CN110518637A - Composite phase change energy-storing microgrid configuration method - Google Patents
Composite phase change energy-storing microgrid configuration method Download PDFInfo
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- CN110518637A CN110518637A CN201910942142.2A CN201910942142A CN110518637A CN 110518637 A CN110518637 A CN 110518637A CN 201910942142 A CN201910942142 A CN 201910942142A CN 110518637 A CN110518637 A CN 110518637A
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- 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"
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- 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
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/28—Arrangements for balancing of the load in a network by storage of energy
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- 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
- Y02E10/00—Energy generation through renewable energy sources
- Y02E10/50—Photovoltaic [PV] energy
- Y02E10/56—Power conversion systems, e.g. maximum power point trackers
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- 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
- Y02E10/00—Energy generation through renewable energy sources
- Y02E10/70—Wind energy
- Y02E10/76—Power conversion electric or electronic aspects
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- 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
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- 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
This application involves a kind of composite phase change energy-storing microgrid configuration methods, comprising: obtains the historical data of wind-force Generate, Generation, Generator volt power generation and load in composite phase change energy-storing microgrid.According to the overall life cycle cost of the composite phase change energy-storing microgrid, establishes microgrid Optimized model and constraint condition is set.According to the historical data, scene set is generated, wherein the scene set includes the activity of force out of the composite phase change energy-storing microgrid.According to the microgrid Optimized model and the constraint condition, it is constrained using the configuration scheme of current scene as the installation lower limit of next scene, iteration optimization one by one is carried out to each scene in the scene set, obtains the allocation optimum scheme of the composite phase change energy-storing microgrid.The ability that composite phase change energy-storing microgrid resists uncertain risk can be enhanced in the allocation optimum scheme of composite phase change energy-storing microgrid, and that realizes composite phase change energy-storing microgrid stablizes safe operation.
Description
Technical field
This application involves micro-capacitance sensor technical fields, more particularly to a kind of composite phase change energy-storing microgrid configuration method.
Background technique
For alleviating energy crisis, sustainable development is realized, using wind-force, photovoltaic power generation as the Renewable Energy Development of representative
Rapidly, it is used widely in worldwide.
But since environmental factor can have an impact wind-force, photovoltaic power generation, there is intermittent and fluctuation in power producing characteristics
The features such as property, this not only results in the waste of renewable energy, while also will affect the stable operation of microgrid.
Summary of the invention
Based on this, it is necessary to aiming at the problem that waste of the renewable energy present in the existing microgrid and fluctuation of service, mention
For a kind of composite phase change energy-storing microgrid configuration method.
The application provides a kind of composite phase change energy-storing microgrid configuration method, comprising:
Obtain the historical data of wind-force Generate, Generation, Generator volt power generation and load in composite phase change energy-storing microgrid；
According to the overall life cycle cost of the composite phase change energy-storing microgrid, establishes microgrid Optimized model and constraint item is set
Part；
According to the historical data, scene set is generated, wherein the scene set includes that the composite phase change energy-storing is micro-
Net goes out activity of force；
According to the microgrid Optimized model and the constraint condition, using the configuration scheme of current scene as next
The installation lower limit of a scene constrains, and carries out iteration optimization one by one to each scene in the scene set, obtains described compound
The allocation optimum scheme of phase-change accumulation energy microgrid.
It is described according to the microgrid Optimized model and the constraint condition in one of the embodiments, to work as front court
The configuration scheme of scape is constrained as the installation lower limit of next scene, to each field in the scene set
Scape carries out iteration optimization one by one, obtains the allocation optimum scheme of the composite phase change energy-storing microgrid, comprising:
Zero is set by the initial value of various kinds of equipment installation number in the composite phase change energy-storing microgrid, wherein described compound
The equipment installed in phase-change accumulation energy microgrid includes wind-driven generator, photovoltaic generator, non-renewable energy resources generator and phase transformation
Energy-storage system；
According to the microgrid Optimized model and the constraint condition, using the configuration scheme of current scene as next
The installation lower limit of scene constrains, and carries out iteration optimization one by one to each scene in the scene set and obtains and the scene collection
The identical multiple configuration schemes of scene quantity in conjunction, wherein the configuration scheme includes the various kinds of equipment peace
Fill quantity and dominant eigenvalues capacity；
According to obtained multiple configuration schemes, the various kinds of equipment installation number and the interconnection are determined
The maximum value of power capacity obtains the allocation optimum scheme of the composite phase change energy-storing microgrid.
