CN115713352A - Power plant operation calculation analysis method based on graphical modeling technology - Google Patents
Power plant operation calculation analysis method based on graphical modeling technology Download PDFInfo
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Abstract
The invention discloses a power plant operation calculation analysis method based on a graphical modeling technology, which comprises the following steps of: s1, constructing an operation index system; s2, operating and modeling: in the model canvas, the establishment of an operation model is completed through the dragging, the configuration and the connection of indexes and formula operators in a tool box; s3, model verification: verifying the configured operation model through model calculation calling and result analysis; s4, budget planning: carrying out budget optimization through an optimization analysis tool by utilizing the established model, and then storing the determined budget calculation into a database for subsequent comparative analysis; s5, operation analysis: and by utilizing the established flow, at the beginning of each month, automatically calculating by utilizing the historical data of the last month, carrying out budget comparison analysis, identifying the main budget deviation and providing an operation decision suggestion.
Description
Technical Field
The invention relates to the technical field of big data analysis and production operation measurement and calculation of a thermal power plant, in particular to a power plant operation calculation analysis method based on a graphical modeling technology.
Background
The production and operation indexes of the power plant are products of scientific analysis developed based on data and data obtained by production statistics, can provide important basis for scientific management of power plant managers, and can effectively guide daily production activities. At present, index calculation is realized by a manual calculation mode or a system code mode, a large amount of manpower is consumed, calculation response is not timely, and the flexible adjustment capability is lacked.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide a power plant operation calculation analysis method based on a graphical modeling technology, which can meet the requirement that power plant personnel independently and quickly construct a production operation model, and automatically calculate and compare operation indexes, thereby assisting the management personnel in making an accurate decision. Firstly, model configuration is completed through a graphical and zero-code modeling form, so that the workload of personnel is greatly reduced; secondly, through an optimization function, index optimization can be performed by using the established model along with the change of the coal price and the electricity price, and more scientific budget estimate plan and plan adjustment are completed in an auxiliary manner; in the actual production process, the actual cost analysis of the whole plant can be automatically carried out, innovative visual comparative analysis is provided, the labor cannot be saved, human errors are avoided, and managers are helped to obtain production information at the first time, so that the decision is quickly carried out.
In order to achieve the purpose, the invention adopts the technical scheme that: a power plant operation calculation analysis method based on a graphical modeling technology comprises the following steps:
s1, constructing an operation index system: creating all indexes around the operation and production requirements of the power plant, and carrying out hierarchical classification management on the indexes in a tree form to form an index system;
s2, operation modeling: in the model canvas, the establishment of an operation model is completed through the dragging, the configuration and the connection of operators in a tool box;
s3, model verification: verifying the configured operation model through model calculation calling and result analysis, and if the operation model fails to pass the verification, returning to the step S2 to modify and optimize the model until the model calculation precision meets the requirement;
s4, budget planning: carrying out budget optimization through an optimization analysis tool by utilizing the established model, and then storing the determined budget calculation into a database for subsequent comparative analysis;
s5, operation analysis: and by utilizing the established flow, at the beginning of each month, automatically calculating by utilizing the historical data of the last month, carrying out budget comparison analysis, identifying the main budget deviation and providing an operation decision suggestion.
On the basis of the technical scheme, in the step S1, the indexes comprise technical transformation project cost, repair cost, material cost, water cost, electricity purchase cost, fuel oil cost, fuel secondary cost and other cost.
On the basis of the above technical solution, in step S1, the index management steps are as follows:
a1, creating an index group, giving an index name, and automatically generating a code by a system; index grouping can be nested in multiple layers;
a2, under the selected grouping, creating indexes, enabling the system to support automatic generation of unified index codes, and describing the index characteristics through combination of letters and numbers according to a certain rule and scientific and reasonable arrangement;
and A3, establishing index use types, wherein for each index, a plurality of types can be established for comparative analysis, and the calculation results of the various types are stored in a time sequence database for trend analysis and comparative analysis.
On the basis of the above technical solution, in step S2, the modeling process includes:
b1, dragging an operator in an operator library to a canvas to form a node;
b2, then carrying out parameter configuration on parameters of operators in the nodes;
and B3, connecting the nodes to complete node data transmission, thereby completing the construction of the flow.
On the basis of the technical scheme, in the step S2, the modeling canvas consists of three parts, namely an operator library, a process canvas and a node configuration panel; the operator library is used for supporting operator calculation; the flow canvas provides a dragging type interactive mode to finish index flow construction, operator nodes are dragged into the canvas, and the nodes are connected in series in a connecting line to finish data transmission among the nodes; the node configuration panel mainly defines input and output parameters in the node, configures an input parameter data source and supports direct input of parameter values or data in an associated database so as to complete node calculation.
On the basis of the technical scheme, the operator library integrates three types of operators, including index reference, arithmetic operation and flow calling, and the process is as follows:
the C1 index quoting operator can quote an index from the index library and transmits the index as input to the arithmetic operator;
c2, providing various calculation functions including algebraic operation, trigonometric function, logical operation and logical judgment in the arithmetic operator, wherein the calculation result of the arithmetic operator can be associated with indexes in the index library;
the C3 flow calling operator can call the sub-flows in one flow, and through the mode, a user can manage the complex calculation model in a layered and partitioned mode.
On the basis of the above technical solution, in step S3, the process of model calculation is as follows:
the D1 system collects input parameters and puts the parameters into a cache;
d2, obtaining the calculation priority of each node by using the node connection relation in calculation and a graph sorting algorithm;
d3, performing calculation on the nodes in the calculation graph one by one based on the identified node calculation sequence, intelligently identifying indexes required by the nodes according to the connection relation by a calculation engine, reading the indexes from a cache, and then executing calculation logic configured on the nodes;
and D4, extracting the calculation result, then putting the calculation result into a cache for storage, and finally completing the calculation of all indexes in sequence.
On the basis of the above technical solution, in step S4, the budget optimization is deployed using an optimization analysis tool as follows:
e11, based on the established cost calculation model, appointing undetermined input indexes in the model as free variables, and giving other indexes as fixed values;
e12, defining the cost index minimization as an optimization target;
e13 defines a constraint condition;
e14, optimizing and analyzing by using a genetic algorithm, and obtaining a cost index through repeated calling of the calculation flow in the step S3 in each example in the optimization process, thereby continuously adjusting the optimization direction of the undetermined input index and finally obtaining an optimization result;
and E15, the user obtains different optimization results by appointing a plurality of different input index combinations, and obtains a final budget plan by analyzing and integrating the results.
On the basis of the technical scheme, after a budget scheme is obtained, the budget plan is recorded into a system for subsequent comparative analysis through the following steps:
f11, collecting a budget plan obtained through optimization analysis, and using the budget plan as an input parameter to call a calculation process to obtain all output indexes of budget;
f12 stores the budget input and output into a time sequence database according to codes for subsequent comparison analysis.
On the basis of the above technical solution, step S5 specifically includes the following steps:
g1, completing the acquisition of input data in various modes, including the statistical analysis of production historical data;
g2, taking the collected parameters as input, and calling the calculation flow in the step S3 to obtain the actual cost index of the month;
g3, storing the calculation input and the calculation result into a time sequence database according to codes;
g4, retrieving plan cost data from the step S4 in synchronization with the actual cost, presenting a plan index and an actual index at the same time in the calculation chart, performing comparison display, and performing early warning on the over-budget index;
g5, providing a histogram comparison display of each sub-index under the deviation index, and helping a user to find a main source of the deviation of the early warning index;
g6, for each index, calling actual index change within a period of time, and performing trend analysis;
and G7, outputting all the data and the charts to the current-period operation report according to the template, directly prompting a manager to budget deviation items, deviation reasons and corresponding measures, helping the manager to make a precise decision, realizing refined management, reducing cost and improving efficiency.
The invention has the beneficial effects that:
1. the invention provides a power plant operation calculation analysis system and method based on a graphical modeling technology, which can be applied to daily production and operation activities of a thermal power plant, provide auxiliary decision analysis and avoid wrong decisions of 'brain bag shooting'.
2. The invention provides an index established by a graphical modeling mode, reduces the working pressure of index calculation of power plant personnel, provides an optimization analysis function, improves the flexible strain capacity of the power plant, meets the operation requirements of cost reduction and efficiency improvement of enterprises, simultaneously conforms to the policy requirements of digital reconstruction and intelligent upgrade of the current manufacturing industry, and actively promotes the construction process of an intelligent power plant.
Drawings
FIG. 1 is a schematic diagram of a power plant operation calculation analysis system implementation path of the graphical modeling technology of the present invention;
FIG. 2 is a schematic diagram of a graphical "drag-type" indicator modeling configuration of the present invention;
FIG. 3 is a schematic diagram of the comparative analysis of the business calculation in the present invention.
