CN113095600B

CN113095600B - Remote monitoring control method and system for cogeneration

Info

Publication number: CN113095600B
Application number: CN202110503577.4A
Authority: CN
Inventors: 汤问天; 汤荣华; 马万军; 唐志军; 张圆明; 黄阔; 许建辉; 杜生华
Original assignee: Liyang Guangdong Energy Saving Technology Co ltd
Current assignee: Liyang Guangdong Energy Saving Technology Co ltd
Priority date: 2021-05-10
Filing date: 2021-05-10
Publication date: 2021-11-09
Anticipated expiration: 2041-05-10
Also published as: CN113095600A

Abstract

The embodiment of the application provides a remote monitoring and controlling method and system for cogeneration, which can analyze the remote monitoring and controlling result of the cogeneration of an acquisition project by combining the monitoring level and the electric energy consumption plan information of the monitoring state component, and can combine the electric energy consumption plan, the state transaction thermodynamic diagram and the monitoring state component. By analyzing the state variation thermodynamic diagram, the content optimization information corresponding to the cogeneration demand control data can be ensured to be determined after the preset alarm condition is met, and the monitoring state component optimization data can be configured for the monitoring process to be optimized according to the content optimization information, so that the monitoring process to be optimized is controlled to be optimized. Therefore, the integrity optimization of the monitoring flow to be optimized can be realized by combining the electric energy consumption plan data, the state transaction thermodynamic diagram and the monitoring state component, and the monitoring reliability is improved.

Description

Remote monitoring control method and system for cogeneration

Technical Field

The application relates to the technical field of remote monitoring of cogeneration, in particular to a method and a system for remote monitoring and control of cogeneration.

Background

Cogeneration (also known as Cogeneration, english: combined heat and power, abbreviated as CHP) utilizes heat engines or power stations to simultaneously generate electricity and useful heat. Thermal power plants (including those that use fissile materials or that burn coal, oil or natural gas) and heat engines in general do not convert all of the thermal energy into electrical energy. In most heat engines, slightly more than half of the heat is lost as excess heat (see: second law of thermodynamics and carnot's theorem). By capturing excess heat, Cogeneration (CHP) uses the heat wasted in conventional power plants, with the potential for reaching thermal efficiencies as high as 80% for the best conventional power plants. This means that less fuel can be consumed to produce as much useful energy. The micro-combustion cogeneration unit is a common mobile hot water supply system at present, a micro internal combustion engine is adopted to drive a generator to generate electricity, hot water is generated while electricity is generated, on one hand, the electricity can continuously generate the hot water by using driving air to provide the COP value of the system, on the other hand, redundant electricity is sold on the internet, so that the income of the electricity sale can be subsidized for the daily maintenance cost of the system.

Cogeneration is the most cost-effective method of reducing heating system carbon emissions in cold climates and is considered the most energy-efficient method of converting energy from fossil fuels or biomass to electricity. Cogeneration plants are commonly used in district heating systems in cities, central heating systems in buildings such as hospitals, prisons, etc., and are commonly used in heat generation processes such as industrial water, cooling, steam production, etc.

In the related art, poor monitoring reliability may occur in an actual cogeneration remote monitoring control process, for example, poor monitoring reliability may occur in the cogeneration remote monitoring control process due to an uncoordinated matching of some monitoring processes with actual needs.

Disclosure of Invention

In order to overcome at least the above disadvantages in the prior art, an object of the present application is to provide a method and a system for remote monitoring and control of cogeneration, which can analyze the cogeneration monitoring and control behavior characteristics to determine the process behavior information of different collection items, so that the monitoring level hierarchy of the monitoring state component and the electric energy consumption plan information can be combined to analyze the cogeneration remote monitoring and control result of the collection items, and the electric energy consumption plan, the state transaction thermodynamic diagram and the monitoring state component can be combined. By analyzing the state variation thermodynamic diagram, the content optimization information corresponding to the cogeneration demand control data can be ensured to be determined after the preset alarm condition is met, and the monitoring state component optimization data can be configured for the monitoring process to be optimized according to the content optimization information, so that the monitoring process to be optimized is controlled to be optimized. Therefore, the integrity optimization of the monitoring flow to be optimized can be realized by combining the electric energy consumption plan data, the state transaction thermodynamic diagram and the monitoring state component, and the monitoring reliability is improved.

In a first aspect, the present application provides a cogeneration remote monitoring and control method, applied to a cogeneration remote monitoring service platform, where the cogeneration remote monitoring service platform is communicatively connected to a plurality of cogeneration operation and maintenance network nodes, and the method includes:

acquiring a cogeneration remote monitoring control plan optimized in advance according to historical cogeneration data of cogeneration partition objects of the cogeneration partitions configured by the plurality of cogeneration operation and maintenance network nodes, wherein the cogeneration remote monitoring control plan comprises cogeneration demand control data of each cogeneration remote monitoring control project;

extracting the cogeneration monitoring and control behavior characteristics of the cogeneration demand control data, and acquiring the process behavior information of each monitoring process corresponding to the cogeneration demand control data according to the cogeneration monitoring and control behavior characteristics;

acquiring at least two target process behavior information according to the monitoring level of the monitoring state component of each monitoring process and the electric energy consumption plan information corresponding to the cogeneration demand control data to obtain at least two target process behavior clusters, and acquiring a cogeneration remote monitoring control result of each monitoring process for any target process behavior cluster according to the real-time monitoring state component information of each monitoring process in the current cogeneration remote monitoring control process in the target process behavior clusters;

acquiring a state transaction sequence of a remote monitoring control result of the cogeneration of each monitoring process included in the target process behavior cluster, acquiring a state transaction thermodynamic diagram of the target process behavior cluster, determining content optimization information corresponding to the cogeneration demand control data when the state transaction thermodynamic diagrams of at least two target process behavior clusters both meet preset alarm conditions, and configuring monitoring state component optimization data for a monitoring process to be optimized corresponding to the cogeneration demand control data according to the content optimization information; wherein, the monitoring flow to be optimized is at least one of the monitoring flows.