It is described according to the historical data in one of the embodiments, generate the scene set, comprising:
The historical data is sampled using monte carlo method, obtains including that the composite phase change energy-storing microgrid is complete
Year goes out the scene set of activity of force, wherein the number of scene is N in the scene set；
Any three scenes in the scene set are combined, obtain including N3The combine scenes of a combine scenes
Set；
Fluctuation probability-distribution function is established according to the historical data, and according to the fluctuation probability-distribution function to described
Combine scenes set carries out scene reduction, obtains the revised scene set.
It is described in one of the embodiments, that the historical data is sampled using the monte carlo method, it obtains
To the scene set for going out activity of force including the composite phase change energy-storing microgrid whole year, comprising:
The historical data is sampled using the monte carlo method, obtains the wind-power electricity generation, the photovoltaic
The annual power data of power generation and the load；
According to the annual power data, the wave of the wind-power electricity generation, the photovoltaic power generation and the load is calculated
Dynamic power data, wherein the fluctuating power data meet accumulated probability distribution function；
According to the fluctuating power data, calculating the composite phase change energy-storing microgrid whole year goes out activity of force, obtains the field
Scape set.
The method of the fluctuation probability-distribution function is established in one of the embodiments, comprising:
According to the historical data, the wind-power electricity generation, the photovoltaic power generation and the load are described using beta distribution
The probability density distribution fluctuated obtains the fluctuation probability-distribution function.
Scene is carried out to the combine scenes set according to the fluctuation probability-distribution function in one of the embodiments,
It cuts down, the method for obtaining the revised scene set, comprising:
The scene in the combine scenes set between any two scene is calculated according to the fluctuation probability-distribution function
Diversity factor obtains the smallest two scenes of diversity factor in the combine scenes set；
The smallest two scenes of diversity factor in the combine scenes set are merged, the combination after being merged
Scene set；
Above-mentioned two step is repeated, until the scene number in the combine scenes set is reduced to preset value, is obtained
The revised scene set.
The calculation method of the scene diversity factor in one of the embodiments, comprising:
The fluctuation probability-distribution function is integrated, obtains any two scene in the combine scenes set
In probability of occurrence；
The product for calculating the Euclidean distance between the probability of occurrence and any two scene, it is poor to obtain the scene
Different degree.
The overall life cycle cost includes all kinds of in the composite phase change energy-storing microgrid sets in one of the embodiments,
Standby installation cost, maintenance cost, operating cost and transaction cost, wherein the equipment installed in the composite phase change energy-storing microgrid
Including wind-driven generator, photovoltaic generator, non-renewable energy resources generator and phase-change accumulation energy system.
The overall life cycle cost according to the composite phase change energy-storing microgrid in one of the embodiments,
It establishes the microgrid Optimized model and is arranged before the constraint condition, comprising:
The self-balancing figureofmerit, redundancy figureofmerit and renewable energy utilization rate for establishing the composite phase change energy-storing microgrid refer to
Mark.
The constraint condition includes microgrid configuration constraint in one of the embodiments, and the microgrid configuration constraint is institute
State the lower limit constraint of self-balancing figureofmerit, the redundancy figureofmerit and the renewable energy utilization rate index.
