Batch control method, device and equipment of generator set and medium

Abstract

The invention provides a batch control method and device for generator sets, equipment and a medium. The method comprises the following steps: acquiring coal consumption data of a plurality of generator sets of a target power system; acquiring the generated power of the plurality of generator sets; classifying the generator sets according to the generated power and coal consumption data of the generator sets to obtain a plurality of set categories; clustering the generator sets in each set category to obtain a plurality of operation coal consumption intervals; fitting each operation coal consumption interval to obtain a corresponding no-load cost interval; and calculating the no-load cost of each generator set based on each no-load cost interval, and controlling each generator set according to the obtained no-load cost. According to the invention, batch control is carried out on the generator sets in the electric power system, the complexity caused by a one-machine-fixed mode is avoided, the consumption of manpower, material resources and time in the control process of the multiple generator sets is reduced, and the overall control efficiency of the electric power system is improved.

Description

Technical Field

[0001] The present invention relates to the field of power resource allocation, and in particular to a batch control method, device, equipment and medium for a generator set. Background Art

[0002] The cost accounting of power generation is an important part of the power market management, which directly affects the pricing mechanism and resource allocation efficiency of the power market. The cost of power generation can be divided into fixed cost and variable cost, and the variable cost can be further divided into startup cost, no-load cost and incremental cost. With the increasing scale of the power market and power system, the efficiency of power generation cost accounting will directly or indirectly affect the operating efficiency of the power system.

[0003] At present, at the level of generator set control, the "one machine, one control" model is mainly adopted, that is, the no-load cost of the target unit is calculated separately, and then its specific control plan is determined. However, when there are a large number of units in the power system that need to determine the control plan, this technical solution requires a lot of manpower, material resources and time, and the results of the control plan are easy to exist, which affects the overall control efficiency of the power system. Summary of the invention

[0004] The present invention application provides a batch control method, device, equipment and medium for a generator set, which can improve the overall control efficiency of the power system.

[0005] In order to solve the above technical problems, the present invention provides a batch control method for a generator set, comprising:

[0006] Obtain coal consumption data of multiple generator sets in a target power system; obtain power generation power of the multiple generator sets;

[0007] According to the power generation and coal consumption data of each generator set, each generator set is classified to obtain multiple unit categories;

[0008] Cluster the generator sets within each unit category to obtain multiple operating coal consumption intervals; fit each operating coal consumption interval separately to obtain the corresponding no-load cost interval;

[0009] The no-load cost of each generator set is calculated based on each of the no-load cost intervals, and then each generator set is controlled according to the obtained no-load cost.

[0010] In the implementation of the present invention, by classifying each generator set to obtain a plurality of unit categories, and then clustering the generator sets in each category to obtain a plurality of operating coal consumption spaces; the no-load cost interval is obtained by fitting, thereby calculating the no-load cost of each generator set, so that when determining the control scheme of the generator set, the no-load cost of the generator set can be batch accounted, thereby realizing batch control of the generator sets in the power system, avoiding the tediousness brought by the "one machine, one fixed" mode, reducing the consumption of manpower, material resources and time in the control process of multiple generator sets, and improving the overall control efficiency of the power system.

[0011] As a preferred solution, each generator set is classified according to the power generation and coal consumption data of each generator set to obtain multiple unit categories, specifically:

[0012] According to the power generation and coal consumption data of each generator set, the scatter points corresponding to each generator set are constructed respectively;

[0013] By equally dividing the generated power, multiple power intervals are obtained, and each power interval is determined as a unit category.

[0014] As a preferred solution, the clustering of the generator sets within each unit category is specifically as follows:

[0015] The generator sets within each unit category are clustered according to the following formula:

[0016]

[0017] Where m is the mth unit category, n is the nth operating coal consumption interval, i is the scattered point number of the generator unit, N is the total number of operating coal consumption intervals, and I m,n is the scattered point set of the generating units in the nth operating coal consumption interval of the mth unit category, p m,n,i is the scattered point of the ith generating unit in the nth operating coal consumption interval of the mth unit category, θ m,n It is the cluster center value of the nth operating coal consumption interval of the mth unit category.