Detailed Description
The technical scheme and the beneficial effects of the invention are clearer and clearer by further describing the specific embodiment of the invention with the accompanying drawings of the specification. The embodiments described below are exemplary and are intended to be illustrative of the invention, but are not to be construed as limiting the invention.
Referring to fig. 1, the embodiment of the present invention provides a power plant operation calculation analysis method based on graphical modeling technology, which includes five steps,
the first step is to construct an operation index system: the operation indexes of the thermal power plant are complicated and various in types, including technical transformation project cost, repair cost, material cost, water cost, electricity purchase cost, fuel oil cost, fuel secondary cost and other cost, and meanwhile, the number of departments is large, the data source is complex, and centralized carding planning is needed. The system provides an index system building in a tree structure mode, and can flexibly configure a multi-level index structure according to departments, index categories and professional classifications, as shown in the left side of fig. 2. The management steps of the operation index are as follows,
a1, creating an index group, giving an index name, and automatically generating a code by a system; the indicator packets may be nested in multiple layers.
A2, under the selected grouping, indexes are created, the system supports the automatic generation of unified index codes, and the characteristics of the indexes are described through the combination of letters and numbers, according to a certain rule and through scientific and reasonable arrangement.
A3, establishing index use types, establishing a plurality of types for comparative analysis for each index, establishing a budget type and an actual type by default, expanding users according to conditions, and storing calculation results of various types into a time sequence database for trend analysis and comparative analysis.
The second step of operation modeling: in the model canvas, the establishment of the operation model is completed through the dragging, the configuration and the connection of the indexes and the formula operators in the tool box, as shown in the right side of fig. 2. The modeling process includes the steps of,
b1, dragging an operator in an operator library to a canvas to form a node;
b2, then carrying out parameter configuration on parameters of operators in the nodes;
and B3, connecting the nodes to complete node data transmission, thereby completing the construction of the flow.
The operator library determines the performance of a modeling function, and integrates three types of operators, including index reference, arithmetic operation and flow calling.
The C1 index quoting operator can quote an index from the index library and transmits the index as input to the arithmetic operator;
the C2 arithmetic operator provides various calculation functions including algebraic operation, trigonometric function, logical operation and logical judgment, and the calculation result of the arithmetic operator can be associated with the indexes in the index library.
The C3 flow calling operator can call the sub-flows in one flow, and through the mode, a user can manage the complex calculation model in a layered and partitioned mode.
Third step model verification: and (3) verifying the configured operation model through model calculation calling and result analysis, and if the model is not verified, returning to the step S2 to revise and optimize the model until the calculation precision of the model meets the requirement. The process of the model calculation is that,
the D1 system collects input parameters and puts the parameters into a cache;
d2, obtaining the calculation priority of each node by using the node connection relation in calculation and a graph sorting algorithm;
d3, performing calculation on the nodes in the calculation graph one by one based on the identified node calculation sequence, intelligently identifying indexes required by the nodes according to the connection relation by a calculation engine, reading the indexes from a cache, and then executing calculation logic configured on the nodes;
and D4, extracting the calculation result, then putting the calculation result into a cache for storage, and finally completing the calculation of all indexes in sequence.
Fourthly, budget planning: and performing budget optimization through an optimization analysis tool provided by the system by using the established model, and then storing the determined budget calculation into a database for subsequent comparative analysis.
Deployment of budget optimization using an optimization analysis tool is as follows,
e11, based on the established cost calculation model, designating the input indexes to be determined in the model as free variables, and setting other indexes as fixed values;
e12, defining the cost index minimization as an optimization target;
e13, defining a constraint condition, such as the minimum proportion of scientific and technological expenditure in the total income;
and E14, optimizing and analyzing by using a genetic algorithm, and obtaining a cost index through repeated calling of the calculation flow in the third step in each calculation example in the optimization process, thereby continuously adjusting the optimization direction of the undetermined input index and finally obtaining an optimization result.
And E15, the user obtains different optimization results by appointing a plurality of different input index combinations, and the final budget plan is obtained by analyzing and integrating the results through experts.
After the budget plan is obtained, the budget plan is recorded into the system for subsequent comparative analysis through the following steps,
f11, collecting the budget plan obtained through optimization analysis, using the budget plan as an input parameter to call a calculation process to obtain all output indexes of the budget
F12, storing the budget input and output into a time sequence database according to codes for subsequent comparison analysis.
