CN117117983A - Thermal power plant peak regulation management method and system combining power distribution network requirements - Google Patents
Thermal power plant peak regulation management method and system combining power distribution network requirements Download PDFInfo
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
- H02J3/466—Scheduling the operation of the generators, e.g. connecting or disconnecting generators to meet a given demand
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/003—Load forecast, e.g. methods or systems for forecasting future load demand
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/10—Power transmission or distribution systems management focussing at grid-level, e.g. load flow analysis, node profile computation, meshed network optimisation, active network management or spinning reserve management
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
- H02J2300/10—The dispersed energy generation being of fossil origin, e.g. diesel generators
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
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Abstract
The application relates to the technical field of power plant peak shaving, and provides a thermal power plant peak shaving management method and system combining power distribution network requirements. The method comprises the following steps: acquiring data of a power distribution network to acquire basic demand data of the power distribution network; acquiring an electric load extremum of a power transmission network; determining electricity consumption data of domestic electricity; carrying out residential electricity identification in the electricity utilization period, simulating electricity utilization data of a thermal power plant, and obtaining simulated electricity utilization data of the thermal power plant; inputting the electricity consumption data of the resident electricity consumption and the simulated electricity consumption data of the thermal power plant into an electric power depth peak shaving model, and outputting the depth peak shaving data of the thermal power plant; and carrying out peak shaving management on the thermal power plant based on the thermal power plant depth peak shaving data. The application solves the technical problem of overlarge load of the power transmission network caused by the operation of the thermal power generating unit and the simultaneous power utilization of resident power utilization peaks in the prior art, and achieves the technical effects of keeping the steady operation of the thermal power generating unit, avoiding overlarge load and damage to the power transmission network and keeping the power utilization stability of users.
Description
Technical Field
The application relates to the technical field of power plant peak shaving, in particular to a thermal power plant peak shaving management method and system combining power distribution network requirements.
Background
A thermal power plant is a thermal power plant for short, and is a plant for producing electric energy by using combustible materials (such as coal) as fuel. Because the operation of the thermal power generating unit of the thermal power plant needs electricity, the daily life of residents also needs electricity, the peak of electricity consumption of the daily life of residents can be just touched when the thermal power generating unit operates, and the problem of overlarge network load can be caused to a power transmission network.
In summary, the application solves the technical problem of overlarge load of a power transmission network caused by simultaneous power utilization of the operation of the thermal power generating unit and the peak of resident power utilization in the prior art.
Disclosure of Invention
Based on the above, it is necessary to provide a thermal power plant peak regulation management method and system combining the power distribution network requirements to improve the power supply efficiency and the energy utilization rate. The application solves the technical problems of low energy utilization rate and serious energy waste condition of the thermal power plant in the prior art, and achieves the technical effects of improving the power supply efficiency and the energy utilization rate.
In a first aspect, an embodiment of the present application provides a thermal power plant peak shaving management method in combination with a power distribution network demand, where the method includes: based on a big data analysis technology, acquiring data of a power distribution network to acquire basic demand data of the power distribution network; acquiring an electric load extremum of a power transmission network according to the basic demand data of the power distribution network; the method comprises the steps of calling a periodic electricity utilization curve of residential electricity utilization through an electricity utilization system, and determining electricity utilization data of residential electricity utilization; carrying out residential electricity identification in an electricity utilization period according to the electricity utilization data of residents, simulating the electricity utilization data of a thermal power plant according to identification information, and obtaining simulated electricity utilization data of the thermal power plant; inputting the electricity consumption data of the resident electricity consumption and the simulated electricity consumption data of the thermal power plant into an electric power depth peak shaving model, and outputting the depth peak shaving data of the thermal power plant; and carrying out peak shaving management on the thermal power plant based on the thermal power plant depth peak shaving data.