[0018] As a preferred solution, the corresponding no-load cost interval is obtained by fitting each operating coal consumption interval, specifically:

[0019] Using a preset fitting function form, each of the operating coal consumption intervals is fitted respectively to obtain an upper boundary regression fitting function and a lower boundary regression fitting function of each operating coal consumption interval;

[0020] According to the upper boundary regression fitting function and the lower boundary regression fitting function of each operating coal consumption interval, each no-load cost interval is calculated respectively.

[0021] As a preferred solution, the above-mentioned upper boundary regression fitting function and lower boundary regression fitting function of each operating coal consumption interval are used to calculate each no-load cost interval, specifically:

[0022] The upper limit of the no-load cost range is calculated according to the following formula:

[0023]

[0024] S 0,n =f N,lower (0), n = N;

[0025] Among them, S 0,n is the upper limit of the nth no-load cost interval, f n,upper (·) is the upper boundary regression fitting function of the nth operating coal consumption interval; f n,lower (·) is the lower boundary regression fitting function of the nth operating coal consumption interval, and N is the total number of operating coal consumption intervals;

[0026] The lower limit of the no-load cost range is calculated according to the following formula:

[0027] S 1,n =f 1,upper (0), n = 1;

[0028]

[0029] Among them, S 1,n is the lower limit of the nth no-load cost interval;

[0030] Each no-load cost interval is determined based on the upper limit and the lower limit of each no-load cost interval.

[0031] As a preferred solution, the obtaining of the power generation power of the multiple generator sets is specifically as follows:

[0032] The rated capacities and load rates of the plurality of generator sets are obtained, and the generated power is calculated according to the rated capacities and load rates.

[0033] As a preferred solution, the coal consumption data of multiple generating units in the target power system are obtained as follows:

[0034] The rated capacity, coal consumption per kilowatt-hour and load rate of the multiple generator sets are obtained, and the operating coal consumption is calculated according to the rated capacity, coal consumption per kilowatt-hour and load rate to obtain the coal consumption data.

[0035] Correspondingly, the present invention also provides a batch control device for a generator set, comprising a data acquisition module, a classification module, a fitting module and a control module; wherein:

[0036] The data acquisition module is used to acquire the coal consumption data of multiple generator sets in the target power system; and acquire the power generation power of the multiple generator sets;

[0037] The classification module is used to classify each generator set according to the power generation and coal consumption data of each generator set to obtain multiple unit categories;

[0038] The fitting module is used to cluster the generator sets in each unit category to obtain multiple operating coal consumption intervals; and to obtain the corresponding no-load cost interval by fitting each operating coal consumption interval respectively;

[0039] The control module is used to calculate the no-load cost of each generator set based on each no-load cost interval, and then control each generator set according to the obtained no-load cost.

[0040] As a preferred solution, the classification module classifies each generator set according to the power generation and coal consumption data of each generator set to obtain multiple unit categories, specifically:

[0041] The classification module constructs scatter points corresponding to each generator set according to the power generation and coal consumption data of each generator set;

[0042] By equally dividing the generated power, multiple power intervals are obtained, and each power interval is determined as a unit category.

[0043] As a preferred solution, the fitting module clusters the generator sets within each unit category, specifically:

[0044] The fitting module clusters the generator sets within each unit category according to the following formula:

[0045]

[0046] Where m is the mth unit category, n is the nth operating coal consumption interval, i is the scattered point number of the generator unit, N is the total number of operating coal consumption intervals, and I m,n is the scattered point set of the generating units in the nth operating coal consumption interval of the mth unit category, p m,n,i is the scattered point of the ith generating unit in the nth operating coal consumption interval of the mth unit category, θ m,n It is the cluster center value of the nth operating coal consumption interval of the mth unit category.

[0047] As a preferred solution, the fitting module obtains the corresponding no-load cost interval by fitting each operating coal consumption interval respectively, specifically:

[0048] The fitting module adopts a preset fitting function form to fit each of the operating coal consumption intervals respectively, and obtains an upper boundary regression fitting function and a lower boundary regression fitting function of each operating coal consumption interval;

[0049] According to the upper boundary regression fitting function and the lower boundary regression fitting function of each operating coal consumption interval, each no-load cost interval is calculated respectively.

