CN117335429B - Optimal scheduling method and system for power transmission channel and electronic equipment - Google Patents
Optimal scheduling method and system for power transmission channel and electronic equipment Download PDFInfo
- Publication number
- CN117335429B CN117335429B CN202311267878.7A CN202311267878A CN117335429B CN 117335429 B CN117335429 B CN 117335429B CN 202311267878 A CN202311267878 A CN 202311267878A CN 117335429 B CN117335429 B CN 117335429B
- Authority
- CN
- China
- Prior art keywords
- power transmission
- receiving end
- transmission channel
- output
- load
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 230000005540 biological transmission Effects 0.000 title claims abstract description 195
- 238000000034 method Methods 0.000 title claims abstract description 37
- 238000011156 evaluation Methods 0.000 claims abstract description 22
- 239000003245 coal Substances 0.000 claims abstract description 15
- 238000005457 optimization Methods 0.000 claims description 42
- 238000004590 computer program Methods 0.000 claims description 8
- 230000009194 climbing Effects 0.000 claims description 7
- 239000000446 fuel Substances 0.000 claims description 6
- 238000010606 normalization Methods 0.000 claims description 5
- 238000012545 processing Methods 0.000 claims description 5
- 230000006870 function Effects 0.000 claims description 3
- 238000010276 construction Methods 0.000 claims description 2
- 230000000295 complement effect Effects 0.000 description 10
- 230000000694 effects Effects 0.000 description 3
- 238000005259 measurement Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000000750 progressive effect Effects 0.000 description 1
- 230000001105 regulatory effect Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
Classifications
-
- 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
- H02J3/04—Circuit arrangements for ac mains or ac distribution networks for connecting networks of the same frequency but supplied from different sources
- H02J3/06—Controlling transfer of power between connected networks; Controlling sharing of load between connected networks
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/22—Matching criteria, e.g. proximity measures
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/06—Energy or water supply
-
- 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
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2123/00—Data types
- G06F2123/02—Data types in the time domain, e.g. time-series data
-
- 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
- H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
-
- 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
- H02J2300/20—The dispersed energy generation being of renewable origin
- H02J2300/22—The renewable source being solar energy
- H02J2300/24—The renewable source being solar energy of photovoltaic origin
-
- 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
- H02J2300/20—The dispersed energy generation being of renewable origin
- H02J2300/28—The renewable source being wind energy
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- Power Engineering (AREA)
- Data Mining & Analysis (AREA)
- Economics (AREA)
- Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
- Bioinformatics & Computational Biology (AREA)
- Water Supply & Treatment (AREA)
- General Engineering & Computer Science (AREA)
- Evolutionary Biology (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Artificial Intelligence (AREA)
- Life Sciences & Earth Sciences (AREA)
- Public Health (AREA)
- Evolutionary Computation (AREA)
- General Health & Medical Sciences (AREA)
- Human Resources & Organizations (AREA)
- Marketing (AREA)
- Primary Health Care (AREA)
- Strategic Management (AREA)
- Tourism & Hospitality (AREA)
- General Business, Economics & Management (AREA)
- Supply And Distribution Of Alternating Current (AREA)
Abstract
The invention provides a power transmission channel optimal scheduling method, a system and electronic equipment, belonging to the field of power grid optimal scheduling, wherein the method comprises the following steps: acquiring information of a power unit of a power transmission and reception end, output information of new energy sources of the power transmission end in a set period of time and load demand information of the power transmission end; determining complementarity evaluation indexes of the new energy source of the transmitting end and the load of the receiving end according to the output information of the new energy source of the transmitting end and the demand information of the load of the receiving end, and further determining a plurality of typical days; the power transmission channel is equivalent to a unit according to the adjustment gear of the transmission power of the power transmission channel, and the constraint of the power transmission channel is determined; based on a plurality of typical days and power transmission channel constraints, according to the new energy output information of a transmitting end, the load demand information of a receiving end and the information of a transmitting and receiving end thermal power unit, taking the minimum sum of the coal consumption cost and the start-stop cost of the thermal power unit as a target, establishing a power transmission channel optimal scheduling model, and solving to obtain a power transmission channel optimal scheduling scheme. The invention improves the power transmission capacity of the power transmission channel and enhances the capacity of the power grid for absorbing new energy.
Description
Technical Field
The invention relates to the field of power grid optimal scheduling, in particular to a power transmission channel optimal scheduling method, a power transmission channel optimal scheduling system and electronic equipment taking the complementary characteristics of a transmitting end and a receiving end into consideration.
Background
At present, the problem of insufficient new energy absorbing capacity of a transmitting end often occurs in a large-scale grid-connected process due to the imbalance of the space-time distribution of new energy resources, so that the power of the transmitting end is excessive and the power supply of a receiving end load is insufficient. In order to improve the consumption rate of excess power in the transmitting end, a reasonable and effective power transmission channel optimization scheduling strategy needs to be formulated. In the current power transmission channel optimal scheduling strategy, most of the new energy bases simply determine a power transmission curve of a power transmission channel according to the load characteristics of a receiving end, so that the power transmission channel is difficult to adapt to flexible power transmission requirements of a power grid under large-scale new energy access, and the space-time complementary characteristics of the new energy of the transmitting end and the load of the receiving end are not fully considered; meanwhile, the daily power transmission channel only has two-level basic power transmission curves, and a fine optimization model of the power transmission capacity of the power transmission channel for transmitting the new energy base power is established based on the complementary characteristics of the power transmission receiving end of the new energy, so that the flexible adjustment potential of the power transmission channel is fully excavated, and the power transmission cost is reduced.
