CN115986849B - Primary frequency modulation self-optimization control method and system - Google Patents
Primary frequency modulation self-optimization control method and system Download PDFInfo
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Abstract
The application provides a primary frequency modulation self-optimization control method and a system, which relate to the technical field of intelligent control, wherein the method comprises the following steps: the method comprises the steps of collecting signals of a plurality of signal output sources of an external generator set of a target power grid, analyzing the signal set of the external generator set to obtain a plurality of variable indexes, analyzing the stability of the power grid of an original running signal set of the target power grid, taking a first stability index as an optimization target, taking a plurality of variable indexes as input variables, building a self-adaptive optimization model, obtaining frequency modulation optimization parameters, and inputting the frequency modulation optimization parameters into a frequency modulation control system for control.
Description
Technical Field
The application relates to the technical field of intelligent control, in particular to a primary frequency modulation self-optimizing control method and system.
Background
The external power supply of the current power grid is continuously increased, clean energy sources such as photovoltaic power generation and wind power generation are connected to the power grid in a large scale, the following problems are more and more prominent, and the external power supply and the clean energy source power generation have no good regulation capability, so that the requirement on the frequency regulation capability of an operation unit is higher, and the situation of large-scale power loss is particularly important.
The machine set in the prior art does not have good adjusting capability, so that the final machine set has low peak regulation and frequency modulation capability.
Disclosure of Invention
The application provides a primary frequency modulation self-optimization control method, which is used for solving the technical problems that a unit in the prior art does not have good adjusting capability and the final unit has low peak and frequency modulation capability.
In view of the above problems, the present application provides a primary frequency modulation self-optimization control method and system.
In a first aspect, the present application provides a primary frequency modulation self-optimization control method, where the method includes: obtaining an external generator set of a target power grid; signal acquisition is carried out on a plurality of signal output sources of the external generator set to obtain an external generator set signal set; the method comprises the steps of analyzing a signal set of an external generator set to obtain a plurality of variable indexes, wherein the variable indexes are indexes which influence the operation stability of the target power grid by the external generator set; acquiring an original running signal set of the target power grid; carrying out power grid stability analysis according to the original running signal set to obtain a first stability index; setting up a self-adaptive optimization model by taking the first stability index as an optimization target and taking the variable indexes as input variables; and acquiring frequency modulation optimization parameters according to the self-adaptive optimization model, and inputting the frequency modulation optimization parameters into the frequency modulation control system for control.
In a second aspect, the present application provides a primary frequency modulation self-optimizing control system, the system comprising: one or more technical schemes provided by the application have at least the following technical effects or advantages: the external connection module is used for obtaining an external connection generator set of the target power grid; the signal acquisition module is used for acquiring signals of a plurality of signal output sources of the external generator set to obtain an external generator set signal set; the analysis module is used for obtaining a plurality of variable indexes by analyzing the signal set of the external generator set, wherein the variable indexes are indexes which influence the operation stability of the target power grid by the external generator set; the original running signal set acquisition module is used for acquiring an original running signal set of the target power grid; the power grid stability analysis module is used for carrying out power grid stability analysis according to the original running signal set to obtain a first stability index; the building module is used for building a self-adaptive optimization model by taking the first stability index as an optimization target and the variable indexes as input variables; and the control module is used for acquiring frequency modulation optimization parameters according to the self-adaptive optimization model, and inputting the frequency modulation optimization parameters into the frequency modulation control system for control.
In a third aspect, a computer device comprises a memory storing a computer program and a processor implementing the following steps when executing the computer program: acquiring data information of a plurality of structures controlled by an air extraction regulating valve, wherein the data information comprises one type of data information and two types of data information; acquiring valve adjustable drop information of a target air extraction regulating valve to obtain a valve opening-dropping ratio; inputting the valve opening-closing ratio into a pre-constructed circulation detection standard database to obtain the structural parameter standard of each structure; based on the structural parameter standard of each structure, performing control optimization on the air extraction regulating valve on the data information of the plurality of structures to obtain a plurality of structural control optimization parameters; constructing an air extraction regulating valve control optimization model; and inputting the plurality of structural control optimization parameters into the air extraction regulating valve control optimization model to obtain a control optimization result.
In a fourth aspect, a computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of: acquiring data information of a plurality of structures controlled by an air extraction regulating valve, wherein the data information comprises one type of data information and two types of data information; acquiring valve adjustable drop information of a target air extraction regulating valve to obtain a valve opening-dropping ratio; inputting the valve opening-closing ratio into a pre-constructed circulation detection standard database to obtain the structural parameter standard of each structure; based on the structural parameter standard of each structure, performing control optimization on the air extraction regulating valve on the data information of the plurality of structures to obtain a plurality of structural control optimization parameters; constructing an air extraction regulating valve control optimization model; and inputting the plurality of structural control optimization parameters into the air extraction regulating valve control optimization model to obtain a control optimization result.
The application provides a primary frequency modulation self-optimizing control method, a system, computer equipment and a storage medium, relates to the technical field of intelligent control, solves the technical problem that a unit does not have good adjusting capability in the prior art, so that the final unit peak-shaving and frequency-modulating capability is low, realizes self-optimizing control of the whole primary frequency modulation process, and ensures that the load of the unit has good frequency-modulating capability.
Drawings
FIG. 1 is a schematic flow chart of a primary frequency modulation self-optimizing control method;
FIG. 2 is a schematic flow chart of obtaining a plurality of variable indexes in a primary frequency modulation self-optimization control method;
FIG. 3 is a schematic flow chart of an activated adaptive optimization model in a primary frequency modulation self-optimization control method;
fig. 4 is a schematic structural diagram of a primary frequency modulation self-optimizing control system.
Fig. 5 is an internal structural diagram of a computer device in one embodiment.
Reference numerals illustrate: the system comprises an external module 1, a signal acquisition module 2, an analysis module 3, an original running signal set acquisition module 4, a power grid stability analysis module 5, a building module 6 and a control module 7.
Detailed Description
The application provides a primary frequency modulation self-optimization control method, which is used for solving the technical problem that a unit in the prior art does not have good adjustment capability, so that the final unit has low peak regulation and frequency modulation capability.
Example 1
As shown in fig. 1, an embodiment of the present application provides a primary frequency modulation self-optimization control method, where the method is applied to a power grid optimization management system, and the power grid optimization management system is in communication connection with the frequency modulation control system, and the method includes:
step S100: obtaining an external generator set of a target power grid;
specifically, the primary frequency modulation self-optimization control method provided by the embodiment of the application is applied to a power grid optimization management system, wherein the power grid optimization management system is in communication connection with a frequency modulation control system, and the frequency modulation control system is used for performing frequency modulation control on an operation unit.
Because the external power of the target power grid is continuously increased, clean energy sources such as photovoltaic power generation, wind power generation and the like are connected into the power grid in a large scale, the energy sources need to be subjected to frequency modulation control by a frequency modulation control system, the external power of the energy sources is the power obtained by power generation of an external power generating set of the target power grid, meanwhile, the external power generating set of the target power grid can be a thermal power generating set, the thermal power generating set is a set which takes coal, oil, combustible gas and the like as fuels, heats water in a boiler to increase the temperature, and steam with certain pressure is used for pushing a gas turbine to generate power, so that the frequency modulation control is realized as an important reference basis for the later period.
Step S200: signal acquisition is carried out on a plurality of signal output sources of the external generator set to obtain an external generator set signal set;
specifically, the primary frequency modulation is that the external generator set generates a signal source through fluctuation of the frequency of a target power grid, the load command is triggered to change to complete the increase or decrease of active power, the change of electric quantity at the user side is met, and therefore the stability of the frequency of the target power grid is maintained, wherein the frequency of the target power grid is determined by the generated power and the user load, when the generated power is larger than the user load, the frequency of the target power grid is increased, otherwise, the frequency of the power grid is decreased, a plurality of signal output sources of the external generator set are obtained according to the fluctuation of the frequency of the target power grid, meanwhile, the plurality of signal output sources of the external generator set are respectively collected, summarized and integrated according to the signal collection device, and all collected signals of the external generator set are recorded as an external generator set signal set on the basis, so that frequency modulation control is guaranteed.
Step S300: the method comprises the steps of analyzing a signal set of an external generator set to obtain a plurality of variable indexes, wherein the variable indexes are indexes which influence the operation stability of the target power grid by the external generator set;
specifically, on the basis of the obtained external unit signal set, the operation stability analysis result of the external unit signal set is in one-to-one correspondence with a plurality of signal output sources in the external unit, the obtained operation stability analysis result is further judged to obtain an identification signal output source which is greater than or equal to a preset association coefficient, wherein the obtained preset association coefficient is preset by a relevant technician according to the power grid operation stability and the plurality of signal output sources in the external unit, and further, the characteristic analysis is performed on the corresponding identification unit signal set in the identification signal output source to obtain a plurality of variable indexes, wherein the plurality of variable indexes are indexes of the external generator set influencing the operation stability of the target power grid and can comprise direct related variables such as main steam pressure, steam extraction flow, valve flow characteristics and the like and primary frequency modulation performance, and the frequency modulation control tamping basis is realized subsequently.
Step S400: acquiring an original running signal set of the target power grid;
specifically, for better optimization of the target power grid, an original running signal set of the target power grid is obtained according to a power grid optimization management system, after the target power grid is connected with an external generator set, load fluctuation influence caused to the target power grid is different due to different power, types and kinds of the external generator set, the original running signal set of the target power grid refers to signal data initially running in the target power grid before the target power grid is connected with the external generator set, and meanwhile the obtained signal data are summarized and arranged, so that the original running signal set of the target power grid is obtained for later frequency modulation control.
Step S500: carrying out power grid stability analysis according to the original running signal set to obtain a first stability index;
specifically, based on the original running signal set, the stability of the power grid is analyzed on the original running signal set in the target power grid, namely, the running stability of the target power grid when the current target power grid is not connected with an external unit is the stable running state of the power grid, namely, the electric power transmitted by the synchronous generator in the power system is a fixed value under the synchronous running state, meanwhile, the voltage of each node in the power system and the power flow of the branch are also fixed values, and if the synchronization cannot be ensured, the power grid loses the stable state. If the stability of the power grid is analyzed, the stability of the power grid mainly comprises the static stability of the power grid, the transient stability of the power grid and the dynamic stability of the power grid, so that the state that the power grid is kept relatively stable for a certain time is recorded as a first stability index, and the method has a propelling effect on realizing frequency modulation control.
Step S600: setting up a self-adaptive optimization model by taking the first stability index as an optimization target and taking the variable indexes as input variables;
specifically, a first stability index of a power grid, which is kept in a relatively stable state within a certain time, is taken as a final target for optimizing the power grid, a plurality of variable indexes obtained by analyzing an external generator set signal set are taken as input variables, an adaptive optimization model is built, firstly, an original frequency modulation parameter of the target power grid is obtained and taken as a regulating variable, a stability index difference is taken as a response target, the variable indexes are taken as input variables, a corresponding objective function is generated, the building of the adaptive optimization model is completed on the basis, a real-time operation signal set after the target power grid is connected with the external generator set is obtained, the power grid stability analysis is carried out according to the real-time operation signal set, the relatively stable state of the power grid is compared with the real-time operation stability state after the target power grid is connected with the external generator set, so that an activation instruction of the adaptive optimization model is generated according to the comparison result of the two, the built adaptive optimization model is further activated according to the model activation instruction, and the deep influence on the post-stage implementation control is achieved.
Step S700: and acquiring frequency modulation optimization parameters according to the self-adaptive optimization model, and inputting the frequency modulation optimization parameters into the frequency modulation control system for control.
Specifically, after the built self-adaptive optimization model is activated, load fluctuation influence is caused to a target power grid in the self-adaptive optimization model due to power, model, type and possible change of the external motor, accurate and adaptive frequency modulation is guaranteed according to the requirement of the target power grid, corresponding frequency modulation optimization parameters are obtained from the activated self-adaptive optimization model on the basis, the obtained frequency modulation optimization parameters are input into a frequency modulation control system in communication connection with a power grid optimization management system, frequency modulation control is carried out on the frequency modulation control system, and finally frequency modulation control is better realized according to the frequency modulation optimization parameters.
Further, as shown in fig. 2, step S300 of the present application further includes:
step S310: carrying out power grid operation stability analysis according to the external unit signal set to obtain a plurality of association coefficients, wherein the plurality of association coefficients are in one-to-one correspondence with the plurality of signal output sources;
step S320: judging according to the plurality of association coefficients to obtain an identification signal output source which is larger than or equal to a preset association coefficient;
step S330: and carrying out feature analysis on the identification unit signal set corresponding to the identification signal output source to obtain the variable indexes.
Specifically, grid operation stability analysis is performed on an external unit signal set sent by an external unit connected with a target power grid, the grid operation stability analysis is performed on a basis of whether the obtained multiple correlation coefficients are greater than or equal to preset correlation coefficients or not, and operation stability of the target power grid is different due to the fact that the influence factors of the analysis operation stability can be different in power, model, type and the like of an external generator, so that multiple correlation coefficients are obtained, the multiple correlation coefficients and the multiple signal output sources in the external generator are in one-to-one correspondence, further, the obtained multiple correlation coefficients are judged, whether the obtained multiple correlation coefficients are greater than or equal to the preset correlation coefficients or not is judged, wherein the obtained preset correlation coefficients are preset by a relevant technician according to the grid operation stability and the multiple signal output sources in the external unit, if the multiple correlation coefficients are greater than or equal to the preset correlation coefficients, the multiple correlation coefficients are obtained, the signal output sources corresponding to the preset correlation coefficients are marked, and further, the characteristics of different main steam pressure, extraction flow and valve flow and the like are carried out on the basis of the marked signal set corresponding to the marked signal output sources, and the important control parameters are analyzed, and the important control effect is achieved.
Further, as shown in fig. 3, step S600 of the present application further includes:
step S610: acquiring a real-time operation signal set of the target power grid after the target power grid is connected with the external generator set;
step S620: carrying out power grid stability analysis according to the real-time operation signal set to obtain a second stability index;
step S630: and generating a model activation instruction by comparing the first stability index with the second stability index, and activating the self-adaptive optimization model according to the model activation instruction.
Specifically, the purpose of frequency modulation self-optimization is based on the signal required to be acquired in the primary frequency modulation prior art, the fluctuation signal under the load condition is controlled, because the external generator is changed according to the power, the model and the type of the generator, the real-time operation signal after the target power grid is connected with the external generator set is required to be acquired in real time, the acquired real-time operation signal set is further subjected to power grid stability analysis, the power grid stability mainly comprises static stability of the power grid, transient stability of the power grid and dynamic stability of the power grid, after the target power grid is accessed to the external generator set, the state that the target power grid is accessed to the external generator set and kept relatively stable for a certain time is recorded as a second stability index, the first stability index obtained by carrying out power grid stability analysis according to the original operation signal set is compared with the second stability index obtained above, meanwhile, whether the stability index difference after the difference is in the preset stability index difference is judged, if the stability index difference is not in the preset stability index difference, a model activation instruction is correspondingly generated, and then the generated model activation instruction is used for self-adaptive optimization is carried out, and the high-efficiency frequency modulation is ensured when the adaptive optimization is controlled.
Further, step S630 of the present application includes:
step S631: acquiring a stability index difference between the first stability index and the second stability index;
step S632: judging whether the stable index difference is in a preset stable index difference or not;
step S633: and if the stable index difference is not in the preset stable index difference, activating the self-adaptive optimization model.
Specifically, after the target power grid is connected with the external power generator set, the stability of the whole system is reduced, so that the first stability index obtained by carrying out power grid stability analysis on the original running signal set and the second stability index obtained by carrying out power grid stability analysis on the real-time running signal set are required to be subjected to difference making, whether the difference made stability index is in a preset stability index difference or not is judged, the preset stability index difference refers to modeling the target power grid and the external power generator set respectively, model fitting is carried out on the modeled two sets, a simulation running signal set is extracted from a model fitting result, the simulation running signal set and the real-time running signal set are further analyzed, if the stability index difference is in the preset stability index difference, the difference between the current simulation running signal set and the real-time running signal set is regarded as small, the optimization space is small, and therefore, if the stability index difference is not in the preset stability index difference, a model activating instruction is correspondingly generated, the self-adaptive optimization model is activated by the generated, and finally the technical effect of providing reference for frequency regulation is achieved.