[0050] As a preferred solution, the fitting module calculates each no-load cost interval according to the upper boundary regression fitting function and the lower boundary regression fitting function of each operating coal consumption interval, specifically:

[0051] The fitting module calculates the upper limit of the no-load cost interval according to the following formula:

[0052]

[0053] S 0,n =f N,lower (0), n = N;

[0054] Among them, S 0,n is the upper limit of the nth no-load cost interval, f n,upper (·) is the upper boundary regression fitting function of the nth operating coal consumption interval; f n,lower (·) is the lower boundary regression fitting function of the nth operating coal consumption interval, and N is the total number of operating coal consumption intervals;

[0055] The lower limit of the no-load cost range is calculated according to the following formula:

[0056] S 1,n =f 1,upper (0), n = 1;

[0057]

[0058] Among them, S 1,n is the lower limit of the nth no-load cost interval;

[0059] Each no-load cost interval is determined based on the upper limit and the lower limit of each no-load cost interval.

[0060] As a preferred solution, the data acquisition module acquires the power generation of the multiple generator sets, specifically:

[0061] The data acquisition module acquires the rated capacity and load rate of the plurality of generator sets, and calculates the generated power according to the rated capacity and load rate.

[0062] As a preferred solution, the data acquisition module acquires the coal consumption data of multiple generator sets in the target power system, specifically:

[0063] The data acquisition module acquires the rated capacity, coal consumption per kilowatt-hour and load rate of the multiple generator sets, calculates the operating coal consumption according to the rated capacity, coal consumption per kilowatt-hour and load rate, and obtains the coal consumption data.

[0064] Correspondingly, the present application also provides a terminal device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, and the processor implements the batch control method of the generator set when executing the computer program.

[0065] Correspondingly, the present application also provides a computer-readable storage medium, which includes a stored computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute the batch control method of the generator set. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] Figure 1 : A flow chart of an embodiment of a batch control method for a generator set provided in the present application.

[0067] Figure 2 : A scatter diagram diagram of an embodiment of the operating coal consumption of a generator set provided in the present invention.

[0068] Figure 3 : A scatter diagram of an embodiment of the clustering results of the operating coal consumption of the power generation unit provided in the present application.

[0069] Figure 4 : A scatter diagram of an embodiment of the operating coal consumption fitting results of the generator set provided in the present invention.

[0070] Figure 5 : A structural schematic diagram of an embodiment of a batch control device for a generator set provided in the present invention. DETAILED DESCRIPTION

[0071] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0072] Embodiment 1

[0073] Please refer to Figure 1 , Figure 1A flow chart of an embodiment of a batch control method for generator sets provided in the present invention is provided. The batch control method for generator sets can be applied to a data center, a server or a central controller of a target power system.

[0074] The batch control method of the generator set in this embodiment includes steps S101 to S104, which are described in detail as follows:

[0075] Step S101, obtaining coal consumption data of multiple generator sets of a target power system; and obtaining the power generation power of the multiple generator sets.

[0076] In this step, the coal consumption data may specifically be the operating coal consumption of the generator set, and the operating coal consumption may be obtained through the power generation coal consumption test data of the generator set.

[0077] In some embodiments, obtaining the coal consumption data of multiple generator sets in the target power system specifically includes: obtaining the rated capacity, coal consumption per kilowatt-hour, and load rate of the multiple generator sets, calculating the operating coal consumption according to the rated capacity, coal consumption per kilowatt-hour, and load rate, and obtaining the coal consumption data.

[0078] The load rate is expressed as a percentage (%). The unit of coal consumption per kilowatt-hour is kilograms per megawatt-hour (kg / MWh), and the unit of rated capacity is megawatt (MW). By calculating the product of rated capacity, coal consumption per kilowatt-hour and load rate, the operating coal consumption (kg / h) can be obtained, and then the coal consumption data can be obtained.

[0079] On the other hand or in another embodiment, the obtaining of the power generation of the plurality of generator sets is specifically: obtaining the rated capacity and load rate of the plurality of generator sets, and calculating the power generation according to the rated capacity and load rate. From the above, the power generation can be obtained by calculating the product of the rated capacity and the load rate.

[0080] Based on the analysis and summary of the coal consumption data and power generation of multiple generating units, several no-load cost spaces can be determined and divided in the subsequent steps, thus laying the foundation for calculating the no-load cost of each generating unit.