In one possible implementation manner of the first aspect, the step of extracting the cogeneration monitoring control behavior feature of the cogeneration demand control data includes:

dividing the configuration information of the thermoelectric generating set corresponding to the cogeneration demand control data into at least two first adaptation working condition configuration data, wherein each first adaptation working condition configuration data has the same adaptation working condition interval;

extracting a combined heat and power generation remote monitoring control component from each first adaptive working condition configuration data by adopting a preset matching model;

and screening the remote monitoring control components of the cogeneration of heat and power of the at least two first adaptive working condition configuration data to obtain the monitoring control behavior characteristics of the cogeneration of power.

In a possible implementation manner of the first aspect, the step of obtaining process behavior information of each monitoring process corresponding to the cogeneration demand control data according to the cogeneration monitoring control behavior feature includes:

inputting the cogeneration monitoring control behavior characteristics into a preset acquisition link fusion network, and outputting process behavior information of a monitoring behavior set corresponding to each monitoring process in the cogeneration demand control data;

the preset acquisition link fusion network is used for detecting flow behavior information matched with the display distribution diagram structure of the monitoring behavior set from the display distribution diagram corresponding to the cogeneration demand control data based on the cogeneration monitoring control behavior characteristics of the monitoring behavior set, and acquiring the flow behavior information of the monitoring behavior set corresponding to the flow behavior information matched with the display distribution diagram structure of the monitoring behavior set in the starting state of the cogeneration demand control data.

In a possible implementation manner of the first aspect, the method further includes:

taking the state transaction thermodynamic node which determines that the state transaction thermodynamic diagrams of the at least two target process behavior clusters both meet the preset alarm condition as a reference state transaction thermodynamic node, and acquiring second adaptation working condition configuration data of a preset adaptation working condition interval from preset adaptation working condition configuration data corresponding to the cogeneration demand control data;

acquiring power backup reference information of the second adaptive working condition configuration data;

when the power backup reference information of the second adaptation working condition configuration data activates optimization information, determining content optimization information corresponding to the cogeneration demand control data;

wherein, the step of obtaining the power backup reference information of the second adaptation condition configuration data includes:

dividing the second adaptive working condition configuration data into at least two adaptive working condition configuration vectors, wherein each adaptive working condition configuration vector has the same adaptive working condition interval;

acquiring a power demand relation of power demand information corresponding to each adaptation working condition configuration vector, and acquiring an overall power demand relation and a distributed power demand relation from the power demand relations corresponding to the at least two adaptation working condition configuration vectors; determining power backup reference information of the second adaptation working condition configuration data based on the requirement relation characteristics of the overall power requirement relation and the distributed power requirement relation;

the second adaptive working condition configuration data comprises at least one of third adaptive working condition configuration data and fourth adaptive working condition configuration data, the third adaptive working condition configuration data is adaptive working condition configuration data of a preset adaptive working condition interval behind a state transaction thermal node in preset adaptive working condition configuration data corresponding to the cogeneration demand control data, and the fourth adaptive working condition configuration data is adaptive working condition configuration data of a preset adaptive working condition interval ahead of the state transaction thermal node in preset adaptive working condition configuration data corresponding to the cogeneration demand control data, wherein the state transaction thermal node is used as a reference state transaction thermal node.

In a possible implementation manner of the first aspect, the step of obtaining at least two target process behavior information according to the monitoring level hierarchy of the monitoring state component of each monitoring process and the electric energy consumption plan information corresponding to the cogeneration demand control data to obtain at least two target process behavior clusters includes:

acquiring each first state thermodynamic diagram based on the monitoring state component frequency information of each monitoring process;

obtaining first target process behavior attributes corresponding to the first state thermodynamic diagrams respectively based on a preset first process behavior attribute sequence, wherein the first target process behavior attributes comprise target process behavior attributes of the first state thermodynamic diagrams corresponding to the process behavior labels of a preset target process behavior cluster respectively;

obtaining second state thermodynamic diagrams based on monitoring state component frequency information of each monitoring process, and generating first state matching information of each second state thermodynamic diagram, wherein the first state matching information is generated based on first target process behavior attributes corresponding to the first state thermodynamic diagrams corresponding to the second state thermodynamic diagrams, and the second state thermodynamic diagrams and the first state thermodynamic diagrams respectively correspond to a positive thermodynamic distribution strategy and a negative thermodynamic distribution strategy;

adding each piece of first state matching information to a preset second process behavior attribute sequence to obtain each second target process behavior attribute corresponding to each second state thermodynamic diagram, wherein the second target process behavior attributes comprise target process behavior attributes of the second state thermodynamic diagram corresponding to the preset target process behavior cluster and/or target process behavior attributes not corresponding to the preset target process behavior cluster;

determining whether the preset target process behavior cluster exists in the monitoring state component frequency information of each monitoring process based on the second target process behavior attribute, and acquiring at least two pieces of target process behavior information of the preset target process behavior cluster so as to obtain at least two target process behavior clusters.