And fifthly, operation analysis: by utilizing the established flow, at the beginning of each month, the historical data of the previous month is utilized to automatically calculate, compare and analyze budgeting, identify main budget deviation and provide an operation decision suggestion, so that a decision maker is assisted to make a quick and accurate management decision, as shown in fig. 3.
G1 completes the collection of input data in a number of ways, including statistical analysis from production history data, such as power generation, data reading from ERP, and prompting the user for manual input, such as purchase coal price.
G2, taking the collected parameters as input, and calling the calculation flow in the third step to obtain the actual cost index of the month;
and G3, storing the calculation input and the calculation result into a time sequence database according to codes.
G4, retrieving plan cost data from the fourth step in synchronization with the actual cost, presenting a plan index and an actual index at the same time of the calculation chart, comparing and displaying, and early warning the over-budget index;
g5, providing comparison and display of histograms of all sub-indexes under the deviation indexes, and helping a user to find a main source of the deviation of the early warning index.
And G6, for each index, calling actual index change in a period of time, and performing trend analysis.
And G7, outputting the actual data, the budget and actual comparison, the index trend data and the chart to a current management report according to a template, and directly prompting a manager to budget deviation items, deviation reasons and corresponding measures, so that the manager is helped to make an accurate decision, fine management is realized, cost is reduced, and efficiency is improved.
The invention greatly reduces key indexes surrounded by each department of the power plant, including data acquisition, automatic calculation, comparative analysis and optimization analysis of technical transformation project cost, repair cost, material cost, water cost, electricity purchase cost, fuel oil cost, fuel secondary cost and other costs. The method and the system realize that index calculation logic modeling and index system management are completed in a 'dragging' interaction mode based on a graphical modeling technology, simultaneously vividly show index calculation results in a system page configuration and diagrammatizing mode, provide budget and actual measurement index comparative analysis, historical trend analysis and optimized analysis capacity, greatly reduce the working pressure of personnel, improve the working efficiency, and simultaneously provide comprehensive analysis data for managers in time, so that the production management and management of the power plant are more precise and scientific, and cost is reduced and efficiency is improved.
In the description of the specification, references to the description of "one embodiment", "preferably", "an example", "a specific example" or "some examples" or the like are intended to mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention, and the schematic representation of the term in this specification does not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The present invention is not limited to the above-described embodiments, and it will be apparent to those skilled in the art that various modifications and improvements can be made without departing from the principle of the present invention, and such modifications and improvements are also considered to be within the scope of the present invention. Those not described in detail in this specification are well within the skill of the art.
Claims (10)
1. A power plant operation calculation analysis method based on a graphical modeling technology is characterized by comprising the following steps:
s1, constructing an operation index system: creating all indexes around the operating and production requirements of the power plant, and performing hierarchical classification management on the indexes in a tree form to form an index system;
s2, operating and modeling: in the model canvas, the establishment of an operation model is completed through dragging, configuration and connection of operators in a tool box;
s3, model verification: verifying the configured operation model through model calculation calling and result analysis, and returning to the step S2 to revise and optimize the model if the model is not verified until the model calculation precision meets the requirement;
s4, budget planning: carrying out budget optimization through an optimization analysis tool by utilizing the established model, and then storing the determined budget calculation into a database for subsequent comparative analysis;
s5, operation analysis: and by utilizing the established flow, at the beginning of each month, automatically calculating by utilizing the historical data of the last month, carrying out budget comparison analysis, identifying the main budget deviation and providing an operation decision suggestion.
2. The method for computationally analyzing power plant operation based on graphical modeling technology as claimed in claim 1, wherein in step S1, the operation index includes technical improvement project cost, repair cost, material cost, water cost, electricity purchase cost, fuel oil cost, fuel secondary cost and other cost.
3. The power plant operation calculation analysis method based on the graphical modeling technology as claimed in claim 1, wherein in step S1, the management steps of the index are as follows:
a1, creating an index group, giving an index name, and automatically generating a code by a system; index groupings can be nested in multiple layers;
a2, under the selected grouping, creating indexes, enabling the system to support automatic generation of unified index codes, and describing the index characteristics through combination of letters and numbers according to a certain rule and scientific and reasonable arrangement;
and A3, establishing index use types, wherein for each index, a plurality of types can be established for comparative analysis, and the calculation results of the various types are stored in a time sequence database for trend analysis and comparative analysis.
4. The power plant operation calculation analysis method based on the graphical modeling technology as claimed in claim 1, wherein in the step S2, the modeling process comprises:
b1, dragging an operator in an operator library to a canvas to form a node;
b2, then carrying out parameter configuration on parameters of operators in the nodes;
and B3, connecting the nodes to complete node data transmission, thereby completing the construction of the flow.
5. The power plant operation calculation analysis method based on the graphical modeling technology as claimed in claim 1, wherein in step S2, the modeling canvas consists of three parts, namely, an operator library, a process canvas and a node configuration panel; the operator library is used for supporting operator calculation; the flow canvas provides a dragging type interactive mode to finish index flow construction, operator nodes are dragged into the canvas, and the nodes are connected in series in a connecting line to finish data transmission among the nodes; the node configuration panel mainly defines input and output parameters in the node, configures an input parameter data source and supports direct input of parameter values or data in an associated database so as to complete node calculation.
6. The power plant operation calculation analysis method based on the graphical modeling technology, as recited in claim 5, wherein the operator library integrates three types of operators, including index reference, arithmetic operation and process call, and the process is as follows:
the C1 index quoting operator can quote an index from the index library and transmits the index as input to the arithmetic operator;
c2, providing various calculation functions including algebraic operation, trigonometric function, logical operation and logical judgment in the arithmetic operator, wherein the calculation result of the arithmetic operator can be associated with indexes in the index library;
the C3 flow calling operator can call the sub-flows in one flow, and through the mode, a user can manage the complex calculation model in a layered and partitioned mode.
7. The method for analyzing the operation calculation of the power plant based on the graphical modeling technology as claimed in claim 1, wherein in the step S3, the model calculation process is as follows:
the D1 system collects input parameters and puts the input parameters into a cache;
d2, obtaining the calculation priority of each node by using the node connection relation in calculation and a graph sorting algorithm;
d3, performing calculation on the nodes in the calculation graph one by one based on the identified node calculation sequence, intelligently identifying indexes required by the nodes according to the connection relation by a calculation engine, reading the indexes from a cache, and then executing calculation logic configured on the nodes;
and D4, extracting the calculation result, then putting the calculation result into a cache for storage, and finally completing the calculation of all indexes in sequence.
8. The graphical modeling technique based plant operation calculation analysis method of claim 1, wherein in step S4, budget optimization deployment using optimization analysis tools is as follows:
e11, based on the established cost calculation model, designating the input indexes to be determined in the model as free variables, and setting other indexes as fixed values;
e12, defining the cost index minimization as an optimization target;
e13 defines a constraint condition;
e14, optimizing and analyzing by using a genetic algorithm, and obtaining a cost index through repeated calling of the calculation flow in the step S3 in each calculation example in the optimization process, thereby continuously adjusting the optimization direction of the undetermined input index and finally obtaining an optimization result;
and E15, the user obtains different optimization results by appointing a plurality of different input index combinations, and obtains the final budget plan by analyzing and integrating the results.
9. The power plant operation calculation analysis method based on graphical modeling technology of claim 8, wherein after obtaining the budget plan, the budget plan is entered into the system for subsequent comparative analysis by:
f11, collecting a budget plan obtained through optimization analysis, and using the budget plan as an input parameter to call a calculation process to obtain all output indexes of budget;
f12 stores the budget input and output into a time sequence database according to codes for subsequent comparison analysis.
10. The graphical modeling technology-based plant operation calculation analysis method according to claim 1, wherein the step S5 specifically comprises the following steps:
g1, completing the acquisition of input data in various ways, including statistical analysis of production historical data;
g2, taking the collected parameters as input, and calling the calculation flow in the step S3 to obtain the actual cost index of the month;
g3, storing the calculation input and the calculation result into a time sequence database according to codes;
g4, retrieving plan cost data from the step S4 in synchronization with the actual cost, presenting a plan index and an actual index at the same time in the calculation chart, performing comparison display, and performing early warning on the over-budget index;
g5, providing a histogram comparison display of each sub-index under the deviation index, and helping a user to find a main source of the deviation of the early warning index;
g6, for each index, calling actual index change within a period of time, and performing trend analysis;
and G7, outputting all the data and the charts to the current-period management report according to the template, directly prompting a manager to budget deviation items, deviation reasons and corresponding measures, helping the manager to make a precise decision, realizing fine management, reducing cost and improving efficiency.
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