[0081] Step S102: classify each generator set according to the power generation and coal consumption data of each generator set to obtain multiple unit categories.

[0082] In this step, the scatter plots corresponding to each generator set can be constructed according to the power generation and coal consumption data of each generator set. Figure 2 In the figure, the horizontal axis is the power generation, and the vertical axis is the (operating) coal consumption.

[0083] For example, Figure 2As shown, the horizontal axis of the scatter plot can be equally divided into M groups. As shown in the figure, M=7, so in this example, by dividing the generator sets based on the generated power, 7 power intervals are obtained, and 7 unit categories can be obtained in this example.

[0084] Step S103, clustering the generator sets in each unit category to obtain multiple operating coal consumption intervals; fitting each operating coal consumption interval separately to obtain the corresponding no-load cost interval.

[0085] In this step, for each equidistant interval of the above-mentioned power generation, or for each unit category, a K-means algorithm can be used for clustering to obtain N operating coal consumption intervals.

[0086] This embodiment is described by taking N=3 as an example. Figure 3 In this embodiment, the clustering dimension is equal to the number of equally spaced groups, and each cluster has a cluster center. Within the same unit category or the same power range, the sum of the Euclidean distances between the scattered points and the corresponding cluster center is the smallest, which can be specifically expressed as follows:

[0087]

[0088] Where m is the mth unit category, n is the nth operating coal consumption interval, i is the scattered point number of the generator unit, N is the total number of operating coal consumption intervals, and I m,n is the scattered point set of the generating units in the nth operating coal consumption interval of the mth unit category, p m,n,i is the scattered point of the ith generating unit in the nth operating coal consumption interval of the mth unit category, θ m,n It is the cluster center value of the nth operating coal consumption interval of the mth unit category.

[0089] The clustering results are as follows Figure 3 As shown, different operating coal consumption intervals are represented by scattered points of different colors, which are in order from high to low, namely the first operating coal consumption interval, the second operating coal consumption interval and the third operating coal consumption interval.

[0090] By fitting each operating coal consumption space separately, the corresponding no-load cost interval can be obtained, and each operating coal consumption space corresponds to a no-load cost interval, for example, the first operating coal consumption interval corresponds to the first no-load cost interval, the second operating coal consumption interval corresponds to the second no-load cost interval, and the third operating coal consumption interval corresponds to the third no-load cost interval.

[0091] Exemplarily: a preset fitting function form is used to fit each of the operating coal consumption intervals, respectively, to obtain an upper boundary regression fitting function and a lower boundary regression fitting function of each operating coal consumption interval; based on the upper boundary regression fitting function and the lower boundary regression fitting function of each operating coal consumption interval, each no-load cost interval is calculated respectively.

[0092] The preset fitting function may be in the form of a quadratic function or a cubic function. Figure 4 As shown, where f 1,upper (p) is the upper boundary regression fitting function of the first operating coal consumption interval, f 1,lower (p) is the lower boundary regression fitting function of the first operating coal consumption interval.

[0093] Furthermore, based on the upper boundary regression fitting function and the lower boundary regression fitting function of each operating coal consumption interval, each no-load cost interval is calculated respectively, specifically:

[0094] The upper limit of the no-load cost range is calculated according to the following formula:

[0095]

[0096] S 0,n =f N,lower (0), n = N;

[0097] Among them, S 0,n is the upper limit of the nth no-load cost interval, f n,upper (·) is the upper boundary regression fitting function of the nth operating coal consumption interval; f n,lower (·) is the lower boundary regression fitting function of the nth operating coal consumption interval, and N is the total number of operating coal consumption intervals;

[0098] The lower limit of the no-load cost range is calculated according to the following formula:

[0099] S 1,n =f 1,upper (0), n = 1;

[0100]

[0101] Among them, S 1,n is the lower limit of the nth no-load cost interval;

[0102] Each no-load cost interval is determined based on the upper limit and the lower limit of each no-load cost interval.

[0103] For the above formula, the basic meaning is: for the generator sets or scattered points within the first operating coal consumption operating range, the upper limit of the first no-load cost range = the value of the upper boundary fitting regression function of the first operating coal consumption operating range when the horizontal axis is 0, and the lower limit of the first no-load cost range = (the value of the lower boundary fitting regression function of the first operating coal consumption operating range when the horizontal axis is 0 + the value of the upper boundary fitting regression function of the second operating coal consumption operating range when the horizontal axis is 0) / 2.

[0104] For the generating units or scattered points within the second operating coal consumption operating range, the upper limit of the second no-load cost range = (the value of the lower boundary fitting regression function of the first operating coal consumption operating range when the horizontal axis is 0 + the value of the upper boundary fitting regression function of the second operating coal consumption operating range when the horizontal axis is 0) / 2, the lower limit of the second no-load cost range = (the value of the lower boundary fitting regression function of the second operating coal consumption operating range when the horizontal axis is 0 + the value of the upper boundary fitting regression function of the third operating coal consumption operating range when the horizontal axis is 0) / 2.

[0105] For the generating units or scattered points within the third operating coal consumption operating range, the upper limit of the third no-load cost range = (the value of the lower boundary fitting regression function of the second operating coal consumption operating range when the horizontal axis is 0 + the value of the upper boundary fitting regression function of the third operating coal consumption operating range when the horizontal axis is 0) / 2, the lower limit of the second no-load cost range = the value of the lower boundary fitting regression function of the third operating coal consumption operating range when the horizontal axis is 0.

[0106] As for the generator sets in the above three different no-load cost ranges, the generator sets in the first no-load cost range can be understood as old-type units with higher no-load costs, the generator sets in the second no-load cost range can be understood as general units with medium no-load costs, and the generator sets in the third no-load cost range can be understood as new-type units with lower no-load costs, so that corresponding controls can be performed on the generator sets with different no-load costs in subsequent steps.

[0107] Step S104, calculating the no-load cost of each generator set based on each of the no-load cost intervals, and then controlling each generator set according to the obtained no-load cost.

[0108] In this step, by obtaining, for example, the power generation and operating coal consumption of multiple units to be tested, and constructing corresponding scatter points, it is determined whether all or most of the scatter points of these units to be tested are distributed in a certain no-load cost interval according to each no-load cost interval, and then the no-load cost of this group of units is determined by the no-load cost interval. For example, the middle value or 75% quantile of the interval can be taken, and the middle value or 75% quantile is determined as the no-load cost of these units.

[0109] In this way, when the operation strategy or operation target of the power system is determined, for example, when the no-load cost is reduced as much as possible, the no-load cost of the units to be tested can be determined according to the above method. When the no-load cost of these units to be tested is high, it is determined that these units to be tested may be old units. By changing the status of these units to be tested, such as shutting down the units to be tested, the purpose of reducing the overall no-load cost of the power system is achieved, thereby realizing batch control of the generator sets.

[0110] Correspondingly, such as Figure 5 As shown, the present invention also provides a batch control device 500 for a generator set, comprising a data acquisition module 501, a classification module 502, a fitting module 503 and a control module 504; wherein,

[0111] The data acquisition module 501 is used to acquire the coal consumption data of multiple generator sets in the target power system; and acquire the power generation of the multiple generator sets;

[0112] The classification module 502 is used to classify each generator set according to the power generation and coal consumption data of each generator set to obtain multiple unit categories;

[0113] The fitting module 503 is used to cluster the generator sets in each unit category to obtain multiple operating coal consumption intervals; and obtain the corresponding no-load cost interval by fitting each operating coal consumption interval respectively;

[0114] The control module 504 is used to calculate the no-load cost of each generator set based on each no-load cost interval, and then control each generator set according to the obtained no-load cost.

[0115] As a preferred solution, the classification module 502 classifies each generator set according to the power generation and coal consumption data of each generator set to obtain multiple unit categories, specifically:

[0116] The classification module 502 constructs scatter points corresponding to each generator set according to the power generation and coal consumption data of each generator set;

[0117] By equally dividing the generated power, multiple power intervals are obtained, and each power interval is determined as a unit category.

[0118] As a preferred solution, the fitting module 503 clusters the generator sets within each unit category, specifically:

[0119] The fitting module 503 clusters the generator sets within each generator set category according to the following formula:

[0120]

[0121] Where m is the mth unit category, n is the nth operating coal consumption interval, i is the scattered point number of the generator unit, N is the total number of operating coal consumption intervals, and I m,n is the scattered point set of the generating units in the nth operating coal consumption interval of the mth unit category, p m,n,i is the scattered point of the ith generating unit in the nth operating coal consumption interval of the mth unit category, θ m,n It is the cluster center value of the nth operating coal consumption interval of the mth unit category.

[0122] As a preferred solution, the fitting module 503 obtains the corresponding no-load cost interval by fitting each operating coal consumption interval, specifically:

[0123] The fitting module 503 adopts a preset fitting function form to fit each of the operating coal consumption intervals respectively, and obtains an upper boundary regression fitting function and a lower boundary regression fitting function of each operating coal consumption interval;

[0124] According to the upper boundary regression fitting function and the lower boundary regression fitting function of each operating coal consumption interval, each no-load cost interval is calculated respectively.

[0125] As a preferred solution, the fitting module 503 calculates each no-load cost interval according to the upper boundary regression fitting function and the lower boundary regression fitting function of each operating coal consumption interval, specifically:

[0126] The fitting module 503 calculates the upper limit of the no-load cost interval according to the following formula:

[0127]

[0128] S 0,n =f N,lower (0), n = N;

[0129] Among them, S 0,n is the upper limit of the nth no-load cost interval, f n,upper (·) is the upper boundary regression fitting function of the nth operating coal consumption interval; f n,lower (·) is the lower boundary regression fitting function of the nth operating coal consumption interval, and N is the total number of operating coal consumption intervals;

[0130] The lower limit of the no-load cost range is calculated according to the following formula:

[0131] S 1,n =f 1,upper (0), n = 1;

[0132]

[0133] Among them, S 1,n is the lower limit of the nth no-load cost interval;

[0134] Each no-load cost interval is determined based on the upper limit and the lower limit of each no-load cost interval.

[0135] As a preferred solution, the data acquisition module 501 acquires the power generation of the multiple generator sets, specifically:

[0136] The data acquisition module 501 acquires the rated capacity and load rate of the multiple generator sets, and calculates the generated power according to the rated capacity and load rate.

[0137] As a preferred solution, the data acquisition module 501 acquires the coal consumption data of multiple generator sets in the target power system, specifically:

[0138] The data acquisition module 501 acquires the rated capacity, coal consumption per kWh and load rate of the multiple generator sets, calculates the operating coal consumption according to the rated capacity, coal consumption per kWh and load rate, and obtains the coal consumption data.

[0139] Correspondingly, the present application also provides a terminal device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, and the processor implements the batch control method of the generator set when executing the computer program.

[0140] The processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the terminal, and various interfaces and lines are used to connect various parts of the entire terminal.

[0141] The memory can be used to store the computer program, and the processor realizes various functions of the terminal by running or executing the computer program stored in the memory and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area can store data created according to the use of the mobile phone (such as audio data, a phone book, etc.), etc. In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (SmartMedia Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0142] Correspondingly, the present application also provides a computer-readable storage medium, which includes a stored computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute the batch control method of the generator set.

[0143] Wherein, if the module integrated in the batch control device of the generator set is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Wherein, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form, etc. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium, etc.

[0144] Compared with the prior art, the embodiments of the present application have at least the following beneficial effects:

[0145] The embodiment of the present invention provides a batch control method, device, equipment and medium for generator sets. By classifying each generator set to obtain multiple unit categories, and then clustering the generator sets in each category to obtain multiple operating coal consumption spaces; the no-load cost interval is obtained by fitting, and the no-load cost of each generator set is calculated. In this way, when determining the control scheme of the generator set, the no-load cost of the generator set can be batch calculated, thereby realizing batch control of the generator sets in the power system, avoiding the tediousness brought by the "one machine, one fixed" mode, reducing the consumption of manpower, material resources and time in the control process of multiple generator sets, and improving the overall control efficiency of the power system.

[0146] The specific embodiments described above further illustrate the purpose, technical solutions and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. It is particularly pointed out that for those skilled in the art, any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the scope of protection of the present invention.

Claims

1. A batch control method for a generator set, characterized in that: include: Obtain coal consumption data of multiple generating units in the target power system; Obtaining the power generation of the multiple generator sets; According to the power generation and coal consumption data of each generator set, each generator set is classified to obtain multiple unit categories; Cluster the generator sets within each unit category to obtain multiple operating coal consumption intervals; fit each operating coal consumption interval separately to obtain the corresponding no-load cost interval; The no-load cost of each generator set is calculated based on each of the no-load cost intervals, and then each generator set is controlled according to the obtained no-load cost.

2. A batch control method for a generator set as claimed in claim 1, characterized in that: According to the power generation and coal consumption data of each generator set, each generator set is classified to obtain multiple unit categories, specifically: According to the power generation and coal consumption data of each generator set, the scatter points corresponding to each generator set are constructed respectively; By equally dividing the generated power, multiple power intervals are obtained, and each power interval is determined as a unit category.

3. A batch control method for a generator set as claimed in claim 2, characterized in that: The clustering of the generator sets within each unit category is specifically as follows: The generator sets within each unit category are clustered according to the following formula: Where m is the mth unit category, n is the nth operating coal consumption interval, i is the scattered point number of the generator unit, N is the total number of operating coal consumption intervals, and I m,n is the scattered point set of the generating units in the nth operating coal consumption interval of the mth unit category, p m,n,i is the scattered point of the ith generating unit in the nth operating coal consumption interval of the mth unit category, θ m,n It is the cluster center value of the nth operating coal consumption interval of the mth unit category.

4. A batch control method for a generator set as claimed in claim 1, characterized in that: By fitting each operating coal consumption interval, the corresponding no-load cost interval is obtained, which is specifically: Using a preset fitting function form, each of the operating coal consumption intervals is fitted respectively to obtain an upper boundary regression fitting function and a lower boundary regression fitting function of each operating coal consumption interval; According to the upper boundary regression fitting function and the lower boundary regression fitting function of each operating coal consumption interval, each no-load cost interval is calculated respectively.

5. A batch control method for a generator set as claimed in claim 4, characterized in that: According to the upper boundary regression fitting function and the lower boundary regression fitting function of each operating coal consumption interval, each no-load cost interval is calculated respectively, specifically: The upper limit of the no-load cost range is calculated according to the following formula: S 0,n =f N,lower (0),n=N; Among them, S 0,n is the upper limit of the nth no-load cost interval, f n,upper (·) is the upper boundary regression fitting function of the nth operating coal consumption interval; f n,lower (·) is the lower boundary regression fitting function of the nth operating coal consumption interval, and N is the total number of operating coal consumption intervals; The lower limit of the no-load cost range is calculated according to the following formula: S 1,n =f 1,upper (0),n=1; Among them, S 1,n is the lower limit of the nth no-load cost interval; Each no-load cost interval is determined based on the upper limit and the lower limit of each no-load cost interval.

6. A batch control method for a generator set as claimed in claim 1, characterized in that: The obtaining of the power generation power of the multiple generator sets is specifically: The rated capacities and load rates of the plurality of generator sets are obtained, and the generated power is calculated according to the rated capacities and load rates.

7. A batch control method for a generator set as claimed in claim 1, characterized in that: The step of obtaining the coal consumption data of multiple generating units in the target power system is as follows: The rated capacity, coal consumption per kilowatt-hour and load rate of the multiple generator sets are obtained, and the operating coal consumption is calculated according to the rated capacity, coal consumption per kilowatt-hour and load rate to obtain the coal consumption data.

8. A batch control device for a generator set, characterized in that: It includes a data acquisition module, a classification module, a fitting module and a control module; wherein, The data acquisition module is used to acquire the coal consumption data of multiple generator sets in the target power system; and acquire the power generation power of the multiple generator sets; The classification module is used to classify each generator set according to the power generation and coal consumption data of each generator set to obtain multiple unit categories; The fitting module is used to cluster the generator sets in each unit category to obtain multiple operating coal consumption intervals; and to obtain the corresponding no-load cost interval by fitting each operating coal consumption interval respectively; The control module is used to calculate the no-load cost of each generator set based on each no-load cost interval, and then control each generator set according to the obtained no-load cost.

9. A terminal device, characterized in that: The method comprises a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor implements the batch control method of the generator set according to any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored computer program, wherein when the computer program is executed, the device where the computer-readable storage medium is located is controlled to execute the batch control method for the generator set according to any one of claims 1 to 7.

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