Further, step S633 of the present application includes:
step S6331: acquiring an original frequency modulation parameter of the target power grid;
step S6332: taking the stable index difference as a response target, taking the original frequency modulation parameter as an adjusting variable, and taking the variable indexes as input variables to generate an objective function;
step S6333: and generating the self-adaptive optimization model based on the objective function.
Specifically, the original frequency modulation parameters of the target power grid before being connected with the external generator set are obtained, the original frequency modulation parameters can be electrical parameters of relevant main elements in the target power grid, such as capacity, voltage, reactance and the like of a generator, a transformer, a circuit and the like, meanwhile, the target power grid is not stable enough after being connected with the external generator, the original frequency modulation parameters need to be optimized in order to enable the target power grid to reach stability, therefore, the obtained stable index difference is taken as a response target, the original frequency modulation parameters of the obtained target power grid are taken as an adjusting variable, a plurality of variable indexes obtained by analyzing a signal set of the external generator set are taken as input variables, an objective function is correspondingly generated on the basis, further, the construction of the adaptive optimization model is completed according to the objective function, the objective function is the pursued objective form expressed by the design variable, the objective function is the function of the design variable, the objective function is a scalar, and meanwhile, the objective function can be the performance standard of the system, namely the reference standard inside the adaptive optimization model, and finally the technical effect of frequency modulation control is achieved.
Further, step S632 of the present application includes:
step S6321: modeling the target power grid to obtain an original power grid model;
step S6322: modeling the external generator set to obtain an external generator set model;
step S6323: performing model fitting on the original power grid model and the external unit model to obtain a model fitting result;
step S6324: obtaining a simulation running signal set according to the model fitting result;
step S6325: and analyzing the simulation operation signal set and the real-time operation signal set to obtain the preset stability index difference.
In particular, the modeling is carried out on the target power grid and the external generator set of the target power grid respectively, the modeling refers to the implementation of optimal control on the system, the key or premise of designing a controller or an optimal control law by using a control theory is that a mathematical model capable of representing the characteristics of the system is provided, based on modeling, obtaining an original power grid model corresponding to a target power grid and an external generator set model corresponding to an external generator set according to methods such as a maximum principle, dynamic programming, feedback, decoupling, pole allocation, self-organization, self-adaption, intelligent control and the like, the main activities in the modeling process include determining data and its related processes, defining data (such as data type, size and default values), ensuring the integrity of the data (using business rules and validation checks), defining operational processes (such as security checks and backups), selecting data storage techniques (such as relational, hierarchical or index storage techniques), further fitting the obtained raw grid model to the obtained external unit model, namely a series of points of the original power grid model and the external unit model on a plane are connected by a smooth curve, thereby obtaining model fitting results of the two models, extracting a simulation running signal set in the model fitting results on the basis, analyzing the extracted simulation running signal set and the current real-time running signal set, i.e., find the magnitude of the difference between the analog running signal set and the real-time running signal set, to see the optimization space existing on the basis of the difference value, and obtaining a model fitting result according to the optimization space correspondence, so as to achieve the technical effect of providing reference for frequency modulation control.
Further, step S6325 of the present application includes:
step S63251: performing frequency out-of-limit node identification on the real-time operation signal set to obtain a plurality of identification nodes;
step S63252: performing interval integration according to the plurality of identification nodes to obtain a plurality of real-time integrated electric quantities;
step S63253: performing frequency out-of-limit node identification on the simulation running signal set to obtain a plurality of simulation identification nodes;
step S63254: performing interval integration according to the plurality of analog identification nodes to obtain a plurality of analog integrated electric quantities;
step S63255: and obtaining the preset stable index difference according to the ratio coefficient of the real-time integrated electric quantity to the analog integrated electric quantity.
Specifically, the frequency limit exceeding node identification is firstly performed on the real-time operation signal set, the frequency limit exceeding node can be set in the first 15s time period after the frequency limit exceeding, so that a plurality of real-time identification nodes are obtained, meanwhile, interval integration is performed on the obtained plurality of real-time identification nodes, the interval integration is a mark representing a partition interval or only represents an independent quantity (differential form), so that a plurality of real-time integration electric quantity is obtained, the plurality of real-time integration electric quantity refers to a signal with the frequency limit exceeding in the real-time identification nodes, the generated electric quantity is unstable, the frequency limit exceeding node identification is further performed on the analog operation signal set, the frequency limit exceeding node can be set in the first 15s time period after the frequency limit exceeding, so that a plurality of analog identification nodes are obtained, meanwhile, the obtained plurality of analog identification nodes are integrated in intervals, namely the frequency limit exceeding signal in the analog identification nodes, the generated electric quantity is unstable, the ratio coefficient of the plurality of real-time integration occupying the plurality of analog integration is calculated, namely the plurality of real-time integration electric quantity is divided by the analog integration, the ratio coefficient is calculated, and the ratio of the plurality of real-time integration electric quantity is calculated, and the ratio is more than the analog integral electric quantity is calculated to be more stable when the frequency modulation space is required to be the optimal, and the residual space is more than the space is optimized, and the residual space is required to be the space-optimized, and the residual space is more stable, and the space is the space-stable is controlled.
Example two
Based on the same inventive concept as the primary frequency modulation self-optimization control method in the foregoing embodiment, as shown in fig. 4, the present application provides a primary frequency modulation self-optimization control system, which includes:
the external connection module 1 is used for acquiring an external connection generator set of a target power grid;
the signal acquisition module 2 is used for acquiring signals of a plurality of signal output sources of the external generator set to obtain an external generator set signal set;
the analysis module 3 is used for obtaining a plurality of variable indexes by analyzing the external generator set signal set, wherein the variable indexes are indexes which influence the external generator set on the running stability of the target power grid;
the original running signal set acquisition module 4 is used for acquiring an original running signal set of the target power grid;
the power grid stability analysis module 5 is used for carrying out power grid stability analysis according to the original running signal set to obtain a first stability index;
the building module 6 is used for building a self-adaptive optimization model by taking the first stability index as an optimization target and the variable indexes as input variables;
and the control module 7 is used for acquiring frequency modulation optimization parameters according to the self-adaptive optimization model, and inputting the frequency modulation optimization parameters into the frequency modulation control system for control.
Further, the system further comprises:
the power grid operation stability analysis module is used for carrying out power grid operation stability analysis according to the external unit signal set to obtain a plurality of association coefficients, wherein the plurality of association coefficients are in one-to-one correspondence with the plurality of signal output sources;
the first judging module is used for judging according to the plurality of association coefficients to obtain an identification signal output source which is larger than or equal to a preset association coefficient;
and the characteristic analysis module is used for carrying out characteristic analysis on the identification unit signal set corresponding to the identification signal output source to obtain the variable indexes.
Further, the system further comprises:
the access module is used for acquiring a real-time operation signal set of the target power grid after the target power grid is accessed to the external generator set;
the first analysis module is used for carrying out power grid stability analysis according to the real-time operation signal set to obtain a second stability index;
the first activation module is used for generating a model activation instruction by comparing the first stability index with the second stability index, and activating the self-adaptive optimization model according to the model activation instruction.
Further, the system further comprises:
the index difference module is used for obtaining the stable index difference between the first stable index and the second stable index;
the second judging module is used for judging whether the stable index difference is in a preset stable index difference or not;
and the second activation module is used for activating the self-adaptive optimization model if the stability index difference is not in the preset stability index difference.
Further, the system further comprises:
the parameter obtaining module is used for obtaining the original frequency modulation parameters of the target power grid;
the input module is used for taking the stable index difference as a response target, taking the original frequency modulation parameter as an adjusting variable and taking the variable indexes as input variables to generate an objective function;
and the model generation module is used for generating the self-adaptive optimization model based on the objective function.
Further, the system further comprises:
the first modeling module is used for modeling the target power grid and obtaining an original power grid model;
the second modeling module is used for modeling the external generator set to obtain an external generator set model;
the fitting module is used for performing model fitting on the original power grid model and the external unit model to obtain a model fitting result;
the simulation operation signal set obtaining module is used for obtaining a simulation operation signal set according to the model fitting result;
and the second analysis module is used for analyzing the simulation operation signal set and the real-time operation signal set to obtain the preset stable index difference.
Further, the system further comprises:
the first identification module is used for carrying out frequency out-of-limit node identification on the real-time operation signal set to obtain a plurality of identification nodes;
the first interval integration module is used for performing interval integration according to the plurality of identification nodes to obtain a plurality of real-time integration electric quantities;
the node identification module is used for carrying out frequency out-of-limit node identification on the simulation running signal set and obtaining a plurality of simulation identification nodes;
the second interval integration module is used for performing interval integration according to the plurality of analog identification nodes to obtain a plurality of analog integration electric quantities;
and the ratio coefficient module is used for obtaining the preset stable index difference according to the ratio coefficient of the real-time integrated electric quantity to the analog integrated electric quantity.
Through the foregoing detailed description of a primary frequency modulation self-optimization control method, those skilled in the art can clearly know a primary frequency modulation self-optimization control method and a system in this embodiment, and for the device disclosed in the embodiment, the description is relatively simple because it corresponds to the method disclosed in the embodiment, and relevant places refer to the method part for description.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
For a specific embodiment of the control optimization system of the industrial bleed air valve, reference may be made to the above embodiment of the control optimization method of the industrial bleed air valve, which is not described herein. The above-mentioned various modules in the control optimizing device of the industrial air extraction regulating valve can be implemented in whole or in part by software, hardware and the combination thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
In one embodiment, a computer device is provided, which may be a server, the internal structure of which may be as shown in fig. 5. The computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer device is used for storing news data, time attenuation factors and other data. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program when executed by a processor implements a control optimization method for an industrial bleed-off valve.
It will be appreciated by those skilled in the art that the structure shown in FIG. 5 is merely a block diagram of some of the structures associated with the present inventive arrangements and is not limiting of the computer device to which the present inventive arrangements may be applied, and that a particular computer device may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.
Example III
As shown in fig. 5, there is provided a computer device comprising a memory and a processor, the memory storing a computer program, the processor implementing the following steps when executing the computer program: obtaining an external generator set of a target power grid; signal acquisition is carried out on a plurality of signal output sources of the external generator set to obtain an external generator set signal set; the method comprises the steps of analyzing a signal set of an external generator set to obtain a plurality of variable indexes, wherein the variable indexes are indexes which influence the operation stability of the target power grid by the external generator set; acquiring an original running signal set of the target power grid; carrying out power grid stability analysis according to the original running signal set to obtain a first stability index; setting up a self-adaptive optimization model by taking the first stability index as an optimization target and taking the variable indexes as input variables; and acquiring frequency modulation optimization parameters according to the self-adaptive optimization model, and inputting the frequency modulation optimization parameters into the frequency modulation control system for control.
Example IV
As shown in fig. 5, there is provided a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of: obtaining an external generator set of a target power grid; signal acquisition is carried out on a plurality of signal output sources of the external generator set to obtain an external generator set signal set; the method comprises the steps of analyzing a signal set of an external generator set to obtain a plurality of variable indexes, wherein the variable indexes are indexes which influence the operation stability of the target power grid by the external generator set; acquiring an original running signal set of the target power grid; carrying out power grid stability analysis according to the original running signal set to obtain a first stability index; setting up a self-adaptive optimization model by taking the first stability index as an optimization target and taking the variable indexes as input variables; and acquiring frequency modulation optimization parameters according to the self-adaptive optimization model, and inputting the frequency modulation optimization parameters into the frequency modulation control system for control.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The above examples illustrate only a few embodiments of the application, which are described in detail and are not to be construed as limiting the scope of the application. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the application, which are all within the scope of the application. Accordingly, the scope of protection of the present application is to be determined by the appended claims.
Claims (10)
1. The utility model provides a frequency modulation self-optimizing control method which is characterized in that the method is applied to a power grid optimizing management system, the power grid optimizing management system is in communication connection with a frequency modulation control system, and the method comprises the following steps:
obtaining an external generator set of a target power grid;
signal acquisition is carried out on a plurality of signal output sources of the external generator set to obtain an external generator set signal set;
the method comprises the steps of analyzing a signal set of an external generator set to obtain a plurality of variable indexes, wherein the variable indexes are indexes which influence the operation stability of the target power grid by the external generator set;
acquiring an original running signal set of the target power grid;
carrying out power grid stability analysis according to the original running signal set to obtain a first stability index;
setting up a self-adaptive optimization model by taking the first stability index as an optimization target and taking the variable indexes as input variables;
and acquiring frequency modulation optimization parameters according to the self-adaptive optimization model, and inputting the frequency modulation optimization parameters into the frequency modulation control system for control.
2. The method of claim 1, wherein the plurality of variable indicators are obtained by analyzing the set of external unit signals, the method further comprising:
carrying out power grid operation stability analysis according to the external unit signal set to obtain a plurality of association coefficients, wherein the plurality of association coefficients are in one-to-one correspondence with the plurality of signal output sources;
judging according to the plurality of association coefficients to obtain an identification signal output source which is larger than or equal to a preset association coefficient;
and carrying out feature analysis on the identification unit signal set corresponding to the identification signal output source to obtain the variable indexes.
3. The method of claim 1, wherein the method further comprises:
acquiring a real-time operation signal set of the target power grid after the target power grid is connected with the external generator set;
carrying out power grid stability analysis according to the real-time operation signal set to obtain a second stability index;
and generating a model activation instruction by comparing the first stability index with the second stability index, and activating the self-adaptive optimization model according to the model activation instruction.
4. The method of claim 3, wherein by comparing the first stability index to the second stability index, the method further comprises:
acquiring a stability index difference between the first stability index and the second stability index;
judging whether the stable index difference is in a preset stable index difference or not;
and if the stable index difference is not in the preset stable index difference, activating the self-adaptive optimization model.
5. The method of claim 4, wherein if the stability index difference is not within the predetermined stability index difference, the method further comprises:
acquiring an original frequency modulation parameter of the target power grid;
taking the stable index difference as a response target, taking the original frequency modulation parameter as an adjusting variable, and taking the variable indexes as input variables to generate an objective function;
and generating the self-adaptive optimization model based on the objective function.
6. The method of claim 4, wherein the method further comprises:
modeling the target power grid to obtain an original power grid model;
modeling the external generator set to obtain an external generator set model;
performing model fitting on the original power grid model and the external unit model to obtain a model fitting result;
obtaining a simulation running signal set according to the model fitting result;
and analyzing the simulation operation signal set and the real-time operation signal set to obtain the preset stability index difference.
7. The method of claim 6, wherein the set of analog operational signals and the set of real-time operational signals are analyzed, the method further comprising:
performing frequency out-of-limit node identification on the real-time operation signal set to obtain a plurality of identification nodes;
performing interval integration according to the plurality of identification nodes to obtain a plurality of real-time integrated electric quantities;
performing frequency out-of-limit node identification on the simulation running signal set to obtain a plurality of simulation identification nodes;
performing interval integration according to the plurality of analog identification nodes to obtain a plurality of analog integrated electric quantities;
and obtaining the preset stable index difference according to the ratio coefficient of the real-time integrated electric quantity to the analog integrated electric quantity.
8. The utility model provides a primary frequency modulation self-optimizing control system which characterized in that, primary frequency modulation self-optimizing control system and frequency modulation control system communication connection, primary frequency modulation self-optimizing control system includes:
the external connection module is used for obtaining an external connection generator set of the target power grid;
the signal acquisition module is used for acquiring signals of a plurality of signal output sources of the external generator set to obtain an external generator set signal set;
the analysis module is used for obtaining a plurality of variable indexes by analyzing the signal set of the external generator set, wherein the variable indexes are indexes which influence the operation stability of the target power grid by the external generator set;
the original running signal set acquisition module is used for acquiring an original running signal set of the target power grid;
the power grid stability analysis module is used for carrying out power grid stability analysis according to the original running signal set to obtain a first stability index;
the building module is used for building a self-adaptive optimization model by taking the first stability index as an optimization target and the variable indexes as input variables;
and the control module is used for acquiring frequency modulation optimization parameters according to the self-adaptive optimization model, and inputting the frequency modulation optimization parameters into the frequency modulation control system for control.
9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any of claims 1 to 7 when the computer program is executed.
10. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 7.
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