CN116488252A - Local optimal cutting method and device, electronic equipment and storage medium - Google Patents
Local optimal cutting method and device, electronic equipment and storage medium 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
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- G—PHYSICS
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
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- G06F30/20—Design optimisation, verification or simulation
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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
- H02J3/007—Arrangements for selectively connecting the load or loads to one or several among a plurality of power lines or power sources
- H02J3/0075—Arrangements for selectively connecting the load or loads to one or several among a plurality of power lines or power sources for providing alternative feeding paths between load and source according to economic or energy efficiency considerations, e.g. economic dispatch
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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
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- Y02P70/00—Climate change mitigation technologies in the production process for final industrial or consumer products
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Abstract
The invention discloses a local optimal cutting method, a device, electronic equipment and a storage medium, wherein the method comprises the following steps: under-cutting the cuttable unit according to the required cutting quantity, and calculating the residual required cutting quantity; selecting a remaining cutter sequence from the remaining cutter set; and searching an optimal cutter scheme in the residual cutter sequence according to the residual cutting amount to determine a residual cutter object. According to the scheme, the partial required cutting quantity is subjected to local optimal treatment, so that the over-cutting quantity or under-cutting quantity can be effectively reduced, and the calculation efficiency can be ensured under the scene of more units.
Description
Technical Field
The invention belongs to the field of power system automation, and particularly relates to a local optimal cutting method, a device, electronic equipment and a storage medium in a power system.
Background
With the continuous expansion of the scale of the power system, the continuous improvement of the new energy capacity and the high-proportion renewable energy source become an outstanding feature of the future development of the power system. The new energy has the characteristics of randomness and volatility, and the centralized access of a large amount of new energy can make the stability problem of the power system more outstanding than before. When the emergency control is carried out after the power system fails, a load cutting measure is generally adopted at the power receiving side or a measure of a power transmission side cutting unit is generally adopted, a stable control main station calculates the required cutting amount according to a strategy during the cutting unit, the required cutting amount is distributed to each execution station, and the execution stations cut. For traditional thermal power, an execution station cuts off a thermal power unit; for new energy plant stations, the execution station cuts off new energy feeders. The conventional cutting method for the current execution station is divided into priority and optimal cutting, and the cutting amount is possibly overlarge for the priority cutting, so that the economic benefit of the power station cannot be ensured; the optimal cutting mode can ensure the economical type of the power station, but has the problem of large calculated amount, and the calculated amount of the optimal cutting mode increases exponentially along with the number of the units, so that when the number of the units is large, the operation efficiency of the optimal cutting mode is very low, and the quick action of the stability control device cannot be realized.
Disclosure of Invention
The invention aims to provide a local optimal cutting method, a device, electronic equipment and a storage medium, so as to solve the problem that the existing cutting method cannot simultaneously consider economy and efficiency when a system fails and a cutting unit is needed.
To achieve the above object, the solution of the present application is:
according to a first aspect of the present application, a locally optimal cutting method is provided, including:
under-cutting the cuttable unit according to the required cutting quantity, and calculating the residual required cutting quantity;
selecting a remaining cutter sequence from the remaining cutter set;
and searching an optimal cutter scheme in the residual cutter sequence according to the residual cutting amount to determine a residual cutter object.
According to some embodiments, the undercutting the cuttable unit according to the required cutting amount, and calculating the remaining required cutting amount includes: cutting the cuttable unit according to the cutting amount in turn according to the order of the cutting power of the unit from large to small until one unit is cut off, and calculating the difference between the cutting amount and the cut amount, namely the residual cutting amount.
According to some embodiments, the selecting the remaining cutter sequence from the remaining cutter sets comprises: the method comprises the steps of sequentially arranging the rest cuttable units according to the unit cuttable power, taking each adjacent N units as a to-be-selected cutting sequence, calculating the power sum of each group of to-be-selected cutting sequences, and taking a group of to-be-selected cutting sequences with the power sum closest to the rest needed cutting amount as rest cutter sequences; wherein N is a natural number, and N is more than or equal to 2.
According to some embodiments, the determining the remaining cutter object by searching for an optimal cutter scheme in the remaining cutter sequence according to the remaining required cutting amount includes:
constructing a mathematical programming model according to the residual cutting quantity and the residual cutting machine sequence;
and searching an optimal cutter scheme in the residual cutter sequence by using a hidden enumeration method or an enumeration method to determine residual cutter objects.
According to some embodiments, in the selection of the remaining cutter sequence, the remaining cutter groups are arranged in sequence according to the size of the cutter group cutting power and are marked as { Pkq } 1 ,Pkq 2 ,Pkq 3 ,…,Pkq n N is the total number of the rest cuttable units; every adjacent N sets are used as a group of to-be-selected sequences (if N is less than or equal to N, only one group of to-be-selected sequences is provided), and then the adjacent N sets are combined into N-N+1 groups of to-be-selected sequences which are { x }, respectively 1 }、{x 2 }、…、{x n-N+1 The N-n+1 set of candidate cut sequences can be expressed as:
calculating the power sum P of each group of to-be-selected cut sequences 1 、P 2 、…、P n-N+1 ：
The sum of the power is closest to the residual required cutting quantity P sy Is a set of the candidate cut sequences { x } k The sequence of the residual cutter is { x } (1.ltoreq.k.ltoreq.n-N+1) as the sequence of the residual cutter k Sum of powers P k The method meets the following conditions:
according to some embodiments, the constructing a mathematical programming model from the remaining required cut and the remaining cutter sequence comprises:
the remaining slicer sequence { x } k }＝{Pkq k ,Pkq k+1 ,…,Pkq k+N-1 N is the number of remaining cutter sequence elements; setting parameter a i =0 or 1 (i=1, 2, …, N) is { x k Coefficients of the corresponding N units of the cuttable power, a i When 1 is the machine set is cut off, the rest cutter scheme is converted into solution a i The 0-1 programming problem of (i=1, 2, …, N) results in the following mathematical programming model:
if an over-cut is required, a i (i=1, 2, …, N) and the remaining cutting amount P qjsy The following formula should be satisfied:
if under-cut is required, a i (i=1, 2, …, N) and the remaining cutting amount P qjsy The following formula should be satisfied:
by implicit enumeration or enumerationSolving the formula (4) or the formula (5) to obtain the residual required cutting quantity P sy Is an optimal cutting scheme.
According to a second aspect of the present application, a locally optimal cutter device is provided, comprising: a unit minimum undercut module, a residual cutter sequence selection module and a residual most preferred cut module, wherein:
the unit minimum undercutting module is used for undercutting the cuttable unit according to the required cutting quantity and calculating the residual required cutting quantity;
the residual cutter sequence selection module is used for selecting residual cutter sequences from residual cutter groups;
and the residual most preferred cutting module is used for searching an optimal cutting scheme in the residual cutting sequence according to the residual needed cutting quantity to determine a residual cutting object.
According to some embodiments, in the unit minimum undercut module, the cuttable unit is cut according to the required cutting amount in sequence from high to low unit cuttable power until one unit is cut, and the difference between the required cutting amount and the cut amount, namely the residual required cutting amount, is calculated.
According to some embodiments, in the remaining cutter sequence selection module, the remaining cuttable units are sequentially arranged according to the unit cuttable power, each adjacent N units are used as a to-be-selected cutting sequence, the power sum of each group of to-be-selected cutting sequences is calculated, and a group of to-be-selected cutting sequences with the power sum closest to the remaining required cutting amount is taken as the remaining cutter sequences; wherein N is a natural number, and N is more than or equal to 2.
According to some embodiments, the remaining amount is most preferably cut into pieces,
constructing a mathematical programming model according to the residual cutting quantity and the residual cutting machine sequence;
and searching an optimal cutter scheme in the residual cutter sequence by using a hidden enumeration method or an enumeration method to determine residual cutter objects.
According to some embodiments, in the selection of the remaining cutter sequence, the remaining cutter groups are arranged in sequence according to the size of the cutter group cutting power and are marked as { Pkq } 1 ,Pkq 2 ,Pkq 3 ,…,Pkq n N is the total number of the rest cuttable units; every adjacent N sets are used as a group of to-be-selected sequences (if N is less than or equal to N, only one group of to-be-selected sequences is provided), and then the adjacent N sets are combined into N-N+1 groups of to-be-selected sequences which are { x }, respectively 1 }、{x 2 }、…、{x n-N+1 The N-n+1 set of candidate cut sequences can be expressed as:
calculating the power sum P of each group of to-be-selected cut sequences 1 、P 2 、…、P n-N+1 ：
The sum of the power is closest to the residual required cutting quantity P sy Is a set of the candidate cut sequences { x } k The sequence of the residual cutter is { x } (1.ltoreq.k.ltoreq.n-N+1) as the sequence of the residual cutter k Sum of powers P k The method meets the following conditions:
according to some embodiments, the remaining most preferred cutting module comprises:
the remaining slicer sequence { x } k }＝{Pkq k ,Pkq k+1 ,…,Pkq k+N-1 N is the number of remaining cutter sequence elements; setting parameter a i =0 or 1 (i=1, 2, …, N) is { x k Coefficients of the corresponding N units of the cuttable power, a i When 1 is the machine set is cut off, the rest cutter scheme is converted into solution a i The 0-1 programming problem of (i=1, 2, …, N) results in the following mathematical programming model:
if an over-cut is required, a i (i=1, 2, …, N) and the remaining cutting amount P qjsy The following formula should be satisfied:
if under-cut is required, a i (i=1, 2, …, N) and the remaining cutting amount P qjsy The following formula should be satisfied:
solving the formula (4) or the formula (5) by using a hidden enumeration method or an enumeration method to obtain the residual required cutting quantity P sy Is an optimal cutting scheme.
