1607
Of K & S Partners
Agent for the Applicant

, Description:FORM 2
THE PATENTS ACT 1970
[39 OF 1970]
&
THE PATENTS RULES, 2003

COMPLETE SPECIFICATION
[See section 10; Rule 13]

TITLE: “DYNAMIC STABILITY SCREENING METHOD FOR TRANSIENT STABILITY ANALYSIS”

Name and Address of the Applicant:
Name of the Applicant: HITACHI, LTD.; 6-6, Marunouchi 1-chome, Chiyoda-ku, Tokyo 100-8280, Japan.

Nationality: Japan

The following specification particularly describes the invention and the manner in which it is to be performed.

TECHNICAL FIELD

The present subject matter is related in general to stability analysis of an electric grid, more particularly, but not exclusively to a method and system for screening contingencies in an electric grid for time-domain stability analysis.

BACKGROUND

Every electrical grid (also referred as a network) may be associated with a stability analysis module for performing analysis of stability of the electric grid. The stability analysis may be performed through a simulation in time-domain to check for faults associated with the electric grid and to correct the faults to achieve transient stability in the electric grid. In existing system, each of contingencies and buses associated with the electric grid is provided for the simulation to perform the time-domain stability analysis. Further, time required for the time-domain stability analysis depends on number of the buses and the contingencies in the electric grid which are to be simulated. As size of the electric grid increases, the number of the buses and the contingencies also increases, by which computation time or time taken to complete time-domain stability analysis increases. Also, larger the electric grid, more complex is model of the electric grid, which is used for the simulation. With complex models of the electric grid, performance of the simulation may be reduced. Also, simulation time may also increase depending upon the complexity.

One or more techniques to reduce time taken for the time-domain stability analysis are implemented in large electric grids. In said one or more techniques, the contingencies in a large electric grid are screened to shortlist suspect or unstable cases before performing the time-domain stability analysis. The screening may include determining instability index for each of the contingencies in the large electric grid. The instability index may be determined using value of generator power, kinetic energy and so on at instance of fault clearing in the respective contingency. Further, time-domain stability may be performed to such contingencies for which the instability index is greater than a threshold value. These techniques eliminate the need for performing time-domain stability analysis for every contingency in the large electric grid. However, such techniques of determining the instability index for every contingency in the large electric grid may require more computation time. Also, such technique would lead to limitations such as computation speed, and cost.

The information disclosed in this background of the disclosure section is for enhancement of understanding of the general background of the invention and should not be taken as an acknowledgement or any form of suggestion that this information forms the prior art already known to a person skilled in the art.

SUMMARY

In an embodiment, the present disclosure relates to a method for screening contingencies in an electric grid for time-domain stability analysis. Initially, operation data and contingency data associated with the electric grid are obtained and an adjacency matrix of a plurality of buses associated with the electric grid is generated based on the operation data and the contingency data. Further, one or more buses from the plurality of buses are grouped based on at least one of the adjacency matrix and Z-thevenin value of each of the plurality of buses, to form one or more contingency groups. Further, each of the one or more contingency groups is determined to be one of stable group and unstable group based on an instability index computed for a bus selected from one or more buses in the corresponding one or more contingency group. Each of the one or more contingency groups determined to be the unstable group id provided for time-domain stability analysis of the electric grid.

In an embodiment, the present disclosure relates to screening system for screening contingencies in an electric grid for time-domain stability analysis. The screening system includes a processor and a memory communicatively coupled to the processor. The memory stores processor-executable instructions, which, on execution, cause the processor to screen the contingencies. Initially, operation data and contingency data associated with the electric grid are obtained and an adjacency matrix of a plurality of buses associated with the electric grid is generated based on the operation data and the contingency data. Further, each of the one or more contingency groups is determined to be one of stable group and unstable group based on an instability index computed for a bus selected from one or more buses in the corresponding one or more contingency group. Each of the one or more contingency groups determined to be the unstable group is provided for time-domain stability analysis of the electric grid.

The foregoing summary is illustrative only and is not intended to be in any way limiting. In addition to the illustrative aspects, embodiments, and features described above, further aspects, embodiments, and features will become apparent by reference to the drawings and the following detailed description.
BRIEF DESCRIPTION OF THE ACCOMPANYING DRAWINGS
The accompanying drawings, which are incorporated in and constitute a part of this disclosure, illustrate exemplary embodiments and, together with the description, serve to explain the disclosed principles. In the figures, the left-most digit(s) of a reference number identifies the figure in which the reference number first appears. The same numbers are used throughout the figures to reference like features and components. Some embodiments of system and/or methods in accordance with embodiments of the present subject matter are now described, by way of example only, and regarding the accompanying figures, in which:

Figure 1 illustrates an exemplary environment for screening contingencies in an electric grid for time-domain stability analysis in accordance with some embodiments of the present disclosure;

Figure 2 shows a detailed block diagram of screening system in accordance with some embodiments of the present disclosure;

Figure 3 illustrates a flowchart showing a method for screening contingencies in an electric grid for time-domain stability analysis in accordance with some embodiments of present disclosure;

Figure 4 illustrates a flowchart showing a method for grouping one or more buses from a plurality of buses based on sorting of Z-thevenin value of the plurality of buses in accordance with some embodiments of present disclosure;

Figure 5 illustrates a flowchart showing a method for grouping one or more buses from a plurality of buses based on adjacency of plurality of buses in accordance with some embodiments of present disclosure;

Figures 6 illustrates exemplary representation of plurality of buses in an electric grid in accordance with some embodiments of present disclosure; and

Figure 8 illustrates a block diagram of an exemplary computer system for implementing embodiments consistent with the present disclosure.

It should be appreciated by those skilled in the art that any block diagrams herein represent conceptual views of illustrative systems embodying the principles of the present subject matter. Similarly, it will be appreciated that any flow charts, flow diagrams, state transition diagrams, pseudo code, and the like represent various processes which may be substantially represented in computer readable medium and executed by a computer or processor, whether such computer or processor is explicitly shown.

DETAILED DESCRIPTION
In the present document, the word "exemplary" is used herein to mean "serving as an example, instance, or illustration." Any embodiment or implementation of the present subject matter described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments.

While the disclosure is susceptible to various modifications and alternative forms, specific embodiment thereof has been shown by way of example in the drawings and will be described in detail below. It should be understood, however that it is not intended to limit the disclosure to the forms disclosed, but on the contrary, the disclosure is to cover all modifications, equivalents, and alternative falling within the spirit and the scope of the disclosure.

The terms “comprises”, “comprising”, or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a setup, device or method that comprises a list of components or steps does not include only those components or steps but may include other components or steps not expressly listed or inherent to such setup or device or method. In other words, one or more elements in a system or apparatus proceeded by “comprises… a” does not, without more constraints, preclude the existence of other elements or additional elements in the system or method.

The terms “includes”, “including”, or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a setup, device or method that includes a list of components or steps does not include only those components or steps but may include other components or steps not expressly listed or inherent to such setup or device or method. In other words, one or more elements in a system or apparatus proceeded by “includes… a” does not, without more constraints, preclude the existence of other elements or additional elements in the system or method.

In the following detailed description of the embodiments of the disclosure, reference is made to the accompanying drawings that form a part hereof, and in which are shown by way of illustration specific embodiments in which the disclosure may be practiced. These embodiments are described in sufficient detail to enable those skilled in the art to practice the disclosure, and it is to be understood that other embodiments may be utilized and that changes may be made without departing from the scope of the present disclosure. The following description is, therefore, not to be taken in a limiting sense.

The present disclosure relates to screening system and method for screening contingencies in an electric grid for an efficient time-domain stability analysis of the electric grid. The present disclosure provisions time-reduced stability analysis of the electric grid by reducing the number of contingency which are to be analysed. The contingencies are screened by the screening system and only the contingencies which are determined to be unstable are provided for the time-domain stability analysis. The screening includes generating an adjacency matrix of the plurality of buses of the electric grid based on operation data and contingency data associated with the electric grid. Further, one or more buses from the plurality of buses are grouped based on at least one of adjacency of the plurality of buses and sorting of Z-thevenin value of each of the plurality of buses, to form one or more contingency groups. Said grouping of the one or more buses is performed to group the one or more buses with similar stability characteristics. Further, each of the one or more contingency groups is determined to be one of stable group and unstable group based on an instability index computed for a bus selected from one or more buses in the corresponding one or more contingency group. Determining the instability index for only one bus in each of the contingency group provisions reduction in computation time of the screening. Each of the one or more contingency groups determined to be the unstable group is provided for time-domain stability analysis of the electric grid. By the method and the screening system disclosed in the present disclosure, efficiency and higher processing speed capability may be achieved in the time-domain stability analysis of the electric grid.

Figure 1 illustrates an exemplary environment 100 for screening contingencies in the electric grid 103 for time-domain stability analysis in accordance with some embodiments of the present disclosure.

As shown in Figure 1, the environment 100 may include a screening system 101, a communication network 102, an electric grid 103 and a stability analysis module 104 associated with the screening system 101. The electric grid 103 may be an electrical power network which comprises of electrical elements deployed to supply, transfer, and use electric power. The electrical elements may include, but are not limited to, one or more generators, one or more loads, transmission lines with plurality of buses (also referred as sub-stations or nodes) and so on. In case of large electric grid, there is a need for stability analysis which includes performing stability analysis of contingencies or transient associated with the electric grid 103. The stability analysis may be performed by a stability analysis module 104 associated with the electric grid 103. In an embodiment, the stability analysis module 104 may be implemented using one or more simulation techniques. Said simulation techniques may be a time-domain simulation and the stability analysis may be referred to as the time-domain stability analysis. For the time-domain stability analysis, the contingencies associated with the electric grid 103 are provided to the stability analysis module 104 and analysis of each of the contingencies is performed. In an embodiment, by the time-domain stability analysis, transient stability of the electric grid 103 may be achieved. In the present disclosure, the contingencies which are to be provided for the time-domain stability analysis are grouped and screened by the screening system 101 for performing stability analysis with lesser computational time.

The screening system 101 comprises a processor 105, Input/ Output (I/O) interface 106, one or more modules 107 and a memory 108. The memory 108 may be communicatively coupled to the processor 105 and stores processor-executable instructions which on execution cause the processor 105 along with the one or more modules 107 to screen the contingencies.

Initially, operation data and contingency data associated with the electric grid 103 are obtained by the screening system 101 from the electric grid 103. In an embodiment, the operation data may include, but not limited to, electric grid network data, equipment data such as data associated with generators, transmission lines and so on in the electric grid 103, Supervisory Control and Data Acquisition (SCADA) data, Phasor Measurement Unit (PMU) data, operator specified daily schedule of the generations and estimated load in the electric grid 103, protection settings associated with the electric grid 103 and so on. The contingency data may include list of contingencies associated with the electric grid 103. In an embodiment, the operation data and the contingency data may be obtained dynamically from the electric grid 103. In an embodiment, the operation data and the contingency data may be obtained from a database associated with the electric grid 103 (not shown in figure).

Upon obtaining the operation data and the contingency data, the screening system 101 generates an adjacency matrix of a plurality of buses associated with the electric grid 103 based on the operation data and the contingency data. The adjacency matrix is a square matrix used to represent a finite graph of the electric grid 103. Elements of the adjacency matrix indicate connectivity associated with pairs of buses in the electric grid 103. One or more techniques, known to a person skilled in the art, may be implemented to generate the adjacency matrix for the electric grid 103.

Further, one or more buses from the plurality of buses are grouped based on at least one of adjacency of the plurality of buses and sorting of Z-thevenin value of each of the plurality of buses and. By said grouping, one or more contingency groups may be formed. Each of the one or more contingency groups may comprise at least one bus from the plurality of buses. The grouping of the one or more buses based on the sorting of the Z-thevenin value includes sorting the Z-thevenin value of each of the plurality of buses in one of a descending order and an ascending order. The Z-thevenin value of each of the plurality of buses may be derived from the operation data associated with the corresponding bus. One or more techniques known to a person skilled in the art may be implemented in the present disclosure for deriving the Z-thevenin value for each of the plurality of buses. In an embodiment, the Z-thevenin value for each of the plurality of buses may be stored in a database associated with the electric grid 103 and obtained by the screening system 101 when performing screening.
Upon sorting, the screening system 101 determines difference of adjacent Z-thevenin values in the sorted Z-thevenin value of each of the plurality of buses. The determined difference is an absolute value. Further, the one or more buses are grouped based on the determined difference to form the one or more contingency groups. Upon sorting and determining the difference, the plurality of buses associated with the difference lesser than a first predefined threshold value are grouped together. Each of the plurality of buses associated with a difference greater than the first predefined threshold value are grouped independently. Also, in each of the one or more contingency groups, condition of difference of Z-thevenin values between each of the one or more buses to be lesser than the first predefined threshold value is to be satisfied. Upon grouping the one or more buses based on the determined difference, one or more buses in each of the one or more contingency groups are verified to be one of not connected and connected via one of direct connectivity and indirect connectivity, with other one or more buses in the corresponding contingency group. Further, one or more new contingency groups are formed in the one or more contingency groups when the one or more buses are verified to be not connected. Each of the one or more new contingency groups comprises the one or more buses verified to be connected via one of the direct connectivity and the indirect connectivity. In an embodiment, the direct connectivity includes that buses are connected directly with each other. In an embodiment, the indirect connectivity includes that the buses are connected via another bus i.e., there is no direct connection between the buses but the connection exists via another bus which is connected to both the buses.

The grouping of the one or more buses based on the adjacency of the plurality of buses includes determining difference of Z-thevenin values for every first bus and second bus from the plurality of buses. Here, the first bus and the second bus are identified to be adjacent to each other. In an embodiment, the adjacency may be verified using the adjacency matrix. The first bus and the second bus are grouped together when the difference is lesser than the first predefined threshold value. Each of the first bus and the second bus are grouped independent to each other when the difference is greater than the first predefined threshold value. In an embodiment, absolute value of the difference is used for grouping of the one or more buses based on the adjacency matrix.

In an electric grid, the plurality of buses with similar stability characteristics may be associated with closer values of Z-thevenin values. Unstable buses from the plurality of buses have influence over stability of the other one or more buses from the plurality of buses with closer Z-thevenin value. Grouping in the present disclosure is based on difference of the Z-thevenin values, which provisions to group the one or more buses with similar stability characteristics.

Upon grouping to form the one or more contingency groups with similar stability characteristics, each of the one or more contingency groups is determined to be one of stable group and unstable group based on an instability index. The instability index may be computed for a bus selected from one or more buses in the corresponding one or more contingency group. In an embodiment, one or more methods known to the person skilled in the art is implemented to compute the instability index. The bus for computing the instability index is selected based on extreme value of one of Z-thevenin values and the operation data associated with the one or more buses of the corresponding one or more contingency groups. Each of the one or more contingency groups is determined to be the stable group when the corresponding instability index is lesser than a second predefined threshold value. Each of the one or more contingency groups is determined to be the unstable group when the corresponding instability index is greater than the second predefined threshold value. Each of the contingency groups which are determined to be the unstable group is provided for time-domain stability analysis of the electric grid. In an embodiment, the time-domain stability analysis comprises detecting faults in the contingencies. In an embodiment, the time-domain analysis may include to determine counter measure (also referred to a pseudo-measurement) for faulty measurements associated with the contingencies. In an embodiment, the time-domain analysis may include preparing corrective controls for the contingencies in the electric grid 103.

In an embodiment, the screening system 101 receives data which include, but are not limited to, the operation data, the contingency data and other associated data for screening the contingencies via the communication network 102 through the I/O interface 106. Also, the screening system 101 may provide output, i.e., the contingencies group determined to be unstable group, via the I/O interface 106. In one embodiment, the output may be provided to at least one of user device, any other display unit and any other device associated with the screening system 101. In an embodiment, the output may be stored in a data source associated with the screening system 101. Further, the I/O interface 106 may be coupled with the processor 105 of the screening system 101. In an embodiment, the screening system 101, the electric grid 103 and the stability analysis system 104 may communicate with each other via the communication network 102. The communication network 102 may include, without limitation, a direct interconnection, local area network (LAN), wide area network (WAN), wireless network (e.g., using Wireless Application Protocol), the Internet, etc. Also, in an embodiment, the prediction unit 101 may be implemented in a variety of computing systems, such as a laptop computer, a desktop computer, a Personal Computer (PC), a notebook, a smartphone, a tablet, e-book readers (e.g., Kindles and Nooks), a server, a network server, and the like.

Figure 2 shows a detailed block diagram of the screening system 101 in accordance with some embodiments of the present disclosure. Data 207 in the memory 108 and one or more modules 107 of the screening system 101 may be described herein in detail.

In one implementation, the one or more modules 107 may include, but are not limited to, a data obtaining module 201, a matrix generation module 202, a buses grouping module 203, a group stability determining module 204, a group providing module 205, and one or more other modules 206 associated with the screening system 101.

In an embodiment, data 207 in the memory 108 may include an operation data 208, a contingency data 209, an adjacency matrix data 210 (also referred as the adjacency matric 210), a contingency group data 211 (also referred as the one or more contingency groups 211), an instability index data 212 (also referred as the instability index 212), Z-thevenin value 213, a first predefined threshold value 214, a second predefined threshold value 215, and other data 216 associated with the screening system 101.

In an embodiment, the data 207 in the memory 108 may be processed by the one or more modules 107 of the screening system 101. As used herein, the term module refers to an application specific integrated circuit (ASIC), an electronic circuit, a field-programmable gate arrays (FPGA), Programmable System-on-Chip (PSoC), a combinational logic circuit, and/or other suitable components that provide the described functionality. The modules when configured with the functionality defined in the present disclosure will result in a novel hardware.

For screening the contingencies in the electric grid 103, initially, operation data 208 and contingency data 209 associated with the electric grid 103 are obtained by the data obtaining module 201 of the screening system 101. An exemplary representation of the electric grid 600 is illustrated in Figure 6. The electric grid 600 comprises of plurality of buses 601.1……601.5. Connectivity between the plurality of buses 601.1……601.5 is also indicated in Figure 6. From the figure, the bus 601.1 is connected to the buses 601.2, 601.5 and 601.4 and the bus 601.3 is connected to the buses 601.4 and 601.2. In an embodiment, the operation data 208 may include, but is not limited to, electric grid network data, equipment data such as data associated with generators, transmission lines and so on in the electric grid 600, Supervisory Control and Data Acquisition (SCADA) data, Phasor Measurement Unit (PMU) data, operator specified daily schedule of the generations and estimated load in the electric grid 600, protection settings associated with the electric grid 600 and so on. The contingency data 209 associated with the electric grid 600 may include list of contingencies associated with the electric grid 600. In an embodiment, the buses 601.2 and 601.4 may be the list of contingencies for the plurality of buses 601.1……601.5.

Upon obtaining the operation data 208 and the contingency data 209, the matrix generation module 202 generates the adjacency matrix 210 of the plurality of buses 601.1……601.5 associated with the electric grid 600 based on the operation data 208 and the contingency data 209. An exemplary representation of the adjacency matrix 210 generated for the electric grid 600 may be as shown in below Table 1:

601.1 601.2 601.3 601.4 601.5
601.1 0 1 0 1 1
601.2 1 0 1 0 1
601.3 0 1 0 1 0
601.4 1 0 1 0 1
601.5 1 1 0 1 0

Table 1

From the above adjacency matrix 210, coordinate in the adjacency matrix 210 associated with the buses which are connected to each other indicate ‘1’. Coordinate in the adjacency matrix 210 associated with the buses which are not connected to each other indicate ‘0’. For example, the buses 601.1 and 601.5 are connected to each other from the electric grid 600 represented in Figure 6. Hence, the coordinate associated with the buses 601.1 and 601.5 indicate ‘1’. The buses 601.2 and 601.4 are not connected to each other from the electric grid 600 represented in Figure 6. Hence, the coordinate associated with the buses 601.2 and 601.4 indicate ‘0’. In an embodiment, one of lower triangle of the adjacency matrix 210 and upper triangle of the adjacency matrix 210 may be considered by the screening system 101 since the adjacency matrix 210 is symmetric about diagonal.

Upon the generation of the adjacency matrix 210, one or more buses from the plurality of buses 601.1……601.5 are grouped by the buses grouping module 203 based on at least one of adjacency of the plurality of buses 601.1……601.5 and sorting of the Z-thevenin value 213 of each of the plurality of buses 601.1……601.5, to form the one or more contingency groups 211. The Z-thevenin value 213 of each of the plurality of buses 601.1……601.5 may be derived from the operation data 208 associated with the corresponding bus. One or more techniques to the person skilled in the art may be implemented for deriving the Z-thevenin value.
For grouping based on the sorting of the Z-thevenin value 213 of each of the plurality of buses 601.1……601.5, consider an example for the plurality of buses 601.1……601.5 in Figure 6 to be associated with the Z-thevenin value 213 as given in below Table 2:

601.1 601.2 601.3 601.4 601.5
4.8 4.1 3.0 3.2 3.1

Table 2
For grouping of the one or more buses based on the Z-thevenin value 213, initially, the Z-thevenin value 213 of each of the plurality of buses 601.1……601.5 are sorted in one of a descending order and an ascending order. For the given example, consider to sort the Z-thevenin in the descending order. The sorted Z-thevenin may be as provided in below Table 3:

601.1 601.2 601.4 601.5 601.3
4.8 4.1 3.2 3.1 3.0

Table 3
Upon sorting, absolute value of difference of adjacent Z-thevenin values 213 in the sorted Z-thevenin value of each of the plurality of buses is determined. One or more modules, known to the person skilled in art, may be implemented for determining the difference in the present disclosure. For the given example, the difference of the buses 601.1 and 601.2 may be 4.8-4.1=0.7; the difference of the buses 601.2 and 601.4 may be 4.1-3.2=0.9; difference of the buses 601.4 and 601.5 may be 3.2-3.1=0.1 and difference of the buses 601.1 and 601.2 may be 3.1-3.0=0.1. The plurality of buses 601.1……601.5 associated with the difference lesser than the first predefined threshold value 214 are grouped together. Each of the plurality of buses 601.1……601.5 associated with the difference greater than the first predefined threshold value 214 are grouped independently. Also, in each of the contingency groups 211, difference of Z-thevenin values 213 between each of the one or more buses is lesser than the first predefined threshold value 214. Consider the first predefined threshold 214 to be 0.95. Hence, for the given example, buses 601.1 and 601.2 may be grouped together to form the first contingency group since the difference is lesser than the first predefined threshold value 214. Further, even though the difference associated with the buses 601.2 and 601.4 is lesser than the first predefined threshold value 214, the bus 601.4 cannot be in the first contingency group since the difference associated with the bus 601.1 and 601.4 is 4.8-3.2= 1.6 which is greater than the predefined threshold value 214. Further, the difference associated with the buses 601.4 and 601.5 and 601.3 are lesser than the first predefined threshold value 214 and the difference between the buses 601.4 and 601.3 i.e., 3.2-3.0=0.2, is lesser than the first predefined threshold value 214. Therefore, the buses 601.4, 601.5 and 601.3 may be grouped to form second contingency group.

Further, grouping based on the sorting of the Z-thevenin value includes verifying one or more buses in each of the one or more contingency groups 211 to be one of not connected and connected via direct connectivity or indirect connectivity with other one or more buses in the corresponding contingency group 211. For the first contingency group, the bus 601.1 is verified to be connected with the bus 601.2. From Figure 6, the buses 601.1 and 601.2 are verified to be connected via the direct connectivity, hence the buses 601.1 and 601.2 remain to be grouped together. Similarly, for the second contingency group, each of the buses 601.4, 601.5 and 601.3 are verified. Here, the bus 601.4 is connected with the buses 601.3 and 601.5 via the direct connectivity, the bus 601.5 is connected with 601.4 via the direct connectivity and with the bus 601.3 via the indirect connectivity through the bus 601.4. Hence the buses 601.4, 60.5 and 601.3 remain to be grouped together.

For grouping of the one or more buses based on the adjacency of the plurality of buses, consider the above example of Z-thevenin values of the plurality of buses 601.1……601.5 provided in Table 2. From the adjacency matrix 210 provided in Table 1 and considering one of the upper triangle and the lower triangle of Table 1, the buses 601.1 and 601.2, 601.1 and 601.4, 601.1 and 601.5, 601.2 and 601.3, 601.2 and 601.5, 601.3 and 601.4 and 601.4 and 601.5 are identified to be adjacent buses i.e., adjacent to each other. Here, for adjacent buses 601.1 and 601.2, the first bus may be 601.1 and the second bus may be 601.2. Similarly, for adjacent buses 601.1 and 601.4. the first bus may be 601.1 and the second bus may be 601.4. Further, the difference of Z-thevenin value 213 for every first bus and second bus in the adjacent buses are determined. When the difference is lesser than the first predefined threshold value 214, the first bus and the second bus are grouped together and when the difference is greater than the first predefined threshold value 214, each of the first bus and the second bus are grouped independently. Absolute value of the difference is used for the grouping. Consider the first predefined threshold value 214 to be 0.95, the difference associated with the adjacent buses 601.1 and 601.2 is 4.8-4.1=0.7, the difference associated with the adjacent buses 601.1 and 601.4 is 4.8-3.2=1.6, the difference associated with the adjacent buses 601.1 and 601.5 is 4.8-3.1=1.7, the difference associated with the adjacent buses 601.2 and 601.3 is 4.1-3.0=1.1, the difference associated with the adjacent buses 601.2 and 601.5 is 4.1-3.1=1.0, the difference associated with the adjacent buses 601.3 and 601.4 is 3.0-3.2=0.2 and the difference associated with the adjacent buses 601.4 and 601.5 is 3.2-3.1=0.1.Here, the difference associated with the adjacent buses 601.1 and 601.2 is lesser than the first predefined threshold value 214. Hence, the adjacent buses 601.1 and 601.2 may be grouped together to form a first contingency group. Similarly, the difference associated with the adjacent buses 601.3 and 601.4 is lesser than the first predefined threshold value 214. Hence, the adjacent buses 601.3 and 601.4 may be grouped together to form a second contingency group. Since, the difference associated with the adjacent buses 601.4 and 601.5 is also lesser than the second predefined threshold value 215, the bus 601.5 may be grouped in the second contingency group which comprises the bus 601.4.

Upon performing grouping to form the first contingency group and the second contingency group, each of the first contingency group and the second contingency group is determined to be one of stable group and unstable group by the group stability determining module 204. The instability index 212 associated with the first contingency group and the second contingency group may be used to determine the contingency group 211 to be one of the stable group and the unstable group. The instability index 212 may be computed for a bus selected from one or more buses in the corresponding one or more contingency group. For the first contingency group, the bus for which the instability index 212 is to be computed may be selected from the buses 601.1 and 601.2. For the second contingency group, the bus for which the instability index 212 is to be computed may be selected from the buses 601.3, 601.4 and 601.5. In an embodiment, the bus may be selected based on extreme value of one of Z-thevenin values 213 and the operation data 208 associated with the one or more buses of the corresponding one or more contingency groups 211. For example, in the first contingency group, the bus 601.1 may be selected, consider the Z-thevenin value 4.8 to be the extreme value. Similarly, in the second contingency group, the bus 601.4 may be selected, consider the Z-thevenin value 302 to be the extreme value.

In an embodiment, the instability index 212 is determined using a simulation in which a fault is simulated on the selected bus. When fault is simulated on the selected bus, reaction of generators in the electric grid 600 may vary and cumulative deviation of angle across the electric grid 600 may also vary. Rotor angles associated with the generators grid may be checked for determining the deviation before and after the fault simulation on the selected bus of each of the one or more contingency groups 211. In an embodiment, the instability index 212 of the selected bus may be an average change in the rotor angle of each of the generators associated with the electric for the selected bus.
In an embodiment, the instability index 212 may be determined using Equation 1 as given below:
Instabilty index= ?_(i=0)^N¦v(??(??_i1-?_i2)?^2/N) ………….. (1)
where, N is number of generators associated with electric grid;
?_i1 are rotor angle of ith generator associated with the electric grid before fault simulation on the selected bus; and
?_i2 are rotor angle of ith generator associated with the electric grid after fault simulation on the selected bus.
Exemplary value of the instability index 212 may be 10 degree which means on an average each of the generators associated with the selected bus undergo change of angle 10 degree for a given fault.

In an embodiment, one or more simulation tools, known to a person skilled in the art may be implemented in the screening system 101 for determining the instability index 212. Upon determining the instability index 212, for each of the first contingency group and the second contingency group, the contingency groups 211 are determined to be the stable group when the corresponding instability index 212 is lesser than a second predefined threshold value 215. The contingency groups 211 are determined to be the stable group when the corresponding instability index 212 is greater than the second predefined threshold value 215. Further, each of the contingency groups 211 which are determined to be the unstable group is provided by the group providing module 205 to the stability analysis module 104 for time-domain stability analysis of the electric grid 600.

Consider another example for the plurality of buses 601.1……601.5 in Figure 6 to be associated with the Z-thevenin value 213 as provided in below Table 4:

601.1 601.2 601.3 601.4 601.5
2.8 4.1 5.5 4.2 1.1

Table 4
For grouping of the one or more buses based on the Z-thevenin value 213, initially, the Z-thevenin value 213 of each of the plurality of buses 601.1……601.5 are sorted in one of a descending order and an ascending order. For the given example, consider to sort the Z-thevenin value 213 in the ascending order. The sorted Z-thevenin value 213 may be provided as in below Table 5:

601.5 601.1 601.2 601.4 601.3
1.1 2.8 4.1 4.2 5.5

Table 5
Upon sorting, difference of adjacent Z-thevenin value 213 in the sorted Z-thevenin value 213 of each of the plurality of buses 601.1……601.5 is determined. The determined difference may be an absolute value. For the given example, the difference of the buses 601.5 and 601.1 may be 1.1-2.8=1.7; the difference of the buses 601.1 and 601.2 may be 2.8-4.1=1.3; difference of the buses 601.2 and 601.4 may be 4.1-4.2=0.1 and difference of the buses 601.4 and 601.3 may be 4.2-5.5=1.3. For the ascending order of sorting of the Z-thevenin value 213, the plurality of buses 601.1……601.5 associated with the difference lesser than the first predefined threshold value 214 are grouped together. Each of the plurality of buses 601.1……601.5 associated with the difference greater than the first predefined threshold value 214 are grouped independently. Also, in each of the contingency groups 211, difference of Z-thevenin values 213 between each of the one or more buses is lesser than the first predefined threshold value 214. Consider the first predefined threshold 214 to be -0.95. For the given example, the difference associated with the buses 601.5 and 601.1 is greater than the first predefined threshold value 214, hence the buses 601.5 and 601.1 may be grouped independently forming a first contingency group comprising the bus 601.5 and a second contingency group comprising the bus 601.1. Further, the difference associated with the buses 601.1 and 601.2 is greater than the first predefined threshold value 214, hence the buses 601.1 and 601.2 may be grouped independently forming a third contingency group comprising the bus 601.2. Further, difference associated with the buses 601.2 and 601.4 is lesser than the first predefined threshold value 214, hence the bus 601.4 may be grouped along with the bus 601.2 in the third contingency group. Further, difference associated with the buses 601.4 and 601.3 is greater than the first predefined threshold value 214, hence the buses 601.4 and 601.3 may be grouped independently forming a fourth contingency group comprising the bus 601.3. Upon forming the contingency groups 211 based on the Z-thevenin value 213, each of the bus in each of the contingency groups 211 is verified to be one of not connected and connected via one of the direct connectivity and the indirect connectivity, with other one or more buses in the corresponding contingency group. Here, the third contingency group need to be verified to check connectivity the bus 601.2 and the bus 601.4. From Figure 6, it may be identified that the bus 601.2 is not connected to the bus 601.4 and hence, a new contingency group, i.e., fifth contingency group may be formed in the one or more contingency groups 211 comprising the bus 601.4. In an embodiment, the third contingency group may comprise the bus 601.4 and the fifth contingency group may comprise the bus 601.2.

Consider a contingency group comprising four buses and in case where any two buses are verified to be connected via direct connectivity and other two buses are connected with each other via direct connectivity with each other and not connected with any of the two buses. Here, a new contingency group may be formed with other two buses which are connected via the direct connectivity.

For grouping of the one or more buses based on the adjacency of the plurality of buses 601.1……601.5, consider the above example of Z-thevenin value of the plurality of buses 601.1……601.5 provided in Table 4. From the adjacency matrix 210 provided in Table 1 and considering one of the upper triangle and the lower triangle of the Table 1, the buses 601.1 and 601.2, the buses 601.1 and 601.4, the buses 601.1 and 601.5, the buses 601.2 and 601.3, the buses 601.2 and 601.5, the buses 601.3 and 601.4 and the buses 601.4 and 601.5 are identified to be adjacent buses i.e., adjacent to each other. Here, for adjacent buses 601.1 and 601.2, the first bus may be 601.2 and the second bus may be 601.1. Similarly, for adjacent buses 601.1 and 601.4. the first bus may be 601.4 and the second bus may be 601.1. Further, the difference of Z-thevenin values for every first bus and second bus in the adjacent buses are determined. The determined difference may be an absolute value. When the difference is lesser than the first predefined threshold value 214, the first bus and the second bus are grouped together and when the difference is greater than the first predefined threshold value 214, each of the first bus and the second bus are grouped independently. Consider the first predefined threshold value 214 to be 0.95, the difference associated with the adjacent buses 601.1 and 601.2 is 4.1-2.8=1.3, the difference associated with the adjacent buses 601.1 and 601.4 is 4.2-2.8=1.4, the difference associated with the adjacent buses 601.1 and 601.5 is 2.8-1.1=1.7, the difference associated with the adjacent buses 601.2 and 601.3 is 5.5-4.1=1.4, the difference associated with the adjacent buses 601.2 and 601.5 is 4.1-1.1=3.0, the difference associated with the adjacent buses 601.3 and 601.4 is 4.2-5.5=1.3 and the difference associated with the adjacent buses 601.4 and 601.5 is 4.2-1.1=3.2. Here, the difference associated with every adjacent bus is greater than the second predefined threshold value 215, hence each of the buses are grouped independently forming the first contingency group comprising 601.1, the second contingency group comprising 601.2, the third contingency group comprising 601.3, the fourth contingency group comprising 601.4 and the fifth contingency group comprising 601.5. In an embodiment, each of the contingency groups may comprise any of the buses 601.1…….601.5.

Upon performing grouping to form the contingency groups 211, each of the contingency groups 211 is determined to be one of stable group and unstable group by the group stability determining module 204. The instability index 212 associated with each of the contingency groups 211 may be used to determine the contingency group to be one of the stable group and the unstable group. The instability index 212 may be computed for a bus selected from one or more buses in the corresponding one or more contingency group 211. Since, each of the contingency groups 211 comprises one bus, the bus associated with each of the contingency bus is selected for computing respective instability index 212. The instability index 212 for the selected bus may be determined using Equation 1 described previously. Upon determining the instability index 212, for each of the first contingency group and the second contingency group, the contingency groups 211 are determined to be the stable group when the corresponding instability index 212 is lesser than the second predefined threshold value 215. The contingency groups 211 are determined to be the stable group when the corresponding instability index 212 is greater than a second predefined threshold value 215. Further, each of the contingency groups 211 which are determined to be the unstable group is provided by the group providing module 205 to the stability analysis module 104 for time-domain stability analysis of the electric grid 600.

The other data 216 may store data, including temporary data and temporary files, generated by modules for performing the various functions of the screening system 101. The one or more modules 107 may also include other modules 206 to perform various miscellaneous functionalities of the screening system 101. It will be appreciated that such modules may be represented as a single module or a combination of different modules.

Figure 3 illustrates a flowchart showing the method for screening the contingencies in the electric grid 103 for time-domain stability analysis in accordance with some embodiments of present disclosure.

At block 301, the data obtaining module 201 obtains the operation data 208 and the contingency data 209 associated with the electric grid 103.

At block 302, the matrix generation module 202 generates the adjacency matrix 210 of the plurality of buses associated with the electric grid 103 based on the operation data 208 and the contingency data 209. The adjacency matrix 210 may be generated using one or more techniques known to a person skilled in art.

At block 303, the buses grouping module 203 groups the one or more buses from the plurality of buses based on at least one of the adjacency of plurality of buses and sorting of the Z-thevenin value 213 of the plurality of buses, to form the one or more contingency groups 211.

At block 304, the group stability determining module 204 determines each of the one or more contingency groups 211 to be one of stable group and unstable group based on the instability index 212 computed for a bus selected from the one or more buses in the corresponding one or more contingency group 211.

At block 305, the group providing module 205, provides each of the one or more contingency groups 211 which are determined to be the unstable group to the stability analysis module 104 for the time-domain stability analysis of the electric grid 103.

Figure 4 illustrates a flowchart showing a method for grouping the one or more buses from the plurality of buses based on the sorting of the Z-thevenin value 213 of the plurality of buses in accordance with some embodiments of present disclosure.

At block 401, the buses grouping module 203 sorts the Z-thevenin value 213 of each of the plurality of buses in one of the descending order and the ascending order.

At block 402, the buses grouping module 203 determines difference of adjacent Z-thevenin values in the sorted Z-thevenin value 213 of the plurality of buses. Absolute value of the difference is determined.

At block 403, upon determining the difference, the buses grouping module 203 checks if each of the determined difference is lesser than the first predefined threshold value 214 If the difference is lesser than the first predefined threshold value, step in block 405 is performed. If the difference is greater than the first predefined threshold value, step in block 404 is performed.

At block 404, if the difference is determined to be greater than the first predefined threshold value 214, the buses grouping module 203 groups each of the plurality of buses associated with the difference independently.

At block 405, if the difference is determined to be lesser than the first predefined threshold value 214, the buses grouping module 203 groups the plurality of buses associated with the difference together.

Figure 5 illustrates a flowchart showing a method for grouping the one or more buses from the plurality of buses based on the adjacency of plurality of buses in accordance with some embodiments of present disclosure.

At block 501, the buses grouping module 203 determines difference of Z-thevenin value 213 for every first bus and second bus from the plurality of buses where the first bus and the second bus are identified to be adjacent to each other in the adjacency matrix 210. The absolute value of the difference is determined.

At block 502, the buses grouping module 203 checks if the determined difference is lesser than the first predefined threshold value 214. If the difference is greater than the first predefined threshold value 214, perform step in block 504 and if the difference is lesser than the first predefined threshold value 214, perform step in block 503.

At block 503, when the difference is determined to be greater than the first predefined threshold value 214, the first bus and the second bus are grouped independent to each other by the buses grouping module 203.

At block 504, when the difference is determined to be lesser than the first predefined threshold value 214, the first bus and the second bus are grouped together by the buses grouping module 203.

As illustrated in Figures 3, 4 and 5, the methods 300 and 303 may include one or more blocks for executing processes in the screening system 101. The methods 300 and 303 may be described in the general context of computer executable instructions. Generally, computer executable instructions can include routines, programs, objects, components, data structures, procedures, modules, and functions, which perform particular functions or implement particular abstract data types.
The order in which the methods 300 and 303 is described may not intended to be construed as a limitation, and any number of the described method blocks can be combined in any order to implement the method. Additionally, individual blocks may be deleted from the methods without departing from the scope of the subject matter described herein. Furthermore, the method can be implemented in any suitable hardware, software, firmware, or combination thereof.

Computing System

Figure 7 illustrates a block diagram of an exemplary computer system for implementing embodiments consistent with the present disclosure. In an embodiment, the computer system 700 is used to implement the screening system 101. The computer system 700 may include a central processing unit (“CPU” or “processor”) 702. The processor 702 may include at least one data processor for executing processes in the screening system 101. The processor 702 may include specialized processing units such as, integrated system (bus) controllers, memory management control units, floating point units, graphics processing units, digital signal processing units, etc. The processor 702 may be disposed in communication with one or more input/output (I/O) devices 709 and 710 via I/O interface 701. The I/O interface 701 may employ communication protocols/methods such as, without limitation, audio, analog, digital, monoaural, RCA, stereo, IEEE-1394, serial bus, universal serial bus (USB), infrared, PS/2, BNC, coaxial, component, composite, digital visual interface (DVI), high-definition multimedia interface (HDMI), RF antennas, S-Video, VGA, IEEE 802.n /b/g/n/x, Bluetooth, cellular (e.g., code-division multiple access (CDMA), high-speed packet access (HSPA+), global system for mobile communications (GSM), long-term evolution (LTE), WiMax, or the like), etc.

Using the I/O interface 701, the computer system 700 may communicate with one or more I/O devices 709 and 710. For example, the input devices 709 may be an antenna, keyboard, mouse, joystick, (infrared) remote control, camera, card reader, fax machine, dongle, biometric reader, microphone, touch screen, touchpad, trackball, stylus, scanner, storage device, transceiver, video device/source, etc. The output devices 710 may be a printer, fax machine, video display (e.g., cathode ray tube (CRT), liquid crystal display (LCD), light-emitting diode (LED), plasma, Plasma display panel (PDP), Organic light-emitting diode display (OLED) or the like), audio speaker, etc.

In some embodiments, the computer system 700 consists of a screening system 101. The processor 702 may be disposed in communication with the communication network 711 via a network interface 703. The network interface 703 may communicate with the communication network 711. The network interface 703 may employ connection protocols including, without limitation, direct connect, Ethernet (e.g., twisted pair 10/100/1000 Base T), transmission control protocol/internet protocol (TCP/IP), token ring, IEEE 802.11a/b/g/n/x, etc. The communication network 711 may include, without limitation, a direct interconnection, local area network (LAN), wide area network (WAN), wireless network (e.g., using Wireless Application Protocol), the Internet, etc. Using the network interface 703 and the communication network 711, the computer system 700 may communicate with an electric grid 712 and a stability analysis module 713 for screening contingencies in the electric grid 712. The network interface 703 may employ connection protocols include, but not limited to, direct connect, Ethernet (e.g., twisted pair 10/100/1000 Base T), transmission control protocol/internet protocol (TCP/IP), token ring, IEEE 802.11a/b/g/n/x, etc.

The communication network 711 includes, but is not limited to, a direct interconnection, an e-commerce network, a peer to peer (P2P) network, local area network (LAN), wide area network (WAN), wireless network (e.g., using Wireless Application Protocol), the Internet, Wi-Fi and such. The first network and the second network may either be a dedicated network or a shared network, which represents an association of the different types of networks that use a variety of protocols, for example, Hypertext Transfer Protocol (HTTP), Transmission Control Protocol/Internet Protocol (TCP/IP), Wireless Application Protocol (WAP), etc., to communicate with each other. Further, the first network and the second network may include a variety of network devices, including routers, bridges, servers, computing devices, storage devices, etc.

In some embodiments, the processor 702 may be disposed in communication with a memory 705 (e.g., RAM, ROM, etc. not shown in Figure 7) via a storage interface 704. The storage interface 704 may connect to memory 705 including, without limitation, memory drives, removable disc drives, etc., employing connection protocols such as, serial advanced technology attachment (SATA), Integrated Drive Electronics (IDE), IEEE-1394, Universal Serial Bus (USB), fibre channel, Small Computer Systems Interface (SCSI), etc. The memory drives may further include a drum, magnetic disc drive, magneto-optical drive, optical drive, Redundant Array of Independent Discs (RAID), solid-state memory devices, solid-state drives, etc.

The memory 705 may store a collection of program or database components, including, without limitation, user interface 706, an operating system 707 etc. In some embodiments, computer system 700 may store user/application data 706, such as, the data, variables, records, etc., as described in this disclosure. Such databases may be implemented as fault-tolerant, relational, scalable, secure databases such as Oracle or Sybase.

The operating system 707 may facilitate resource management and operation of the computer system 700. Examples of operating systems include, without limitation, Apple Macintosh OS X, Unix, Unix-like system distributions (e.g., Berkeley Software Distribution (BSD), FreeBSD, NetBSD, OpenBSD, etc.), Linux distributions (e.g., Red Hat, Ubuntu, Kubuntu, etc.), IBM OS/2, Microsoft Windows (XP, Vista/7/8, etc.), Apple iOS, Google Android, Blackberry OS, or the like.

Furthermore, one or more computer-readable storage media may be utilized in implementing embodiments consistent with the present disclosure. A computer-readable storage medium refers to any type of physical memory on which information or data readable by a processor may be stored. Thus, a computer-readable storage medium may store instructions for execution by one or more processors, including instructions for causing the processor(s) to perform steps or stages consistent with the embodiments described herein. The term “computer-readable medium” should be understood to include tangible items and exclude carrier waves and transient signals, i.e., be non-transitory. Examples include Random Access Memory (RAM), Read-Only Memory (ROM), volatile memory, non-volatile memory, hard drives, CD ROMs, DVDs, flash drives, disks, and any other known physical storage media.

An embodiment of the present disclosure provides a contingency screening method that improves computation speed with growing network size and increasing need for real time performance for time-domain stability analysis of an electric grid.
An embodiment of the present disclosure provisions an efficient simulation method for larger electric grid with complex network model.

An embodiment of the present disclosure provides robust performance with respect to changes in operating conditions in the electric grid by grouping the contingencies based on Z-thevenin values. By this, changes in operating conditions may be dynamically reflected in the screening system.

The described operations may be implemented as a method, system or article of manufacture using standard programming and/or engineering techniques to produce software, firmware, hardware, or any combination thereof. The described operations may be implemented as code maintained in a “non-transitory computer readable medium”, where a processor may read and execute the code from the computer readable medium. The processor is at least one of a microprocessor and a processor capable of processing and executing the queries. A non-transitory computer readable medium may include media such as magnetic storage medium (e.g., hard disk drives, floppy disks, tape, etc.), optical storage (CD-ROMs, DVDs, optical disks, etc.), volatile and non-volatile memory devices (e.g., EEPROMs, ROMs, PROMs, RAMs, DRAMs, SRAMs, Flash Memory, firmware, programmable logic, etc.), etc. Further, non-transitory computer-readable media may include all computer-readable media except for a transitory. The code implementing the described operations may further be implemented in hardware logic (e.g., an integrated circuit chip, Programmable Gate Array (PGA), Application Specific Integrated Circuit (ASIC), etc.).

Still further, the code implementing the described operations may be implemented in “transmission signals”, where transmission signals may propagate through space or through a transmission media, such as, an optical fibre, copper wire, etc. The transmission signals in which the code or logic is encoded may further comprise a wireless signal, satellite transmission, radio waves, infrared signals, Bluetooth, etc. The transmission signals in which the code or logic is encoded is capable of being transmitted by a transmitting station and received by a receiving station, where the code or logic encoded in the transmission signal may be decoded and stored in hardware or a non-transitory computer readable medium at the receiving and transmitting stations or devices. An “article of manufacture” includes non-transitory computer readable medium, hardware logic, and/or transmission signals in which code may be implemented. A device in which the code implementing the described embodiments of operations is encoded may include a computer readable medium or hardware logic. Of course, those skilled in the art will recognize that many modifications may be made to this configuration without departing from the scope of the invention, and that the article of manufacture may include suitable information bearing medium known in the art.

The terms “an embodiment”, “embodiment”, “embodiments”, “the embodiment”, “the embodiments”, “one or more embodiments”, “some embodiments”, and “one embodiment” mean “one or more (but not all) embodiments of the invention(s)” unless expressly specified otherwise.

The terms “including”, “comprising”, “having” and variations thereof mean “including but not limited to”, unless expressly specified otherwise.

The enumerated listing of items does not imply that any or all of the items are mutually exclusive, unless expressly specified otherwise.

The terms “a”, “an” and “the” mean “one or more”, unless expressly specified otherwise.

A description of an embodiment with several components in communication with each other does not imply that all such components are required. On the contrary a variety of optional components are described to illustrate the wide variety of possible embodiments of the invention.

When a single device or article is described herein, it will be readily apparent that more than one device/article (whether or not they cooperate) may be used in place of a single device/article. Similarly, where more than one device or article is described herein (whether or not they cooperate), it will be readily apparent that a single device/article may be used in place of the more than one device or article or a different number of devices/articles may be used instead of the shown number of devices or programs. The functionality and/or the features of a device may be alternatively embodied by one or more other devices which are not explicitly described as having such functionality/features. Thus, other embodiments of the invention need not include the device itself.

The illustrated operations of Figure 3, 4 and 5 show certain events occurring in a certain order. In alternative embodiments, certain operations may be performed in a different order, modified or removed. Moreover, steps may be added to the above described logic and still conform to the described embodiments. Further, operations described herein may occur sequentially or certain operations may be processed in parallel. Yet further, operations may be performed by a single processing unit or by distributed processing units.

Finally, the language used in the specification has been principally selected for readability and instructional purposes, and it may not have been selected to delineate or circumscribe the inventive subject matter. It is therefore intended that the scope of the invention be limited not by this detailed description, but rather by any claims that issue on an application based here on. Accordingly, the disclosure of the embodiments of the invention is intended to be illustrative, but not limiting, of the scope of the invention, which is set forth in the following claims.

While various aspects and embodiments have been disclosed herein, other aspects and embodiments will be apparent to those skilled in the art. The various aspects and embodiments disclosed herein are for purposes of illustration and are not intended to be limiting, with the true scope and spirit being indicated by the following claims.

Referral numerals:
Reference Number Description
100 Environment
101 Screening system
102 Communication network
103 Electric grid
104 Stability analysis module
105 Processor
106 I/O interface
107 Modules
108 Memory
201 Data obtaining module
202 Matrix generation module
203 Buses grouping module
204 Group stability determining module
205 Group providing module
206 Other modules
207 Data
208 Operation data
209 Contingency data
210 Adjacency matrix data
211 Contingency group data
212 Instability index data
213 Z-thevenin data
214 First predefined threshold value
215 Second predefined threshold value
216 Other data
600 Electric grid
601.1….601.5 Plurality of buses
700 Computer System
701 I/O Interface
702 Processor
703 Network Interface
704 Storage Interface
705 Memory
706 User Interface
707 Operating System
708 Web Server
709 Input Devices
710 Output Devices
711 Communication Network
712 Electric grid
713 Stability analysis module