The constraint condition includes the operation constraint of microgrid phase-change accumulation energy system, the microgrid in one of the embodiments,
The operation constraint of phase-change accumulation energy system are as follows:
Wherein, HbtEnthalpy for the phase-change accumulation energy system in period t, HbFor the full enthalpy of the phase-change accumulation energy system,WithThe charging and discharging power of the phase-change accumulation energy system heat pump respectively, ηcAnd ηdThe respectively described heat pump electricity turns heat
Efficiency and the heat pump radiating efficiency, Δ t are time interval, and φ is the phase-change accumulation energy system from heat liberation rate, heat release rate,SOCWithThe minimum and maximum heat accumulation state of the respectively described phase-change accumulation energy system, SOC are the phase-change accumulation energy system in period t
Heat accumulation state.
Composite phase change energy-storing microgrid configuration method provided by the present application, according to the life-cycle of the composite phase change energy-storing microgrid
Life cycle costing establishes microgrid Optimized model, and going through according to wind-force Generate, Generation, Generator volt power generation in composite phase change energy-storing microgrid and load
History data generate scene set.It is constrained using the configuration scheme of current scene as the installation lower limit of next scene, to institute
The each scene stated in scene set carries out iteration optimization one by one, obtains the allocation optimum side of the composite phase change energy-storing microgrid
Case.The allocation optimum scheme of composite phase change energy-storing microgrid can reduce wind-force Generate, Generation, Generator volt in composite phase-change microgrid and generate electricity not
Certainty bring adverse effect, enhancing composite phase change energy-storing microgrid resist the ability of uncertain risk, realize composite phase-change storage
Energy microgrid stablizes safe operation.
Detailed description of the invention
Fig. 1 is a kind of composite phase change energy-storing microgrid configuration method flow chart provided by the embodiments of the present application；
Fig. 2 is a kind of wind speed whole year historical data provided by the embodiments of the present application；
Fig. 3 is a kind of illumination whole year historical data provided by the embodiments of the present application；
Fig. 4 is a kind of load whole year historical data provided by the embodiments of the present application；
Fig. 5 is another composite phase change energy-storing microgrid configuration method flow chart provided by the embodiments of the present application；
Fig. 6 be the embodiment of the present application body a kind of different scenes under composite phase change energy-storing microgrid allocation plan.
Specific embodiment
In order to make the above objects, features, and advantages of the present application more apparent, with reference to the accompanying drawing to the application
Specific embodiment be described in detail.Many details are explained in the following description in order to fully understand this Shen
Please.But the application can be implemented with being much different from other way described herein, those skilled in the art can be not
Similar improvement is done in the case where violating the application intension, therefore the application is not limited by following public specific implementation.
It should be noted that it can directly on the other element when element is referred to as " being fixed on " another element
Or there may also be elements placed in the middle.When an element is considered as " connection " another element, it, which can be, is directly connected to
To another element or it may be simultaneously present centering elements.
Unless otherwise defined, all technical and scientific terms used herein and the technical field for belonging to the application
The normally understood meaning of technical staff is identical.The term used in the description of the present application is intended merely to description tool herein
The purpose of the embodiment of body, it is not intended that in limitation the application.Term " and or " used herein includes one or more phases
Any and all combinations of the listed item of pass.
Referring to Figure 1, the application provides a kind of composite phase change energy-storing microgrid configuration method.The configuration of composite phase change energy-storing microgrid
Method includes: step S100, obtains the historical data of wind-force Generate, Generation, Generator volt power generation and load in composite phase change energy-storing microgrid.Step
Rapid S200 establishes microgrid Optimized model and constraint item is arranged according to the overall life cycle cost of the composite phase change energy-storing microgrid
Part.Step S300 generates scene set according to the historical data, wherein the scene set includes the composite phase-change storage
Energy microgrid goes out activity of force.Step S400, according to the microgrid Optimized model and the constraint condition, with the excellent of current scene
The installation lower limit for changing allocation plan as next scene constrains, and carries out iteration one by one to each scene in the scene set
Optimization, obtains the allocation optimum scheme of the composite phase change energy-storing microgrid.
In view of randomness and fluctuation that wind energy and luminous energy are contributed in power generation process, the temperature built in microgrid is easy
Uncertain fluctuation is generated, therefore the preferable material of thermal storage performance can be used to absorb heat to keep constant temperature.If be appreciated that
It will exceed the energy more than needed of resident's demand, i.e., extra wind energy and luminous energy, thermal energy storage be converted to by heat pump, can subtract
Light is abandoned in few abandonment, improves the utilization rate of renewable energy.And the key of heating power energy storage is energy-accumulating medium.It is appreciated that phase transformation
Material is that one kind temperature change in phase transition process is smaller, while can be absorbed or discharge the energy-accumulating medium of big energy.Phase transformation
Material has many advantages, such as that preparation cost is low, energy storage density is big and life cycle is long, can be in building preparation, Cold Storage Material for Air Conditioning
Equal fields are widely applied.
It is appreciated that by inside construction wall lay packaging phase change material heat pipe, can by microgrid have more than needed
Renewable energy is converted to thermal energy storage in phase-change material by heat pump, while using phase-change material absorption or when releasing energy
Room temperature is remained human comfort's temperature by temperature-resistant characteristic, is solved while meeting and building temperature requirements renewable
The consumption difficult problem of the energy.Composite phase change energy-storing microgrid provided by the present application is sufficiently counted and wind-force, photovoltaic power generation power output be not true
It qualitatively influences, the redundant configuration that reduction technology forms composite phase change energy-storing microgrid is generated by scene, so that composite phase-change stores up
Energy microgrid has the stronger ability for resisting uncertainty and risk, guarantees the safe and stable operation of composite phase change energy-storing microgrid.
In the step s 100, wind-force hair in composite phase change energy-storing microgrid can be obtained from grid dispatching center and Meteorological Center
The historical data of electricity, photovoltaic power generation and load.In step s 200, according to the life cycle management of the composite phase change energy-storing microgrid
Cost establishes microgrid Optimized model and constraint condition is arranged.It is appreciated that the overall life cycle cost of composite phase-change microgrid can be with
As objective function, and then the minimum value of Optimization Solution overall life cycle cost.Wherein, the life-cycle of composite phase change energy-storing microgrid
Period can indicate are as follows:
C=Can+Cwei+Cyun+Cbar (1)
Wherein, CanFor composite phase change energy-storing microgrid installation cost, may include wind power plant, photovoltaic power generation equipment,
The installation cost of diesel power generation equipment and building phase-change accumulation energy system installation.CweiIt is the maintenance cost of composite phase change energy-storing microgrid,
Usually with composite phase change energy-storing microgrid installation cost at preset ratio.CyunIt is the operating cost of composite phase change energy-storing microgrid, including
Wind power plant, photovoltaic power generation equipment, the switching cost of diesel power generation equipment and diesel power generation equipment fuel cost.
CbarIt is the transaction cost of composite phase change energy-storing microgrid, i.e. the cost that generates of composite phase change energy-storing microgrid and power grid Change Power.Tool
Body is as follows:
Cwei=αwei·Can (3)
Wherein, npi、nwi、nsiAnd ndiRespectively photovoltaic power generation equipment, wind power plant, phase-change energy-storage units and diesel oil
The installation number of generating equipment.Photovoltaic power generation equipment, wind power plant, phase-change energy-storage units in one of the embodiments,
Installation number with diesel power generation equipment can be respectively photovoltaic cell installation number, wind-driven generator installation number, phase transformation storage
It can unit installation number and diesel-driven generator installation number.Cwi、Cpi、Cdi、CsiCan be respectively wind-driven generator, photovoltaic cell,
The unit deployment cost of diesel-driven generator and phase-change energy-storage units, and τ is PVIFAi, n.αweiFor composite phase change energy-storing
The ratio of microgrid maintenance cost and installation cost, usually takes 3%-5%.cwi、cpiRespectively wind-driven generator and photovoltaic cell
Start-up and shut-down costs coefficient；csiFor phase-change energy-storage units depreciable cost coefficient,；c'diFor the power cost coefficient of diesel-driven generator；
cdiFor the start and stop state cost coefficient of diesel-driven generator；Swi,t、Spi,t、Sdi,tIt is integer variable, respectively indicates different moments wind
Power generator, the starting of photovoltaic cell and diesel-driven generator, halted state；Usi,tIt is filling for different moments phase-change energy-storage units
Discharge condition [0,1] variable.cbuy、csellElectricity is bought from power grid for composite phase change energy-storing microgrid and sells electricity price lattice；Pbuy,t、Psell,tPoint
Not Wei t moment composite phase change energy-storing microgrid from buying for power grid electricity and sell electricity.In addition, WT, PV, DE and ES difference wind-force hair
Number of motors, photovoltaic cell quantity, diesel-driven generator quantity and phase-change energy-storage units quantity.
In step S300, according to the historical data, scene set is generated, wherein the scene set includes described multiple
Close activity of force and the load fluctuation out of phase-change accumulation energy microgrid wind-power electricity generation, photovoltaic power generation.According to wind-power electricity generation, photovoltaic power generation and
The scene set of hybrid wind power generation, photovoltaic power generation power output uncertainty and load fluctuation can be generated in the historical data of load.
It is appreciated that scene set may include wind power plant, photovoltaic power generation equipment, diesel generation in composite phase change energy-storing microgrid
The activity of force out of equipment and building phase-change accumulation energy.
In step S400, constrained using the configuration scheme of current scene as the installation lower limit of next scene, it is right
Each scene in the scene set carries out iteration optimization one by one.By constantly correcting the allocation plan of composite phase-change microgrid,
The stability that composite phase-change microgrid can be improved obtains the allocation optimum scheme of the composite phase change energy-storing microgrid.It is appreciated that
The allocation optimum scheme of composite phase-change microgrid is redundant configuration, and redundant configuration scheme can be supported improving composite phase change energy-storing microgrid
Under the premise of anti-uncertainty risk, the overall life cycle cost of composite phase change energy-storing microgrid is minimized.
Composite phase change energy-storing microgrid configuration method provided by the present application, according to the life-cycle of the composite phase change energy-storing microgrid
Life cycle costing establishes microgrid Optimized model, and going through according to wind-force Generate, Generation, Generator volt power generation in composite phase change energy-storing microgrid and load
History data generate scene set.Go out activity of force with the corresponding composite phase change energy-storing microgrid of the configuration scheme of current scene
Installation lower limit as next scene constrains, and carries out iteration optimization one by one to each scene in scene set, obtains described
The allocation optimum scheme of composite phase change energy-storing microgrid.Composite phase change energy-storing microgrid configuration method provided by the present application, which can integrate, to be examined
Consider load, wind-power electricity generation, photovoltaic power generation fluctuation, refer in the performance for meeting composite phase change energy-storing microgrid independence or being incorporated into the power networks
Under the conditions of target, realizes the robust configuration of composite phase change energy-storing microgrid capacity, obtain the allocation optimum of composite phase change energy-storing microgrid
Scheme.Composite phase change energy-storing microgrid configuration method can reduce wind-force Generate, Generation, Generator in composite phase-change microgrid and lie prostrate the uncertain of power generation
Property bring adverse effect, enhancing composite phase change energy-storing microgrid resist uncertainty and risk ability, and using building phase-change accumulation energy
Unit stores wind, light renewable energy, and that realizes composite phase change energy-storing microgrid stablizes safe operation.
