CN116308301B - Coordinated multi-region power transmission maintenance method, device, computer equipment and medium - Google Patents
Coordinated multi-region power transmission maintenance method, device, computer equipment and medium Download PDFInfo
- Publication number
- CN116308301B CN116308301B CN202310525853.6A CN202310525853A CN116308301B CN 116308301 B CN116308301 B CN 116308301B CN 202310525853 A CN202310525853 A CN 202310525853A CN 116308301 B CN116308301 B CN 116308301B
- Authority
- CN
- China
- Prior art keywords
- area
- power
- region
- regional
- constraint
- 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
Classifications
-
- 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
- G06Q10/00—Administration; Management
- G06Q10/20—Administration of product repair or maintenance
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
-
- 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
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
-
- 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
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
-
- 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—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/06—Electricity, gas or water supply
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2111/00—Details relating to CAD techniques
- G06F2111/04—Constraint-based CAD
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
Abstract
The invention relates to the field of power grid overhaul, in particular to a coordinated multi-region power transmission overhaul method, a coordinated multi-region power transmission overhaul device, computer equipment and a medium, wherein the method comprises the following steps: acquiring the net load peak-valley time periods of each region, and constructing a key time period set; acquiring the output cost relation and the electric quantity standby relation of each area in the key time period set; constructing an upper maintenance plan model according to the output cost relation, the electric quantity standby relation, the tie line power and the upper constraint of each area; constructing an area maintenance plan model according to the output cost relation of each area, the power of the connecting line and the area constraint; and (3) carrying out iterative computation on the two models by adopting a target cascading algorithm based on the tie line power to obtain the power transmission maintenance plan of each region. By implementing the invention, the current cascade algorithm is adopted, and different optimization modes of two-stage scheduling are considered through two-stage coordination. Meanwhile, the calculation scale under the complex constraint of regional standby, related network safety and the like is reduced, and the calculation efficiency can meet the actual requirements of multi-region power grid dispatching.
Description
Technical Field
The invention relates to the field of power grid overhaul, in particular to a coordinated multi-region power transmission overhaul method, a coordinated multi-region power transmission overhaul device, computer equipment and a medium.
Background
Multi-level scheduling exists in the power grid system, and particularly includes provincial scheduling and national hierarchical scheduling (superior scheduling). The upper level scheduling is responsible for inter-provincial tie line planning and inter-provincial standby auxiliary service market operation, but the power transmission maintenance mode is that each provincial reports a power transmission equipment maintenance initial plan according to the power grid condition of each provincial, the upper level scheduling carries out consultation and wholesale based on experience, and the global optimization of the maintenance plan cannot be realized in a multi-region joint angle. Therefore, the current power transmission maintenance plan is difficult to realize overall optimization within the whole network range.
Disclosure of Invention
In view of the above, the invention provides a coordinated multi-area power transmission maintenance method, a coordinated multi-area power transmission maintenance device, computer equipment and a medium, so as to solve the problem that the conventional power transmission maintenance plan is difficult to realize overall optimization within the whole network range.
In a first aspect, the present invention provides a method for coordinating multiple areas of power transmission maintenance, the method comprising: acquiring the net load peak-valley time periods of each region, and constructing a key time period set; acquiring the output cost relation and the electric quantity standby relation of each area in the key time period set; constructing an upper maintenance plan model according to the output cost relation, the electric quantity standby relation, the tie line power and the upper constraint of each area; constructing an area maintenance plan model according to the output cost relation of each area, the power of the connecting line and the area constraint; and (3) based on the tie line power, performing iterative computation on the upper maintenance plan model and the regional maintenance plan model by adopting a target cascading algorithm to obtain the power transmission maintenance plans of all the regions.
In an alternative embodiment, the power reserve relationship includes a new energy rejection desired power and negative reserve relationship and a no-load desired power and positive reserve relationship.
In an alternative embodiment, constructing an upper maintenance plan model according to the regional output cost relationship, the electric quantity standby relationship, the tie line power and the upper constraint comprises: constructing an upper objective function with the minimum cost as a target according to the output cost relation, the electric quantity standby relation and the tie line power of each area; and constructing an upper maintenance plan model according to the upper objective function and the upper constraint, wherein the upper constraint comprises regional output and standby related constraint, maintenance constraint, regional power balance constraint and network constraint.
In an alternative embodiment, the superior objective function includes:
in the method, in the process of the invention,N m representing the number of regions; t represents the total time period number;N c,t representing a set of critical time periods,p m,k indicating the force exerted by the region m during the critical period k,F（p m,k ) Representing a force cost relationship;C w,m 、C d,m the new energy waste cost and the lost load cost are respectively the area m;R d,m,k 、ΔR d,m,k a local negative standby and an external negative standby for region m respectively,R u,m,k 、ΔR u,m,k local positive standby and external positive standby for region m respectively, And->The new energy waste expected electric quantity function and the load loss expected electric quantity function of the region m in the key period k are respectively represented; />、/>Respectively the t-th of the time period t-zone mlSquare term coefficients of deviation and primary term coefficients of deviation of the tie lines; />、/>Respectively the t-th of the time period t-zone mlThe upper computing power of the tie line and the computing power of each region.
In an alternative embodiment, constructing an area repair plan model based on the area output cost relationships, tie line power, and area constraints includes: constructing a region objective function with minimum cost as a target according to the output cost relation of each region; and constructing an area maintenance plan model according to the area objective function and the area constraint, wherein the area constraint comprises standby related constraint, maintenance constraint, unit output of the area and network constraint.
In an alternative embodiment, the region objective function includes:
。
in an alternative embodiment, based on the tie line power, performing iterative computation on the upper maintenance plan model and the regional maintenance plan model by using a target cascading algorithm to obtain a power transmission maintenance plan of each region, including: calculating the upper-level tie line power according to the upper-level maintenance plan model and the preset area tie line power; calculating new regional tie line power according to the upper-layer network line power and the regional maintenance plan model; calculating new upper-level network line power according to the regional interconnection line power and the upper-level maintenance plan model; judging whether the new upper cascade network line power and the new regional interconnecting line power meet convergence conditions; when the network power and the area network power do not meet the requirements, updating the upper maintenance plan model parameters and the area maintenance plan model parameters, and calculating new upper network line power and new area tie line power according to the updated upper maintenance plan model and the area maintenance plan model; if the new upper-level network line power and the new area network line power do not meet the convergence condition, repeating the steps of updating the parameters, calculating the upper-level network line power and the new area network line power until the obtained new upper-level network line power and the new area network line power meet the convergence condition; and when the convergence condition is met, obtaining a power transmission maintenance plan of the line in each area.
According to the coordinated multi-region power transmission maintenance method provided by the invention, the two-stage coordination mode is adopted, and different optimization modes of two-stage scheduling can be considered through the current cascading algorithm. The upper scheduling focuses on the overall power generation condition of each region, so that the maintenance arrangement of the inter-region interconnecting lines can be better realized; and each lower-level region is based on the solving result of the upper-level model, and the reasonable arrangement of the power transmission line overhaul plan in the region is realized by combining own specific requirements and constraints. Meanwhile, according to the power transmission maintenance method, through information integration, the upper-level scheduling enables each area to be equivalent to one node, the calculation scale under complex constraints such as partition standby and related network safety is reduced, and the calculation efficiency can meet the actual requirements of multi-area power grid scheduling.
In a second aspect, the present invention provides a coordinated multi-region power transmission maintenance apparatus, the apparatus comprising: the set construction module is used for acquiring the net load peak-valley time periods of each region and constructing a key time period set; the relation determining module is used for acquiring the output cost relation and the electric quantity standby relation of each area in the key time period set; the upper model construction module is used for constructing an upper maintenance plan model according to the output cost relation, the electric quantity standby relation, the tie line power and the upper constraint of each area; the regional model construction module is used for constructing a regional maintenance plan model according to the output cost relation of each region, the power of the connecting line and the regional constraint; and the target cascading module is used for carrying out iterative computation on the upper maintenance plan model and the regional maintenance plan model by adopting a target cascading algorithm based on the tie line power to obtain the power transmission maintenance plan of each region.
In a third aspect, the present invention provides a computer device comprising: the device comprises a memory and a processor, wherein the memory and the processor are in communication connection, the memory stores computer instructions, and the processor executes the computer instructions, so that the coordinated multi-region power transmission maintenance method according to the first aspect or any corresponding embodiment of the first aspect is executed.
In a fourth aspect, the present invention provides a computer readable storage medium having stored thereon computer instructions for causing a computer to perform the coordinated multi-region transmission service method of the first aspect or any of its corresponding embodiments.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the present invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flow diagram of a coordinated multi-zone power transmission overhaul method according to an embodiment of the invention;
FIG. 2 is a schematic diagram of a cumulative supply curve for region m according to an embodiment of the present invention;
FIG. 3 is an IEEE 118 three-region wiring diagram in accordance with an embodiment of the invention;
FIGS. 4 (a) and 4 (b) are diagrams of new energy prediction and payload prediction for regions, respectively, according to embodiments of the present invention;
FIG. 5 is a schematic diagram of tie-line service optimization results according to an embodiment of the present invention;
FIG. 6 is a schematic diagram of external positive alternate configuration results obtained for various regions according to an embodiment of the present invention;
FIG. 7 is a schematic diagram of external negative alternate configuration results obtained for various regions according to an embodiment of the present invention;
FIG. 8 is a schematic diagram of new energy power rejection expectations according to various aspects of an embodiment of the present invention;
FIG. 9 is a schematic diagram of a load shedding scheme in accordance with an embodiment of the present invention;
FIG. 10 is a full network payload and new energy prediction capability schematic according to an embodiment of the present invention;
FIG. 11 is a schematic diagram of new energy power curtailment and load shedding expectations according to various aspects of an embodiment of the present invention;
fig. 12 is a block diagram of a coordinated multi-zone power transmission service apparatus according to an embodiment of the invention;
fig. 13 is a schematic diagram of a hardware structure of a computer device according to an embodiment of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. 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.
As in the background art, it is difficult to achieve overall optimization of the current transmission maintenance plan in the whole network. And the following factors need to be considered in the joint optimization programming of the maintenance plan of the whole network: firstly, the scheduling targets and the consideration constraints of each province are different, and if the transmission maintenance of the whole network is uniformly optimized by the upper-level scheduling, the condition that the operation requirements in the province cannot be met possibly occurs. Secondly, when power shortage or excess occurs in a certain area, the power supply or new energy consumption level can be effectively improved through inter-area mutual aid, so that the inter-area mutual aid function needs to be fully considered when power transmission maintenance is compiled. Thirdly, in the middle-long term scale of the year and month, high-dimensional uncertainty factors of bus load prediction and new energy unit output prediction on a plurality of power grid nodes are overlapped, so that the refined network model cannot accurately consider the trend distribution situation.
If the initial overhaul plan is reported by each area, the upper-level scheduling is based on the mode of coordination and slight correction, which is the mode commonly adopted in the actual power grid at present, and the programming result is mainly based on the self condition of each area to carry out programming, so that the overall optimization within the whole network range is difficult to realize. And the method is also based on a full network model and medium-long term prediction data, and the unified optimization programming of the overhaul plan is carried out on the superior scheduling. The scheme has large calculation scale, and is difficult to simultaneously consider the specific targets and constraints of all areas; meanwhile, the low medium-long term prediction precision of the annual and monthly time scales is considered, the random variables such as the bus load in the power grid, the output of the new energy unit and the like are large in quantity and distributed, and the solving difficulty is high.
In view of this, the embodiment of the invention provides a coordinated multi-region power transmission maintenance method, which adopts a two-stage coordination mode, and can give consideration to different optimization modes of two-stage scheduling through the current cascading algorithm. The upper scheduling focuses on the overall power generation condition of each region, so that the maintenance arrangement of the inter-region interconnecting lines can be better realized; and each lower-level region is based on the solving result of the upper-level model, and the reasonable arrangement of the power transmission line overhaul plan in the region is realized by combining own specific requirements and constraints. Meanwhile, according to the power transmission maintenance method, through information integration, the upper-level scheduling enables each area to be equivalent to one node, the calculation scale under complex constraints such as partition standby and related network safety is reduced, and the calculation efficiency can meet the actual requirements of multi-area power grid scheduling.
In accordance with an embodiment of the present invention, there is provided an embodiment of a coordinated multi-region power transmission overhaul method, it being noted that the steps shown in the flowchart of the drawings may be performed in a computer system such as a set of computer executable instructions, and, although a logical sequence is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than what is shown or described herein.
In this embodiment, a coordinated multi-region power transmission maintenance method is provided, which may be used for an electronic device, and fig. 1 is a flowchart of a coordinated multi-region power transmission maintenance method according to an embodiment of the present invention, as shown in fig. 1, where the flowchart includes the following steps:
step S101, obtaining the net load peak-valley time periods of each region, and constructing a key time period set; the net load is specifically the difference between the load and the new energy. When the peak-valley period of the payload of each region is acquired, the period in the medium-long time scale can be acquired, however, in the medium-long time scale, high-precision prediction of the load prediction and the new energy power prediction is difficult to ensure. The probability distribution characteristic curves of the load and the new energy output are different in different seasons and different months of one year, so that the medium-long time scale can be divided, and analysis can be performed in each divided period. For example, in this embodiment, the division is made in units of weeks, and if the medium-long time scale is on the order of years, 52 periods (i.e., 52 weeks) can be divided.
In the embodiment, when the power transmission plan is formulated, the periods of the high net load peak or the low net load valley are selected for analysis, and whether maintenance is performed in other periods has no influence. The power structures and load levels of different areas are different, so that the areas need to determine periods of time in which no load or light is lost due to wind abandonment possibly occurs in different periods of time (different weeks), for example, the net load valley period with high wind power ratio is usually at night, and wind abandonment easily occurs; the provincial payload valley period of high photovoltaic duty is typically in the middle of the day, with easy light rejection.
In forming the critical period set, firstly, obtaining periods in which no load or no wind and no light can occur in different periods (different weeks) from each region, then, summarizing the periods and combining the same periods by an upper level to form a critical period set, wherein the critical period set comprises the summarized payload peak and payload valley periods, for example, the period t (week) comprises the following period every dayN p,t Peak of net loadN v,t The net load is low.
Step S102, acquiring output cost relation and electric quantity standby relation of each area in a key period set; in one embodiment, the power reserve relationship includes a new energy source waste desired power and a negative reserve relationship and a no-load desired power and a positive reserve relationship.
Specifically, for the output cost relationship of each area, the superior scheduling does not need to acquire details of each unit cost in each area, and each area can form an accumulated supply curve based on the output cost relationship. For example, when 52 time periods are divided, each zone sums the 52 time periods to form 52 cumulative supply curves including key time periods, while determining maximum and minimum startup output limits for each key time period. Where the cumulative supply curve means the total force of the area at a marginal cost. The specific formation method comprises determining the starting capacity of the corresponding key time period according to the load level of the corresponding key time period, thereby obtaining the maximum and minimum starting output limit valuesP m,t,max AndP m,t,min the turned-on generator sets are sorted according to ascending order of segmentation cost, and an in-area accumulated supply curve is obtained, as shown in fig. 2. The curve can reflect the region within the periodmRelation between output and cost of (a)。
Taking the region m as an example, it is set in the critical periodkIs subjected to normal distribution of loadN(p d,m,k ,σ d,m,k ) New energy output obeys normal distributionN(p w,m,k ,σ w,m,k ) The net load (= load-new energy output) output obeys normal distributionN(p n,m,k ,σ n,m,k ) The probability distribution Pr (·) of the payload prediction error obeys the normal distribution N(0,σ n,m,k )。
Area thenmDuring critical time periodskDesired electric quantity for new energy waste and negative standby of the arear d The correlation function of (2) is:
formula (1)
Wherein:xrepresenting the prediction error of the payload of the data,T t for a period of timetFor the number of days, e.g. annual service in weeks, thenT t =7；T k Is a critical periodkThe number of hours sustained;P w,m,max is a regionmNew energy installation capacity of the system.
Region(s)mDuring critical time periodskAnd the desired power for the region and the positive reserve for the regionr u The correlation function of (2) is:
formula (2)
Wherein:P d,m,t,max is a regionmDuring critical time periodskIs used for the prediction of the maximum load.
Step S103, constructing an upper maintenance plan model according to the output cost relation, the electric quantity standby relation, the tie line power and the upper constraint of each area; specifically, when an upper-level maintenance plan model is built, an upper-level objective function with the minimum cost as a target is built according to the output cost relation, the electric quantity standby relation and the tie-line power of each area; and then constructing an upper maintenance plan model according to the upper objective function and upper constraints, wherein the upper constraints comprise regional output and standby related constraints, maintenance constraints, regional power balance constraints and network constraints.
Step S104, constructing an area maintenance plan model according to the output cost relation of each area, the power of the connecting line and the area constraint; specifically, when each region builds a region maintenance plan model, a region objective function with minimum cost as a target is built according to the output cost relation of each region; and then constructing an area maintenance planning model according to the area objective function and the area constraint, wherein the area constraint comprises standby related constraint, maintenance constraint, unit output of the area and network constraint.
And step 105, carrying out iterative computation on the upper maintenance plan model and the regional maintenance plan model by adopting a target cascading algorithm based on the tie line power to obtain the power transmission maintenance plan of each region. Specifically, the target cascading algorithm adopts the tie line power to carry out two-stage iteration, solves the tie line power calculated by the upper level maintenance planning model, sends the tie line power to the lower level, namely each region, solves the regional maintenance planning model according to the tie line power calculated by the upper level to obtain the tie line power calculated by the lower level, and then determines whether the iteration process is completed or not according to whether convergence conditions are met between the tie line powers calculated by the upper level and the lower level. And after the power transmission maintenance plans of all the areas are formed according to the connecting lines corresponding to the calculated connecting line power.
The coordinated multi-region power transmission maintenance method provided by the embodiment of the invention adopts a two-stage coordination mode, and can give consideration to different optimization modes of two-stage scheduling through the current cascading algorithm. The upper scheduling focuses on the overall power generation condition of each region, so that the maintenance arrangement of the inter-region interconnecting lines can be better realized; and each lower-level region is based on the solving result of the upper-level model, and the reasonable arrangement of the power transmission line overhaul plan in the region is realized by combining own specific requirements and constraints. Meanwhile, according to the power transmission maintenance method, through information integration, the upper-level scheduling enables each area to be equivalent to one node, the calculation scale under complex constraints such as partition standby and related network safety is reduced, and the calculation efficiency can meet the actual requirements of multi-area power grid scheduling.
In one embodiment, the superior objective function includes:
formula (3)
In the method, in the process of the invention,N m representing the number of regions; t represents the total time period number;N c,t representing a set of critical time periods,p m,k indicating the force exerted by the region m during the critical period k,F（p m,k ) Representing a force cost relationship;C w,m 、C d,m the new energy waste cost and the lost load cost of the region m can be obtained according to experience;R d,m,k 、ΔR d,m,k a local negative standby and an external negative standby for region m respectively,R u,m,k 、ΔR u,m,k local positive standby and external positive standby for region m respectively,and->The new energy waste expected electric quantity function and the load loss expected electric quantity function of the region m in the key period k are respectively represented; />、/>The +.sup.th of the period ttribute m respectively>Square term coefficients of deviation and primary term coefficients of deviation of the tie lines; />、/>The +.sup.th of the period ttribute m respectively>The upper computing power of the tie line and the computing power of each region.
Specifically, the above step S102 gives a correlation function of a specific desired electric quantity and standby, but the two correlation functions of the formula (1) and the formula (2) are integral functions, and the nonlinearity is difficult to solve, so that the nonlinearity is approximately converted into a linear relationship, and the specific method is as follows:r d fetch interval [0, P ]]A kind of electronic deviceI(e.g. takingI=5) point of equivalence, namely:
formula (4)
Order theApproximately linearizing equation (1) to:
formula (5)
Similarly, an approximate piecewise linear function of equation (2) can be obtainedLinearization of the integral function is achieved to facilitate solution.
Based on the linearization process described above, both equation (1) and equation (2) are transformed to approximate piecewise linear functions. Thus, in the objective function formula (3)And->Each being an approximately linear piecewise function representation of the correlation function.
In one embodiment, the upper level constraints include regional and backup related constraints, overhaul constraints, regional power balance constraints, and network constraints. Wherein the region and standby related constraints are expressed using equations (6) through (13):
formula (6)
Formula (7)
Formula (8)
Formula (9)
Formula (10)
Formula (11)
Formula (12)
Formula (13)
Equations (6) and (7) indicate that the regional output and reserve provided by the regional output do not exceed the upper and lower limits of the startup capacity of the regional output in the period, equations (8) and (9) limit the local reserve to positive values, and equations (10) and (11) limit the reserve supported by the local external network not to exceed the maximum local reserve capacity provided by the regional output. Formulas (12) and (13) represent the back-up sum balance of support and acceptance for each zone.
The overhaul constraint is modeled using a three-variable approach, as shown in equations (14) through (18):
formula (14)
Formula (15)
Formula (16)
Formula (17)
Formula (18)
Wherein:for line->In the time periodt1 is maintenance, 0 is operation; />Taking 1 when the line is changed from operation to maintenance, and taking 0 at the rest time; />Taking 1 when the line is changed from overhauling to running, and taking 0 at the rest time; />For line->Is used for the maintenance period of the equipment. The formula (14) represents maintenance period constraint, the formula (15) represents that maintenance period can be maintained for 1 time, continuous maintenance time is guaranteed, and the formulas (16) - (18) determine the relation among three variables. Wherein the constraint conditions obtained from the overhaul constraint are used to generate constraints on the formula (20) in the subsequent network constraints.
The regional power balance constraint is expressed by equation (19):
formula (19)
Wherein: phi m Is a regionmA set of tie-lines connected to each other,is a circuitlIn the direction of tide, the head end is atmThen 1, otherwise-1, < >>Is a circuitlDuring critical time periodskIs a trend of (3).
Network constraints mainly include constraints in network power flow. When the network power flow is considered, not only the condition that the transmission power of the inter-regional interconnecting line in the ground state is not out of limit, but also the condition that the external reserve obtained by each region is not blocked is required to realize the recall of reserve mutual aid. The network constraints are expressed using the following formulas (20) to (23):
Formula (20)
Formula (21)
Formula (22)
Formula (23)
Wherein:θ ls,k 、θ le,k is a circuitlAt the key timekIs used for the phase angle of the head and the tail,x l is a circuitlIs used for the reactance of the (c),P l,max 、P l,min is a circuitlUpper and lower limits of power flow. Equation (20) obtains the power flow of each line through the direct current power flow, equation (21) limits the line power flow, equation (22) and(23) And realizing that the section of the time zone interconnecting line is not out of limit in standby calling.
In one embodiment, the region objective function includes:
formula (24)
And constructing an objective function in each region according to a formula (24), wherein the objective function is used for forming a region maintenance planning model of each region together with the standby related constraint, the maintenance constraint, the unit output of the region and the network constraint. Wherein the maintenance constraint in each region is expressed by the above-described formulas (14) to (18). The backup related constraints, regional unit output and network constraints are expressed using the formulas (24) through (31):
formula (25)
Formula (26)
Formula (27)
Formula (28)
Formula (29)
Formula (30)
Formula (31)
Wherein:p i,k indicating machine setiDuring critical time periodskIs a force of the (a);r u,i,k 、r d,i,k respectively the unitsiDuring critical time periodskA positive standby and a negative standby are provided,G m is a regionmThe set of the internal units phi Uj 、Φ Lj Is a nodejThe machine set and the line set which are connected are arranged on the machine,p n,j,k is a nodejDuring critical time periodskIs a payload of (a).
In addition, for the regional constraint adopted in the construction of the regional maintenance plan model, in addition to the constraint conditions, additional constraint can be added according to specific regional requirements, such as section power flow control, concurrent mutually exclusive maintenance, maintenance window period and the like.
In one embodiment, based on the tie line power, performing iterative computation on the upper maintenance plan model and the regional maintenance plan model by using a target cascading algorithm to obtain a power transmission maintenance plan of each region, including: calculating the upper-level tie line power according to the upper-level maintenance plan model and the preset area tie line power; calculating new regional tie line power according to the upper-layer network line power and the regional maintenance plan model; calculating new upper-level network line power according to the regional interconnection line power and the upper-level maintenance plan model; judging whether the new upper cascade network line power and the new regional interconnecting line power meet convergence conditions; when the network power and the area network power do not meet the requirements, updating the upper maintenance plan model parameters and the area maintenance plan model parameters, and calculating new upper network line power and new area tie line power according to the updated upper maintenance plan model and the area maintenance plan model; if the new upper-level network line power and the new area network line power do not meet the convergence condition, repeating the steps of updating the parameters, calculating the upper-level network line power and the new area network line power until the obtained new upper-level network line power and the new area network line power meet the convergence condition; and when the convergence condition is met, obtaining a power transmission maintenance plan of the line in each area.
Specifically, taking the nth iteration as an example, the target cascading algorithm will be described. In the first placeIn the iteration, each region is according to the upper level +.>The upper-level connecting line calculated power value obtained by the iteration is used for carrying out optimization solving of the lower-level sub-problem to obtain the +.>Calculating power values by each regional interconnecting line of the secondary iteration, uploading the power values obtained by the secondary optimization to an upper-level scheduling, and optimizing the upper-level scheduling again to obtain the +.>The upper cascade network line of the iteration calculates the power value, and judges whether to converge according to a formula (32):
formula (32)
Wherein:is a regionmIs the first of (2)lUpper limit of transmission power of strip connecting line, < >>Is the convergence threshold.
And if the current operation is judged to be non-convergence, carrying out the next iteration, and updating the deviation term coefficient and the deviation square term coefficient in the upper maintenance plan model and the regional maintenance plan model until the iteration is converged. The coefficient update is expressed by using the formula (33) and the formula (34):
formula (33)
Formula (34)
Wherein:is->Square term coefficients of deviation of the secondary iteration; />Is->The deviation term coefficient of the secondary iteration; />Is constant, usually 1 to 3.
According to the coordinated multi-region power transmission maintenance method provided by the embodiment of the invention, the key period set of peak-valley periods of each region and the medium-long term net load prediction error are considered, and the regional standby optimal configuration is carried out in the model, so that the expected electric quantity of lost load and abandoned new energy can be effectively reduced, and the uncertainty of power prediction can be better dealt with.
In one embodiment, the coordinated multi-area transmission maintenance method will be described by taking annual maintenance planning of the IEEE 118 node system as an example. In the node system, the node comprises 3 areas, namely, an area 1 and an area 2, an area 1 and an area 3, and 3, 1 and 4 connecting lines are respectively arranged between the area 2 and the area 3, and the numbers of the connecting lines are shown in fig. 3. The conventional unit parameters are shown in table 1, the power generation cost of each unit is divided into five sections averagely according to the output interval, the cost of each section is shown in table 2, and other units are new energy units. The load and the new energy output are scaled according to the actual data of a power grid in a certain area in China, wherein the area 1 is the area with the highest new energy output ratio, the area 3 is the area with the highest load level, and the new energy output and the net load of each area are shown in fig. 4 (a) and 4 (b). The new energy prediction error of the region 1 is close to 3 times of the load prediction error of the region 3. And the upper level dispatching equivalent each area as a node and optimally compiling a tie line for maintenance. The whole year takes the week as a period unit and is divided into 52 calculation periods, and each calculation period considers two key periods or two key points of a peak and a valley, so that the 52 calculation periods comprise 104 key periods or key points in total. Whereby the abscissa critical period in fig. 4 (a) and 4 (b) represents these 104 critical points. The critical periods in the other figures are synonymous. The new energy waste cost is 300 yuan/MWh, and the load loss cost is 3000 yuan/MWh. The simulation process adopts CPLEX 12.10.0 to solve, the minimum gap MIPgap is 1e-6, the hardware environment is a Thinkpad T470 notebook computer, the CPU model is Intel Core i5-6200, and the memory is 8G.
Table 1 set parameters
Table 2 cost of generator set
The initial plan of the tie line overhaul is shown in table 3, and the upper-level dispatch overhaul optimization result is shown in fig. 5. From fig. 4 (a) and fig. 4 (b), it can be seen that there is a significant new energy source of the power grid, namely the large hair period and the small hair period. Accordingly, as can be seen from fig. 5, the overhauling of the line 1-4 connected to the area 1 is concentrated in the periods 12-20, 64-69 and 77-84, which are all periods with less new energy output, because the load power in the area 1 is smaller, wind power cannot be completely received, surplus new energy needs to be transmitted to other areas through the connecting lines formed by the line 1-4, and negative standby needs to be supported by other areas to cope with the uncertainty of new energy output. The load level in the area 3 is higher, especially the load level is highest in the summer period of 49-57, and the tie lines formed by the lines 1 and 5-8 receive new energy of the external network and positive standby power for supporting, so that the line maintenance connected with the area 3 is concentrated in the periods of 4-9, 13-20 and 79-97, and the period of high load level is avoided. Therefore, through the multi-region joint optimization of the superior scheduling, the method can realize that the tie lines related to new energy transmission and load supply are properly arranged in the time periods with lower new energy and load levels respectively, and the power transmission lines between the regions are overhauled while considering the load and the output of the new energy because the output curve of the new energy is inconsistent with the output curve of the load.
TABLE 3 line information to be serviced
As shown in fig. 6 and 7, the multi-zone standby allocation results show that in the standby aspect, the new energy source of the zone 1 is more, the primary transmission is adopted, the positive standby can be supported for the external network, the load level of the zone 3 is high, the primary power is received, and the negative standby is supported for the external network. The spare allocation of each area is generally scheduled at an upper level, and the maintenance period can be better determined by the combined optimization with maintenance, and the maintenance planning in each area is carried out based on the spare allocation result.
In an embodiment, the coordinated multi-region power transmission maintenance method of the present embodiment is compared with the existing initial maintenance plan reported by the adopted region, without considering the global optimization mode. The first scheme is an initial maintenance plan reported by the area, and is not considered as a global optimization scheme, and the second scheme is a coordinated multi-area power transmission maintenance method of the embodiment. The new energy power-losing amount and the load-losing amount of each scheme are shown in fig. 8 and 9. As can be seen from fig. 8 and fig. 9, by adopting the scheme two and comparing with the scheme one, the optimized adjustment of the overhaul period enables the new energy power-off expected electric quantity to be reduced from 1785MWh to 1217MWh, the load loss expected electric quantity to be reduced from 177.9MWh to 98.5MWh, and the risks of power-off and load loss of the new energy are effectively reduced.
The calculation time results required by the coordinated multi-region power transmission maintenance method are shown in table 4. It can be seen that although the upper level scheduling simplifies each area into 1 node respectively and only 3 nodes in total, the calculation time reaches 1175.03 seconds, and the number of nodes in each area is more, but the time is far less than that of the upper level scheduling. The method is characterized in that the superior scheduling considers standby optimal configuration, and the standby cross-region support is considered to enable a large number of network constraints to act, so that the calculated amount is greatly increased, and the standby optimal configuration and transportation are not considered in each regional power grid, so that the network out-of-limit constraints acting in the ground state are greatly reduced, and the calculation time is less. Considering that a multi-region actual power grid contains a large number of nodes and network constraints, if the upper-level scheduling is unified to carry out full-network maintenance and standby joint optimization, the method has a great challenge on computing capacity; therefore, each region is respectively equivalent to one node through the coordinated multi-region power transmission maintenance method, so that the calculation accuracy and calculation speed of the model can well meet the actual demands.
Table 4 two-stage dispatch service plan optimization calculation time
In one embodiment, the analysis is performed according to the actual annual maintenance schedule of the power grid in the northern area, which includes 4 provinces A, B, C, D, and total 12 tie lines between provinces need to be maintained, wherein two provinces have higher new energy output, and each province has more average load distribution, and the new energy and the net load predicted output of the whole power grid are shown in fig. 10. The parameter settings such as the calculation period, the new energy abandoning cost, the lost load cost and the like are the same as those of the above embodiment. In this embodiment, the following two schemes are considered: the scheme 1 is a currently adopted maintenance planning method, each province analyzes the load of different months based on historical experience, and the maintenance plan is arranged in spring and autumn with lower load level. In the scheme 2, the coordinated multi-area power transmission maintenance method of the embodiment is adopted, the upper level scheduling equivalent each province to 1 node, and 4 nodes in total are adopted to optimize the inter-province tie line maintenance plan, and the result is used as the boundary for the establishment of the intra-province maintenance plan. The results of the service plans for both schemes are shown in table 5.
Table 5 results of service plans under different scenarios
As shown in fig. 11, no load loss occurred in both schemes due to the lower overall load level in the northern regional power grid, but the new energy waste of scheme 2 was reduced from 3037.5GWh to 2772.1GWh compared to scheme 1. The method is characterized in that each province arranges the maintenance schedule of each tie line in spring and autumn with lower load according to historical experience, so that the condition that a plurality of tie lines are maintained at the same time is easy to occur, for example, the time periods of 28-31 and 72-77 have great mutual influence on power transmission and standby between provinces, the uncertain performance of new energy sources is reduced, and the condition that the expected electric quantity of the new energy source is obviously increased in the time periods is caused. Therefore, by adopting the scheme 2, the unified global optimization configuration is carried out on the line maintenance schedule and the provincial standby, and as can be seen from the table 5, the maintenance schedule result distribution of the scheme 2 is more dispersed, the influence of the maintenance schedule on the regional mutual economy is reduced, and the overall new energy consumption level is further improved. Therefore, through the scheme 2, the global optimization of the line overhaul plan can be better performed in the actual power grid. When the upper scheduling is used for compiling a tie-line maintenance plan, the power grid is equivalent to 4 nodes, the calculation scale is small, the calculation time is 1566 seconds, and the actual requirements can be met.
The present embodiment provides a coordinated multi-region power transmission maintenance device, as shown in fig. 12, including:
the set construction module 501 is configured to acquire peak-to-valley periods of the payload in each region and construct a set of key periods;
the relationship determining module 502 is configured to obtain a cost relationship and an electric quantity standby relationship of each region in the set of key time periods;
the upper model construction module 503 is configured to construct an upper maintenance plan model according to the output cost relationship, the electric quantity standby relationship, the tie line power and the upper constraint of each region;
the regional model construction module 504 is configured to construct a regional overhaul plan model according to the output cost relationship, the tie line power and the regional constraint of each region;
and the target cascading module 505 is configured to perform iterative computation on the upper maintenance plan model and the regional maintenance plan model by using a target cascading algorithm based on the tie line power, so as to obtain a power transmission maintenance plan of each region.
The coordinated multi-region power transmission service apparatus in this embodiment is presented in the form of functional units, where the units refer to ASIC circuits, processors and memories executing one or more software or fixed programs, and/or other devices that can provide the above described functionality.
Further functional descriptions of the above respective modules and units are the same as those of the above corresponding embodiments, and are not repeated here.
The embodiment of the invention also provides computer equipment, which is provided with the power transmission maintenance device for coordinating multiple areas shown in the figure 12.
Referring to fig. 13, fig. 13 is a schematic structural diagram of a computer device according to an alternative embodiment of the present invention, as shown in fig. 13, the computer device includes: one or more processors 10, memory 20, and interfaces for connecting the various components, including high-speed interfaces and low-speed interfaces. The various components are communicatively coupled to each other using different buses and may be mounted on a common motherboard or in other manners as desired. The processor may process instructions executing within the computer device, including instructions stored in or on memory to display graphical information of the GUI on an external input/output device, such as a display device coupled to the interface. In some alternative embodiments, multiple processors and/or multiple buses may be used, if desired, along with multiple memories and multiple memories. Also, multiple computer devices may be connected, each providing a portion of the necessary operations (e.g., as a server array, a set of blade servers, or a multiprocessor system). One processor 10 is illustrated in fig. 13.
The processor 10 may be a central processor, a network processor, or a combination thereof. The processor 10 may further include a hardware chip, among others. The hardware chip may be an application specific integrated circuit, a programmable logic device, or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general-purpose array logic, or any combination thereof.
Wherein the memory 20 stores instructions executable by the at least one processor 10 to cause the at least one processor 10 to perform a method for implementing the embodiments described above.
The memory 20 may include a storage program area that may store an operating system, at least one application program required for functions, and a storage data area; the storage data area may store data created from the use of the computer device of the presentation of a sort of applet landing page, and the like. In addition, the memory 20 may include high-speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid-state storage device. In some alternative embodiments, memory 20 may optionally include memory located remotely from processor 10, which may be connected to the computer device via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
Memory 20 may include volatile memory, such as random access memory; the memory may also include non-volatile memory, such as flash memory, hard disk, or solid state disk; the memory 20 may also comprise a combination of the above types of memories.
The computer device also includes a communication interface 30 for the computer device to communicate with other devices or communication networks.
The embodiments of the present invention also provide a computer readable storage medium, and the method according to the embodiments of the present invention described above may be implemented in hardware, firmware, or as a computer code which may be recorded on a storage medium, or as original stored in a remote storage medium or a non-transitory machine readable storage medium downloaded through a network and to be stored in a local storage medium, so that the method described herein may be stored on such software process on a storage medium using a general purpose computer, a special purpose processor, or programmable or special purpose hardware. The storage medium can be a magnetic disk, an optical disk, a read-only memory, a random access memory, a flash memory, a hard disk, a solid state disk or the like; further, the storage medium may also comprise a combination of memories of the kind described above. It will be appreciated that a computer, processor, microprocessor controller or programmable hardware includes a storage element that can store or receive software or computer code that, when accessed and executed by the computer, processor or hardware, implements the methods illustrated by the above embodiments.
Although embodiments of the present invention have been described in connection with the accompanying drawings, various modifications and variations may be made by those skilled in the art without departing from the spirit and scope of the invention, and such modifications and variations fall within the scope of the invention as defined by the appended claims.
Claims (10)
1. A method of coordinating multiple areas of power transmission maintenance, the method comprising:
acquiring the net load peak-valley time periods of each region, and constructing a key time period set;
acquiring output cost relation and electric quantity standby relation of each area in the key time period set;
constructing an upper maintenance plan model according to the output cost relation, the electric quantity standby relation, the tie line power and the upper constraint of each area;
constructing an area maintenance plan model according to the output cost relation of each area, the power of the connecting line and the area constraint;
and carrying out iterative computation on the superior maintenance plan model and the regional maintenance plan model by adopting a target cascading algorithm based on the tie line power to obtain the power transmission maintenance plan of each region.
2. The method of claim 1, wherein the power reserve relationship comprises a new energy waste desired power and negative reserve relationship and a no-load desired power and positive reserve relationship.
3. The method of claim 1, wherein constructing an upper maintenance planning model based on the regional output cost relationships, the electrical backup relationships, the tie-line power, and the upper constraints comprises:
constructing an upper objective function with the minimum cost as a target according to the output cost relation, the electric quantity standby relation and the tie line power of each area;
and constructing a superior maintenance plan model according to the superior objective function and the superior constraint, wherein the superior constraint comprises regional output and standby related constraint, maintenance constraint, regional power balance constraint and network constraint.
4. A method according to claim 3, wherein the upper level objective function comprises:
in the method, in the process of the invention,N m representing the number of regions; t represents the total time period number;N c,t representing a set of critical time periods,p m,k indicating the force exerted by the region m during the critical period k,F（p m,k ) Representing a force cost relationship;C w,m 、C d,m the new energy waste cost and the lost load cost are respectively the area m;R d,m,k 、ΔR d,m,k a local negative standby and an external negative standby for region m respectively,R u,m,k 、ΔR u,m,k local positive standby and external positive standby for region m respectively,and->The new energy waste expected electric quantity function and the load loss expected electric quantity function of the region m in the key period k are respectively represented; / >、/>Respectively the t-th of the time period t-zone mlSquare term coefficients of deviation and primary term coefficients of deviation of the tie lines; />、/>Respectively the t-th of the time period t-zone mlThe upper computing power of the tie line and the computing power of each region.
5. The method of claim 1, wherein constructing an area repair plan model based on the area output cost relationships, tie line power, and area constraints comprises:
constructing a region objective function with minimum cost as a target according to the output cost relation of each region;
and constructing an area maintenance plan model according to the area objective function and the area constraint, wherein the area constraint comprises a standby related constraint, a maintenance constraint, an area unit output and a network constraint.
6. The method of claim 5, wherein the region objective function comprises:
wherein T represents the total period number;N c,t representing a set of critical time periods,p m,k indicating the force exerted by the region m during the critical period k,F（p m,k ) Representing a force cost relationship;、/>respectively the t-th of the time period t-zone mlSquare term coefficients of deviation and primary term coefficients of deviation of the tie lines; />、/>Respectively the t-th of the time period t-zone mlStrip connecting lineUpper-level calculation power and each region calculation power; T t For a period of timetDays of (2);T k is a critical periodkFor a number of hours.
7. The method of claim 1, wherein iteratively calculating the superior repair plan model and the regional repair plan model based on tie-line power using a target cascading algorithm results in each regional transmission repair plan, comprising:
calculating the upper-level tie line power according to the upper-level maintenance planning model and the preset area tie line power;
calculating new regional tie line power according to the superior tie line power and the regional maintenance plan model;
calculating new upper-level network line power according to the regional network line power and the upper-level maintenance plan model;
judging whether the new upper-layer network line power and the new regional interconnecting line power meet a convergence condition or not;
when the model parameters are not satisfied, updating the upper maintenance plan model parameters and the regional maintenance plan model parameters,
calculating new upper-level network line power and new regional interconnecting line power according to the updated upper-level maintenance plan model and the regional maintenance plan model;
if the new upper-level network line power and the new area network line power do not meet the convergence condition, repeating the steps of updating the parameters, calculating the upper-level network line power and the new area network line power until the obtained new upper-level network line power and the new area network line power meet the convergence condition;
And when the convergence condition is met, obtaining a power transmission maintenance plan of the line in each area.
8. A coordinated multi-region power transmission service apparatus, the apparatus comprising:
the set construction module is used for acquiring the net load peak-valley time periods of each region and constructing a key time period set;
the relation determining module is used for acquiring the output cost relation and the electric quantity standby relation of each area in the key time period set;
the upper model construction module is used for constructing an upper maintenance plan model according to the output cost relation, the electric quantity standby relation, the tie line power and the upper constraint of each area;
the regional model construction module is used for constructing a regional maintenance plan model according to the output cost relation of each region, the power of the connecting line and the regional constraint;
and the target cascading module is used for carrying out iterative computation on the superior maintenance plan model and the regional maintenance plan model by adopting a target cascading algorithm based on the tie line power to obtain the power transmission maintenance plans of all the regions.
9. A computer device, comprising:
a memory and a processor, the memory and the processor being communicatively connected to each other, the memory having stored therein computer instructions, the processor executing the computer instructions to perform the coordinated multi-region transmission service method of any one of claims 1 to 7.
10. A computer-readable storage medium having stored thereon computer instructions for causing a computer to perform the coordinated multi-region power transmission service method of any one of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310525853.6A CN116308301B (en) | 2023-05-11 | 2023-05-11 | Coordinated multi-region power transmission maintenance method, device, computer equipment and medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310525853.6A CN116308301B (en) | 2023-05-11 | 2023-05-11 | Coordinated multi-region power transmission maintenance method, device, computer equipment and medium |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN116308301A CN116308301A (en) | 2023-06-23 |
| CN116308301B true CN116308301B (en) | 2023-07-21 |
Family
ID=86781766
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310525853.6A Active CN116308301B (en) | 2023-05-11 | 2023-05-11 | Coordinated multi-region power transmission maintenance method, device, computer equipment and medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116308301B (en) |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108808740A (en) * | 2018-06-15 | 2018-11-13 | 南方电网科学研究院有限责任公司 | Dispatching method, device and the storage medium of the Multiple Time Scales of multi area interconnection power grid |
| CN109583664A (en) * | 2018-12-21 | 2019-04-05 | 国网山西省电力公司电力科学研究院 | A kind of interregional grid Unit Combination decentralized coordinating optimisation strategy containing generation of electricity by new energy |
| CN109829576A (en) * | 2019-01-17 | 2019-05-31 | 国家电网有限公司 | A kind of integrated multi-stage scheduling optimization method of total portions |
| CN110443401A (en) * | 2019-06-17 | 2019-11-12 | 中国电力科学研究院有限公司 | A kind of Optimization Scheduling of smart grid |
| CN115952933A (en) * | 2023-03-15 | 2023-04-11 | 国网四川省电力公司电力科学研究院 | Power transmission maintenance plan generation method, device, equipment and storage medium |
| CN115994626A (en) * | 2023-03-21 | 2023-04-21 | 国网四川省电力公司电力科学研究院 | Power transmission line maintenance method and device, computer equipment and medium |
-
2023
- 2023-05-11 CN CN202310525853.6A patent/CN116308301B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108808740A (en) * | 2018-06-15 | 2018-11-13 | 南方电网科学研究院有限责任公司 | Dispatching method, device and the storage medium of the Multiple Time Scales of multi area interconnection power grid |
| CN109583664A (en) * | 2018-12-21 | 2019-04-05 | 国网山西省电力公司电力科学研究院 | A kind of interregional grid Unit Combination decentralized coordinating optimisation strategy containing generation of electricity by new energy |
| CN109829576A (en) * | 2019-01-17 | 2019-05-31 | 国家电网有限公司 | A kind of integrated multi-stage scheduling optimization method of total portions |
| CN110443401A (en) * | 2019-06-17 | 2019-11-12 | 中国电力科学研究院有限公司 | A kind of Optimization Scheduling of smart grid |
| CN115952933A (en) * | 2023-03-15 | 2023-04-11 | 国网四川省电力公司电力科学研究院 | Power transmission maintenance plan generation method, device, equipment and storage medium |
| CN115994626A (en) * | 2023-03-21 | 2023-04-21 | 国网四川省电力公司电力科学研究院 | Power transmission line maintenance method and device, computer equipment and medium |
Non-Patent Citations (3)
| Title |
|---|
| 四川电网发输电设备检修计划的协调优化;张蓓;《中国优秀硕士学位论文全文数据库工程科技Ⅱ辑》(第6期);C042-334 * |
| 考虑两级协调和分区备用的多区域输电检修计划;蔡帜 等;《智慧电力 》;第51卷(第5期);第15-22页 * |
| 面向联合检修的电力信息物理系统输电线路脆弱相关性辨识;李妍莎 等;《电力系统保护与控制》;第50卷(第24期);第120-128页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN116308301A (en) | 2023-06-23 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11757404B2 (en) | Coordinated control of renewable electric generation resource and charge storage device | |
| Alharbi et al. | Stochastic optimal planning of battery energy storage systems for isolated microgrids | |
| US11238474B2 (en) | Distributed energy control | |
| Vu et al. | An integrated energy management approach for the economic operation of industrial microgrids under uncertainty of renewable energy | |
| US9489701B2 (en) | Adaptive energy management system | |
| Aghaei et al. | Transmission switching, demand response and energy storage systems in an innovative integrated scheme for managing the uncertainty of wind power generation | |
| US11916422B2 (en) | Battery charge and discharge power control in a power grid | |
| Nick et al. | Wind power optimal capacity allocation to remote areas taking into account transmission connection requirements | |
| US20220029424A1 (en) | Hybrid power plant | |
| WO2019093009A1 (en) | Electricity plan device, electricity supply-demand control system, and electricity plan method | |
| CN110570020A (en) | Medium-and-long-term transaction electric quantity safety checking method suitable for regional alternating current-direct current hybrid power grid | |
| Vardanyan et al. | The state-of-the-art of the short term hydro power planning with large amount of wind power in the system | |
| Farzin et al. | A hierarchical scheme for outage management in multi‐microgrids | |
| CN114498638A (en) | Source network load storage coordination planning method and system considering source load bilateral uncertainty | |
| CN116308301B (en) | Coordinated multi-region power transmission maintenance method, device, computer equipment and medium | |
| CN111178618A (en) | Intelligent power grid load prediction method | |
| Do Prado et al. | Stochastic distribution system market clearing and settlement via sample average approximation | |
| US20220057767A1 (en) | Methods and systems for energy storage dispatch | |
| CN111344724A (en) | Control of a microgrid | |
| Zhu et al. | A new pricing scheme for controlling energy storage devices in future smart grid | |
| CN117375113A (en) | Distributed power supply scheduling method and system | |
| Abugchem et al. | Optimal Battery Dispatch Using Finite-Input Set Non-Linear Model Predictive Control: Algorithm Development and Case Study. Electronics 2022, 11, 101 | |
| CN117391311A (en) | Charging station and power distribution network collaborative planning method considering carbon emission and uncertainty | |
| CN115471089A (en) | Configuration method and device of composite power station, computer equipment and storage medium | |
| CN116937710A (en) | New energy base power control method, device, equipment and medium |
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 |