In a possible implementation manner of the first aspect, for any target process behavior cluster, the step of obtaining the cogeneration remote monitoring control result of each monitoring process according to the real-time monitoring state component information of each monitoring process in the current cogeneration remote monitoring control process in the target process behavior cluster includes:

extracting monitoring process enabling data of each monitoring process through a state node corresponding to real-time monitoring state component information of each monitoring process in the current cogeneration remote monitoring control process in the target process behavior cluster, identifying current monitoring target information under enabling data of each monitoring process from monitoring process execution information corresponding to each monitoring process through a planning evaluation thread corresponding to real-time monitoring state component information of each monitoring process in the target process behavior cluster, screening the current monitoring target information under enabling data of each monitoring process in the monitoring process execution information corresponding to each monitoring process as first monitoring confirmation information, and screening monitoring target information except the first monitoring confirmation information in the monitoring process execution information corresponding to each monitoring process as second monitoring confirmation information;

on the premise that dynamic process change data and non-dynamic process change data exist in monitoring process execution information corresponding to each monitoring process based on monitoring process enabling data, monitoring target related parameters between second target current monitoring target information of second monitoring confirmation information under the non-dynamic process change data and first target current monitoring target information of the second monitoring confirmation information under the dynamic process change data are determined according to first target current monitoring target information under the dynamic process change data and monitoring target structure distribution of the first target current monitoring target information in the second monitoring confirmation information;

distributing second target current monitoring target information of the second monitoring confirmation information under the non-dynamic process change data and the first target current monitoring target information under the dynamic process change data, which has similarity on monitoring target related parameters, to the dynamic process change data based on the monitoring target related parameters; wherein, under the condition that the non-dynamic flow change data corresponding to the second monitoring confirmation information contains a plurality of current monitoring target information with activation behaviors on the continuous behavior characteristics, determining the monitoring target related parameters of the second monitoring confirmation information among the current monitoring target information with the activated behavior on the continuous behavior characteristics under the non-dynamic process change data according to the first target current monitoring target information of the second monitoring confirmation information under the dynamic process change data and the monitoring target structure distribution of the first target current monitoring target information, screening the current monitoring target information with the activated behavior on the continuous behavior characteristic under the non-dynamic process change data according to the relevant parameters of the monitoring target between the current monitoring target information with the activated behavior on the continuous behavior characteristic; setting a monitoring target ratio for the screened third target current monitoring target information according to the first target current monitoring target information of the second monitoring confirmation information under the dynamic process change data and the monitoring target structure distribution of the first target current monitoring target information, and sequentially distributing part of the third target current monitoring target information under the dynamic process change data based on the magnitude sequence of the monitoring target ratio;

determining a first scene environment component of a first scene environment dimension characteristic used for representing current monitoring target information in the first monitoring confirmation information, a second scene environment component of a second scene environment dimension characteristic used for representing current monitoring target information of the second monitoring confirmation information under the dynamic process change data, and a third scene environment component of a third scene environment dimension characteristic used for representing current monitoring target information of the second monitoring confirmation information under the non-dynamic process change data; calculating similar components of the first scene environment component and the second scene environment component, and judging whether the proportion of the third scene environment component to the similar components exceeds a target proportion;

and when the ratio of the third scene environment component to the similar component does not exceed the target ratio, determining the current monitoring target information under the non-dynamic process change data as static monitoring target information, and determining the cogeneration remote monitoring control result of each monitoring process according to the static monitoring target information, the current monitoring target information in the first monitoring confirmation information and the current monitoring target information under the dynamic process change data.

In a possible implementation manner of the first aspect, the obtaining a state transaction thermodynamic diagram of the target process behavior cluster by obtaining a state transaction sequence of a cogeneration remote monitoring control result of each monitoring process included in the target process behavior cluster includes:

determining the state transaction sequence according to the control correlation degree between the remote monitoring control results of the cogeneration of each monitoring process included in the target process behavior cluster;

and extracting the thermal characteristics of the state transaction object in the state transaction sequence, and obtaining the state transaction thermodynamic diagram of the target process behavior cluster based on the thermal characteristics of the state transaction object.

In a possible implementation manner of the first aspect, when the state transaction thermodynamic diagrams of at least two target process behavior clusters both meet a preset alarm condition, determining content optimization information corresponding to the cogeneration demand control data includes:

and when the different dynamic thermal intervals corresponding to the state different dynamic thermodynamic diagrams of at least two target process behavior clusters cover a preset different dynamic thermal interval, determining the content optimization information according to the track floating characteristic object corresponding to the state different dynamic thermodynamic diagrams.

In a possible implementation manner of the first aspect, the configuring, according to the content optimization information, monitoring state component optimization data for a monitoring process to be optimized corresponding to the cogeneration demand control data includes:

determining a plurality of content optimization unit information from the content optimization information;

determining monitoring state component optimization parameters corresponding to each content optimization unit information;

selecting a monitoring flow corresponding to the optimization template corresponding to the minimum monitoring state component optimization parameter as the monitoring flow to be optimized;

and configuring the monitoring state component optimization data for the monitoring process to be optimized through the content optimization unit information.

In a second aspect, an embodiment of the present application further provides a cogeneration remote monitoring and control device, which is applied to a cogeneration remote monitoring service platform, where the cogeneration remote monitoring service platform is communicatively connected to a plurality of cogeneration operation and maintenance network nodes, and the device includes:

a first obtaining module, configured to obtain a cogeneration remote monitoring control plan optimized in advance according to historical cogeneration data of cogeneration partition objects of cogeneration partitions configured by the plurality of cogeneration operation and maintenance network nodes, where the cogeneration remote monitoring control plan includes cogeneration demand control data of each cogeneration remote monitoring control project;

the extraction module is used for extracting the combined heat and power generation monitoring and controlling behavior characteristics of the combined heat and power generation demand control data and acquiring the process behavior information of each monitoring process corresponding to the combined heat and power generation demand control data according to the combined heat and power generation monitoring and controlling behavior characteristics;

the second acquisition module is used for acquiring at least two target process behavior information according to the monitoring level levels of the monitoring state components of each monitoring process and the electric energy consumption plan information corresponding to the cogeneration demand control data to obtain at least two target process behavior clusters, and for any one target process behavior cluster, acquiring a cogeneration remote monitoring control result of each monitoring process according to the real-time monitoring state component information of each monitoring process in the target process behavior cluster in the current cogeneration remote monitoring control process;

the configuration module is used for acquiring a state transaction sequence of a cogeneration remote monitoring control result of each monitoring process included by the target process behavior cluster, obtaining a state transaction thermodynamic diagram of the target process behavior cluster, determining content optimization information corresponding to cogeneration demand control data when the state transaction thermodynamic diagrams of at least two target process behavior clusters both meet preset alarm conditions, and configuring monitoring state component optimization data for a monitoring process to be optimized corresponding to the cogeneration demand control data according to the content optimization information; wherein, the monitoring flow to be optimized is at least one of the monitoring flows.

In a third aspect, an embodiment of the present application further provides a cogeneration remote monitoring and control system, where the cogeneration remote monitoring and control system includes a cogeneration remote monitoring service platform and a plurality of cogeneration operation and maintenance network nodes communicatively connected to the cogeneration remote monitoring service platform;

the cogeneration remote monitoring service platform is used for:

In a fourth aspect, an embodiment of the present application further provides a cogeneration remote monitoring service platform, where the cogeneration remote monitoring service platform includes a processor, a machine-readable storage medium, and a network interface, where the machine-readable storage medium, the network interface, and the processor are connected through a bus system, the network interface is configured to be communicatively connected to at least one cogeneration operation and maintenance network node, the machine-readable storage medium is configured to store a program, instructions, or code, and the processor is configured to execute the program, instructions, or code in the machine-readable storage medium to perform the cogeneration remote monitoring control method in the first aspect or any possible implementation manner of the first aspect.

In a fifth aspect, an embodiment of the present application provides a computer-readable storage medium, where instructions are stored in the computer-readable storage medium, and when the instructions are executed, the computer executes the method for remote monitoring and controlling cogeneration of heat and power in the first aspect or any one of the possible implementations of the first aspect.

Based on any one of the aspects, the method and the device can analyze the monitoring and control behavior characteristics of the cogeneration so as to determine the flow behavior information of different acquisition projects, so that the monitoring level hierarchy of the monitoring state component and the electric energy consumption plan information can be combined to analyze the remote monitoring and control result of the cogeneration of the acquisition projects, and the electric energy consumption plan, the state transaction thermodynamic diagram and the monitoring state component can be combined. By analyzing the state variation thermodynamic diagram, the content optimization information corresponding to the cogeneration demand control data can be ensured to be determined after the preset alarm condition is met, and the monitoring state component optimization data can be configured for the monitoring process to be optimized according to the content optimization information, so that the monitoring process to be optimized is controlled to be optimized. Therefore, the integrity optimization of the monitoring flow to be optimized can be realized by combining the electric energy consumption plan data, the state transaction thermodynamic diagram and the monitoring state component, and the monitoring reliability is improved.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that need to be called in the embodiments are briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.

Fig. 1 is a schematic view of an application scenario of a cogeneration remote monitoring and control system according to an embodiment of the present application;

fig. 2 is a schematic flow chart of a cogeneration remote monitoring control method according to an embodiment of the present application;

fig. 3 is a functional block diagram of a cogeneration remote monitoring and control device according to an embodiment of the present application;

fig. 4 is a schematic block diagram of structural components of a cogeneration remote monitoring service platform for implementing the cogeneration remote monitoring control method according to an embodiment of the present application.

Detailed Description

The present application will now be described in detail with reference to the drawings, and the specific operations in the method embodiments may also be applied to the apparatus embodiments or the system embodiments.

Fig. 1 is an interactive schematic diagram of a cogeneration remote monitoring and control system 10 according to an embodiment of the present application. The cogeneration remote monitoring control system 10 may include a cogeneration remote monitoring service platform 100 and a cogeneration operation and maintenance network node 200 communicatively connected to the cogeneration remote monitoring service platform 100. The cogeneration remote monitoring and control system 10 shown in fig. 1 is only one possible example, and in other possible embodiments, the cogeneration remote monitoring and control system 10 may include only a portion of the components shown in fig. 1 or may include other components.

In this embodiment, the cogeneration remote monitoring service platform 100 and the cogeneration operation and maintenance network node 200 in the cogeneration remote monitoring and control system 10 may cooperate to execute the cogeneration remote monitoring and control method described in the following method embodiment, and specific steps of executing the cogeneration remote monitoring service platform 100 and the cogeneration operation and maintenance network node 200 may refer to the detailed description of the following method embodiment.

Fig. 2 is a schematic flow chart of a cogeneration remote monitoring and control method according to an embodiment of the present application, which can be executed by the cogeneration remote monitoring service platform 100 shown in fig. 1, and the cogeneration remote monitoring and control method is described in detail below.

Step S110 is to acquire a cogeneration remote monitoring control plan optimized in advance based on historical cogeneration data of the cogeneration partition objects of the cogeneration partitions configured by the plurality of cogeneration operation and maintenance network nodes.