According to a third aspect of the present application, there is provided an electronic device comprising: a processor; and a memory storing computer instructions that, when executed by the processor, cause the processor to perform the locally optimal cut method described above.
According to a fourth aspect of the present application, a non-transitory computer storage medium is presented, storing a computer program, which when executed by a plurality of processors, causes the processors to perform the locally optimal cutting method described above.
After the scheme is adopted, compared with the prior art, the invention has the beneficial effects that: when the system fails and needs to cut the machine group, the minimum undercut is preferably carried out according to the needed cutting quantity, then the residual cutting machine sequence is selected, and the most preferable cutting is carried out according to the residual needed cutting quantity.
Drawings
Fig. 1 is a schematic diagram of a locally optimal cutting method according to an embodiment of the present application.
FIG. 2 is a distribution histogram of cutter errors and program operation time obtained by a simulation test of the method of the present invention.
Fig. 3 is a schematic diagram of a locally optimal cutter device according to an embodiment of the present application.
Fig. 4 is a block diagram of an electronic device provided in the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. It will be apparent that the described embodiments are only some, but not all, of the embodiments of the present application. All other embodiments, which can be made by those skilled in the art based on the embodiments herein without making any inventive effort, are intended to be within the scope of the present application.
The applicant finds that when the cutting machine needs to be executed in face of the stability problem of the power system, the cutting machine method commonly used by the current execution station has priority cutting and optimal cutting, and both cutting methods cannot simultaneously consider economical efficiency and efficiency. In view of this, the embodiment of the present application provides a locally optimal cutting method, as shown in a flowchart in fig. 1, the method includes the following steps:
s101: and under-cutting the cuttable unit according to the required cutting quantity, and calculating the residual required cutting quantity.
In some embodiments, the cuttable unit is cut according to the required cutting amount in sequence from large to small, until one unit is cut, and the difference between the required cutting amount and the cut amount, namely the residual required cutting amount, is calculated.
S102: a remaining cutter sequence is selected from the remaining cutter sets.
In some embodiments, the rest of the cuttable units are sequentially arranged according to the cuttable power of the units, each adjacent N units are used as a to-be-selected cutting sequence, the power sum of each group of to-be-selected cutting sequences is calculated, and a group of to-be-selected cutting sequences with the power sum closest to the rest to-be-cut amount is taken as a rest cutter sequence; wherein N is a natural number, and N is more than or equal to 2. If the number of the remaining cutter groups is less than or equal to N, only one group of the to-be-selected cutting sequences is selected, and the group of the to-be-selected cutting sequences is the remaining cutter sequences.
In some embodiments, in the selection of the remaining cutter sequence, the remaining cutter sets are arranged in sequence according to the size of the cutter set cutting power and are marked as { Pkq ] 1 ,Pkq 2 ,Pkq 3 ,…,Pkq n And n is the total number of the residual cuttable unit. Wherein, the cutting power of the machine set can be sequentially arranged according to the size of the cutting power of the machine set, and can be arranged from large to small, or can be arranged according to the size of the cutting power of the machine setAnd the steps are arranged from small to large. Every adjacent N sets are used as a group of to-be-selected sequences (if N is less than or equal to N, only one group of to-be-selected sequences is provided), and then the adjacent N sets are combined into N-N+1 groups of to-be-selected sequences which are { x }, respectively 1 }、{x 2 }、…、{x n-N+1 The N-n+1 set of candidate cut sequences can be expressed as:
calculating the power sum P of each group of to-be-selected cut sequences 1 、P 2 、…、P n-N+1 ：
The sum of the power is closest to the residual required cutting quantity P sy Is a set of the candidate cut sequences { x } k The sequence of the residual cutter is { x } (1.ltoreq.k.ltoreq.n-N+1) as the sequence of the residual cutter k Sum of powers P k The method meets the following conditions:
s103: and searching an optimal cutter scheme in the residual cutter sequence according to the residual cutting amount to determine a residual cutter object. The sum of the cutting amounts in step S101 and step S103 is the total cutting amount of the present operation.
In some embodiments, a mathematical programming model is first constructed from the remaining cut-out needed and the remaining cutter sequence; and then searching the optimal cutter scheme in the residual cutter sequence by using an hidden enumeration method or an enumeration method to determine the residual cutter object.
In some embodiments, said constructing a mathematical programming model from said remaining cut-to-be-cut and said remaining cutter sequence comprises:
the remaining slicer sequence { x } k }＝{Pkq k ,Pkq k+1 ,…,Pkq k+N-1 N is the number of remaining cutter sequence elements; setting parameter a i =0 or 1 (i=1, 2, …N) is { x k Coefficients of the corresponding N units of the cuttable power, a i When 1 is the machine set is cut off, the rest cutter scheme is converted into solution a i The 0-1 programming problem of (i=1, 2, …, N) results in the following mathematical programming model:
if an over-cut is required, a i (i=1, 2, …, N) and the remaining cutting amount P qjsy The following formula should be satisfied:
if under-cut is required, a i (i=1, 2, …, N) and the remaining cutting amount P qjsy The following formula should be satisfied:
solving the formula (4) or the formula (5) by using a hidden enumeration method or an enumeration method to obtain the residual required cutting quantity P sy Is an optimal cutting scheme.
The following description is provided in connection with a specific embodiment to facilitate a clearer understanding of the technical aspects of the present application.
Assuming that a certain wind power generation and cutting machine has 20 collector wires, the cutting power is 7.1MW, 19.81MW, 5.72MW, 1.67MW, 17.38MW, 3.32MW, 15.38MW, 0.5MW, 12.69MW, 15.58MW, 2.47MW, 12.57MW, 6.94MW, 9.02MW, 14.58MW, 12.04MW, 4.23MW, 11.65MW, 10.02MW and 11.83MW respectively. The scheme of this application mainly includes three links: the method comprises the steps of (1) a minimum undercut link of a unit, (2) a sequence selection link of a residual cutter and (3) a most preferable cutting link of the residual cutter.
(1) And in the minimum undercut link of the unit, undercutting is carried out on the cuttable unit according to the required cutting quantity, and the residual required cutting quantity is calculated. Assuming that the cutting amount is 140.49MW, cutting the cuttable unit according to the order of the cutting power of the unit from large to small until the cutting of the next unit is performed, and respectively cutting the cutting unit according to the order of the cutting power of the unit from large to small, wherein the cutting unit power is 19.81MW, 17.38MW, 15.58MW, 15.38MW, 14.58MW, 12.69MW, 12.57MW, 12.04MW and 11.83MW. The cutting amount is 131.86MW,then cutting off one (11.65 MW) to obtain the residual required cutting amount P sy ＝8.63MW。
(2) In the selection link of the sequence of the rest cutting machine, the rest cutting machine groups are arranged in the sequence from small to large, namely {0.5,1.67,2.47,3.32,4.23,5.72,6.94,7.1,9.02,10.02,11.65} (unit: MW). In this embodiment, each 8 adjacent units are used as a set of to-be-selected sequences, and a total of 4 sets of to-be-selected sequences are respectively { x } 1 }、{x 2 }、{x 3 }、{x 4 These 4 sets of candidate cut sequences can be expressed as:
{x 1 }＝{0.5,1.67,2.47,3.32,4.23,5.72,6.94,7.1}；
{x 2 }＝{1.67,2.47,3.32,4.23,5.72,6.94,7.1,9.02}；
{x 3 }＝{2.47,3.32,4.23,5.72,6.94,7.1,9.02,10.02}；
{x 4 }＝{3.32,4.23,5.72,6.94,7.1,9.02,10.02,11.65}；
calculating the power sum P of each group of to-be-selected cut sequences 1 、P 2 、P 3 、P 4 31.95, 40.47, 48.82, 58, respectively.
The sum of the power is closest to the residual required cutting quantity P sy A set of candidate cut sequences of 8.63MW as the remaining cut sequences, the remaining cut sequences are { x } 1 }。
(3) And in the most preferable cutting link of the residual quantity, searching an optimal cutting scheme in the residual cutting sequence according to the residual quantity to be cut, and determining the residual cutting object. The remaining slicer sequence { x } 1 Setting parameter a i =0 or 1 (i=1, 2, …, 8) is { x 1 Coefficient of the cuttable power of 8 units in }, a i The unit is cut off when 1.
Taking over-cut as an example, then a i (i=1, 2, …, 8) and the remaining cutting amount P qjsy The following formula should be satisfied:
minP qjsy ＝0.5a 1 +1.67a 2 +2.47a 3 +3.32a 4 +4.43a 5 +5.72a 6 +6.94a 7 +7.1a 8
in the example, the hidden enumeration method is used for solving the above-mentioned 0-1 programming problem, the solving process is shown in the following table, and the a is sequentially carried out i (i=1, 2, …, 8) and calculating the remaining cutting amount P qjsy Judging whether the constraint condition is met, if not, directly carrying out the next strip, and if so, using the residual cutting machine quantity P at the time qjsy The subsequent enumeration is filtered as a filter term, where the filter term is updated during the computation.
When a is 1 、a 3 、a 6 At 1, the most preferred cut for the remaining required cut in the sequence of the remaining cutter was achieved, with the power cut being 0.5MW, 2.47MW, 5.72MW, and a total of 8.69MW.
The minimum undercut link of the unit cuts 131.86MW, the rest most preferably cuts 8.69MW, the action cuts 140.55MW altogether, the overcut amount is 0.06MW, and the cutter error is 0.04%.
Generating 50 groups of 80 cuttable unit sequences conforming to normal distribution, carrying out 100 times (the cutting quantity required to be generated each time is a random number meeting the normal distribution) cutting test according to the implementation mode aiming at each group of cuttable unit sequences, carrying out 5000 times of simulation tests in total, and counting the cutting errors and program operation time of each test.
In summary, through implementation of the scheme, the method can perform local optimal processing on partial needed cutting quantity, reduce unit power loss caused by excessive cutting quantity, be applicable to a scene with more units, and effectively improve calculation efficiency by limiting the most optimal cutting logic to N objects.
Fig. 3 shows a locally optimal cutting device 200 according to an embodiment of the present application, including: a crew minimum under-cut module 201, a remaining cutter sequence selection module 202, and a remaining most preferred cut module 203. Wherein:
the unit minimum undercut module 201 is configured to undercut the cuttable unit according to the required cutting amount, and calculate the remaining required cutting amount.
The remaining cutter sequence selection module 202 is configured to select a remaining cutter sequence from the remaining cuttable unit.
The most preferable cutting module 203 of the surplus is used for searching the optimal cutting scheme in the surplus cutting sequence according to the surplus needed cutting quantity to determine the surplus cutting object.
In some embodiments, in the unit minimum undercut module, the cuttable unit is cut according to the required cutting amount in sequence from large to small according to the unit cuttable power until one unit is cut off, and the difference between the required cutting amount and the cut amount, namely the residual required cutting amount, is calculated.
In some embodiments, in the remaining cutter sequence selection module, the remaining cuttable units are sequentially arranged according to the unit cuttable power, each adjacent N units are used as a to-be-selected cutting sequence, the power sum of each group of to-be-selected cutting sequences is calculated, and a group of to-be-selected cutting sequences with the power sum closest to the remaining required cutting amount are taken as the remaining cutter sequences; wherein N is a natural number, and N is more than or equal to 2.
In some embodiments, in a residual most preferred cutting module, a mathematical programming model is constructed according to the residual needed cutting amount and the residual cutting machine sequence; and searching an optimal cutter scheme in the residual cutter sequence by using a hidden enumeration method or an enumeration method to determine residual cutter objects.
In some embodiments, in the selection of the remaining cutter sequence, the remaining cutter sets are arranged in sequence according to the size of the cutter set cutting power and are marked as { Pkq ] 1 ,Pkq 2 ,Pkq 3 ,…,Pkq n N is the total number of the rest cuttable units; every adjacent N sets are used as a group of to-be-selected sequences (if N is less than or equal to N, only one group of to-be-selected sequences is provided), and then the adjacent N sets are combined into N-N+1 groups of to-be-selected sequences which are { x }, respectively 1 }、{x 2 }、…、{x n-N+1 -N-n+1 set of candidatesThe sequence can be expressed as:
calculating the power sum P of each group of to-be-selected cut sequences 1 、P 2 、…、P n-N+1 ：
The sum of the power is closest to the residual required cutting quantity P sy Is a set of the candidate cut sequences { x } k The sequence of the residual cutter is { x } (1.ltoreq.k.ltoreq.n-N+1) as the sequence of the residual cutter k Sum of powers P k The method meets the following conditions:
in some embodiments, the remaining amount most preferably comprises, in the cutting module:
the remaining slicer sequence { x } k }＝{Pkq k ,Pkq k+1 ,…,Pkq k+N-1 N is the number of remaining cutter sequence elements; setting parameter a i =0 or 1 (i=1, 2, …, N) is { x k Coefficients of the corresponding N units of the cuttable power, a i When 1 is the machine set is cut off, the rest cutter scheme is converted into solution a i The 0-1 programming problem of (i=1, 2, …, N) results in the following mathematical programming model:
if an over-cut is required, a i (i=1, 2, …, N) and the remaining cutting amount P qjsy The following formula should be satisfied:
if under-cut is required, a i (i=1, 2, …, N) and the remaining cutting amount P qjsy The following formula should be satisfied:
solving the formula (4) or the formula (5) by using a hidden enumeration method or an enumeration method to obtain the residual required cutting quantity P sy Is an optimal cutting scheme.
The sum of the cutting machine quantity selected by the minimum undercutting module of the machine set and the cutting machine quantity selected by the most preferable cutting module of the residual quantity is the total cutting machine quantity of the current action.
Fig. 4 shows a block diagram of an electronic device provided in the present application. Fig. 4 provides an electronic device including a processor and a memory. The memory stores computer instructions that, when executed by the processor, cause the processor to execute the computer instructions to implement the method and refinement as shown in fig. 1.
It should be understood that the above-described device embodiments are illustrative only and that the disclosed device may be implemented in other ways. For example, the division of the units/modules in the above embodiments is merely a logic function division, and there may be another division manner in actual implementation. For example, multiple units, modules, or components may be combined, or may be integrated into another system, or some features may be omitted or not performed.
In addition, unless specifically described, each functional unit/module in each embodiment of the present invention may be integrated into one unit/module, or each unit/module may exist alone physically, or two or more units/modules may be integrated together. The integrated units/modules described above may be implemented either in hardware or in software program modules.
The integrated units/modules, if implemented in hardware, may be digital circuits, analog circuits, etc. Physical implementations of hardware structures include, but are not limited to, transistors, memristors, and the like. The processor or chip may be any suitable hardware processor, such as CPU, GPU, FPGA, DSP and ASIC, etc., unless otherwise specified. The on-chip cache, off-chip Memory, memory may be any suitable magnetic or magneto-optical storage medium, such as resistive Random Access Memory RRAM (Resistive Random Access Memory), dynamic Random Access Memory DRAM (Dynamic Random Access Memory), static Random Access Memory SRAM (Static Random Access Memory), enhanced dynamic Random Access Memory EDRAM (Enhanced Dynamic Random Access Memory), high-Bandwidth Memory HBM (High-Bandwidth Memory), hybrid Memory cube HMC (Hybrid Memory Cube), and the like, unless otherwise indicated.
The integrated units/modules may be stored in a computer readable memory if implemented in the form of software program modules and sold or used as a stand-alone product. Based on such understanding, the technical solution of the present invention may be embodied in essence or a part contributing to the prior art or all or part of the technical solution in the form of a software product stored in a memory, comprising several instructions for causing a computer device (which may be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present disclosure. And the aforementioned memory includes: a U-disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a removable hard disk, a magnetic disk, or an optical disk, or other various media capable of storing program codes.
Embodiments of the present application also provide a non-transitory computer storage medium storing a computer program that, when executed by a plurality of processors, causes the processors to perform the method and refinement as shown in fig. 1.
It should be clearly understood that this application describes how to make and use particular examples, but is not limited to any details of these examples. Rather, these principles can be applied to many other embodiments based on the teachings of the present disclosure.
Furthermore, it should be noted that the above-described figures are merely illustrative of the processes involved in the method according to the exemplary embodiments of the present application, and are not intended to be limiting. It will be readily appreciated that the processes shown in the above figures do not indicate or limit the temporal order of these processes. In addition, it is also readily understood that these processes may be performed synchronously or asynchronously, for example, among a plurality of modules.
The above embodiments are only for illustrating the technical idea of the present invention, and the protection scope of the present invention is not limited thereto, and any modification made on the basis of the technical scheme according to the technical idea of the present invention falls within the protection scope of the present invention.
Claims (14)
1. A locally optimal cutting method, comprising:
under-cutting the cuttable unit according to the required cutting quantity, and calculating the residual required cutting quantity;
selecting a remaining cutter sequence from the remaining cutter set;
and searching an optimal cutter scheme in the residual cutter sequence according to the residual cutting amount to determine a residual cutter object.
2. The method of claim 1, wherein the undercutting the cuttable unit according to the required cut amount and calculating the remaining required cut amount comprises: cutting the cuttable unit according to the cutting amount in turn according to the order of the cutting power of the unit from large to small until one unit is cut off, and calculating the difference between the cutting amount and the cut amount, namely the residual cutting amount.
3. The method of claim 1, wherein selecting a remaining cutter sequence from a remaining set of cuttable machines comprises: the method comprises the steps of sequentially arranging the rest cuttable units according to the unit cuttable power, taking each adjacent N units as a to-be-selected cutting sequence, calculating the power sum of each group of to-be-selected cutting sequences, and taking a group of to-be-selected cutting sequences with the power sum closest to the rest needed cutting amount as rest cutter sequences; wherein N is a natural number, and N is more than or equal to 2.
4. The method of claim 1, wherein the determining a residual cutter object by finding an optimal cutter scheme in the residual cutter sequence based on the residual cut-needed amount comprises:
constructing a mathematical programming model according to the residual cutting quantity and the residual cutting machine sequence;
and searching an optimal cutter scheme in the residual cutter sequence by using a hidden enumeration method or an enumeration method to determine residual cutter objects.
5. A method as claimed in claim 3, wherein: in the selection of the residue cutter sequence,
the rest of the cuttable units are sequentially arranged according to the unit cuttable power and are marked as { Pkq ] 1 ，Pkq 2 ，Pkq 3 ，...，Pkq n N is the total number of the rest cuttable units;
every adjacent N sets are used as a group of to-be-selected sequences (if N is less than or equal to N, only one group of to-be-selected sequences is provided), and then the adjacent N sets are combined into N-N+1 groups of to-be-selected sequences which are { x }, respectively 1 }、{x 2 }、...、{x n-N+1 The N-n+1 set of candidate cut sequences can be expressed as:
calculating the power sum P of each group of to-be-selected cut sequences 1 、P 2 、...、P n-N+1 ：
The sum of the power is closest to the residual required cutting quantity P sy Is a set of the candidate cut sequences { x } k The sequence of the residual cutter is { x } (1.ltoreq.k.ltoreq.n-N+1) as the sequence of the residual cutter k Sum of powers P k The method meets the following conditions:
6. the method of claim 4, wherein: the constructing a mathematical programming model according to the residual needed cutting quantity and the residual cutting machine sequence comprises the following steps:
the remaining slicer sequence { x } k }＝{Pkq k ，Pkq k+1 ，...，Pkq k+N-1 N is the number of remaining cutter sequence elements; setting parameter a i =0 or 1 (i=1, 2, …, N) is { x k Coefficients of the corresponding N units of the cuttable power, a i When 1 is the machine set is cut off, the rest cutter scheme is converted into solution a i The 0-1 programming problem of (i=1, 2, …, N) results in the following mathematical programming model:
if an over-cut is required, a i (i=1, 2, …, N) and the remaining cutting amount P qjsy The following formula should be satisfied:
if under-cut is required, a i (i=1, 2, …, N) and the remaining cutting amount P qjsy The following formula should be satisfied:
solving the formula (4) or the formula (5) by using a hidden enumeration method or an enumeration method to obtain the residual required cutting quantity P sy Is an optimal cutting scheme.
7. A locally optimal cutter device, comprising: a unit minimum undercut module, a residual cutter sequence selection module and a residual most preferred cut module, wherein:
the unit minimum undercutting module is used for undercutting the cuttable unit according to the required cutting quantity and calculating the residual required cutting quantity;
the residual cutter sequence selection module is used for selecting residual cutter sequences from residual cutter groups;
and the residual most preferred cutting module is used for searching an optimal cutting scheme in the residual cutting sequence according to the residual needed cutting quantity to determine a residual cutting object.
8. The device according to claim 7, wherein in the unit minimum undercut module, the unit which can be cut is sequentially cut according to the unit cutting power from large to small according to the required cutting amount, and the difference between the required cutting amount and the cut amount, namely the residual required cutting amount, is calculated until one unit is cut.
9. The apparatus of claim 7, wherein in the remaining cutter sequence selection module, the remaining cutter sets are sequentially arranged according to the size of the cutting power of the sets, each adjacent N sets are used as a cutting sequence to be selected, the power sum of each set of cutting sequences to be selected is calculated, and a set of cutting sequences, the power sum of which is closest to the remaining cutting amount, is used as the remaining cutter sequence; wherein N is a natural number, and N is more than or equal to 2.
10. The apparatus of claim 7, wherein said remaining amount is most preferably cut out of the module,
constructing a mathematical programming model according to the residual cutting quantity and the residual cutting machine sequence;
and searching an optimal cutter scheme in the residual cutter sequence by using a hidden enumeration method or an enumeration method to determine residual cutter objects.
11. The apparatus as claimed in claim 9, wherein: in the selection of the residue cutter sequence,
the rest of the cuttable units are sequentially arranged according to the unit cuttable power and are marked as { Pkq ] 1 ，Pkq 2 ，Pkq 3 ，...，Pkq n N is the total number of the rest cuttable units;
every adjacent N sets are used as a group of to-be-selected sequences (if N is less than or equal to N, only one group of to-be-selected sequences is provided), and then the adjacent N sets are combined into N-N+1 groups of to-be-selected sequences which are { x }, respectively 1 }、{x 2 }、...、{x n-N+1 The N-n+1 set of candidate cut sequences can be expressed as:
calculating the power sum P of each group of to-be-selected cut sequences 1 、P 2 、...、P n-N+1 ：
The sum of the power is closest to the residual required cutting quantity P sy Is a set of the candidate cut sequences { x } k The sequence of the residual cutter is { x } (1.ltoreq.k.ltoreq.n-N+1) as the sequence of the residual cutter k Sum of powers P k The method meets the following conditions:
12. the apparatus as claimed in claim 10, wherein: the most preferable cutting module of the residual comprises:
the remaining slicer sequence { x } k }＝{Pkq k ，Pkq k+1 ，...，Pkq k+N-1 N is the number of remaining cutter sequence elements; setting parameter a i =0 or 1 (i=1, 2, …, N) is { x k Coefficients of the corresponding N units of the cuttable power, a i When 1 is the machine set is cut off, the rest cutter scheme is converted into solution a i The 0-1 programming problem of (i=1, 2, …, N) results in the following mathematical programming model:
if an over-cut is required, a i (i=1, 2, …, N) and the remaining cutting amount P qjsy The following formula should be satisfied:
if under-cut is required, a i (i=1, 2, …, N) and the remaining cutting amount P qjsy The following formula should be satisfied:
solving the formula (4) or the formula (5) by using a hidden enumeration method or an enumeration method to obtain the residual required cutting quantity P sy Is an optimal cutting scheme.
13. An electronic device, comprising:
a processor; and
a memory storing computer instructions that, when executed by the processor, cause the processor to perform the method of any of claims 1-6.
14. A non-transitory computer storage medium storing a computer program which, when executed by a plurality of processors, causes the processors to perform the method of any of claims 1-6.
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Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103595053A (en) * | 2013-11-19 | 2014-02-19 | 云南电网公司电网规划研究中心 | Optimization generator tripping method of power grid stability strategy on basis of capacity proximity principle |
| CN105515054A (en) * | 2016-02-16 | 2016-04-20 | 南京南瑞继保电气有限公司 | Electric power system optimized generator tripping method based on implicit enumeration method |
| CN108539750A (en) * | 2018-05-17 | 2018-09-14 | 国网山东省电力公司经济技术研究院 | A kind of accurate load control system and method based on steady control technology |
| CN111478332A (en) * | 2020-04-02 | 2020-07-31 | 贵州电网有限责任公司 | Transient stability emergency control tripping fixed value online adjustment method based on conservative limit |
| CN111585286A (en) * | 2020-07-06 | 2020-08-25 | 内蒙古电力(集团)有限责任公司内蒙古电力科学研究院分公司 | Security and stability control system strategy making method considering cluster power coefficient |
| CN112803426A (en) * | 2021-01-05 | 2021-05-14 | 许继集团有限公司 | Load shedding control method and device |
| CN113241761A (en) * | 2020-09-08 | 2021-08-10 | 云南电网有限责任公司 | Fixed value setting method and system for linear machine switching quantity required by power grid stability control |
| CN114865716A (en) * | 2022-05-11 | 2022-08-05 | 南京南瑞继保电气有限公司 | Cutter amount distribution method and system |
| CN115800307A (en) * | 2022-10-14 | 2023-03-14 | 国家电网有限公司西北分部 | Method for selecting high-frequency generator tripping points of multi-direct-current transmission-end power grid |
-
2023
- 2023-03-24 CN CN202310301095.XA patent/CN116488252B/en active Active
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103595053A (en) * | 2013-11-19 | 2014-02-19 | 云南电网公司电网规划研究中心 | Optimization generator tripping method of power grid stability strategy on basis of capacity proximity principle |
| CN105515054A (en) * | 2016-02-16 | 2016-04-20 | 南京南瑞继保电气有限公司 | Electric power system optimized generator tripping method based on implicit enumeration method |
| CN108539750A (en) * | 2018-05-17 | 2018-09-14 | 国网山东省电力公司经济技术研究院 | A kind of accurate load control system and method based on steady control technology |
| CN111478332A (en) * | 2020-04-02 | 2020-07-31 | 贵州电网有限责任公司 | Transient stability emergency control tripping fixed value online adjustment method based on conservative limit |
| CN111585286A (en) * | 2020-07-06 | 2020-08-25 | 内蒙古电力(集团)有限责任公司内蒙古电力科学研究院分公司 | Security and stability control system strategy making method considering cluster power coefficient |
| CN113241761A (en) * | 2020-09-08 | 2021-08-10 | 云南电网有限责任公司 | Fixed value setting method and system for linear machine switching quantity required by power grid stability control |
| CN112803426A (en) * | 2021-01-05 | 2021-05-14 | 许继集团有限公司 | Load shedding control method and device |
| CN114865716A (en) * | 2022-05-11 | 2022-08-05 | 南京南瑞继保电气有限公司 | Cutter amount distribution method and system |
| CN115800307A (en) * | 2022-10-14 | 2023-03-14 | 国家电网有限公司西北分部 | Method for selecting high-frequency generator tripping points of multi-direct-current transmission-end power grid |
Non-Patent Citations (1)
| Title |
|---|
| 程维杰等: "基于隐枚举法的快速分级切负荷优化方法", 《电力系统保护与控制》, vol. 49, no. 5, 31 May 2021 (2021-05-31), pages 063 - 068 * |
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