In a second aspect, an embodiment of the present application provides a peak shaving management system for a thermal power plant in combination with a power distribution network demand, where the system includes: the power distribution network basic demand data acquisition module is used for acquiring data of the power distribution network based on a big data analysis technology and acquiring power distribution network basic demand data; the electric load extremum acquisition module is used for acquiring an electric load extremum of the power transmission network according to the basic demand data of the power distribution network; the resident electricity data determining module is used for calling a periodic electricity utilization curve of resident electricity through the electricity utilization system to determine resident electricity utilization data; the thermal power plant electricity data simulation module is used for carrying out residential electricity identification in an electricity utilization period according to the electricity utilization data of the residential electricity, simulating the thermal power plant electricity data according to the identification information and obtaining the thermal power plant simulated electricity data; the thermal power plant depth peak regulation data output module is used for inputting the electricity utilization data of resident electricity and the simulated electricity utilization data of the thermal power plant into an electric power depth peak regulation model and outputting thermal power plant depth peak regulation data; the thermal power plant peak shaving management module is used for carrying out peak shaving management on the thermal power plant based on the thermal power plant depth peak shaving data.
One or more technical schemes provided by the application have at least the following technical effects or advantages:
firstly, based on a big data analysis technology, carrying out data acquisition on a power distribution network to acquire basic demand data of the power distribution network; secondly, acquiring an electric load extremum of a power transmission network according to the basic demand data of the power distribution network; then, through the electricity utilization system, a periodic electricity utilization curve of residential electricity utilization is called, and electricity utilization data of residential electricity utilization is determined; then, according to the electricity consumption data of the residents, residential electricity identification is carried out in an electricity consumption period, and according to the identification information, the electricity consumption data of the thermal power plant is simulated, and the simulated electricity consumption data of the thermal power plant is obtained; then, the electricity consumption data of the resident electricity and the simulated electricity consumption data of the thermal power plant are input into an electric power depth peak shaving model, and the thermal power plant depth peak shaving data is output; and finally, carrying out peak shaving management on the thermal power plant based on the thermal power plant depth peak shaving data. The application solves the technical problem of overlarge load of the power transmission network caused by the operation of the thermal power generating unit and the simultaneous power utilization of resident power utilization peaks in the prior art, and achieves the technical effects of keeping the steady operation of the thermal power generating unit, avoiding overlarge load and damage to the power transmission network and keeping the power utilization stability of users.
The foregoing description is only an overview of the present application, and is intended to be implemented in accordance with the teachings of the present application in order that the same may be more clearly understood and to make the same and other objects, features and advantages of the present application more readily apparent.
Drawings
FIG. 1 is a schematic flow chart of a thermal power plant peak shaver management method in combination with power distribution network requirements according to an embodiment;
FIG. 2 is a schematic flow chart of a method for peak shaver management of a thermal power plant in combination with power distribution network requirements according to an embodiment of the present application;
fig. 3 is a block diagram of a thermal power plant peak shaver management system that incorporates power distribution network requirements in one embodiment.
Reference numerals illustrate: the system comprises a power distribution network basic demand data acquisition module 11, an electric load extremum acquisition module 12, a resident electricity data determination module 13, a thermal power plant electricity data simulation module 14, a thermal power plant deep peak regulation data output module 15 and a thermal power plant peak regulation management module 16.
Detailed Description
The present application will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present application more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.
Having introduced the basic principles of the present application, the technical solutions of the present application will now be clearly and fully described with reference to the accompanying drawings, it being apparent that the embodiments described are only some, but not all, embodiments of the present application, and it is to be understood that the present application is not limited to the exemplary embodiments described herein. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application. It should be further noted that, for convenience of description, only some, but not all of the drawings related to the present application are shown.
As shown in fig. 1, the application provides a thermal power plant peak shaving management method combined with power distribution network requirements, which comprises the following steps:
s100: based on a big data analysis technology, acquiring data of a power distribution network to acquire basic demand data of the power distribution network;
the application provides a thermal power plant peak regulation management method combining power distribution network requirements, which is characterized in that basic demand data of a power distribution network and power transmission network power load extremum are acquired, power consumption data of domestic electricity are determined, the power consumption data of the thermal power plant is simulated according to identification information, and then the deep peak regulation data of the thermal power plant is obtained through a deep peak regulation model of the thermal power plant, so that the thermal power plant is subjected to peak regulation management, the technical problem of overlarge power transmission network load caused by simultaneous power consumption of operation of a thermal power unit and peak of resident power consumption in the prior art is solved, and the technical effects of keeping stable operation of the thermal power unit, avoiding overlarge load and damage to the power transmission network and keeping user power consumption stable are achieved.
Big data analysis techniques are a collection of large and complex data sets that are difficult to store and process, including capturing, managing, storing, searching, sharing, transmitting, analyzing and visualizing, using available database management tools or traditional data processing applications; the distribution network is a power network which receives electric energy from a power transmission network or a regional power plant and distributes the electric energy to various users locally through a distribution facility or distributes the electric energy step by step according to voltage; the data acquisition is a process of automatically acquiring information from analog and digital tested units such as sensors and other devices to be tested, and the process of automatically acquiring information from a power distribution network; the basic demand data of the power distribution network are power supply data, power consumption data and the like of the power distribution network. Based on big data analysis technology, carry out data acquisition to the distribution network, acquire distribution network basic demand data, through the acquisition to distribution network basic demand data, make the bedding for obtaining electric load extremum later on.
As shown in fig. 2, further, the steps of the present application include:
s110: in a preset power distribution period, power supply monitoring is carried out on the power distribution network, and power supply data are obtained;
s120: determining an electricity load value in the preset power distribution period according to the power supply data;
s130: calculating electricity consumption data in the preset power distribution period based on the electricity load value;
s140: and determining the basic demand data of the power distribution network through the electricity consumption data.
Specifically, the preset power distribution period is data set by a worker, and the period comprises a peak value and a valley value of power supply and power consumption of the power distribution network according to actual conditions; the power supply monitoring is to monitor and measure the power supply condition of the power distribution network, such as voltage, frequency, harmonic wave and the like; the power supply data are data such as electric quantity, load and voltage provided by the power distribution network; the electricity load value refers to the sum of the electric power taken by the electric equipment to the electric power system at a certain moment; the electricity consumption data refer to the consumption data of energy sources when the power distribution network supplies power.
In a preset power distribution period, power supply monitoring is carried out on the power distribution network, and power supply data are obtained; determining an electricity load value in the preset power distribution period according to the power supply data; calculating electricity consumption data in the preset power distribution period based on the electricity load value; and determining the basic demand data of the power distribution network through the electricity consumption data. And by acquiring the basic demand data of the power distribution network, contribution is made to the follow-up acquisition of the electric load extremum of the power transmission network.
S200: acquiring an electric load extremum of a power transmission network according to the basic demand data of the power distribution network;
specifically, the power transmission network is a network for transmitting electric energy, is an important component link of the overall function of the power system, establishes a power plant at a place with proper primary energy resource conditions such as hydraulic power, coal and the like, and can transmit the electric energy to a load center far away from the power plant through power transmission, so that the development and the utilization of the electric energy exceed the limitation of regions; an electrical load extremum refers to the maximum value of the electrical load that can be carried in the electrical transmission network. And acquiring an electric load extremum of the power transmission network according to the basic demand data of the power distribution network. By acquiring the electricity load extreme value of the power transmission network, a bedding is made for the follow-up simulation of the electricity consumption data of the thermal power plant.
S300: the method comprises the steps of calling a periodic electricity utilization curve of residential electricity utilization through an electricity utilization system, and determining electricity utilization data of residential electricity utilization;
in particular, the power system refers to a power utility, which refers to equipment and accessories that are powered by a consumer from receiving power to all power delivered by the consumer. The periodic electricity utilization curve refers to electricity utilization conditions of residents in one period, and has time marks; the electricity consumption data refers to electricity consumption data of residents at a certain moment. The method comprises the steps of calling a periodic electricity utilization curve of residential electricity utilization through an electricity utilization system, and determining electricity utilization data of residential electricity utilization; the method is used for making a bedding for the acquisition of the electricity consumption peak value, the electricity consumption valley value, the electricity consumption peak value period and the electricity consumption valley value period of the residents.
Further, the steps of the application also comprise:
s310: determining a resident electricity utilization period based on electricity utilization nodes in a resident electricity utilization rule;
s320: extracting resident electricity consumption period information and resident electricity consumption information according to the resident electricity consumption period;
s330: taking the electricity consumption time period of the residents as a first coordinate axis and taking the electricity consumption information of the residents as a second coordinate axis;
s340: and constructing a periodic electricity utilization curve of the resident electricity utilization through the first coordinate axis and the second coordinate axis.
Specifically, the electricity utilization rule refers to a rule of using electricity by residents, for example, in a day, the electricity consumption of the residents is lower in the daytime, but becomes higher after a time point at night and becomes lower when the residents sleep, and the electricity utilization rule is called as the electricity utilization rule of the residents in a period of time; the electricity utilization node refers to a time node of using electric power by residents, and the electricity utilization period of the residents refers to a time period of using the electric power by the residents and is determined by the electricity utilization node; the electricity consumption time period information refers to time period information of resident electricity consumption, such as seven to eleven at night; the resident electricity consumption information refers to the electricity consumption of residents, and can be obtained by inquiring an ammeter or a power system.
Determining a resident electricity utilization period based on electricity utilization nodes in a resident electricity utilization rule; extracting resident electricity consumption period information and resident electricity consumption information according to the resident electricity consumption period; taking the electricity consumption time period of the residents as a first coordinate axis and taking the electricity consumption information of the residents as a second coordinate axis; and constructing a periodic electricity utilization curve of the resident electricity utilization through the first coordinate axis and the second coordinate axis. And laying a cushion for obtaining residential electricity load data for subsequent calculation by constructing a periodic electricity utilization curve of the residential electricity utilization.
Further, the steps of the application also comprise:
s350: based on the periodic electricity utilization curve of the resident electricity, extracting a maximum value and a minimum value in the curve to be respectively used as an electricity utilization peak value and an electricity utilization valley value of the resident;
s360: reversely matching the electricity consumption peak value, the electricity consumption valley value and the periodic electricity consumption curve of the resident electricity consumption, and determining an electricity consumption peak value period and an electricity consumption valley value period;
s370: calculating according to the electricity consumption peak value, the electricity consumption valley value, the electricity consumption peak value period and the electricity consumption valley value period to obtain domestic electric load data;
s380: and adding the resident electricity load data to the electricity consumption data.
Specifically, the electricity consumption peak value and the electricity consumption valley value refer to the maximum value and the minimum value of the electricity consumption of residents respectively; reverse matching refers to; the electricity peak value time period and the electricity valley value time period respectively refer to a time point of maximum electricity consumption and a time point of minimum electricity consumption of residents; the residential electrical load data refers to the sum of the electrical power taken by the electrical equipment of the residents to the electrical power system at a certain moment.
Based on the periodic electricity utilization curve of the resident electricity, extracting a maximum value and a minimum value in the curve to be respectively used as an electricity utilization peak value and an electricity utilization valley value of the resident; reversely matching the electricity consumption peak value, the electricity consumption valley value and the periodic electricity consumption curve of the resident electricity consumption, and determining an electricity consumption peak value period and an electricity consumption valley value period; calculating according to the electricity consumption peak value, the electricity consumption valley value, the electricity consumption peak value period and the electricity consumption valley value period to obtain domestic electric load data; and adding the resident electricity load data to the electricity consumption data. According to the obtained electricity consumption data, resident electricity consumption identifiers in the electricity consumption period can be obtained, and a mat is made for the electricity consumption data of the follow-up honey-spreading thermal power plant.
S400: carrying out residential electricity identification in an electricity utilization period according to the electricity utilization data of residents, simulating the electricity utilization data of a thermal power plant according to identification information, and obtaining simulated electricity utilization data of the thermal power plant;
specifically, the resident electricity consumption identification refers to marking and identifying time nodes of resident electricity consumption, for example, the time nodes of the electricity consumption and the time nodes of the electricity non-consumption in a day take a day as a period, and the time nodes of the electricity consumption are identified; the simulation of the power consumption data of the thermal power plant refers to marking the time of using electricity through the identification of resident electricity consumption in the electricity consumption period, finding idle time, interleaving the power consumption of the thermal power plant, simulating the electricity consumption period and the power consumption of the thermal power plant, and making a bedding for the follow-up construction of the power depth peak regulation model.
S500: inputting the electricity consumption data of the resident electricity consumption and the simulated electricity consumption data of the thermal power plant into an electric power depth peak shaving model, and outputting the depth peak shaving data of the thermal power plant;
specifically, the deep peak shaving refers to an operation mode that the peak shaving is carried out by the generator set exceeding the basic peak shaving range because the peak-valley difference of the load of the power grid is greatly influenced, so that the power of each thermal power plant is reduced, and the load rate of the deep peak shaving is 40-30 percent in general; and inputting the electricity consumption data of the resident electricity consumption and the simulated electricity consumption data of the thermal power plant into an electric power depth peak shaving model, and outputting the depth peak shaving data of the thermal power plant. And (3) paving a subsequent peak regulation management for the thermal power plant by constructing an electric power depth peak regulation model.
Further, the method comprises the following steps:
s510: based on a BP neural network, constructing the electric power depth peak shaving model, wherein input data of the electric power depth peak shaving model comprise electricity utilization data of resident electricity utilization and simulated electricity utilization data of the thermal power plant, and output data comprise the depth peak shaving data of the thermal power plant;
s520: the electric power depth peak regulation model comprises a data input layer, a depth peak regulation control layer and a peak regulation result output layer;
s530: respectively marking the resident electricity load data contained in the resident electricity consumption data and the thermal power plant simulation electricity load data contained in the thermal power plant simulation electricity consumption data to obtain a construction data set, wherein the construction data set comprises a training set and a verification set;
s540: and performing supervision training and verification on the electric power depth peak shaving model by adopting the training set and the verification set until the electric power depth peak shaving model converges or the accuracy reaches a preset requirement, and outputting the depth peak shaving data of the thermal power plant.
Specifically, based on the electricity data of the resident electricity and the simulated electricity data of the thermal power plant, a power depth peak shaving model is constructed, and the process of constructing the power depth peak shaving model is as follows: based on a BP neural network, constructing a network structure of the electric power depth peak shaving model, wherein the electric power depth peak shaving model comprises a data input layer, a depth peak shaving control layer and a peak shaving result output layer; the electric power depth peak shaving model comprises a plurality of simple units simulating human brain neurons, the electric power depth peak shaving model can form parameters such as weight, threshold and the like connected between the simple units in the supervision training process, the electric power depth peak shaving model after training can carry out complex nonlinear logic operation according to input data, the electric power plant depth peak shaving data are output, the input data of the electric power depth peak shaving model are power consumption data of resident power consumption and simulated power consumption data of the thermal power plant, and the output data are the thermal power plant depth peak shaving data. The method comprises the steps of obtaining a construction data set and constructing an electric power depth peak shaving model, wherein the construction data set comprises resident electricity load data contained in resident electricity consumption data and thermal power plant simulation electricity load data contained in thermal power plant simulation electricity consumption data for data marking, and further the construction data set is subjected to data marking and divided according to a certain proportion to obtain a training set and a verification set. And training and verifying the power depth peak shaving model through the constructed data set to obtain the power depth peak shaving model.
The electric power depth peak regulation model is a neural network model which can be continuously subjected to iterative optimization in machine learning, and is obtained through supervision training by a training set. Dividing the constructed data set into a training set and a verification set according to a preset data dividing rule, wherein the preset data dividing proportion can be set in a user-defined manner based on actual conditions by a person skilled in the art, for example: 85%, 15%. The power depth peak shaving model is supervised and trained through the training set, when the model output results tend to be in a convergence state, the verification set is used for verifying the accuracy of the output results of the power depth peak shaving model, a preset verification accuracy index is obtained, and a person skilled in the art can customize setting based on actual conditions, for example: 90%. And when the accuracy of the output result of the electric power depth peak shaving model is more than or equal to the preset verification accuracy index, obtaining the electric power depth peak shaving model. By constructing the electric power depth peak shaving model based on the BP neural network, the efficiency and accuracy of obtaining the depth peak shaving data of the thermal power plant can be improved.
S600: and carrying out peak shaving management on the thermal power plant based on the thermal power plant depth peak shaving data.
Specifically, the peak shaving refers to the whole process of controlling the generated energy according to the user demand, and the peak shaving management is performed on the generated energy of the thermal power plant according to the depth peak shaving data of the thermal power plant according to the user demand. The effects of improving the power supply efficiency and the energy utilization rate are achieved.
Further, the method comprises the following steps:
s610: acquiring a power peak value period and a power valley value period of the thermal power plant according to the deep peak regulation data of the thermal power plant;
s620: extracting abnormal fault information of a historical thermal power plant, and comparing data of the peak value period of the thermal power plant and the valley value period of the thermal power plant to determine abnormal fault nodes of the thermal power plant;
s630: data monitoring of the power plant electrical load is carried out on the abnormal fault node of the thermal power plant, and when the power plant electrical load is larger than a preset electrical load, a regulation and control alarm instruction is generated;
s640: and carrying out abnormal correction on the electricity load of the thermal power plant according to the regulation and control alarm instruction.
Specifically, the peak power consumption period and the valley power consumption period of the thermal power plant refer to the time points of the highest and lowest power consumption of the thermal power plant; the historical abnormal fault information of the thermal power plant refers to information when the thermal power plant generates faults in the past time period, such as electricity consumption and electricity consumption time period when the thermal power plant generates the abnormality; abnormal fault nodes of the thermal power plant mean that faults are generated in a certain time period or a certain place, such as a superheater fault, a problem of a turbine unit and the like; the preset electricity load is an electricity load value set by a worker by himself, if the electricity load of the thermal power plant is larger than the preset electricity load, abnormal faults of the thermal power plant are proved to occur, for example, the preset electricity load is set to 10000w, when the electricity load of an abnormal fault node of the thermal power plant is smaller than the preset electricity load, the abnormal fault node of the thermal power plant is proved to be likely to have the problems of machine aging and the like, and if the electricity load of the abnormal fault node of the thermal power plant is larger than the preset electricity load, the abnormal fault node of the thermal power plant is proved to confirm the faults; the regulation and control alarm instruction refers to a command for sending out early warning when the power load of the thermal power plant is regulated and controlled.
Acquiring a power peak value period and a power valley value period of the thermal power plant according to the deep peak regulation data of the thermal power plant; extracting abnormal fault information of a historical thermal power plant, and comparing data of the peak value period of the thermal power plant and the valley value period of the thermal power plant to determine abnormal fault nodes of the thermal power plant; data monitoring of the power plant electrical load is carried out on the abnormal fault node of the thermal power plant, and when the power plant electrical load is larger than a preset electrical load, a regulation and control alarm instruction is generated; according to the regulation and control alarm instruction, the abnormal correction of the electricity load of the thermal power plant is carried out, and the embodiment of the application achieves the technical effect of reducing the failure times and the power failure time of the thermal power plant.
The application provides a thermal power plant peak regulation management method combining power distribution network demands, which is characterized in that basic demand data of a power distribution network and power transmission network power load extremum are acquired, power consumption data of domestic power is determined, power consumption data of a thermal power plant is simulated according to identification information, and the thermal power plant deep peak regulation data is obtained through a thermal power plant deep peak regulation model to carry out peak regulation management on the thermal power plant.
As shown in fig. 3, the present application further provides a peak shaving management system of a thermal power plant for combining the demands of a power distribution network, where the system includes:
the power distribution network basic demand data acquisition module 11 is used for acquiring data of the power distribution network based on a big data analysis technology to acquire power distribution network basic demand data;
the electric load extremum acquisition module 12 is used for acquiring an electric load extremum of the power transmission network according to the basic requirement data of the power distribution network;
the resident electricity data determining module 13 is used for determining resident electricity data by calling a periodic electricity utilization curve of resident electricity through the electricity utilization system;
the thermal power plant electricity data simulation module 14 is used for carrying out residential electricity identification in an electricity utilization period according to electricity utilization data of the residents, simulating the thermal power plant electricity data according to the identification information, and obtaining thermal power plant simulated electricity data;
the thermal power plant depth peak regulation data output module 15 is used for inputting the electricity utilization data of resident electricity and the simulated electricity utilization data of the thermal power plant into an electric power depth peak regulation model and outputting the thermal power plant depth peak regulation data;
the thermal power plant peak shaving management module 16, the thermal power plant peak shaving management module 16 is used for carrying out peak shaving management on the thermal power plant based on the thermal power plant depth peak shaving data.
Further, the embodiment of the application further comprises:
the power supply data acquisition module is used for carrying out power supply monitoring on the power distribution network in a preset power distribution period to acquire power supply data;
the power consumption load value determining module is used for determining the power consumption load value in the preset power distribution period according to the power supply data;
the electricity consumption data calculation module is used for calculating electricity consumption data in the preset power distribution period based on the electricity load value;
and the power distribution network basic demand data acquisition module is used for determining the power distribution network basic demand data through the power consumption data.
Further, the embodiment of the application further comprises:
the resident electricity utilization period determining module is used for determining resident electricity utilization periods based on electricity utilization nodes in resident electricity utilization laws;
the resident electricity consumption information extraction module is used for extracting resident electricity consumption period information and resident electricity consumption information according to the resident electricity consumption period;
the resident electricity coordinate axis establishment module is used for taking the resident electricity utilization period as a first coordinate axis and taking the resident electricity utilization information as a second coordinate axis;
and the periodic electricity utilization curve construction module is used for constructing the periodic electricity utilization curve of the resident electricity through the first coordinate axis and the second coordinate axis.
Further, the embodiment of the application further comprises:
the resident electricity utilization extremum extraction module is used for extracting a maximum value and a minimum value in a curve based on a periodic electricity utilization curve of the resident electricity utilization, and the maximum value and the minimum value are respectively used as an electricity utilization peak value and an electricity utilization valley value of the resident;
the resident electricity curve matching module is used for reversely matching the electricity peak value, the electricity valley value and the periodic electricity curve of resident electricity to determine an electricity peak value period and an electricity valley value period;
the resident electricity load data calculation module is used for calculating and obtaining resident electricity load data according to the electricity consumption peak value, the electricity consumption valley value, the electricity consumption peak value period and the electricity consumption valley value period;
and the electricity consumption data adding module is used for adding the resident electricity load data into the electricity consumption data.
Further, the embodiment of the application further comprises:
the power depth peak shaving model construction module is used for constructing the power depth peak shaving model based on a BP neural network, wherein input data of the power depth peak shaving model comprise power utilization data of resident power utilization and simulated power utilization data of the thermal power plant, and output data comprise the depth peak shaving data of the thermal power plant;
the power depth peak regulation model comprises a module, wherein the power depth peak regulation model comprises a data input layer, a depth peak regulation control layer and a peak regulation result output layer;
the construction data set obtaining module is used for respectively marking the resident electricity load data contained in the resident electricity consumption data and the thermal power plant simulation electricity load data contained in the thermal power plant simulation electricity consumption data to obtain a construction data set, wherein the construction data set comprises a training set and a verification set;
and the thermal power plant depth peak regulation data output module is used for performing supervision training and verification on the electric power depth peak regulation model by adopting the training set and the verification set until the electric power depth peak regulation model converges or the accuracy reaches a preset requirement, and outputting the thermal power plant depth peak regulation data.
Further, the embodiment of the application further comprises:
the thermal power plant electricity period acquisition module is used for acquiring a thermal power plant electricity peak value period and a thermal power plant electricity valley value period according to the thermal power plant deep peak regulation data;
the abnormal fault node determining module of the thermal power plant is used for extracting abnormal fault information of the historical thermal power plant, comparing data of the peak value time period of the thermal power plant and the valley value time period of the thermal power plant, and determining abnormal fault nodes of the thermal power plant;
the regulation and control alarm instruction generation module is used for carrying out data monitoring on the power plant electrical load of the abnormal fault node of the thermal power plant, and when the power plant electrical load is larger than a preset power load, a regulation and control alarm instruction is generated;
and the electricity load abnormality correction execution module is used for carrying out abnormality correction on the electricity load of the thermal power plant according to the regulation and control alarm instruction.
For a specific embodiment of a thermal power plant peak shaving management system that incorporates power distribution network requirements, reference may be made to the above embodiment of a thermal power plant peak shaving management method that incorporates power distribution network requirements, which is not described herein. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The above examples illustrate only a few embodiments of the application, which are described in detail and are not to be construed as limiting the scope of the application. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the application, which are all within the scope of the application. Accordingly, the scope of protection of the present application is to be determined by the appended claims.
Claims (7)
1. A thermal power plant peak shaver management method in combination with power distribution network requirements, the method comprising:
based on a big data analysis technology, acquiring data of a power distribution network to acquire basic demand data of the power distribution network;
acquiring an electric load extremum of a power transmission network according to the basic demand data of the power distribution network;
the method comprises the steps of calling a periodic electricity utilization curve of residential electricity utilization through an electricity utilization system, and determining electricity utilization data of residential electricity utilization;
carrying out residential electricity identification in an electricity utilization period according to the electricity utilization data of residents, simulating the electricity utilization data of a thermal power plant according to identification information, and obtaining simulated electricity utilization data of the thermal power plant;
inputting the electricity consumption data of the resident electricity consumption and the simulated electricity consumption data of the thermal power plant into an electric power depth peak shaving model, and outputting the depth peak shaving data of the thermal power plant;
and carrying out peak shaving management on the thermal power plant based on the thermal power plant depth peak shaving data.
2. The method of claim 1, wherein the obtaining the base demand data for the power distribution network, the method further comprises:
in a preset power distribution period, power supply monitoring is carried out on the power distribution network, and power supply data are obtained;
determining an electricity load value in the preset power distribution period according to the power supply data;
calculating electricity consumption data in the preset power distribution period based on the electricity load value;
and determining the basic demand data of the power distribution network through the electricity consumption data.
3. The method of claim 1, wherein the invoking the periodic electricity usage profile of residential electricity, the method further comprising:
determining a resident electricity utilization period based on electricity utilization nodes in a resident electricity utilization rule;
extracting resident electricity consumption period information and resident electricity consumption information according to the resident electricity consumption period;
taking the electricity consumption time period of the residents as a first coordinate axis and taking the electricity consumption information of the residents as a second coordinate axis;
and constructing a periodic electricity utilization curve of the resident electricity utilization through the first coordinate axis and the second coordinate axis.
4. The method of claim 3, wherein said determining electricity usage data for the residents' electricity usage further comprises:
based on the periodic electricity utilization curve of the resident electricity, extracting a maximum value and a minimum value in the curve to be respectively used as an electricity utilization peak value and an electricity utilization valley value of the resident;
reversely matching the electricity consumption peak value, the electricity consumption valley value and the periodic electricity consumption curve of the resident electricity consumption, and determining an electricity consumption peak value period and an electricity consumption valley value period;
calculating according to the electricity consumption peak value, the electricity consumption valley value, the electricity consumption peak value period and the electricity consumption valley value period to obtain domestic electric load data;
and adding the resident electricity load data to the electricity consumption data.
5. The method of claim 1, wherein the outputting thermal power plant depth peaking data, the method further comprising:
based on a BP neural network, constructing the electric power depth peak shaving model, wherein input data of the electric power depth peak shaving model comprise electricity utilization data of resident electricity utilization and simulated electricity utilization data of the thermal power plant, and output data comprise the depth peak shaving data of the thermal power plant;
the electric power depth peak regulation model comprises a data input layer, a depth peak regulation control layer and a peak regulation result output layer;
respectively marking the resident electricity load data contained in the resident electricity consumption data and the thermal power plant simulation electricity load data contained in the thermal power plant simulation electricity consumption data to obtain a construction data set, wherein the construction data set comprises a training set and a verification set;
and performing supervision training and verification on the electric power depth peak shaving model by adopting the training set and the verification set until the electric power depth peak shaving model converges or the accuracy reaches a preset requirement, and outputting the depth peak shaving data of the thermal power plant.
6. The method of claim 1, wherein the method further comprises:
acquiring a power peak value period and a power valley value period of the thermal power plant according to the deep peak regulation data of the thermal power plant;
extracting abnormal fault information of a historical thermal power plant, and comparing data of the peak value period of the thermal power plant and the valley value period of the thermal power plant to determine abnormal fault nodes of the thermal power plant;
data monitoring of the power plant electrical load is carried out on the abnormal fault node of the thermal power plant, and when the power plant electrical load is larger than a preset electrical load, a regulation and control alarm instruction is generated;
and carrying out abnormal correction on the electricity load of the thermal power plant according to the regulation and control alarm instruction.
7. A thermal power plant peak shaver management system that incorporates power distribution network requirements, the system comprising:
the power distribution network basic demand data acquisition module is used for acquiring data of the power distribution network based on a big data analysis technology and acquiring power distribution network basic demand data;
the electric load extremum acquisition module is used for acquiring an electric load extremum of the power transmission network according to the basic demand data of the power distribution network;
the resident electricity data determining module is used for calling a periodic electricity utilization curve of resident electricity through the electricity utilization system to determine resident electricity utilization data;
the thermal power plant electricity data simulation module is used for carrying out residential electricity identification in an electricity utilization period according to the electricity utilization data of the residential electricity, simulating the thermal power plant electricity data according to the identification information and obtaining the thermal power plant simulated electricity data;
the thermal power plant depth peak regulation data output module is used for inputting the electricity utilization data of resident electricity and the simulated electricity utilization data of the thermal power plant into an electric power depth peak regulation model and outputting thermal power plant depth peak regulation data;
the thermal power plant peak shaving management module is used for carrying out peak shaving management on the thermal power plant based on the thermal power plant depth peak shaving data.
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| CN117387056B (en) * | 2023-12-13 | 2024-03-08 | 华能济南黄台发电有限公司 | Thermal power plant depth peak regulation state monitoring method and system |
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