Disclosure of Invention
The invention aims to provide a power transmission channel optimal scheduling method, a power transmission channel optimal scheduling system and electronic equipment, which can improve the power transmission capacity of a power transmission channel and enhance the capacity of a power grid for absorbing new energy.
In order to achieve the above object, the present invention provides the following solutions:
an optimized scheduling method for a power transmission channel comprises the following steps:
Acquiring information of a power unit of a power transmission and reception end, output information of new energy sources of the power transmission end in a set period of time and load demand information of the power transmission end;
Determining the complementarity evaluation index of the new energy source of the transmitting end and the load of the receiving end according to the output information of the new energy source of the transmitting end and the load demand information of the receiving end in a set period;
determining a plurality of typical days according to complementarity evaluation indexes of the new energy source of the transmitting end and the load of the receiving end;
According to the adjustment gear of the transmission power of the transmission channel, the transmission channel is equivalent to a unit, and the constraint of the transmission channel is determined;
based on a plurality of typical days and the constraint of the power transmission channel, according to the new energy output information of the transmitting end, the load demand information of the receiving end and the information of the transmitting and receiving end thermal power unit, a power transmission channel optimization scheduling model is established by taking the minimum sum of the coal consumption cost and the start-stop cost of the thermal power unit as a target;
Solving the power transmission channel optimal scheduling model to obtain a power transmission channel optimal scheduling scheme; the power transmission channel optimization scheduling scheme comprises state variables of all thermal power units, output of all thermal power units, state variables of all equivalent units and output of all equivalent units in a scheduling period.
In order to achieve the above purpose, the present invention also provides the following solutions:
A power transmission channel optimization scheduling system, comprising:
The data acquisition module is used for acquiring the information of the sending and receiving end thermal power unit, the output information of the sending end new energy source in a set period of time and the demand information of the receiving end load;
The complementarity determining module is connected with the data acquisition module and used for determining complementarity evaluation indexes of the new energy source of the sending end and the load of the receiving end according to the output information of the new energy source of the sending end and the load demand information of the receiving end in a set period of time;
The typical day determining module is connected with the complementarity determining module and is used for determining a plurality of typical days according to complementarity evaluation indexes of the new energy source of the transmitting end and the load of the receiving end;
the channel constraint determining module is used for equivalent of the power transmission channel as a unit according to the adjustment gear of the transmission power of the power transmission channel and determining the constraint of the power transmission channel;
The model construction module is respectively connected with the data acquisition module, the typical day determination module and the channel constraint determination module and is used for establishing a power transmission channel optimization scheduling model based on a plurality of typical days and the power transmission channel constraint and taking the minimum sum of the coal consumption cost and the start-stop cost of the thermal power generating unit as a target according to the power transmission end new energy output information, the receiving end load demand information and the power transmission end thermal power generating unit information;
The optimization scheme determining module is connected with the model constructing module and used for solving the power transmission channel optimization scheduling model to obtain a power transmission channel optimization scheduling scheme; the power transmission channel optimization scheduling scheme comprises state variables of all thermal power units, output of all thermal power units, state variables of all equivalent units and output of all equivalent units in a scheduling period.
In order to achieve the above purpose, the present invention also provides the following solutions:
an electronic device comprising a memory and a processor, the memory being configured to store a computer program, the processor being configured to run the computer program to cause the electronic device to perform the power transmission channel optimization scheduling method described above.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects: according to the invention, the complementarity evaluation index of the new energy source of the transmitting end and the load of the receiving end is determined according to the output information of the new energy source of the transmitting end and the demand information of the load of the receiving end in a set period, and the complementarity evaluation index can be used for analyzing the complementarity conditions of different new energy source power stations and load ends under different typical days. And then the transmission channel is equivalent to a unit according to the adjustment gear of the transmission power of the transmission channel, the constraint of the transmission channel is determined, the transmission power of the transmission channel is discretely optimized, the stepped constraint of the transmission power of the transmission channel can be met, and the scheduling capability of the transmission channel is more refined. And then based on a plurality of typical days and power transmission channel constraints, according to the new energy output information of the transmitting end, the load demand information of the receiving end and the information of the transmitting and receiving end thermal power unit, taking the minimum sum of the coal consumption cost and the start-stop cost of the thermal power unit as a target, establishing a power transmission channel optimal scheduling model, and solving to obtain a power transmission channel optimal scheduling scheme. The invention fully digs the flexible adjustment potential of the transmission channel, reduces the transmission cost, improves the transmission capacity of the transmission channel, and enhances the capacity of the power grid for absorbing new energy.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions of the prior art, the drawings that are needed in the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of a power transmission channel optimization scheduling method provided by the invention;
fig. 2 is a schematic diagram of an optimized scheduling system for a power transmission channel provided by the invention.
Symbol description: the system comprises a 1-data acquisition module, a 2-complementarity determining module, a 3-typical day determining module, a 4-channel constraint determining module, a 5-model building module and a 6-optimization scheme determining module.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The invention aims to solve the problems of excessive power of a transmitting end and insufficient power supply of a receiving end load, and provides a power transmission channel optimal scheduling method, a system and electronic equipment.
In order that the above-recited objects, features and advantages of the present invention will become more readily apparent, a more particular description of the invention will be rendered by reference to the appended drawings and appended detailed description.
Example 1
As shown in fig. 1, this embodiment provides a power transmission channel optimization scheduling method, including:
Step 100: and acquiring the information of the power generating unit of the transmitting and receiving end, the output information of new energy sources of the transmitting end in a set period of time and the demand information of the load of the receiving end.
Specifically, the new energy output information of the transmitting end comprises the new energy output of the transmitting end at each moment in a set period. The receiving end load demand information comprises receiving end load values at all moments in a set period. The sending and receiving terminal thermal power generating unit information comprises: the method comprises the steps of feeding the total number of the thermal power units at the end, receiving the total number of the thermal power units at the end, the fuel cost coefficient of each thermal power unit at the end, the single starting cost of each thermal power unit at the end, the single stopping cost of each thermal power unit at the end and the single stopping cost of each thermal power unit at the end.
Step 200: and determining the complementarity evaluation index of the new energy source of the transmitting end and the load of the receiving end according to the output information of the new energy source of the transmitting end and the load demand information of the receiving end in the set period.
The invention researches the trend of the new energy output curve of the transmitting end and the load demand curve of the receiving end in a certain time period and is used as a basis for describing whether the two groups of data are similar or not. The similarity degree is judged by calculating the distance between the output of the new energy source at the transmitting end and the load value at the receiving end at a certain moment, and the smaller the value is, the better the matching performance between the new energy source at the transmitting end and the load value at the receiving end is. Further, step 200 includes:
(21) And determining a time sequence similarity coefficient according to the output information of the new energy source of the transmitting end and the load demand information of the receiving end in a set period based on the Euclidean distance and the cosine distance.
Specifically, the following formula is used to determine the time sequence similarity coefficient:
α＝0.3D1+0.7D2；
Wherein alpha is a time sequence similarity coefficient, D 1 is Euclidean distance between new energy output of a transmitting end and load value of a receiving end, D 2 is cosine distance between new energy output of the transmitting end and load value of the receiving end, T ' is total time number in a set period, P ' load,t' is ratio of load value of the receiving end at time T ' to maximum load in whole day, P ' g,t is ratio of new energy output of the transmitting end at time T ' to maximum output in whole day, P load,t' is load value of the receiving end at time T ', P g,t' is new energy output of the transmitting end at time T ', For setting the maximum value of the load value of the receiving end in the period of time,/>For setting the maximum value of the new energy output of the transmitting end in the period, 0.3 and 0.7 are weights of Euclidean distance and cosine distance respectively.
(22) According to the new energy output information of the transmitting end in the set period, carrying out normalization processing on the new energy output of the transmitting end at each moment in the set period to obtain normalized transmitting end output at each moment in the set period: Wherein P 'g,t' is the normalized delivery end output at time t'/> The minimum value of the new energy output of the transmitting end in the set period is set.
(23) According to the receiving end load demand information in the set period, carrying out normalization processing on the receiving end load values at all the moments in the set period to obtain normalized receiving end load values at all the moments in the set period: Wherein P 'load,t' is the normalized receiver-side load value at time t'/> Is the minimum value of the load value of the receiving end in the set period.
(24) According to the normalized output of the output end at each moment in the set period, determining the fluctuation amount of the output end at each moment: ΔP "g,t'＝P″g,t'+1-P″g,t'.
(25) According to the normalized receiving end load value at each moment in the set period, determining the fluctuation amount of the receiving end load at each moment: ΔP "load,t'＝P″load,t'+1-P″load,t'.
(26) And determining a fluctuation consistency coefficient according to the fluctuation amount of the sending end output at each moment and the fluctuation amount of the receiving end load at each moment.
And (22) to (26) simplifying the load tracking coefficient, adopting normalization processing to the data, and representing the matching difference of the new energy output and the load by using the ratio of the fluctuation difference of the transmitting end and the receiving end.
Specifically, the fluctuation consistency coefficient is determined using the following formula:
Wherein, beta is the fluctuation consistency coefficient, T 'is the total time number in the set period, beta t' is the fluctuation coefficient at the time of T', deltaP 'load,t' is the fluctuation amount of the receiving end load at the time of T', deltaP 'g,t' is the fluctuation amount of the sending end output at the time of T'.
(27) And carrying out weighted summation on the time sequence similarity coefficient and the fluctuation consistency coefficient to obtain a complementarity evaluation index of the new energy source of the transmitting end and the load of the receiving end: γ=ω 1α+ω2 β; wherein, γ is the complementarity evaluation index of the new energy source at the transmitting end and the load at the receiving end, ω 1 is the weight parameter of the time sequence similarity coefficient, ω 2 is the weight parameter of the fluctuation consistency coefficient, and in this embodiment, ω 1 and ω 2 are both 0.5.
Step 300: and determining a plurality of typical days according to the complementarity evaluation indexes of the new energy source at the transmitting end and the load at the receiving end. The complementary evaluation index and the matching are described in table 1.
TABLE 1 complementarity evaluation index and matching description Table
| Index of complementarity evaluation | 0～2 | 2～4 | 4～8 | >8 |
| Matchability description | Strong matching | Moderate matching | Weak matching | Mismatch of |
According to table 1, a description of the matching is selected, and typical days of four matching types are selected respectively to compare the difference between the current cost and the original cost under different matching intensities.
The invention firstly collects wind power and photovoltaic output information of a transmitting and receiving end, load demand information of the transmitting and receiving end and thermal power unit information which can be put into use, wherein the wind power and photovoltaic output information of the transmitting and receiving end comprises: and the wind power and photovoltaic unit output collection and the wind power and photovoltaic output fluctuation information of each time period are obtained within 24 hours. The load demand information of the sending and receiving end comprises: and sending receiving end load demand information and load demand fluctuation information of each time period within 24 hours, then constructing complementary characteristic indexes of new energy sources of the sending end and the receiving end load by utilizing Euclidean distance, cosine distance and load tracking, further obtaining complementary coefficients of the new energy sources of the sending end and the receiving end load under different typical days, and providing a scheduling scene for a subsequent power transmission channel optimal scheduling model.
Step 400: and (3) according to the adjustment gear of the transmission power of the transmission channel, the transmission channel is equivalent to a unit, and the constraint of the transmission channel is determined.
Considering that the transmission power adjustment of the direct current transmission channel needs to meet various complex constraint conditions, the modeling complexity is increased, and the modeling method for equivalent transmission channel into a unit is adopted: and assuming N gears for adjusting transmission power of the transmission channel, then assuming N equivalent generator sets. The output forces of the N equivalent generator sets are superimposed to form a transmission power curve of the transmission channel.
In this embodiment, the power transmission channel constraint includes an equivalent unit output constraint, an equivalent unit adjustment time constraint, and a daily channel power transmission constraint.
(41) The output constraint of the equivalent unit is as follows:
Wherein n=1, 2, N is the total number of equivalent units corresponding to the transmission channel, t=1, 2, T is the number of times in the scheduling period, P line,n,t is the output of the nth equivalent unit at time T, u n,t is the state variable of the nth equivalent unit at time T, if the nth equivalent unit at time T is in an operating state, u n,t =1, otherwise u n,t =0, Is the minimum output of the nth equivalent unit,/>The maximum output of the nth equivalent unit.
To ensure the stepping of the overall curve power: I.e. the output level of the equivalent unit is limited at/>, as long as the unit is started up
(42) The equivalent unit adjustment time constraint is:
Wherein n=1, 2, & gt, N, t=1, 2, & gt, T, v n,t is the start 0-1 variable of the nth equivalent unit at time T, if the nth equivalent unit is started at time T, v n,t =1, otherwise v n,t＝0,vn,t-1 is a starting 0-1 variable of the nth equivalent unit at the time T-1, u n,t-1 is a state variable of the nth equivalent unit at the time T-1, and S n is an upper limit of the starting times of the nth equivalent unit in a set period.
The equivalent unit must not be reversely regulated in a short time: u n,t≤un,t-1.
The start-stop sequence of the equivalent units is specified in the adjustment time constraint of the equivalent units, and only when the first equivalent unit is in a start-up state, the second equivalent unit can be started, and the minimum continuous start-up time constraint of the equivalent units is overlapped, so that the effect that the equivalent units cannot be reversely adjusted in a short time is achieved.
(43) The daily channel transmission electric quantity constraint is as follows:
Wherein P line,t is the total output of the equivalent unit at time t, and Y is the scheduled daily channel transmission electric quantity preset quantity.
Step 500: based on a plurality of typical days and the constraint of the power transmission channel, according to the output information of the new energy source at the transmitting end, the load demand information of the receiving end and the information of the thermal power unit at the transmitting end, the minimum sum of the coal consumption cost and the start-stop cost of the thermal power unit is taken as a target, and a power transmission channel optimization scheduling model is established.
The schedule of the present invention is based on a long time scale, continuously optimized for 24 hours at 1 hour intervals. And optimizing and scheduling the power transmission channel connected with the power transmission and reception end by taking the minimum coal consumption cost and start-stop cost of the thermal power generating unit within 24 hours as targets, coordinating and optimizing the operation of the thermal power generating unit and the operation plan of the direct current line under the condition of minimum cost, and constructing a power transmission channel optimizing and scheduling model considering the complementary characteristics of the power transmission and reception end. The direct current system can be connected with a power grid of the receiving end, power fluctuation of new energy sources is stabilized through the matched thermal power generating unit, and meanwhile, the receiving end outputs redundant electric quantity to the receiving end through a power transmission channel.
Specifically, the power transmission channel optimization scheduling model aims at reducing the overall operation cost and optimizing the thermal power output ratio of the power transmission and reception ends, and the objective function is as follows:
minE＝H+Cstart+Cstop；
Wherein E is the sum of the coal consumption cost and the start-stop cost of the thermal power generating unit, H is the sum of the coal consumption cost of the power generating unit at the sending end and the coal consumption cost of the power generating unit at the receiving end, C start is the sum of the start-up cost of the power generating unit at the sending end and the start-up cost of the power generating unit at the receiving end, C stop is the sum of the stop cost of the power generating unit at the sending end and the stop cost of the power generating unit at the receiving end, K s is the total number of power generating units at the sending end, K r is the total number of power generating units at the receiving end, T is the time in the scheduling period, For the fuel cost coefficient of the k 1 thermal power generating unit at the sending end,/> Is the fuel cost coefficient of the k 2 thermal power generating unit at the receiving end,/>Output of the k 1 thermal power generating unit is sent to the end at time t,/>Output of the k 2 thermal power generating unit at t moment receiving end,/>As the state variable of the k 1 thermal power generating unit at the t moment, if the k 1 thermal power generating unit at the t moment is in the running state, the method is thatOtherwise Is the state variable of the (k 1) th thermal power unit sent at the time of t-1,/>As the state variable of the k 2 thermal power generating unit at the receiving end at the moment t, if the k 2 thermal power generating unit at the receiving end at the moment t is in the running state, the following is trueOtherwise/> Is the state variable of the k 2 thermal power generating unit at the receiving end at the time t-1,/>For the single start cost of the k 1 thermal power generating unit of the sending end,/>Is the single start cost of the k 2 thermal power generating unit at the receiving end, i.e./>For the single shutdown cost of the k 1 thermal power generating unit at the sending end, the method comprises the following steps ofThe method is the single shutdown cost of the k 2 th thermal power generating unit at the receiving end.
Constraints of the power transmission channel optimization scheduling model further include: the power supply and receiving end power balance constraint, the thermal power unit output constraint, the thermal power unit climbing constraint, the thermal power unit start-stop time constraint and the hot standby constraint.
(51) The power balance constraint of the transmitting and receiving end means that the transmitting end transmits redundant output to the receiving end by using a power transmission channel, and a balance relation exists between the output of the transmitting and receiving end and the load of the receiving end:
wherein, Is the sum of the output of new energy sent by the end at the moment t,/>The sum of the output of the new energy source of the receiving end at the moment t; For the load demand of the sending end at the moment t,/> And P line,t is the transmission power of the transmission channel at the moment t for the load demand of the receiving end at the moment t.
(52) The output constraint of the thermal power generating unit is as follows:
Wherein k 1＝1,2,...,Ks,k2＝1,2,...,Kr, t=1, 2,.., Is the minimum output value of the k 1 thermal power generating unit at the transmitting end,/>For the maximum output value of the k 1 thermal power generating unit at the transmitting end, the maximum output value of the k 1 thermal power generating unit is/areIs the minimum output value of the k 2 thermal power generating unit at the receiving end,/>The maximum output value of the k 2 thermal power generating unit at the receiving end.
(53) The climbing constraint of the thermal power generating unit is as follows:
Wherein k 1＝1,2,...,Ks,k2＝1,2,...,Kr, t=1, 2,.., For the maximum downward climbing rate of the k 1 thermal power generating unit at the transmitting end,/>For the maximum upward climbing rate of the k 1 thermal power generating unit at the transmitting end,/>Is the downward maximum climbing rate of the k 2 th thermal power generating unit at the receiving end,/>The maximum upward climbing rate of the k 2 thermal power generating unit at the receiving end is achieved.
(54) The starting and stopping time constraint of the thermal power generating unit is that after the generator unit is started or stopped, a certain time requirement is met to start or stop again:
Wherein k 1＝1,2,...,Ks,k2＝1,2,...,Kr, t=1, 2,.., For the minimum running time of the power generating unit of the power transmitting end, the power transmitting end is provided with a power transmitting endFor minimum down time of power unit for power deliveryFor the minimum running time of the receiving end thermal power generating unit,/>Is the minimum downtime of the receiving thermal power generating unit.
(55) When the thermal standby constraint, namely the receiving end thermal power unit breaks down, the thermal standby equipment acts as a task of the fault unit:
Where ρ represents the hot standby rate of the receiving end.
Step 600: and solving the power transmission channel optimal scheduling model to obtain a power transmission channel optimal scheduling scheme. The power transmission channel optimization scheduling scheme comprises state variables of all thermal power units, output of all thermal power units, state variables of all equivalent units and output of all equivalent units in a scheduling period.
The power transmission channel optimal scheduling model established by the invention is a mixed integer nonlinear programming model, adopts a piecewise linearization idea, uses branch-and-bound algorithms (branch andbound, B & B) as reference, reduces the number of different proportions of the thermal power generating unit to be solved by the algorithm through branch-reduction operation, and improves the solving speed of the power transmission channel optimal scheduling model. In addition, the algorithm starts iteration from the upper and lower boundaries which are closer to the optimal value, the branch reduction quantity is improved, the convergence of the algorithm is accelerated, and Matlab and CPLEX software are used for solving.
Further, the power transmission channel optimal scheduling method further comprises the following steps:
Step 700: according to the output force of each equivalent unit at any moment in the scheduling period, determining the transmission power of the transmission channel at the corresponding moment: Wherein P line,t is the transmission power of the transmission channel at time t.
The invention provides a measurement mode of two source load matching characteristics of a time sequence similarity coefficient (alpha) and a fluctuation consistency coefficient (beta), and the measurement mode is used for evaluating the complementary characteristics of a transmitting end and a receiving end, can be used for analyzing the complementary conditions of different new energy source power stations and load ends under different typical days, and can be used for optimizing and scheduling under the complementary characteristics of the transmitting end and the receiving end in the follow-up. Meanwhile, a modeling method for equivalent power transmission channels into units is provided in an optimized scheduling model of the power transmission channels, the transmission power of the power transmission channels is subjected to discrete optimization, the stepped constraint of the transmission power of the power transmission channels can be met, and meanwhile, the unidirectional adjustment of the power transmission channels is realized by prescribing the logic relation of starting and stopping of the equivalent units, so that the scheduling capability of the power transmission channels is more refined, the flexible adjustment potential of the power transmission channels is fully excavated, and the power transmission cost is reduced.
Example two
In order to execute the method corresponding to the above embodiment to achieve the corresponding functions and technical effects, a power transmission channel optimization scheduling system is provided below.
As shown in fig. 2, the power transmission channel optimization scheduling system provided in this embodiment includes: the system comprises a data acquisition module 1, a complementarity determining module 2, a typical day determining module 3, a channel constraint determining module 4, a model building module 5 and an optimization scheme determining module 6.
The data acquisition module 1 is used for acquiring power unit information of a power transmission and reception terminal, power output information of new energy sources of the power transmission terminal in a set period of time and load demand information of the power transmission terminal.
The complementarity determining module 2 is connected with the data obtaining module 1, and the complementarity determining module 2 is used for determining complementarity evaluation indexes of the new energy source of the sending end and the load of the receiving end according to the output information of the new energy source of the sending end and the load demand information of the receiving end in a set period.
The typical day determining module 3 is connected with the complementarity determining module 2, and the typical day determining module 3 is used for determining a plurality of typical days according to complementarity evaluation indexes of the new energy source at the transmitting end and the load at the receiving end.
The channel constraint determining module 4 is used for equivalent the transmission channel as a unit according to the adjustment gear of the transmission power of the transmission channel and determining the constraint of the transmission channel.
The model building module 5 is respectively connected with the data acquisition module 1, the typical day determination module 3 and the channel constraint determination module 4, and the model building module 5 is used for building a power transmission channel optimization scheduling model based on a plurality of typical days and the power transmission channel constraint, according to the power transmission end new energy output information, the power receiving end load demand information and the power transmission and receiving end thermal power unit information, and with the minimum sum of the coal consumption cost and the start-stop cost of the thermal power unit as a target.
The optimization scheme determining module 6 is connected with the model constructing module 5, and the optimization scheme determining module 6 is used for solving the power transmission channel optimization scheduling model to obtain a power transmission channel optimization scheduling scheme. The power transmission channel optimization scheduling scheme comprises state variables of all thermal power units, output of all thermal power units, state variables of all equivalent units and output of all equivalent units in a scheduling period.
Compared with the prior art, the power transmission channel optimal scheduling system provided by the embodiment has the same beneficial effects as the power transmission channel optimal scheduling method provided by the first embodiment, and is not described herein again.
Example III
The embodiment provides an electronic device, including a memory and a processor, where the memory is configured to store a computer program, and the processor is configured to run the computer program to cause the electronic device to execute the power transmission channel optimization scheduling method of the first embodiment.
Alternatively, the electronic device may be a server.
In addition, the embodiment of the invention also provides a computer readable storage medium, which stores a computer program, and when the computer program is executed by a processor, the power transmission channel optimization scheduling method of the first embodiment is realized.
In the present specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different point from other embodiments, and identical and similar parts between the embodiments are all enough to refer to each other.
The principles and embodiments of the present invention have been described herein with reference to specific examples, the description of which is intended only to assist in understanding the methods of the present invention and the core ideas thereof; also, it is within the scope of the present invention to be modified by those of ordinary skill in the art in light of the present teachings. In view of the foregoing, this description should not be construed as limiting the invention.
Claims (9)
1. The power transmission channel optimal scheduling method is characterized by comprising the following steps of:
Acquiring information of a power unit of a power transmission and reception end, output information of new energy sources of the power transmission end in a set period of time and load demand information of the power transmission end; the new energy output information of the transmitting end comprises the new energy output of the transmitting end at each moment in a set period; the receiving end load demand information comprises receiving end load values at all moments in a set period;
Determining a complementarity evaluation index of the new energy source of the transmitting end and the load of the receiving end according to the output information of the new energy source of the transmitting end and the load demand information of the receiving end in a set period of time, wherein the method specifically comprises the following steps:
Determining a time sequence similarity coefficient according to the output information of the new energy source of the transmitting end and the load demand information of the receiving end in a set period of time based on the Euclidean distance and the cosine distance;
Normalizing the new energy output of the transmitting end at each moment in the set time period according to the new energy output information of the transmitting end in the set time period to obtain normalized transmitting end output at each moment in the set time period;
According to the receiving end load demand information in the set period, carrying out normalization processing on the receiving end load values at all the moments in the set period to obtain normalized receiving end load values at all the moments in the set period;
Determining the fluctuation amount of the delivery end output at each moment according to the normalized delivery end output at each moment in the set period;
determining the fluctuation amount of the receiving end load at each moment according to the normalized receiving end load value at each moment in the set period;
determining a fluctuation consistency coefficient according to the fluctuation amount of the power output of the power transmission end at each moment and the fluctuation amount of the load of the power reception end at each moment;
Carrying out weighted summation on the time sequence similarity coefficient and the fluctuation consistency coefficient to obtain a complementarity evaluation index of the new energy source of the transmitting end and the load of the receiving end;
determining a plurality of typical days according to complementarity evaluation indexes of the new energy source of the transmitting end and the load of the receiving end;
According to the adjustment gear of the transmission power of the transmission channel, the transmission channel is equivalent to a unit, and the constraint of the transmission channel is determined;
based on a plurality of typical days and the constraint of the power transmission channel, according to the new energy output information of the transmitting end, the load demand information of the receiving end and the information of the transmitting and receiving end thermal power unit, a power transmission channel optimization scheduling model is established by taking the minimum sum of the coal consumption cost and the start-stop cost of the thermal power unit as a target;
Solving the power transmission channel optimal scheduling model to obtain a power transmission channel optimal scheduling scheme; the power transmission channel optimization scheduling scheme comprises state variables of all thermal power units, output of all thermal power units, state variables of all equivalent units and output of all equivalent units in a scheduling period.
2. The power transmission channel optimized scheduling method according to claim 1, wherein the time sequence similarity coefficient is determined by adopting the following formula:
α＝0.3D1+0.7D2；
Wherein alpha is a time sequence similarity coefficient, D 1 is Euclidean distance between new energy output of a transmitting end and load value of a receiving end, D 2 is cosine distance between new energy output of the transmitting end and load value of the receiving end, T ' is total time number in a set period, P ' load,t' is ratio of load value of the receiving end at time T ' to maximum load in whole day, P ' g,t is ratio of new energy output of the transmitting end at time T ' to maximum output in whole day, P load,t' is load value of the receiving end at time T ', P g,t' is new energy output of the transmitting end at time T ', For setting the maximum value of the load value of the receiving end in the period of time,/>The maximum value of the new energy output of the transmitting end in the set period is set.
3. The power transmission channel optimized scheduling method of claim 1, wherein the fluctuation consistency coefficient is determined by adopting the following formula:
Wherein, beta is the fluctuation consistency coefficient, T 'is the total time number in the set period, beta t' is the fluctuation coefficient at the time of T', deltaP 'load,t' is the fluctuation amount of the receiving end load at the time of T', deltaP 'g,t' is the fluctuation amount of the sending end output at the time of T'.
4. The power transmission channel optimization scheduling method according to claim 1, wherein the power transmission channel constraints comprise equivalent unit output constraints, equivalent unit adjustment time constraints and daily channel transmission power constraints;
The output constraint of the equivalent unit is as follows:
Wherein n=1, 2, N is the total number of equivalent units corresponding to the transmission channel, t=1, 2, T is the number of times in the scheduling period, P line,n,t is the output of the nth equivalent unit at time T, u n,t is the state variable of the nth equivalent unit at time T, if the nth equivalent unit at time T is in an operating state, u n,t =1, otherwise u n,t =0, Is the minimum output of the nth equivalent unit,/>Maximum output of the nth equivalent unit;
the equivalent unit adjustment time constraint is as follows:
un,t≤un,t-1；
Wherein v n,t is a variable of starting 0-1 of the nth equivalent unit at time t, if the nth equivalent unit is started at time t, v n,t =1, otherwise v n,t＝0,un,t-1 is a variable of state of the nth equivalent unit at time t-1, and S n is an upper limit of the number of times of starting the nth equivalent unit in a set period;
The daily channel transmission electric quantity constraint is as follows:
Wherein P line,t is the total output of the equivalent unit at time t, and Y is the scheduled daily channel transmission electric quantity preset quantity.
5. The power transmission channel optimized scheduling method according to claim 1, wherein the transmitting-receiving terminal power unit information includes: the method comprises the steps of feeding the total number of the thermal power units at the end, receiving the total number of the thermal power units at the end, the fuel cost coefficient of each thermal power unit at the end, the single starting cost of each thermal power unit at the end, the single stopping cost of each thermal power unit at the end and the single stopping cost of each thermal power unit at the end;
The objective function of the power transmission channel optimization scheduling model is as follows:
minE＝H+Cstart+Cstop；
Wherein E is the sum of the coal consumption cost and the start-stop cost of the thermal power generating unit, H is the sum of the coal consumption cost of the power generating unit at the sending end and the coal consumption cost of the power generating unit at the receiving end, C start is the sum of the start-up cost of the power generating unit at the sending end and the start-up cost of the power generating unit at the receiving end, C stop is the sum of the stop cost of the power generating unit at the sending end and the stop cost of the power generating unit at the receiving end, K s is the total number of power generating units at the sending end, K r is the total number of power generating units at the receiving end, T is the time in the scheduling period, For the fuel cost coefficient of the k 1 thermal power generating unit at the sending end,/> Is the fuel cost coefficient of the k 2 thermal power generating unit at the receiving end,/>Output of the k 1 thermal power generating unit is sent to the end at time t,/>Output of the k 2 thermal power generating unit at t moment receiving end,/>As the state variable of the k 1 thermal power generating unit at the t moment, if the k 1 thermal power generating unit at the t moment is in the running state, the method is thatOtherwise/> Is the state variable of the (k 1) th thermal power unit sent at the time of t-1,/>As the state variable of the k 2 thermal power generating unit at the receiving end at the moment t, if the k 2 thermal power generating unit at the receiving end at the moment t is in the running state, the following is trueOtherwise/> Is the state variable of the k 2 thermal power generating unit at the receiving end at the time t-1,/>For the single starting cost of the k 1 thermal power generating unit at the sending end,Is the single start cost of the k 2 thermal power generating unit at the receiving end, i.e./>For the single shutdown cost of the k 1 thermal power generating unit at the sending end,The method is the single shutdown cost of the k 2 th thermal power generating unit at the receiving end.
6. The power transmission channel optimization scheduling method according to claim 1, wherein the constraint condition of the power transmission channel optimization scheduling model further comprises: the power supply and receiving end power balance constraint, the thermal power unit output constraint, the thermal power unit climbing constraint, the thermal power unit start-stop time constraint and the hot standby constraint.
7. The power transmission channel optimized scheduling method according to claim 1, characterized in that the power transmission channel optimized scheduling method further comprises:
and determining the transmission power of the transmission channel at the corresponding moment according to the output force of each equivalent unit at any moment in the scheduling period.
8. An optimized power transmission channel scheduling system, characterized in that the optimized power transmission channel scheduling system comprises:
The data acquisition module is used for acquiring the information of the sending and receiving end thermal power unit, the output information of the sending end new energy source in a set period of time and the demand information of the receiving end load;
The complementarity determining module is connected with the data acquisition module and is used for determining complementarity evaluation indexes of the new energy source of the sending end and the load of the receiving end according to the output information of the new energy source of the sending end and the load demand information of the receiving end in a set period of time, and specifically comprises the following steps: determining a time sequence similarity coefficient according to the output information of the new energy source of the transmitting end and the load demand information of the receiving end in a set period of time based on the Euclidean distance and the cosine distance; normalizing the new energy output of the transmitting end at each moment in the set time period according to the new energy output information of the transmitting end in the set time period to obtain normalized transmitting end output at each moment in the set time period; according to the receiving end load demand information in the set period, carrying out normalization processing on the receiving end load values at all the moments in the set period to obtain normalized receiving end load values at all the moments in the set period; determining the fluctuation amount of the delivery end output at each moment according to the normalized delivery end output at each moment in the set period; determining the fluctuation amount of the receiving end load at each moment according to the normalized receiving end load value at each moment in the set period; determining a fluctuation consistency coefficient according to the fluctuation amount of the power output of the power transmission end at each moment and the fluctuation amount of the load of the power reception end at each moment; carrying out weighted summation on the time sequence similarity coefficient and the fluctuation consistency coefficient to obtain a complementarity evaluation index of the new energy source of the transmitting end and the load of the receiving end;
The typical day determining module is connected with the complementarity determining module and is used for determining a plurality of typical days according to complementarity evaluation indexes of the new energy source of the transmitting end and the load of the receiving end;
the channel constraint determining module is used for equivalent of the power transmission channel as a unit according to the adjustment gear of the transmission power of the power transmission channel and determining the constraint of the power transmission channel;
The model construction module is respectively connected with the data acquisition module, the typical day determination module and the channel constraint determination module and is used for establishing a power transmission channel optimization scheduling model based on a plurality of typical days and the power transmission channel constraint and taking the minimum sum of the coal consumption cost and the start-stop cost of the thermal power generating unit as a target according to the power transmission end new energy output information, the receiving end load demand information and the power transmission end thermal power generating unit information;
The optimization scheme determining module is connected with the model constructing module and used for solving the power transmission channel optimization scheduling model to obtain a power transmission channel optimization scheduling scheme; the power transmission channel optimization scheduling scheme comprises state variables of all thermal power units, output of all thermal power units, state variables of all equivalent units and output of all equivalent units in a scheduling period.
9. An electronic device comprising a memory for storing a computer program and a processor that runs the computer program to cause the electronic device to perform the power transmission channel optimization scheduling method of any one of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311267878.7A CN117335429B (en) | 2023-09-28 | 2023-09-28 | Optimal scheduling method and system for power transmission channel and electronic equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311267878.7A CN117335429B (en) | 2023-09-28 | 2023-09-28 | Optimal scheduling method and system for power transmission channel and electronic equipment |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN117335429A CN117335429A (en) | 2024-01-02 |
| CN117335429B true CN117335429B (en) | 2024-05-24 |
Family
ID=89278448
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311267878.7A Active CN117335429B (en) | 2023-09-28 | 2023-09-28 | Optimal scheduling method and system for power transmission channel and electronic equipment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117335429B (en) |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104537440A (en) * | 2014-12-29 | 2015-04-22 | 国家电网公司华中分部 | Transmission capacity and wind fire bundling optimization method for extra-high voltage channel based on entropy method |
| CN107769215A (en) * | 2018-01-19 | 2018-03-06 | 国网天津市电力公司 | Garden energy mix system optimization dispatching method based on energy hub |
| CN114925926A (en) * | 2022-05-31 | 2022-08-19 | 西安交通大学 | Direct current channel planning and operation method with polynomial time complexity |
-
2023
- 2023-09-28 CN CN202311267878.7A patent/CN117335429B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104537440A (en) * | 2014-12-29 | 2015-04-22 | 国家电网公司华中分部 | Transmission capacity and wind fire bundling optimization method for extra-high voltage channel based on entropy method |
| CN107769215A (en) * | 2018-01-19 | 2018-03-06 | 国网天津市电力公司 | Garden energy mix system optimization dispatching method based on energy hub |
| CN114925926A (en) * | 2022-05-31 | 2022-08-19 | 西安交通大学 | Direct current channel planning and operation method with polynomial time complexity |
Non-Patent Citations (1)
| Title |
|---|
| 用于提高输电通道输送功率限额的日前发电计划优化方法;张雨薇等;可再生能源;20201215;第38卷(第12期);第1640-1646页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN117335429A (en) | 2024-01-02 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111525627B (en) | Day-ahead scheduling method for flexible direct-current transmission system with pumped storage and new energy power generation | |
| CN107944757A (en) | Electric power interacted system regenerative resource digestion capability analysis and assessment method | |
| US20220029424A1 (en) | Hybrid power plant | |
| CN111769553A (en) | Optimal operation method of gas-electricity interconnection system considering wind electricity uncertainty | |
| CN110909954B (en) | Multi-stage power supply planning method for maximizing renewable energy utilization | |
| CN107959285B (en) | Optimization method, system and device for day-ahead power generation and transmission plan among regions | |
| US10713674B2 (en) | Reducing substation demand fluctuations using decoupled price schemes for demand response | |
| CN112508402B (en) | DC power transmission curve scene generation method, electronic equipment and medium | |
| CN113193547A (en) | Day-ahead-day cooperative scheduling method and system for power system considering uncertainty of new energy and load interval | |
| CN109103924A (en) | The analysis method of renewable energy digestion capability key factor based on flexibility analysis | |
| CN111342486A (en) | Optimal scheduling method of wind, light and water complementary power generation system containing cascade hydropower | |
| CN113872253B (en) | Optimal scheduling method and device for pumped storage power station combined new energy power generation | |
| CN112769156B (en) | Source network load storage coordinated operation method considering large-scale offshore wind power grid connection | |
| CN103208813A (en) | Power system daily peak regulation capability assessment method for accurately calculating wind power influence | |
| CN112018756A (en) | Day-ahead robust coordinated optimization scheduling method for gas-electricity combined system | |
| CN116823000B (en) | Hydropower compensation peak regulation analysis and evaluation method and device thereof | |
| CN118412929A (en) | Virtual power plant operation control method considering scheduling response capability | |
| CN117335429B (en) | Optimal scheduling method and system for power transmission channel and electronic equipment | |
| CN110729721B (en) | Global spare capacity calculation method for power system | |
| Wang et al. | Generation-expansion planning with linearized primary frequency response constraints | |
| CN116777147A (en) | Power balance capability calculation method, device, equipment and storage medium | |
| CN116562554A (en) | Long-short-period energy storage joint planning method considering flexible supply-demand balance | |
| CN109447456B (en) | Wind power grid-connected power system planning method considering short-term demand response | |
| CN117996861B (en) | Scheduling method for light-water coupling residual electricity hydrogen production of power distribution network and energy management device | |
| CN118674236B (en) | Day-ahead decision method and device for multi-energy complementary system, storage medium and electronic equipment |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |