CN116706892B - Rail transit optical storage configuration method, system and electronic equipment - Google Patents
Rail transit optical storage configuration method, system and electronic equipment Download PDFInfo
- Publication number
- CN116706892B CN116706892B CN202310707380.1A CN202310707380A CN116706892B CN 116706892 B CN116706892 B CN 116706892B CN 202310707380 A CN202310707380 A CN 202310707380A CN 116706892 B CN116706892 B CN 116706892B
- Authority
- CN
- China
- Prior art keywords
- power
- power generation
- photovoltaic power
- photovoltaic
- loss
- 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
- 238000000034 method Methods 0.000 title claims abstract description 38
- 230000003287 optical effect Effects 0.000 title claims description 26
- 238000010248 power generation Methods 0.000 claims abstract description 161
- 238000004146 energy storage Methods 0.000 claims abstract description 53
- 238000005286 illumination Methods 0.000 claims abstract description 32
- 238000007599 discharging Methods 0.000 claims abstract description 8
- 239000003990 capacitor Substances 0.000 claims description 67
- 230000009467 reduction Effects 0.000 claims description 25
- 230000005540 biological transmission Effects 0.000 claims description 14
- 238000011084 recovery Methods 0.000 claims description 13
- 238000005070 sampling Methods 0.000 claims description 13
- 238000004590 computer program Methods 0.000 claims description 8
- 230000006870 function Effects 0.000 claims description 8
- 238000012423 maintenance Methods 0.000 claims description 8
- 230000001360 synchronised effect Effects 0.000 claims description 4
- 101150067055 minC gene Proteins 0.000 claims description 3
- 238000006467 substitution reaction Methods 0.000 claims description 3
- 241001055394 Badis Species 0.000 claims description 2
- 230000001172 regenerating effect Effects 0.000 claims description 2
- 230000035699 permeability Effects 0.000 abstract description 6
- 230000007246 mechanism Effects 0.000 description 5
- 230000001186 cumulative effect Effects 0.000 description 4
- 239000008186 active pharmaceutical agent Substances 0.000 description 3
- 238000004364 calculation method Methods 0.000 description 3
- 238000009826 distribution Methods 0.000 description 3
- 239000011159 matrix material Substances 0.000 description 3
- 238000010586 diagram Methods 0.000 description 2
- 238000005315 distribution function Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004422 calculation algorithm Methods 0.000 description 1
- 238000004134 energy conservation Methods 0.000 description 1
- 238000005265 energy consumption Methods 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 230000000750 progressive effect Effects 0.000 description 1
- 230000002035 prolonged effect Effects 0.000 description 1
- 238000004064 recycling Methods 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 238000009827 uniform distribution 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
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60M—POWER SUPPLY LINES, AND DEVICES ALONG RAILS, FOR ELECTRICALLY- PROPELLED VEHICLES
- B60M3/00—Feeding power to supply lines in contact with collector on vehicles; Arrangements for consuming regenerative power
-
- 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
- H02J3/28—Arrangements for balancing of the load in a network by storage of energy
-
- 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
- H02J3/28—Arrangements for balancing of the load in a network by storage of energy
- H02J3/32—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means
-
- 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
-
- 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
- H02J3/381—Dispersed generators
-
- 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
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
- H02J3/466—Scheduling the operation of the generators, e.g. connecting or disconnecting generators to meet a given demand
-
- 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
- H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
- H02J7/34—Parallel operation in networks using both storage and other dc sources, e.g. providing buffering
- H02J7/345—Parallel operation in networks using both storage and other dc sources, e.g. providing buffering using capacitors as storage or buffering devices
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/10—Power transmission or distribution systems management focussing at grid-level, e.g. load flow analysis, node profile computation, meshed network optimisation, active network management or spinning reserve management
-
- 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
-
- 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
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E70/00—Other energy conversion or management systems reducing GHG emissions
- Y02E70/30—Systems combining energy storage with energy generation of non-fossil origin
Landscapes
- Engineering & Computer Science (AREA)
- Power Engineering (AREA)
- Mechanical Engineering (AREA)
- Charge And Discharge Circuits For Batteries Or The Like (AREA)
Abstract
The invention provides a track traffic light storage configuration method, a system and electronic equipment, belonging to the field of track traffic, wherein the method comprises the following steps: acquiring historical illumination intensity data of a traction substation area; generating a plurality of photovoltaic power generation power typical scenes according to the historical illumination intensity data, and determining the probability of each photovoltaic power generation power typical scene; based on a plurality of photovoltaic power generation power typical scenes and corresponding probabilities, constructing a light storage configuration model with the lowest total operation loss as a target, and solving to obtain a light storage configuration result; the photovoltaic configuration result comprises power exchanged between the power grid and the rail transit system at each moment in a typical scene of each photovoltaic power generation power, capacity of an energy storage device, charging and discharging power and capacity of a photovoltaic power station; and configuring the capacity of the photovoltaic power station, the capacity of the energy storage device, the charge and discharge power and the power exchanged with the power grid according to the light storage configuration result. The invention improves the photovoltaic permeability of the rail transit system and can cut peaks and fill valleys of traction load.
Description
Technical Field
The invention relates to the field of rail transit, in particular to a rail transit light storage configuration method, a system and electronic equipment considering photovoltaic randomness and power loss.
Background
With the increasing demand for energy and traffic, the mileage of electrified railways is rapidly developed, and with this, the consumption of electric energy is rapidly increased. In order to support the strategy of sustainable development, the energy conservation and emission reduction are realized, and the comprehensive energy consumption of the electrified railway is further reduced. The photovoltaic power generation is used as a representative of new energy, has the advantages of easy acquisition, no pollution and the like, and the photovoltaic resources along the railway of part of areas are quite rich. In consideration of the fluctuation of the traction load of the high-speed train, the photovoltaic is connected into the traction substation, and the hybrid energy storage system is configured, so that the photovoltaic permeability can be improved, and peak clipping and valley filling can be performed on the traction load. Based on the background and the significance, the research on photovoltaic power supply and hybrid energy storage capacity/power configuration of the track traffic energy source consistent system is necessary.