In this embodiment, the remote monitoring and control plan for cogeneration may specifically include the cogeneration demand control data of each remote monitoring and control project for cogeneration. For example, the cogeneration remote monitoring control project may refer to a cogeneration remote monitoring control project plan for a certain cogeneration demand, and the cogeneration demand control data may refer to configuration information of a thermodynamic distribution strategy configured in a subsequent cogeneration remote monitoring control process for the cogeneration remote monitoring control project.

And step S120, extracting the cogeneration monitoring and control behavior characteristics of the cogeneration demand control data, and acquiring the process behavior information of each monitoring process corresponding to the cogeneration demand control data according to the cogeneration monitoring and control behavior characteristics.

In this embodiment, the process behavior information may be used to characterize each process behavior that each monitored process needs to traverse in the subsequent cogeneration remote monitoring control process.

Step S130, acquiring at least two target process behavior information according to the monitoring level levels of the monitoring state components of each monitoring process and the electric energy consumption plan information corresponding to the cogeneration demand control data, acquiring at least two target process behavior clusters, and acquiring the cogeneration remote monitoring control result of each monitoring process for any one target process behavior cluster according to the real-time monitoring state component information of each monitoring process in the current cogeneration remote monitoring control process in the target process behavior cluster.

Step S140, obtaining a state transaction sequence of the remote monitoring control results of the cogeneration of each monitoring process included by the target process behavior cluster, obtaining a state transaction thermodynamic diagram of the target process behavior cluster, determining content optimization information corresponding to the cogeneration demand control data when the state transaction thermodynamic diagrams of at least two target process behavior clusters both meet preset alarm conditions, and configuring monitoring state component optimization data for the to-be-optimized monitoring process corresponding to the cogeneration demand control data according to the content optimization information. Wherein, the monitoring process to be optimized is at least one of the monitoring processes.

Based on the steps, the embodiment can analyze the monitoring and control behavior characteristics of the cogeneration so as to determine the flow behavior information of different acquisition projects, so that the monitoring level hierarchy of the monitoring state component and the electric energy consumption plan information can be combined to analyze the cogeneration remote monitoring and control result of the acquisition projects, and the electric energy consumption plan, the state transaction thermodynamic diagram and the monitoring state component can be combined. By analyzing the state variation thermodynamic diagram, the content optimization information corresponding to the cogeneration demand control data can be ensured to be determined after the preset alarm condition is met, and the monitoring state component optimization data can be configured for the monitoring process to be optimized according to the content optimization information, so that the monitoring process to be optimized is controlled to be optimized. Therefore, the integrity optimization of the monitoring flow to be optimized can be realized by combining the electric energy consumption plan data, the state transaction thermodynamic diagram and the monitoring state component, and the monitoring reliability is improved.

In one embodiment, for step S120, in the process of extracting the cogeneration monitoring control behavior feature of the cogeneration demand control data, the following exemplary substeps may be implemented.

And a substep S121, dividing the configuration information of the thermoelectric generating set corresponding to the cogeneration demand control data into at least two first adaptation working condition configuration data, wherein each first adaptation working condition configuration data has the same adaptation working condition interval.

And a substep S122, extracting a remote monitoring control component of the combined heat and power generation from each first adaptive working condition configuration data by adopting a preset matching model.

And a substep S123 of screening the remote monitoring and control components of the cogeneration of at least two first adaptive working condition configuration data to obtain the monitoring and control behavior characteristics of the cogeneration.

In an embodiment, still referring to step S120, in the process of acquiring the process behavior information of each monitoring flow corresponding to the cogeneration demand control data according to the cogeneration monitoring control behavior characteristics, the following exemplary sub-steps may be implemented.

And a substep S124 of inputting the cogeneration monitoring control behavior characteristics into a preset acquisition link fusion network and outputting the process behavior information of the monitoring behavior set corresponding to each monitoring process in the cogeneration demand control data.

It should be noted that the preset acquisition link fusion network is configured to detect, based on the cogeneration monitoring and control behavior feature of the monitoring behavior set, flow behavior information matched with the structure of the display distribution diagram of the monitoring behavior set from the display distribution diagram corresponding to the cogeneration demand control data, and acquire the flow behavior information of the monitoring behavior set corresponding to the flow behavior information matched with the structure of the display distribution diagram of the monitoring behavior set in the enabled state of the cogeneration demand control data.

In an embodiment, further, in this embodiment, a state transition thermodynamic node that determines that the state transition thermodynamic diagrams of at least two target process behavior clusters both meet the preset alarm condition may be taken as a reference state transition thermodynamic node, and second adaptation working condition configuration data of a preset adaptation working condition interval may be obtained from preset adaptation working condition configuration data corresponding to cogeneration demand control data.

On the basis, the power backup reference information of the second adaptation working condition configuration data is obtained, and when the power backup reference information of the second adaptation working condition configuration data activates the optimization information, the content optimization information corresponding to the cogeneration demand control data is determined.

Based on the above described logic, in the process of acquiring the power backup reference information of the second adaptation condition configuration data, the following exemplary embodiments may be implemented.

(1) And dividing the second adaptive working condition configuration data into at least two adaptive working condition configuration vectors, wherein each adaptive working condition configuration vector has the same adaptive working condition interval.

(2) And acquiring the power demand relation of the power demand information corresponding to each adaptation working condition configuration vector, and acquiring the whole power demand relation and the distributed power demand relation from the power demand relations corresponding to at least two adaptation working condition configuration vectors.

(3) And determining power backup reference information of the second adaptation working condition configuration data based on the requirement relation characteristics of the overall power requirement relation and the distributed power requirement relation.

The second adaptive working condition configuration data comprises at least one of third adaptive working condition configuration data and fourth adaptive working condition configuration data, the third adaptive working condition configuration data is adaptive working condition configuration data of a preset adaptive working condition interval behind a state transaction thermal node in the preset adaptive working condition configuration data corresponding to the cogeneration demand control data, and the fourth adaptive working condition configuration data is adaptive working condition configuration data of a preset adaptive working condition interval ahead of the state transaction thermal node in the preset adaptive working condition configuration data corresponding to the cogeneration demand control data, wherein the state transaction thermal node is used as a reference state transaction thermal node.

On this basis, in an embodiment, for step S130, in the process of obtaining at least two target process behavior information according to the monitoring level hierarchy of the monitoring state component of each monitoring process and the electric energy consumption plan information corresponding to the cogeneration demand control data, obtaining at least two target process behavior clusters, the following exemplary sub-steps may be implemented.

In substep S131, each first state thermodynamic diagram is obtained based on the monitored state component frequency information of each monitoring process.

And a substep S132, obtaining each first target process behavior attribute corresponding to each first state thermodynamic diagram respectively based on the preset first process behavior attribute sequence.

For example, the first target process behavior attribute may include each target process behavior attribute of each process behavior tag corresponding to the preset target process behavior cluster respectively in the first state thermodynamic diagram.

In sub-step S133, each second state thermodynamic diagram is obtained based on the monitored state component frequency information of each monitoring flow, and first state matching information of each second state thermodynamic diagram is generated.

For example, the first state matching information is generated based on the first target process behavior attribute corresponding to each first state thermodynamic diagram corresponding to the second state thermodynamic diagram, where each second state thermodynamic diagram and each first state thermodynamic diagram correspond to a positive thermodynamic distribution strategy and a negative thermodynamic distribution strategy, respectively.

And a substep S134, adding each first state matching information to a preset second process behavior attribute sequence, and obtaining each second target process behavior attribute corresponding to each second state thermodynamic diagram respectively.

For example, the second target process behavior attribute includes a target process behavior attribute corresponding to the preset target process behavior cluster and/or a target process behavior attribute not corresponding to the preset target process behavior cluster.

In the substep S135, it is determined whether a preset target process behavior cluster exists in the monitoring state component frequency information of each monitoring process based on the second target process behavior attribute, and at least two pieces of target process behavior information having the preset target process behavior cluster are obtained to obtain at least two target process behavior clusters.

On this basis, still referring to step S130, in the process of obtaining the cogeneration remote monitoring control result of each monitoring process according to the real-time monitoring state component information of each monitoring process in the target process behavior cluster in the current cogeneration remote monitoring control process for any kind of target process behavior cluster, in one embodiment, the following exemplary sub-steps can be implemented.

Substep S136, extracting monitoring process enabling data of each monitoring process through the state node corresponding to the real-time monitoring state component information of each monitoring process in the current cogeneration remote monitoring control process in the target process behavior cluster, and identifying the current monitoring target information under the enabling data of each monitoring process from the monitoring process execution information corresponding to each monitoring process through a planning evaluation thread corresponding to the real-time monitoring state component information of each monitoring process in the remote monitoring and control process of the cogeneration of heat and power in the target process behavior cluster, screening the current monitoring target information under the enabling data of each monitoring process in the monitoring process execution information corresponding to each monitoring process as first monitoring confirmation information, and screening the monitoring target information except the first monitoring confirmation information in the monitoring process execution information corresponding to each monitoring process as second monitoring confirmation information.

And a substep S137, determining, on the premise that dynamic process change data and non-dynamic process change data exist in the monitoring process execution information corresponding to each monitoring process based on the monitoring process enabling data, monitoring target related parameters between each second target current monitoring target information of the second monitoring confirmation information under the non-dynamic process change data and each first target current monitoring target information of the second monitoring confirmation information under the dynamic process change data according to the first target current monitoring target information under the dynamic process change data and the monitoring target structure distribution of the first target current monitoring target information in the second monitoring confirmation information.

And a substep S138, based on the monitoring target related parameters, allocating the second target current monitoring target information, in which the second monitoring confirmation information has similarity to the first target current monitoring target information in the dynamic process change data in the monitoring target related parameters, to the dynamic process change data in the non-dynamic process change data.

For example, when the non-dynamic process change data corresponding to the second monitoring confirmation information includes a plurality of pieces of current monitoring target information having an activated behavior on a continuous behavior characteristic, the monitoring target related parameters between the pieces of current monitoring target information having an activated behavior on a continuous behavior characteristic of the second monitoring confirmation information under the non-dynamic process change data are determined according to the first target current monitoring target information of the second monitoring confirmation information under the dynamic process change data and the monitoring target structure distribution of the first target current monitoring target information, and the current monitoring target information having an activated behavior on a continuous behavior characteristic of each piece of non-dynamic process change data is screened according to the monitoring target related parameters between the pieces of current monitoring target information having an activated behavior on a continuous behavior characteristic. And setting a monitoring target ratio for the screened third target current monitoring target information according to the first target current monitoring target information of the second monitoring confirmation information under the dynamic process change data and the monitoring target structure distribution of the first target current monitoring target information, and sequentially distributing part of the third target current monitoring target information to the dynamic process change data based on the magnitude sequence of the monitoring target ratios.

And a substep S139, determining a first scene environment component of a first scene environment dimension characteristic used for representing the current monitoring target information in the first monitoring confirmation information, a second scene environment component of a second scene environment dimension characteristic used for representing the current monitoring target information of the second monitoring confirmation information under the dynamic process change data, and a third scene environment component of a third scene environment dimension characteristic used for representing the current monitoring target information of the second monitoring confirmation information under the non-dynamic process change data. And calculating similar components of the first scene environment component and the second scene environment component, and judging whether the proportion of the third scene environment component to the similar components exceeds a target proportion.

And a substep S1391, determining current monitoring target information under the non-dynamic process change data as static monitoring target information when the ratio of the third scene environment component to the similar component does not exceed the target ratio, and determining a cogeneration remote monitoring control result of each monitoring process according to the static monitoring target information, the current monitoring target information in the first monitoring confirmation information and the current monitoring target information under the dynamic process change data.

In one embodiment, for step S140, in the process of obtaining the state transition thermodynamic diagram of the target process behavior cluster by obtaining the state transition sequence of the remote monitoring control result of cogeneration of each monitoring process included in the target process behavior cluster, the following exemplary sub-steps may be implemented.

And a substep S141, determining a state transaction sequence according to the control correlation degree between the remote monitoring control results of the cogeneration of each monitoring process included in the target process behavior cluster.

And a substep S142, extracting the thermodynamic characteristics of the state transaction object in the state transaction sequence, and obtaining the state transaction thermodynamic diagram of the target process behavior cluster based on the thermodynamic characteristics of the state transaction object.

In an embodiment, still referring to step S140, in the process of determining the content optimization information corresponding to the cogeneration demand control data when the state transaction thermodynamic diagrams of at least two target process behavior clusters both meet the preset alarm condition, the following exemplary sub-steps may be implemented.

And S143, when the abnormal thermal intervals corresponding to the state abnormal thermal diagrams of at least two target process behavior clusters cover the preset abnormal thermal intervals, determining content optimization information according to the track floating characteristic objects corresponding to the state abnormal thermal diagrams.

In one embodiment, still referring to step S140, in configuring the monitoring state component optimization data for the monitoring process to be optimized corresponding to the cogeneration demand control data according to the content optimization information, the following exemplary sub-steps may be implemented.

And a substep S144 of determining a plurality of content optimization unit information from the content optimization information.

And a substep S145, determining the monitoring state component optimization parameter corresponding to each content optimization unit information.

And a substep S146, selecting the monitoring process corresponding to the optimization template corresponding to the minimum monitoring state component optimization parameter as the monitoring process to be optimized.

And a substep S147, configuring the monitoring state component optimization data for the monitoring process to be optimized through the content optimization unit information.

Fig. 3 is a schematic diagram of functional modules of a cogeneration remote monitoring and control device 300 according to an embodiment of the present disclosure, and in this embodiment, the cogeneration remote monitoring and control device 300 may be divided into the functional modules according to an embodiment of a method performed by the cogeneration remote monitoring and control platform 100, that is, the following functional modules corresponding to the cogeneration remote monitoring and control device 300 may be used to perform the embodiment of the method performed by the cogeneration remote monitoring and control platform 100. The cogeneration remote monitoring and control device 300 may include a first obtaining module 310, an extracting module 320, a second obtaining module 330, and a configuring module 340, and the functions of the functional modules of the cogeneration remote monitoring and control device 300 are described in detail below.

A first obtaining module 310, configured to obtain a cogeneration remote monitoring control plan optimized in advance according to historical cogeneration data of cogeneration partition objects of the cogeneration partition configured by the plurality of cogeneration operation and maintenance network nodes, the cogeneration remote monitoring control plan including cogeneration demand control data for each cogeneration remote monitoring control project. The first obtaining module 310 may be configured to perform the step S110, and for a detailed implementation of the first obtaining module 310, reference may be made to the detailed description of the step S110.

The extracting module 320 is configured to extract a cogeneration monitoring control behavior feature of the cogeneration demand control data, and obtain flow behavior information of each monitoring flow corresponding to the cogeneration demand control data according to the cogeneration monitoring control behavior feature. The extracting module 320 may be configured to perform the step S120, and the detailed implementation of the extracting module 320 may refer to the detailed description of the step S120.

The second obtaining module 330 is configured to obtain at least two pieces of target process behavior information according to the monitoring level hierarchy of the monitoring state component of each monitoring process and the power consumption plan information corresponding to the cogeneration demand control data, obtain at least two target process behavior clusters, and obtain a cogeneration remote monitoring control result of each monitoring process for any one target process behavior cluster according to the real-time monitoring state component information of each monitoring process in the target process behavior cluster in the current cogeneration remote monitoring control process. The second obtaining module 330 may be configured to perform the step S130, and the detailed implementation of the second obtaining module 330 may refer to the detailed description of the step S130.

A configuration module 340, configured to obtain a state transaction sequence of the cogeneration remote monitoring control result of each monitoring process included in the target process behavior cluster, obtain a state transaction thermodynamic diagram of the target process behavior cluster, determine content optimization information corresponding to the cogeneration demand control data when the state transaction thermodynamic diagrams of at least two target process behavior clusters both meet a preset alarm condition, and configure monitoring state component optimization data for a to-be-optimized monitoring process corresponding to the cogeneration demand control data according to the content optimization information; wherein, the monitoring flow to be optimized is at least one of the monitoring flows. The configuration module 340 may be configured to perform the step S140, and the detailed implementation manner of the configuration module 340 may refer to the detailed description of the step S140.

Fig. 4 is a schematic diagram illustrating a hardware structure of a cogeneration remote monitoring service platform 100 for implementing the cogeneration remote monitoring control method, according to an embodiment of the present disclosure, and as shown in fig. 4, the cogeneration remote monitoring service platform 100 may include a processor 110, a machine-readable storage medium 120, a bus 130, and a transceiver 140.

In a specific implementation process, the at least one processor 110 executes computer-executable instructions stored in the machine-readable storage medium 120 (for example, the first obtaining module 310, the extracting module 320, the second obtaining module 330, and the configuring module 340 included in the cogeneration remote monitoring and control device 300 shown in fig. 3), so that the processor 110 may execute the cogeneration remote monitoring and control method according to the above method embodiment, where the processor 110, the machine-readable storage medium 120, and the transceiver 140 are connected by the bus 130, and the processor 110 may be configured to control transceiving actions of the transceiver 140, so as to perform data transceiving with the aforementioned cogeneration operation and maintenance network node 200.

For a specific implementation process of the processor 110, reference may be made to the above-mentioned method embodiments executed by the cogeneration remote monitoring service platform 100, which implement the principle and the technical effect similarly, and the detailed description of the embodiment is omitted here.

In addition, the embodiment of the application also provides a readable storage medium, and the readable storage medium stores computer-executable instructions, and when a processor executes the computer-executable instructions, the method for remote monitoring and controlling cogeneration is realized.

The foregoing description has been directed to specific embodiments of this disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.

Finally, it should be understood that the examples in this specification are only intended to illustrate the principles of the examples in this specification. Other variations are also possible within the scope of this description. Thus, by way of example, and not limitation, alternative configurations of the embodiments of the specification can be considered consistent with the teachings of the specification. Accordingly, the embodiments of the present description are not limited to only those embodiments explicitly described and depicted herein.

Claims

1. A remote monitoring and controlling method for cogeneration is applied to a cogeneration remote monitoring service platform which is in communication connection with a plurality of cogeneration operation and maintenance network nodes, and comprises the following steps:

acquiring a state transaction sequence of a remote monitoring control result of the cogeneration of each monitoring process included in the target process behavior cluster, acquiring a state transaction thermodynamic diagram of the target process behavior cluster, determining content optimization information corresponding to the cogeneration demand control data when the state transaction thermodynamic diagrams of at least two target process behavior clusters both meet preset alarm conditions, and configuring monitoring state component optimization data for a monitoring process to be optimized corresponding to the cogeneration demand control data according to the content optimization information; wherein, the monitoring flow to be optimized is at least one of the monitoring flows;

wherein the method further comprises:

the second adaptive working condition configuration data comprises at least one of third adaptive working condition configuration data and fourth adaptive working condition configuration data, the third adaptive working condition configuration data is adaptive working condition configuration data of a preset adaptive working condition interval behind a state transaction thermal node in preset adaptive working condition configuration data corresponding to the cogeneration demand control data, and the fourth adaptive working condition configuration data is adaptive working condition configuration data of a preset adaptive working condition interval ahead of the state transaction thermal node in preset adaptive working condition configuration data corresponding to the cogeneration demand control data, wherein the state transaction thermal node is taken as a reference state transaction thermal node;

the step of obtaining at least two target process behavior information and obtaining at least two target process behavior clusters according to the monitoring level hierarchy of the monitoring state component of each monitoring process and the electric energy consumption plan information corresponding to the cogeneration demand control data includes:

determining whether the preset target process behavior cluster exists in the monitoring state component frequency information of each monitoring process based on the second target process behavior attribute, and acquiring at least two pieces of target process behavior information of the preset target process behavior cluster to obtain at least two target process behavior clusters;

the step of acquiring the remote monitoring and control result of the cogeneration of each monitoring process according to the real-time monitoring state component information of each monitoring process in the current cogeneration remote monitoring and control process in any target process behavior cluster comprises the following steps:

2. A cogeneration remote monitoring and control method according to claim 1, wherein said step of extracting a cogeneration monitoring control behavior characteristic of said cogeneration demand control data comprises:

3. A cogeneration remote monitoring and control method according to claim 1, wherein the step of acquiring flow behavior information of each monitoring flow corresponding to the cogeneration demand control data according to the cogeneration monitoring and control behavior characteristics includes:

4. The method for remote monitoring and controlling of cogeneration according to any one of claims 1 to 3, wherein the obtaining of the state transaction sequence of the cogeneration remote monitoring control results of each monitoring process included in the target process behavior cluster to obtain the state transaction thermodynamic diagram of the target process behavior cluster comprises:

5. The remote monitoring and controlling method for cogeneration of heat and power as claimed in claim 4, wherein the determining of the content optimization information corresponding to the cogeneration demand control data when the state transaction thermodynamic diagrams of at least two target process behavior clusters both meet a preset alarm condition comprises:

6. The remote monitoring and control method for cogeneration according to claim 5, wherein the step of configuring monitoring state component optimization data for the to-be-optimized monitoring process corresponding to the cogeneration demand control data according to the content optimization information includes:

7. The remote monitoring and control system for the cogeneration is characterized by comprising a cogeneration remote monitoring service platform and a plurality of cogeneration operation and maintenance network nodes which are in communication connection with the cogeneration remote monitoring service platform;

the cogeneration remote monitoring service platform is used for:

wherein, the cogeneration remote monitoring service platform is further used for:

the method for acquiring the power backup reference information of the second adaptation condition configuration data includes:

the method for obtaining at least two target process behavior information and obtaining at least two target process behavior clusters according to the monitoring level hierarchy of the monitoring state component of each monitoring process and the electric energy consumption plan information corresponding to the cogeneration demand control data includes:

the method for acquiring the remote monitoring and control result of the cogeneration of each monitoring process according to the real-time monitoring state component information of each monitoring process in the current cogeneration remote monitoring and control process in any target process behavior cluster comprises the following steps: