CN117951626A - Power grid abnormal state detection method and system based on intelligent optimization algorithm - Google Patents
Power grid abnormal state detection method and system based on intelligent optimization algorithm Download PDFInfo
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Abstract
The invention belongs to the technical field related to power grid data processing, and discloses a power grid abnormal state detection method and system based on an intelligent optimization algorithm, which are used for solving the problems that in the existing algorithm, local optimization capability is weak, premature and local optimization is easy to occur, so that abnormal states of a power grid are inaccurate to detect and failure elements are difficult to accurately identify when the data is processed, judging a failure area according to action information, and forming the elements contained in the area into an unsafe database; according to the action protection principle, the expected states of the protection and the circuit breaker are determined, the objective function is set, the objective function is subjected to objective optimization based on an improved quadruple parameter second-order oscillation particle swarm optimization algorithm, and the element corresponding to the minimized objective function is obtained, so that the fault element is determined, the detection of the abnormal state of the power grid is completed, the local searching capability is higher, and the fault positioning is more accurate.
Description
Technical Field
The invention belongs to the technical field of power grid data processing, and particularly relates to a power grid abnormal state detection method and system based on an intelligent optimization algorithm.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
In the fault diagnosis process of the power system, the fault elements or the circuit breakers and the protection with false actions need to be identified by utilizing the action information between the circuit breakers and the protection, so that how to accurately identify the fault elements becomes a key problem in the field. Currently, the identification methods for the faulty components can be generally categorized into four main categories, namely: logic calculation method, expert system analysis method, artificial neural network processing method and algorithm-based optimization technique method.
With the development of the power grid system, the formed circuit topology structure and the generated power grid data become more and more huge, and technicians begin to process the abnormal power grid data by using the idea of algorithm optimization and search for fault elements. The existing algorithm optimization method is mainly widely applicable algorithms such as a genetic algorithm, a simulated annealing algorithm and the like, and the global optimizing capability of the algorithm is good, but when complex power grid data are processed, the local optimizing capability is obviously weak, the problem of premature and local optimization is easy to occur, inaccurate detection is caused when the data of abnormal power grid states are processed, and fault elements are difficult to accurately identify.
Disclosure of Invention
In order to overcome the defects in the prior art, the invention provides a power grid abnormal state detection method and system based on an intelligent optimization algorithm, which are used for judging a fault area according to action information and forming elements contained in the area into an unsafe database; according to the action protection principle, the expected states of the protection and the circuit breaker are determined, the objective function is set, the objective function is subjected to objective optimization based on an improved quadruple parameter second-order oscillation particle swarm optimization algorithm, and the element corresponding to the minimized objective function is obtained, so that the fault element is determined, the detection of the abnormal state of the power grid is completed, the local searching capability is higher, and the fault positioning is more accurate.
In order to achieve the above object, a first aspect of the present invention provides a method for detecting an abnormal state of a power grid based on an intelligent optimization algorithm, including:
And acquiring action information under the abnormal state of the power grid.
Sequentially numbering the information of the action, judging a fault area according to the action information, tentatively setting elements contained in the fault area as unsafe elements, and combining all unsafe elements to form an unsafe element library.
Determining expected states of the protection and the circuit breaker according to an action protection principle; and taking the error function between the actual state and the expected state of each protection and circuit breaker as a new objective function.
And optimizing the objective function based on an improved quadruple parameter second-order oscillation particle swarm optimization algorithm, converting the objective function into an objective function minimization problem, carrying out objective optimization by using the particle swarm, and acquiring an element corresponding to the minimized objective function, thereby determining a fault element and completing detection of an abnormal state of the power grid.
The second aspect of the invention provides a power grid abnormal state detection system based on an intelligent optimization algorithm, which comprises the following components:
A data reading module configured to: and acquiring action information under the abnormal state of the power grid.
An element storage module configured to: the method is used for sequentially numbering information of actions, judging a fault area according to the action information, tentatively setting elements contained in the fault area as unsafe elements, and combining all unsafe elements to form an unsafe element library.
A data processing module configured to: the method is used for determining expected states of each protection and the circuit breaker according to an action protection principle, optimizing an objective function based on an improved quadruple parameter second-order oscillation particle swarm optimization algorithm, converting the objective function into an objective function minimization problem, and carrying out objective optimization by using the particle swarm to obtain an element corresponding to the minimized objective function.
A third aspect of the present invention provides a computer apparatus comprising: the system comprises a processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor, when the computer device runs, the processor and the memory are communicated through the bus, and the machine-readable instructions are executed by the processor to execute steps in a power grid abnormal state detection method based on an intelligent optimization algorithm.
A fourth aspect of the present invention provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs steps in a method for detecting abnormal states of a power grid based on an intelligent optimization algorithm.
The one or more of the above technical solutions have the following beneficial effects:
The invention judges the fault area according to the action information and composes the elements contained in the area into an unsafe database; according to the action protection principle, the expected states of the protection and the circuit breaker are determined, the objective function is set, the objective function is subjected to objective optimization based on an improved quadruple parameter second-order oscillation particle swarm optimization algorithm, and the element corresponding to the minimized objective function is obtained, so that the fault element is determined, the detection of the abnormal state of the power grid is completed, the local searching capability is higher, and the fault positioning is more accurate.
Additional aspects of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the invention.
Fig. 1 is a flowchart of obtaining error functions of actual states and expected states of protection and circuit breakers in accordance with a first embodiment of the present invention.
FIG. 2 is a flowchart of a quad-parametric second-order Oscillating particle swarm optimization algorithm according to an embodiment of the present invention.
Detailed Description
It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the invention. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the present invention.
Embodiments of the invention and features of the embodiments may be combined with each other without conflict.
Example 1
As shown in fig. 1 and fig. 2, the embodiment discloses a power grid abnormal state detection method based on an intelligent optimization algorithm, which includes the following steps:
Step one: and acquiring action information under the abnormal state of the power grid, wherein the action information comprises action protection state and breaker switch gate information.
Step two: the method comprises the steps of sequentially numbering information of actions and judging fault areas, and searching elements which possibly have faults from the fault areas, wherein the elements can be resistors, circuit breakers, protection, buses, bypass lines and the like, all unsafe elements are combined into an unsafe element library, and the specific process is realized through steps S2-1 to S2-3.
Step S2-1, analyzing the acquired action information: the information that can cause the action protection is ordered and numbered sequentially from the numeral 1.
S2-2, analyzing the action ranges protected by the protection devices with the protection actions, marking the elements in the protected ranges as unsafe elements, and forming an independent element library by the unsafe elements in the same protection range.
S2-3, observing the number of independent element libraries, and if the number is 1, the independent element libraries are the final unsafe element libraries; if the number of independent component libraries is two or more, then all independent component libraries will be consolidated to obtain the final unsecure component library, i.e., the unsecure component library contains all unsecure components.
Step three: after the unsafe element library is synthesized, the expected states of the protection and the circuit breaker are determined according to the action protection principle, and the method specifically comprises the following steps:
Firstly, determining the expected states of protection, namely comprehensively considering the protection actions of the protection device on the elements, dividing the protection into three protection types, namely main protection, near backup protection and far backup protection, and calculating the expected states corresponding to the three types of protection according to the following three formulas respectively.
Wherein,Logical AND and logical OR operators, respectively,/>Representing the i-th element,/>Representing element/>Main protection of/>Respectively represent element/>The desired state of the primary protection, the near backup protection, and the far backup protection,Representing the state of the xth element protected by near-backing protection,/> Representing the state of the corresponding associated path.
The actual state of the protection action is then formed into a logical or operation to determine the desired state of the circuit breaker, as shown in the following equation:
Wherein, Representing the actual state of the xth protection,/>Representing the state of the i-th element; thus, the desired state of both the protection and the circuit breaker has been determined; s represents the state of the elements within the system and P represents the actual state of protection.
Step four: in order to accurately obtain the difference between the actual state and the expected state of each protection and the breaker, an error function between the actual state and the expected state of each protection and the breaker is taken as a new objective function F, namely:
Wherein, Respectively representing the total number of circuit breakers and protections, S representing the state of elements in the system, P representing the actual state of protection,/>, respectivelyRespectively represent the actual state and the expected state of the xth circuit breaker,/>Representing the actual state and the expected state of the y-th protection, respectively.
Step five: the method comprises the steps of optimizing an objective function based on an improved quadruple parameter second-order oscillation particle swarm optimization algorithm, converting the objective function into an objective function minimization problem, carrying out objective optimization by using a particle swarm, and obtaining an element corresponding to the minimized objective function, thereby determining a fault element, and completing detection of an abnormal state of a power grid, wherein the specific process is realized through steps S5-1 to S5-3.
Step S5-1, randomly generating a first group of initial solutions as an initial particle population, wherein the number of the initial solutions is consistent with the number of unsafe elements, and each randomly generated initial solution is 0 or 1.
Step S5-2, an initialization operation is executed on the particle swarm, and the specific steps are as follows:
Step S5-2-1, setting the initial speed of each particle individual as any random value between [ -5,5 ];
Step S5-2-2, setting particle swarm inertia factor Learning factor/>；
Step S5-2-2, setting the maximum iteration number of algorithm iteration。
Step S5-3, using the objective function F in the step four as the fitness function of the quadruple parameter second-order oscillation particle swarm algorithm, and starting an iterative optimization process, wherein the specific steps are as follows:
And step S5-3-1, calculating the fitness value of the particles in the initial particle population.
Step S5-3-2, updating the position and the speed of the particles, wherein the position and the speed of the particles are updated according to the formula:
Wherein, Indicating that the jth particle is at the/>The position at the time of the iteration; /(I)Indicating that the jth particle is at the/>Speed at iteration,/>Is an inertial factor,/>As learning factor,/>Is a random parameter in the [0,1] interval,/>Representing the individual optimal solution of the jth particle,/>Then a globally optimal solution is represented.
S5-3-3, marking the optimal position of each particle individual in the current iteration as the current individual optimal value, comparing the fitness values corresponding to the optimal position and the current individual fitness value, and updating the individual optimal value when the current individual fitness value is lower than the original individual fitness value, otherwise, not updating the individual optimal value; similarly, the new individual optimal value is compared with the fitness value of the optimal position of the global experience, and if the fitness value of the new individual optimal value is better, the global optimal value is updated, otherwise, the fitness value of the optimal position of the global experience is not updated.
And step S5-3-4, judging whether the current iteration reaches the maximum iteration times or not when each iteration is completed. If the maximum iteration number is not reached, continuing to execute the step S5-3-3; if the maximum iteration times are reached, the iteration optimizing is deduced, and an optimal value set is output; the failed component is determined from the optimal set of values.
Example two
The embodiment discloses a power grid abnormal state detecting system based on intelligent optimization algorithm, which comprises:
a data reading module configured to: and the method is used for acquiring the action information under the abnormal state of the power grid.
An element storage module configured to: the method is used for sequentially numbering information of actions, judging a fault area according to the action information, tentatively setting elements contained in the fault area as unsafe elements, and combining all unsafe elements to form an unsafe element library.
A data processing module configured to: the method is used for determining expected states of each protection and the circuit breaker according to an action protection principle, optimizing an objective function F based on an improved quadruple parameter second-order oscillation particle swarm optimization algorithm, converting the objective function F into an objective function minimization problem, carrying out objective optimization by using a particle swarm, and acquiring an element corresponding to the minimized objective function, thereby determining a fault element and completing detection of an abnormal state of a power grid.
Example III
The present embodiment provides a computer device including: the system comprises a processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor, when the computer device runs, the processor and the memory are communicated through the bus, and the machine-readable instructions are executed by the processor to execute the steps in the power grid abnormal state detection method based on the intelligent optimization algorithm in the embodiment 1 of the disclosure.
Example IV
The present embodiment provides a computer readable storage medium, on which a computer program is stored, where the computer program when executed by a processor performs the steps in a method for detecting an abnormal state of a power grid based on an intelligent optimization algorithm described in embodiment 1 of the present disclosure.
The steps involved in the devices of the second, third and fourth embodiments correspond to those of the first embodiment of the method, and the detailed description of the embodiments can be found in the related description section of the first embodiment. The term "computer-readable storage medium" should be taken to include a single medium or multiple media including one or more sets of instructions; it should also be understood to include any medium capable of storing, encoding or carrying a set of instructions for execution by a processor and that cause the processor to perform any one of the methods of the present invention.
It will be appreciated by those skilled in the art that the modules or steps of the invention described above may be implemented by general-purpose computer means, alternatively they may be implemented by program code executable by computing means, whereby they may be stored in storage means for execution by computing means, or they may be made into individual integrated circuit modules separately, or a plurality of modules or steps in them may be made into a single integrated circuit module. The present invention is not limited to any specific combination of hardware and software.
While the foregoing description of the embodiments of the present invention has been presented in conjunction with the drawings, it should be understood that it is not intended to limit the scope of the invention, but rather, it is intended to cover all modifications or variations within the scope of the invention as defined by the claims of the present invention.
Claims (10)
1. The utility model provides a power grid abnormal state detection method based on intelligent optimization algorithm, which is characterized by comprising the following steps:
acquiring action information under an abnormal state of a power grid;
Sequentially numbering information of actions, judging a fault area according to the action information, tentatively setting elements contained in the fault area as unsafe elements, and combining all unsafe elements to form an unsafe element library;
Determining expected states of the protection and the circuit breaker according to an action protection principle; taking error functions between the actual state and the expected state of each protection and circuit breaker as new objective functions;
And optimizing the objective function based on an improved quadruple parameter second-order oscillation particle swarm optimization algorithm, converting the objective function into an objective function minimization problem, carrying out objective optimization by using the particle swarm, and acquiring an element corresponding to the minimized objective function, thereby determining a fault element and completing detection of an abnormal state of the power grid.
2. The method for detecting abnormal state of power grid based on intelligent optimization algorithm as set forth in claim 1, wherein the action information includes action protection state and breaker switch gate information.
3. The method for detecting abnormal states of a power grid based on an intelligent optimization algorithm as set forth in claim 1, wherein the protection includes a main protection, a near backup protection and a far backup protection, and for an ith element, the expected states of the various types of protection of the element are respectively expressed as:
Wherein, Logical AND and logical OR operators, respectively,/>Representing the i-th element,/>Representing element/>Main protection of/>Respectively represent element/>Is the desired state of the primary protection, near backup protection, and far backup protection,/>Representing the state of the xth element protected by near-backing protection,/>Representing the state of the corresponding associated path.
4. The method for detecting abnormal state of power grid based on intelligent optimization algorithm as set forth in claim 1, wherein the expected state of the circuit breaker is expressed as:
Wherein, Representing a logical OR operator,/>Representing the actual state of the xth protection,/>Representing the state of the i-th element; s represents the state of the elements within the system and P represents the actual state of protection.
5. The method for detecting abnormal states of a power grid based on an intelligent optimization algorithm according to claim 1, wherein the objective function represents a difference relation between actual states and expected states of each protection and circuit breaker, specifically:
Wherein, Respectively representing the total number of circuit breakers and protections, S representing the state of elements in the system, P representing the actual state of protection,/>, respectivelyRespectively represent the actual state and the expected state of the xth circuit breaker,/>Representing the actual state and the expected state of the y-th protection, respectively.
6. The method for detecting abnormal states of a power grid based on an intelligent optimization algorithm as set forth in claim 1, wherein the improved position and speed update formula of the quad-parameter second-order oscillating particle swarm optimization algorithm is as follows:
Wherein, Indicating that the jth particle is at the/>The position at the time of the iteration; /(I)Indicating that the jth particle is at the jthSpeed at iteration,/>Is an inertial factor,/>As learning factor,/>Is a random parameter in the [0,1] interval,/>Representing an individual optimal solution for the jth particle; /(I)Then a globally optimal solution is represented.
7. The method for detecting abnormal state of power grid based on intelligent optimization algorithm as claimed in claim 1, wherein the specific implementation steps of using particle swarm for target optimization are as follows:
S1: randomly generating a set of initial solutions as an initial particle population;
S2: initializing a particle swarm and setting the maximum iteration times of the particle swarm;
s3: starting an iterative optimization process based on a quadruple parameter second-order oscillation particle swarm algorithm; updating the particle speed and the particle position in the process; and judging whether the maximum iteration times are reached or not after each iteration is completed, stopping iteration when the maximum iteration times are reached, and outputting an optimal set.
8. An abnormal state detection system of a power grid based on an intelligent optimization algorithm is characterized by comprising the following components:
a data reading module configured to: the method is used for acquiring action information under the abnormal state of the power grid;
An element storage module configured to: the method comprises the steps of sequentially numbering information of actions, judging a fault area according to the action information, tentatively setting elements contained in the fault area as unsafe elements, and combining all unsafe elements to form an unsafe element library;
A data processing module configured to: the method is used for determining expected states of each protection and the circuit breaker according to an action protection principle, optimizing an objective function based on an improved quadruple parameter second-order oscillation particle swarm optimization algorithm, converting the objective function into an objective function minimization problem, carrying out objective optimization by using a particle swarm, and acquiring an element corresponding to the minimized objective function, thereby determining a fault element and completing detection of an abnormal state of a power grid.
9. A computer device, comprising: a processor, a memory and a bus, said memory storing machine readable instructions executable by said processor, said processor and said memory communicating via the bus when the computer device is running, said machine readable instructions when executed by said processor performing the steps of a method for detecting an abnormal state of a power grid based on an intelligent optimization algorithm as claimed in any one of claims 1 to 7.
10. A computer readable storage medium, characterized in that the computer readable storage medium has stored thereon a computer program which, when executed by a processor, performs the steps of a method for detecting abnormal states of a power grid based on an intelligent optimization algorithm according to any one of claims 1 to 7.
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