Disclosure of Invention
The invention aims to provide a track traffic light storage configuration method, a system and electronic equipment taking photovoltaic randomness and power loss into consideration, which can improve the photovoltaic permeability of a track traffic system and cut peaks and fill valleys of traction load.
In order to achieve the above object, the present invention provides the following solutions:
a rail transit optical storage configuration method, comprising:
acquiring historical illumination intensity data of a traction substation area;
generating a plurality of photovoltaic power generation power typical scenes according to the historical illumination intensity data, and determining the probability of each photovoltaic power generation power typical scene; each photovoltaic power generation power typical scene comprises photovoltaic power generation power at each moment in the corresponding scene;
based on a plurality of photovoltaic power generation power typical scenes and the probability of each photovoltaic power generation power typical scene, constructing a light storage configuration model with the minimum total operation loss as a target;
solving the optical storage configuration model to obtain an optical storage configuration result; the light storage configuration result comprises the capacity of a photovoltaic power station, the capacity of an energy storage device, the power exchanged between a power grid and a rail transit system at each moment under a typical scene of each photovoltaic power generation power and the charge and discharge power of the energy storage device;
and configuring the capacity of the photovoltaic power station, the capacity of the energy storage device, the charge and discharge power of the energy storage device and the power exchanged between the rail transit system and the power grid according to the light storage configuration result.
In order to achieve the above purpose, the present invention also provides the following solutions:
a rail transit optical storage configuration system, comprising:
the data acquisition unit is used for acquiring historical illumination intensity data of the traction substation area;
the scene determining unit is connected with the data acquisition unit and is used for generating a plurality of photovoltaic power generation power typical scenes according to the historical illumination intensity data and determining the probability of each photovoltaic power generation power typical scene; each photovoltaic power generation power typical scene comprises photovoltaic power generation power at each moment in the corresponding scene;
the model building unit is connected with the scene determining unit and is used for building a light storage configuration model with the minimum total operation loss as a target based on a plurality of photovoltaic power generation typical scenes and the probability of each photovoltaic power generation typical scene;
the solving unit is connected with the model building unit and is used for solving the optical storage configuration model to obtain an optical storage configuration result; the light storage configuration result comprises the capacity of a photovoltaic power station, the capacity of an energy storage device, the power exchanged between a power grid and a rail transit system at each moment under a typical scene of each photovoltaic power generation power and the charge and discharge power of the energy storage device;
the configuration unit is respectively connected with the solving unit, the photovoltaic power station and the energy storage device and is used for configuring the capacity of the photovoltaic power station, the capacity of the energy storage device, the charge and discharge power of the energy storage device and the power exchanged by the rail transit system and the power grid according to the light storage configuration result.
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 running the computer program to cause the electronic device to perform the rail transit optical storage configuration method described above.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
according to the invention, photovoltaic power generation power typical scenes are generated according to historical illumination intensity data of traction substation areas to describe randomness of the photovoltaic, then, a photovoltaic configuration model with the lowest total operation loss as a target is constructed based on a plurality of photovoltaic power generation power typical scenes and probabilities of all photovoltaic power generation power typical scenes, and the capacity of a photovoltaic power station, the capacity of an energy storage device, the power exchanged between a power grid and a rail transit system at all times under all photovoltaic power generation power typical scenes, the charge and discharge power of the energy storage device and the power exchanged between the photovoltaic power station and the power grid are obtained after solving, so that the capacity of the photovoltaic power station, the capacity of the energy storage device, the charge and discharge power of the energy storage device and the power exchanged between the rail transit system and the power grid are configured, the photovoltaic permeability of the rail transit system is improved, and peak clipping and valley filling of traction loads can be carried out.
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 flow chart of a track traffic light storage configuration method provided by the invention;
FIG. 2 is a flow chart of the generation of a typical scene of solar intensity;
FIG. 3 is a schematic diagram of a rail transit energy source consistent system;
fig. 4 is a schematic diagram of a track traffic light storage configuration system provided by the invention.
Symbol description:
the system comprises a 1-data acquisition unit, a 2-scene determination unit, a 3-model establishment unit, a 4-solving unit, a 5-configuration unit, a 6-photovoltaic power station, a 7-energy storage device, an 8-storage battery and a 9-super capacitor.
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 provide a track traffic light storage configuration method, a system and electronic equipment, which are used for configuring a photovoltaic power station and an energy storage device which are connected to a traction substation by considering the fluctuation of traction load of a high-speed train, so that the photovoltaic permeability can be improved, and peak clipping and valley filling can be performed on the traction load.
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, the present embodiment provides a track traffic light storage configuration method, including:
step 100: and acquiring historical illumination intensity data of the traction substation area.
Step 200: and generating a plurality of photovoltaic power generation power typical scenes according to the historical illumination intensity data, and determining the probability of each photovoltaic power generation power typical scene. Each photovoltaic power generation power typical scene comprises photovoltaic power generation power at each moment in the corresponding scene.
Further, step 200 includes:
step 201: and sampling the historical illumination intensity data by using a Latin hypercube sampling method to obtain a plurality of initial scenes with daily illumination intensity. Specifically, according to the randomness of the photovoltaic output, latin hypercube sampling (Latin hyper cube sampling, LHS) is carried out on sunlight intensity historical data of a traction substation area, and an initial sunlight intensity scene is generated.
Let x be 1 ,x 2 ,x 3 ,...,x p Is the illumination intensity over p time periods, the cumulative probability distribution function of which is: f (F) xi ＝f i (x i ) The method comprises the steps of carrying out a first treatment on the surface of the Where i=1, 2,..p. By LHSThe steps of generating N initial scenes are as follows:
(1) The sampling size is defined as N.
(2) For illumination intensity x within any period of time i Will x i Cumulative probability distribution curve F of (2) xi ＝f i (x i ) Equally probable divided into N intervals, each interval having a width of 1/N, randomly extracting a value in each interval to satisfy x i1 <x i2 ...<x ik ...<x iN And has
(3) For illumination intensity x i Is x of the kth sample value of (2) ik The corresponding cumulative distribution probabilities are: f (F) xi (k)＝(1/N)r u ++ (k-1)/N; wherein r is u N (0, 1) obeys uniform distribution; k=1, 2,..n. By calculating cumulative distribution function F xi Can be used to find x i Is x of the kth sample value of (2) ik ：
(4) After the sampling is finished, the sampling values of the illumination intensity in each time period are arranged into one column of a matrix to form an NxP sampling matrix S. The invention uses Gram-Schmidt orthogonalization method to sequence the sampling values of each column of the matrix, and minimizes the correlation of each column through calculation. And finally, forming N sampling scenes, namely, an initial scene of sunlight intensity.
Step 202: and adopting a synchronous back substitution reduction method to reduce the initial scenes with the sunlight intensity to obtain a plurality of typical scenes with the sunlight intensity. In order to improve the operation efficiency, the invention adopts synchronous back substitution subtraction (simultaneous backward reduction, SBR) to perform scene reduction on the initial scene of the sunlight intensity, so as to obtain the typical scene of the sunlight intensity.
Assume that there are N initial scenes of solar intensity: s= { θ i I=1,.. the probability of each initial scene of sunlight intensity is p i Obviously generated by LHSThe probability of each initial scene of sunlight intensity is 1/N. The basic steps of the SBR algorithm are as follows:
(1) Calculating the initial scene theta of sunlight intensity i And the initial scene θ of sunlight intensity j Distance D (θ) i ,θ j )：D(θ i ,θ j )＝||θ i -θ j || 2 ，i,j＝1,2,...,N。
(2) Initial scene θ for any one day illumination intensity k Finding out the initial scene theta of the sunlight intensity with the shortest distance to the initial scene theta r D (θ) k ,θ r )＝minD(θ k ,θ s )，θ k ≠θ s ，θ k ∈S,θ s ∈S。
(3) Initial scene θ of solar illumination intensity k The probability of (2) is p (θ) k ) Calculation ofWherein (1)>Initial scene θ for solar illumination intensity k And the initial scene θ of sunlight intensity r Find the probability distance of meetingInitial scene θ of solar intensity of (2) d Will be theta d And determining the scene to be deleted. Namely deleting all scenes with the minimum PD value in the initial scene of the sunlight intensity.
(4) Correcting the initial scene set S of sunlight intensity, the deleted scene set DS and the related probability: s=s- { θ d }，DS＝DS+{θ d }，p(θ r )＝p(θ r )+p(θ d )。
(5) N=n-1, when n=sw, i.e. the number of remaining scenes is the required number of typical scenes, the iteration is terminated, otherwise, go to step (2).
Using latin hypercube sampling and synchronous back-generation clipping techniques, SW sunlight intensity representative scenes and probabilities of each sunlight intensity representative scene are generated, as shown in fig. 2.
Step 203: based on the linear relation between illumination intensity and photovoltaic power generation power, generating a plurality of photovoltaic power generation power typical scenes according to a plurality of sunlight intensity typical scenes, and determining the probability of each photovoltaic power generation power typical scene. In this embodiment, the following formula is used to determine the photovoltaic power generation power at the time t under the typical scenario sw:
wherein,is the photovoltaic power generation power at the moment t under the typical scene sw of the photovoltaic power generation power, and is +.>For rated photovoltaic power, +.>Is the illumination intensity beta at the time t under the typical scene sw of the photovoltaic power generation power N Is a pre-configured nominal illumination intensity.
Step 300: and constructing a light storage configuration model with the minimum total operation loss as a target based on the plurality of photovoltaic power generation typical scenes and the probability of each photovoltaic power generation typical scene.
Based on a supply quantity loss mechanism, the invention performs track traffic light storage configuration modeling under the condition that the photovoltaic power generation allowance power of the traction substation is transmitted to the power grid. The main body of the rail transit system comprises a power generation side grid-connected main body, a load side grid-connected main body and an energy storage device. The power generation side grid-connected main body related to the invention refers to a photovoltaic power station; the load side main body refers to industrial and commercial loads and the like which can respond to the instructions of electric power dispatching institutions above, and specifically refers to high-speed rail traction loads in the invention; the energy storage device refers to a hybrid energy storage system configured at a traction substation. In this embodiment, the energy storage device includes a storage battery and a super capacitor.
The difference in power transmitted to the rail transit system based on the supply side transmission power loss mechanism affects the power loss reduction, whereas the power loss reduction affects the transmission power, so the transmission power response and the power loss reduction interact. The present invention establishes a supply-side power loss elastic coefficient representing the influence of supply-side transmission power offset on loss reduction, taking into consideration the influence of the above-described interaction.
Reference transmission power of known photovoltaic power plantsThe power grid company obtains real-time loss decrement through optimal power flow calculation and publishes a reference loss decrement coefficient +.>The photovoltaic actually transmitted power of the network has a certain offset compared with the reference transmitted power, and the loss decrement is influenced by the offset of the supply quantity. The invention introduces a power loss reduction elastic coefficient lambda to describe loss reduction coefficient offset caused by the network transmission electric quantity offset, namely:
wherein the power loss reduction elastic coefficient lambda is known,for loss decrement coefficient offset at time t under photovoltaic power generation power typical scene sw, +.> The offset of the internet transmission power at the moment t under the typical scene sw of the photovoltaic power generation power is +.> The power transmitted to the power grid by the photovoltaic power station at the moment t under the typical scene sw of the photovoltaic power generation power.
From the above, the final real-time loss reduction coefficient can be deducedThe method comprises the following steps:
specifically, the invention establishes an objective function with the objective of optimizing the total loss of the track traffic photovoltaic and the hybrid energy storage model based on a plurality of photovoltaic power generation typical scenes, the probability of each photovoltaic power generation typical scene and the real-time loss reduction elastic coefficient. The total loss comprises loss of power transmitted by the power grid to the rail transit system, loss of hybrid energy storage, loss of photovoltaic power generation, loss of a converter and loss decrement of new energy.
The objective function of the optical storage configuration model is as follows:
minC＝C 1 +C 2 +C 3 +C 4 +C 5 -C 6 ；
wherein C is the objective function value, C 1 C, loss of power transmitted to rail transit system by power grid 2 C is the full life cycle loss of the storage battery 3 Is the full life cycle loss of the super capacitor, C 4 C is the loss of photovoltaic power generation 5 C is the loss of the converter 6 The new energy loss is reduced.
Wherein SW is the total number of typical scenes of photovoltaic power generation power, P sw Typical scene sw for photovoltaic generation powerProbability, T is the total time span (1 day), C price Is the loss coefficient of the transmission power of the power grid,the power transmitted by the power grid to the rail transit system at the moment t under the typical scene sw of the photovoltaic power generation power is shown as delta t, and the delta t is the time interval (1 minute).
C 2 ＝C SYS-Ba +C OP-Ba +C RC-Ba ；
C SYS-Ba1 ＝C Ba-p P Ba,rate +C Ba-e E Ba,rate ；
C RC-Ba1 ＝-σ Ba-res ·C SYS-Ba1 ；
Wherein C is SYS-Ba For the equivalent daily running loss of the capacity of the storage battery, C OP-Ba For the operation and maintenance loss of the storage battery, the operation and maintenance loss of the storage battery is related to the charge and discharge power and the charge and discharge time of the storage battery, C RC-Ba The recovery loss decrement is scrapped for the storage battery, and when the storage battery reaches the service life, the residual value obtained through recovery and utilization is the recovery loss decrement of the storage battery. C (C) SYS-Ba1 For the total equivalent loss of the storage battery capacity, C Ba-p Loss coefficient of unit power of storage battery, P Ba,rate For rated power of accumulator, C Ba-e Loss factor of unit capacity of storage battery, E Ba,rate Is the rated capacity of the accumulator. Considering the loss of the whole life cycle, adopting a unified annual value method to convert the total loss into equivalent daily operation loss, and r is the discountRate, L Ba The service life of the storage battery is prolonged. C (C) OP-Baunit The running maintenance loss of the unit charge-discharge energy of the storage battery,charging power of storage battery at t moment under typical scene sw of photovoltaic power generation power, +.>The discharge power of the storage battery at the t moment under the typical scene sw of the photovoltaic power generation power. Considering the cost under the whole life cycle, adopting a unified annual value method to convert the scrapped recovery loss decrement into daily scrapped recovery loss decrement, -sigma Ba-res The recovery residual value rate of the storage battery is usually 3% -5%.
C 3 ＝C SYS-SC +C OP-SC +C RC-SC ；
C SYS-SC1 ＝C SC-p P SC,rate +C SC-e E SC,rate ；
C RC-SC1 ＝-σ SC-res ·C SYS-SC1 ；
The full life cycle loss of the super capacitor comprises the capacity equivalent daily operation loss C of the super capacitor SYS-SC Operation maintenance loss C of super capacitor OP-SC Scrapped recovery loss decrement C of super capacitor RC-SC . The operation and maintenance loss of the super capacitor is related to the charge and discharge power and charge and discharge time, and when the super capacitor reaches the service life, the super capacitor can be used for dischargingAnd recycling to obtain the loss residual value. Wherein C is SYS-SC1 Is the total equivalent loss of the capacity of the super capacitor, C SC-p Loss coefficient of unit power of super capacitor, P SC,rate Rated power of super capacitor, C SC-e Loss coefficient of unit capacity of super capacitor E SC,rate Rated capacity of super capacitor, C OP-SCunit The operation maintenance loss of the charging and discharging energy of the super capacitor unit,charging power of super capacitor at t moment under typical scene sw of photovoltaic power generation power, +.>The discharge power of the super capacitor at the t moment under the typical scene sw of the photovoltaic power generation power. Considering the loss under the whole life cycle, adopting a unified annual value method, converting the total equivalent loss into equivalent daily operation loss, and converting the recovery loss into daily. r is the discount rate, L SC Is the service life of the super capacitor, -sigma SC-res The recovery residual value rate of the super capacitor is usually 3% -5%.
Wherein m is PV The running loss of the unit power generation power of the photovoltaic power generation station,the photovoltaic power generation power is the photovoltaic power generation power at the moment t under a typical scene sw of the photovoltaic power generation power.
Considering the cost under the whole life cycle, adopting a unified annual value method to convert the total loss value into daily value, wherein r is the discount rate, L converter For the service life of the converter, C converter Is a variable flowThe total value is lost once.
C 6 ＝C totalsell +C sub ；
The loss decrement of the new energy mainly comprises two parts of loss decrement of power transmitted to the power grid and loss decrement of new energy power generation. The loss mechanism of the transmission power of the photovoltaic power station to the power grid is different from the traditional mechanism, and the real-time loss decrement elastic coefficient model is built in the steps; meanwhile, for the consumption of new energy, the loss decrement of the energy is also considered. Wherein C is totalsell C for loss reduction of transmission power to the grid sub Loss of new energy is reduced, m sub The loss of the unit electric quantity is reduced.
Constraints of the optical storage configuration model include: and (5) power balance constraint and energy storage device constraint. The energy storage device constraints include charge and discharge power constraints and state of charge constraints.
According to a typical photovoltaic power generation power scene sw according to a tide distribution rule of each unit of the track traffic energy source consistent system shown in fig. 3, establishing a power balance constraint of the node:
wherein,the photovoltaic power generation power is the photovoltaic power generation power at the moment t under the typical scene sw of the photovoltaic power generation powerRate of->The power transmitted by the power grid to the rail transit system at the t moment under the typical scene sw of the photovoltaic power generation power, < + >>Is the discharge power of the storage battery 8 at the moment t under the typical scene sw of the photovoltaic power generation power, +.>The discharge power of the super capacitor 9 at the t moment under the typical scene sw of the photovoltaic power generation power is +.>Charging power of the storage battery 8 at time t under a typical photovoltaic power generation power scene sw is +.>Charging power of the super capacitor 9 at t moment under typical scene sw of photovoltaic power generation power, +.>A positive value indicates the traction power consumption of the train at the time t, and a negative value indicates the generation of regenerative braking energy of the train at the time t, +.>The power transmitted to the power grid by the photovoltaic power station 6 at the moment t under the typical scene sw of the photovoltaic power generation power.
The charge and discharge power constraint is as follows:
wherein,charging power of the storage battery 8 at time t under a typical photovoltaic power generation power scene sw is +.>Is the discharge power of the storage battery 8 at the moment t under the typical scene sw of the photovoltaic power generation power, +.>For the charge state of the accumulator 8 at time t under the photovoltaic power generation power typical scene sw, +.>Is the discharge state of the storage battery 8 at the moment t under the typical scene sw of the photovoltaic power generation power, P Ba,rate For the rated power of the accumulator 8>Charging power of the super capacitor 9 at t moment under typical scene sw of photovoltaic power generation power, +.>The discharge power of the super capacitor 9 at the t moment under the typical scene sw of the photovoltaic power generation power is +.>The method is that the time t is exceeded under the typical scene sw of the photovoltaic power generation powerThe state of charge of the stage capacitor 9 +.>Is the discharge state of the super capacitor 9 at the moment t under the typical scene sw of the photovoltaic power generation power, P SC,rate Is the rated power of the super capacitor 9. The accumulator 8 and the super capacitor 9 can only have a charging or discharging working state at any time t.
The state of charge constraint of the storage battery 8 and the super capacitor 9 is as follows:
wherein,the state of charge of the storage battery 8 at the time t under the typical scene sw of the photovoltaic power generation power,the charge state of the super capacitor 9 at the moment t under the typical scene sw of the photovoltaic power generation power is +.>For the initial state of charge of the battery 8 under the photovoltaic power generation power typical scenario sw, +.>The initial charge state of the super capacitor 9 under the typical scene sw of the photovoltaic power generation power is represented by T, wherein T is the total time span, < >>For the final state of charge of the battery 8 under the photovoltaic power generation power typical scenario sw, +.>Is the final charge state of the super capacitor 9 under the typical scene sw of the photovoltaic power generation power, +.>Charging power of the storage battery 8 at time t under a typical photovoltaic power generation power scene sw is +.>Is the discharge power of the storage battery 8 at the moment t under the typical scene sw of the photovoltaic power generation power, +.>For the charge state of the accumulator 8 at time t under the photovoltaic power generation power typical scene sw, +.>Is the discharge state eta of the storage battery 8 at the moment t under the typical scene sw of the photovoltaic power generation power Bacha For the charging efficiency, eta of the accumulator 8 Badis For the discharge efficiency of the accumulator 8>Is typical of photovoltaic power generation powerCharging power of super capacitor 9 at time t under scene sw, +.>The discharge power of the super capacitor 9 at the t moment under the typical scene sw of the photovoltaic power generation power is +.>The charging state of the super capacitor 9 at the moment t under the typical scene sw of the photovoltaic power generation power is +.>The discharge state of the super capacitor 9 at the moment t under the typical scene sw of the photovoltaic power generation power is shown as delta t, delta t is the time interval, eta SCcha For the charging efficiency of the super capacitor 9, eta SCdis For discharging efficiency of super capacitor 9, E Ba,rate For the rated capacity of the accumulator 8, E SC,rate For the rated capacity of the supercapacitor 9 +.>For the lower limit of the state of charge of the accumulator 8, < >>Upper limit of state of charge of battery 8, +.>Is the lower limit of the state of charge of the supercapacitor 9, < ->Is the upper limit of the state of charge of the supercapacitor 9.
Step 400: and solving the optical storage configuration model to obtain an optical storage configuration result. The light storage configuration result comprises the capacity of the photovoltaic power station, the capacity of the energy storage device, the power exchanged between the power grid and the rail transit system at each moment under the typical scene of the power generated by each photovoltaic power, the charge and discharge power of the energy storage device and the power exchanged between the photovoltaic power station 6 and the power grid.
Step 500: and configuring the capacity of the photovoltaic power station 6, the capacity of the energy storage device, the charge and discharge power of the energy storage device and the power exchanged between the rail transit system and the power grid according to the light storage configuration result.
According to the invention, firstly, a typical photovoltaic power generation scene is generated according to historical illumination intensity data to describe the randomness of the photovoltaic, secondly, a new energy power loss reduction mechanism is considered, a real-time power loss reduction elastic coefficient model is established, finally, a light storage configuration model which aims at minimum light storage configuration capacity and optimal running loss of a track traffic system is established, the capacities of a photovoltaic power station and an energy storage device, the power exchanged between a power grid and the track traffic system and the charging and discharging power of the energy storage device at each moment in each photovoltaic power generation typical scene are obtained after solving, and then the capacities of the photovoltaic power station, the capacity of the energy storage device, the charging and discharging power of the energy storage device and the power exchanged between the track traffic system and the power grid are configured, so that the photovoltaic permeability of the track traffic is improved, and the traction load is subjected to peak clipping and valley filling.
Example two
In order to execute the corresponding method of the above embodiment to achieve the corresponding functions and technical effects, a track traffic light storage configuration system is provided below.
As shown in fig. 4, the track traffic light storage configuration system provided in this embodiment includes: a data acquisition unit 1, a scene determination unit 2, a model establishment unit 3, a solving unit 4 and a configuration unit 5.
The data acquisition unit 1 is used for acquiring historical illumination intensity data of a traction substation area.
The scene determining unit 2 is connected to the data acquiring unit 1, and the scene determining unit 2 is configured to generate a plurality of photovoltaic power generation power typical scenes according to the historical illumination intensity data, and determine probabilities of the photovoltaic power generation power typical scenes. Each photovoltaic power generation power typical scene comprises photovoltaic power generation power at each moment in the corresponding scene.
The model building unit 3 is connected with the scene determining unit 2, and the model building unit 3 is used for building a light storage configuration model with the lowest total operation loss as a target based on a plurality of photovoltaic power generation typical scenes and the probability of each photovoltaic power generation typical scene.
The solving unit 4 is connected with the model building unit 3, and the solving unit 4 is used for solving the light storage configuration model to obtain a light storage configuration result. The photovoltaic configuration result comprises the capacity of the photovoltaic power station 6, the capacity of the energy storage device 7, the power exchanged between the power grid and the rail transit system at each moment under the typical scene of each photovoltaic power generation power and the charging and discharging power of the energy storage device.
The configuration unit 5 is respectively connected with the solving unit 4, the photovoltaic power station 6 and the energy storage device 7, and the configuration unit 5 is used for configuring the capacity of the photovoltaic power station 6, the capacity of the energy storage device 7, the charge and discharge power of the energy storage device 7 and the power exchanged between the rail transit system and the power grid according to the light storage configuration result.
Compared with the prior art, the track traffic light storage configuration system provided by the embodiment has the same beneficial effects as the track traffic light storage configuration method provided by the first embodiment, and is not repeated here.
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 runs the computer program to enable the electronic device to execute the track traffic light storage configuration 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 the computer program realizes the track traffic light storage configuration method of the first embodiment when being executed by a processor.
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 track traffic light storage configuration method is characterized by comprising the following steps of:
acquiring historical illumination intensity data of a traction substation area;
generating a plurality of photovoltaic power generation power typical scenes according to the historical illumination intensity data, and determining the probability of each photovoltaic power generation power typical scene; each photovoltaic power generation power typical scene comprises photovoltaic power generation power at each moment in the corresponding scene;
based on a plurality of photovoltaic power generation power typical scenes and the probability of each photovoltaic power generation power typical scene, constructing a light storage configuration model with the minimum total operation loss as a target; the objective function of the optical storage configuration model is as follows:
minC＝C 1 +C 2 +C 3 +C 4 +C 5 -C 6 ；
C 2 ＝C SYS-Ba +C OP-Ba +C RC-Ba ；
C 3 ＝C SYS-SC +C OP-SC +C RC-SC ；
C 6 ＝C totalsell +C sub ；
wherein C is the objective function value，C 1 C, loss of power transmitted to rail transit system by power grid 2 C is the full life cycle loss of the storage battery 3 Is the full life cycle loss of the super capacitor, C 4 C is the loss of photovoltaic power generation 5 C is the loss of the converter 6 For new energy loss decrement, SW is the total number of typical scenes of photovoltaic power generation power, P sw Probability of typical scene sw of photovoltaic power generation, T is total time span, C price Is the loss coefficient of the transmission power of the power grid,the power transmitted by a power grid to a rail transit system at the moment t under a typical scene sw of photovoltaic power generation power is represented by delta t, wherein delta t is a time interval, and C SYS-Ba For the equivalent daily running loss of the capacity of the storage battery, C OP-Ba Maintenance loss for operation of battery, C RC-Ba C for the scrapping recovery loss reduction of the storage battery SYS-SC The daily operation loss of the capacity equivalent of the super capacitor is C OP-SC Maintaining loss for operation of super capacitor C RC-SC Loss reduction for scrapping recovery of super capacitor, m PV Operating loss per unit of power generated for a photovoltaic power plant, < >>The power is photovoltaic power generation power at time t under a typical scene sw, r is the discount rate, L converter For the service life of the converter, C converter C is the total value of the disposable loss of the converter totalsell C for loss reduction of transmission power to the grid sub Loss reduction for new energy sources;
solving the optical storage configuration model to obtain an optical storage configuration result; the light storage configuration result comprises the capacity of a photovoltaic power station, the capacity of an energy storage device, the power exchanged between a power grid and a rail transit system at each moment under a typical scene of each photovoltaic power generation power and the charge and discharge power of the energy storage device; the energy storage device comprises a storage battery and a super capacitor;
and configuring the capacity of the photovoltaic power station, the capacity of the energy storage device, the charge and discharge power of the energy storage device and the power exchanged between the rail transit system and the power grid according to the light storage configuration result.
2. The track traffic light storage configuration method according to claim 1, wherein generating a plurality of photovoltaic power generation power typical scenes according to the historical illumination intensity data, and determining the probability of each photovoltaic power generation power typical scene, specifically comprises:
sampling the historical illumination intensity data by using a Latin hypercube sampling method to obtain a plurality of initial scenes of sunlight intensity;
adopting synchronous back substitution reduction method to reduce a plurality of initial scenes with sunlight intensity to obtain a plurality of typical scenes with sunlight intensity;
based on the linear relation between illumination intensity and photovoltaic power generation power, generating a plurality of photovoltaic power generation power typical scenes according to a plurality of sunlight intensity typical scenes, and determining the probability of each photovoltaic power generation power typical scene.
3. The track traffic light storage configuration method according to claim 2, wherein the following formula is adopted to determine the photovoltaic power generation power at the time t under the typical scene sw:
wherein,is the photovoltaic power generation power at the moment t under the typical scene sw of the photovoltaic power generation power, and is +.>For rated photovoltaic power, +.>Is photovoltaic power generationIllumination intensity at t moment under power typical scene sw, beta N Is rated illumination intensity.
4. The rail transit light storage configuration method of claim 1, wherein the constraints of the light storage configuration model include: power balance constraint and energy storage device constraint; the energy storage device constraints include charge and discharge power constraints and state of charge constraints.
5. The rail transit optical storage configuration method of claim 4, wherein the power balance constraint is:
wherein,is the photovoltaic power generation power at the moment t under the typical scene sw of the photovoltaic power generation power, and is +.>The power transmitted by the power grid to the rail transit system at the t moment under the typical scene sw of the photovoltaic power generation power, < + >>Is the discharge power of the storage battery at the moment t under the typical scene sw of the photovoltaic power generation power, +.>The discharge power of the super capacitor at the t moment under the typical scene sw of the photovoltaic power generation power is +.>Charging power of storage battery at t moment under typical scene sw of photovoltaic power generation power, +.>Charging power of super capacitor at t moment under typical scene sw of photovoltaic power generation power, +.>A positive value indicates the traction power consumption of the train at the time t, and a negative value indicates the generation of regenerative braking energy of the train at the time t, +.>The power transmitted to the power grid by the photovoltaic power station at the moment t under the typical scene sw of the photovoltaic power generation power.
6. The rail transit optical storage configuration method of claim 4, wherein the charge-discharge power constraint is:
wherein,charging power of storage battery at t moment under typical scene sw of photovoltaic power generation power, +.>Is the discharge power of the storage battery at the moment t under the typical scene sw of the photovoltaic power generation power, +.>Is the charging state of the storage battery at the moment t under the typical scene sw of the photovoltaic power generation power, and is +.>Is the discharge state of the storage battery at the moment t under the typical scene sw of the photovoltaic power generation power, P Ba,rate For the rated power of the accumulator, < > for>The charging power of the super capacitor at the t moment under the typical scene sw of the photovoltaic power generation power,the discharge power of the super capacitor at the t moment under the typical scene sw of the photovoltaic power generation power is +.>The charging state of the super capacitor at the moment t under the typical scene sw of the photovoltaic power generation power is +.>Is the discharge state of the super capacitor at the moment t under the typical scene sw of the photovoltaic power generation power, P SC,rate Is the rated power of the super capacitor.
7. The rail transit optical storage configuration method of claim 4, wherein the state of charge constraint is:
wherein,the charge state of the storage battery at the moment t under the typical scene sw of the photovoltaic power generation power is +.>The charge state of the super capacitor at t moment under the typical scene sw of the photovoltaic power generation power is +.>For storing power under typical scene sw of photovoltaic power generation powerInitial state of charge of the cell, +.>The initial charge state of the super capacitor under the typical scene sw of the photovoltaic power generation power is represented by T, wherein T is the total time span, < >>As the final state of charge of the storage battery under the photovoltaic power generation power typical scene sw,the final charge state of the super capacitor under the typical scene sw of the photovoltaic power generation power is +.>Charging power of storage battery at t moment under typical scene sw of photovoltaic power generation power, +.>Is the discharge power of the storage battery at the moment t under the typical scene sw of the photovoltaic power generation power, +.>Is the charging state of the storage battery at the moment t under the typical scene sw of the photovoltaic power generation power, and is +.>Is the discharge state eta of the storage battery at the moment t under the typical scene sw of the photovoltaic power generation power Bacha For charging efficiency, eta of the accumulator Badis For the discharge efficiency of the accumulator,/->Charging power of super capacitor at t moment under typical scene sw of photovoltaic power generation power, +.>The discharge power of the super capacitor at the t moment under the typical scene sw of the photovoltaic power generation power is +.>The charging state of the super capacitor at the moment t under the typical scene sw of the photovoltaic power generation power is +.>The discharge state of the super capacitor at the moment t under the typical scene sw of the photovoltaic power generation power is shown, wherein deltat is the time interval eta SCcha Charging efficiency of super capacitor, eta SCdis For discharging efficiency of super capacitor E Ba,rate For rated capacity of accumulator, E SC,rate Rated capacity of super capacitor, +.>Is the lower limit of the state of charge of the battery,upper limit of state of charge of battery, +.>Is the lower limit of the charge state of the super capacitor, < ->Is the upper limit of the charge state of the super capacitor.
8. A rail transit optical storage allocation system applied to the rail transit optical storage allocation method according to any one of claims 1 to 7, characterized in that the rail transit optical storage allocation system comprises:
the data acquisition unit is used for acquiring historical illumination intensity data of the traction substation area;
the scene determining unit is connected with the data acquisition unit and is used for generating a plurality of photovoltaic power generation power typical scenes according to the historical illumination intensity data and determining the probability of each photovoltaic power generation power typical scene; each photovoltaic power generation power typical scene comprises photovoltaic power generation power at each moment in the corresponding scene;
the model building unit is connected with the scene determining unit and is used for building a light storage configuration model with the minimum total operation loss as a target based on a plurality of photovoltaic power generation typical scenes and the probability of each photovoltaic power generation typical scene; the objective function of the optical storage configuration model is as follows:
minC＝C 1 +C 2 +C 3 +C 4 +C 5 -C 6 ；
C 2 ＝C SYS-Ba +C OP-Ba +C RC-Ba ；
C 3 ＝C SYS-SC +C OP-SC +C RC-SC ；
C 6 ＝C totalsell +C sub ；
wherein C is the objective function value, C 1 C, loss of power transmitted to rail transit system by power grid 2 C is the full life cycle loss of the storage battery 3 Is the full life cycle loss of the super capacitor, C 4 C is the loss of photovoltaic power generation 5 C is the loss of the converter 6 For new energy loss decrement, SW is the total number of typical scenes of photovoltaic power generation power, P sw Probability of typical scene sw of photovoltaic power generation, T is total time span, C price For electric network transmissionThe loss coefficient of the power transmission is calculated,the power transmitted by a power grid to a rail transit system at the moment t under a typical scene sw of photovoltaic power generation power is represented by delta t, wherein delta t is a time interval, and C SYS-Ba For the equivalent daily running loss of the capacity of the storage battery, C OP-Ba Maintenance loss for operation of battery, C RC-Ba C for the scrapping recovery loss reduction of the storage battery SYS-SC The daily operation loss of the capacity equivalent of the super capacitor is C OP-SC Maintaining loss for operation of super capacitor C RC-SC Loss reduction for scrapping recovery of super capacitor, m PV Operating loss per unit of power generated for a photovoltaic power plant, < >>The power is photovoltaic power generation power at time t under a typical scene sw, r is the discount rate, L converter For the service life of the converter, C converter C is the total value of the disposable loss of the converter totalsell C for loss reduction of transmission power to the grid sub Loss reduction for new energy sources;
the solving unit is connected with the model building unit and is used for solving the optical storage configuration model to obtain an optical storage configuration result; the light storage configuration result comprises the capacity of a photovoltaic power station, the capacity of an energy storage device, the power exchanged between a power grid and a rail transit system at each moment under a typical scene of each photovoltaic power generation power and the charge and discharge power of the energy storage device; the energy storage device comprises a storage battery and a super capacitor;
the configuration unit is respectively connected with the solving unit, the photovoltaic power station and the energy storage device and is used for configuring the capacity of the photovoltaic power station, the capacity of the energy storage device, the charge and discharge power of the energy storage device and the power exchanged by the rail transit system and the power grid according to the light storage configuration result.
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 rail transit optical storage configuration method of any one of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310707380.1A CN116706892B (en) | 2023-06-15 | 2023-06-15 | Rail transit optical storage configuration method, system and electronic equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310707380.1A CN116706892B (en) | 2023-06-15 | 2023-06-15 | Rail transit optical storage configuration method, system and electronic equipment |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN116706892A CN116706892A (en) | 2023-09-05 |
| CN116706892B true CN116706892B (en) | 2023-12-29 |
Family
ID=87835432
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310707380.1A Active CN116706892B (en) | 2023-06-15 | 2023-06-15 | Rail transit optical storage configuration method, system and electronic equipment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116706892B (en) |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107134789A (en) * | 2017-06-30 | 2017-09-05 | 华南理工大学 | Optimal load flow control method is stored up based on the light for expanding QV nodes |
| CN111178619A (en) * | 2019-12-25 | 2020-05-19 | 东南大学 | Multi-objective optimization method considering distributed power supply and charging station joint planning |
| CN112785027A (en) * | 2020-06-22 | 2021-05-11 | 国网江苏省电力有限公司经济技术研究院 | Wind-solar-storage combined power generation system confidence capacity evaluation method and system |
| CN114266480A (en) * | 2021-12-22 | 2022-04-01 | 国网新疆电力有限公司经济技术研究院 | Photovoltaic output typical scene extraction method combined with spectral clustering algorithm |
| CN114336605A (en) * | 2021-12-29 | 2022-04-12 | 西安交通大学 | Capacity allocation method and system for flexible electro-hydrogen production, storage and injection integrated station |
| CN116011153A (en) * | 2022-11-16 | 2023-04-25 | 国网四川省电力公司经济技术研究院 | Power distribution network reliability assessment method based on light-load correlation enhanced reliability |
| CN116151486A (en) * | 2023-04-19 | 2023-05-23 | 国网天津市电力公司城西供电分公司 | Multi-time-scale random optimization method and device for photovoltaic charging station with energy storage system |
-
2023
- 2023-06-15 CN CN202310707380.1A patent/CN116706892B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107134789A (en) * | 2017-06-30 | 2017-09-05 | 华南理工大学 | Optimal load flow control method is stored up based on the light for expanding QV nodes |
| CN111178619A (en) * | 2019-12-25 | 2020-05-19 | 东南大学 | Multi-objective optimization method considering distributed power supply and charging station joint planning |
| CN112785027A (en) * | 2020-06-22 | 2021-05-11 | 国网江苏省电力有限公司经济技术研究院 | Wind-solar-storage combined power generation system confidence capacity evaluation method and system |
| CN114266480A (en) * | 2021-12-22 | 2022-04-01 | 国网新疆电力有限公司经济技术研究院 | Photovoltaic output typical scene extraction method combined with spectral clustering algorithm |
| CN114336605A (en) * | 2021-12-29 | 2022-04-12 | 西安交通大学 | Capacity allocation method and system for flexible electro-hydrogen production, storage and injection integrated station |
| CN116011153A (en) * | 2022-11-16 | 2023-04-25 | 国网四川省电力公司经济技术研究院 | Power distribution network reliability assessment method based on light-load correlation enhanced reliability |
| CN116151486A (en) * | 2023-04-19 | 2023-05-23 | 国网天津市电力公司城西供电分公司 | Multi-time-scale random optimization method and device for photovoltaic charging station with energy storage system |
Non-Patent Citations (1)
| Title |
|---|
| "含高渗透率光伏的配电网电压协调控制方法研究";马伟;《中国博士学位论文全文数据库 工程科技II辑》(第2期);C042-112 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN116706892A (en) | 2023-09-05 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108258695B (en) | A kind of random robust coupled mode Optimization Scheduling of alternating current-direct current mixed connection microgrid | |
| CN102694391B (en) | Day-ahead optimal scheduling method for wind-solar storage integrated power generation system | |
| CN110661246B (en) | Capacity optimization configuration method for urban rail transit photovoltaic energy storage system | |
| CN107944757A (en) | Electric power interacted system regenerative resource digestion capability analysis and assessment method | |
| CN107134789B (en) | Optical storage optimal power flow control method based on expansion QV node | |
| CN113824111B (en) | Energy storage capacity configuration and scheduling method in optical energy storage scene | |
| CN103151803A (en) | Method for optimizing wind power system-contained unit and backup configuration | |
| CN106096773A (en) | A kind of electric automobile serves as the Multiobjective Optimal Operation method of energy storage | |
| CN103683326A (en) | Method for calculating optimal admitting ability for wind power multipoint access of regional power grid | |
| CN106532764A (en) | Electric vehicle charging load regulation and control method for locally consuming photovoltaic power generation | |
| CN114021390A (en) | Random robust optimization method for urban comprehensive energy system and application thereof | |
| CN113300395B (en) | Hybrid energy storage optimal capacity configuration method for flexible traction power supply system | |
| CN111626527A (en) | Intelligent power grid deep learning scheduling method considering fast/slow charging/discharging form of schedulable electric vehicle | |
| CN103475013A (en) | Method and system for comprehensively optimizing energy storing power station planning and operating | |
| CN115065078B (en) | Energy storage capacity configuration method and system in micro-grid environment | |
| CN115036918B (en) | Method for optimizing economic operation cost and load variance of optical storage charging station | |
| CN112862253B (en) | Electric-gas-thermal energy storage collaborative planning method and system considering wind power uncertainty | |
| CN109849694B (en) | Hybrid energy storage type tramcar energy management method based on online convex programming | |
| CN106058900A (en) | Hybrid energy storage capacity optimization configuration method in grid connected wind-solar generation | |
| CN111762057B (en) | Intelligent charging and discharging management method for V2G electric vehicle in regional microgrid | |
| CN106779250A (en) | A kind of isolated distributed power grid collocation method based on new Optimized model | |
| CN103166248B (en) | Engineering configuration method of independent wind-diesel-storage micro grid system capacity | |
| CN115102160A (en) | Day-ahead energy optimization scheduling method for traction power supply system under weak power grid condition | |
| CN103577893A (en) | Energy-saving optimization method for new energy and thermal power bidirectionally supplying power for high energy carrying loads | |
| CN114091958B (en) | Comprehensive energy efficiency evaluation method and power grid planning method for intelligent electricity utilization cell |
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 |