It is described according to the microgrid Optimized model and the constraint condition in one of the embodiments, to work as front court
The configuration scheme of scape is constrained as the installation lower limit of next scene, to each field in the scene set
Scape carries out iteration optimization one by one, obtains the allocation optimum scheme of the composite phase change energy-storing microgrid, comprising: will be described compound
The initial value of various kinds of equipment installation number is set as zero in phase-change accumulation energy microgrid, wherein installing in the composite phase change energy-storing microgrid
Equipment include wind-driven generator, photovoltaic generator, non-renewable energy resources generator and phase-change accumulation energy system.According to described micro-
Net Optimized model and the constraint condition, the installation lower limit using the configuration scheme of current scene as next scene is about
Beam, in the scene set each scene carry out one by one iteration optimization obtain it is identical as scene quantity in the scene set
Multiple configuration schemes, wherein the configuration scheme includes the various kinds of equipment installation number and interconnection
Power capacity.According to obtained multiple configuration schemes, the various kinds of equipment installation number and the contact are determined
The maximum value of linear heat generation rate capacity obtains the allocation optimum scheme of the composite phase change energy-storing microgrid.
It is appreciated that non-renewable energy resources generator can be diesel-driven generator.Scene collection in one of the embodiments,
Conjunction may include M wind-power electricity generation, photovoltaic power generation and load fluctuation scene.For the Shandong of that operation of enhancing composite phase change energy-storing
Stick can carry out capacity configuration to the equipment of composite phase change energy-storing microgrid.Meeting M random scene operation and configuration constraint
Under the constraint of condition, the capacity configuration scheme of composite phase change energy-storing microgrid can be gradually corrected.It wraps in one of the embodiments,
The scene set for including M wind-power electricity generation, photovoltaic power generation and load fluctuation scene can be after carrying out scene reduction to whole scenes
The remaining scene set of formation.M can be the scene quantity that is manually set in one of the embodiments, according to operating experience,
M can be 10.
The initial value value of the equipment installation number of composite phase change energy-storing microgrid can be set first in one of the embodiments,
It is set to zero.For first scene, optimization obtains the optimal installation number of devices and dominant eigenvalues of composite phase change energy-storing microgrid
Capacity, i.e. (ni,opt,Pg,opt).It is appreciated that power transmission line of the interconnection between composite phase change energy-storing microgrid and power grid, it is compound
Phase-change accumulation energy microgrid can carry out Power Exchange by interconnection and power grid.Secondly, can distributing rationally with first scene
Scheme constrains (n as the installation lower limit of second scenarioi,min,Pg,min).According to above-mentioned rule, to M scene one by one successively into
Row iteration optimization.It should be noted that the allocation optimum scheme that each scene optimization obtains can be used as down in optimization process
The installation lower limit of a scene optimization constrains, and finally obtains M group prioritization scheme.It is appreciated that every group of prioritization scheme includes compound
The equipment installation number and dominant eigenvalues capacity of phase-change accumulation energy microgrid.For M group prioritization scheme, the installation number of every kind of equipment
The maximum value in M group scheme can be chosen, i.e., last group of prioritization scheme successively optimized is composite phase change energy-storing microgrid
Allocation optimum scheme.It can guarantee that the allocation optimum scheme of final composite phase change energy-storing microgrid can satisfy all scenes at this time
Operation demand forms redundant configuration.
Distinct device quantity and interconnection function in composite phase change energy-storing microgrid when Optimized model in one of the embodiments,
Rate is constantly updated.To guarantee redundant safety configuration, composite phase change energy-storing microgrid number of devices can be set in an iterative process about
Beam and dominant eigenvalues constraint.Wherein, the number of devices of composite phase change energy-storing microgrid and dominant eigenvalues can under original state
To be set as 0.The constraint of each iteration optimization can indicate are as follows:
Wherein, PgIt is the dominant eigenvalues of each iteration optimization；nwi,min, npi,min, nsi,min, ndi,minRespectively by upper
The installation number of wind-driven generator, photovoltaic cell, phase-change energy-storage units and diesel-driven generator that one scene optimization iteration is formed
Measure lower limit, Pg,minIt is the dominant eigenvalues lower limit formed by a upper scene optimization iteration.
It is described according to the historical data in one of the embodiments, generate the scene set, comprising: using illiteracy
Special Carlow method is sampled the historical data, obtains including the institute for the composite phase change energy-storing microgrid whole year going out activity of force
Scene set is stated, wherein the number of scene is N in the scene set.Any three scenes in the scene set are carried out
Combination, obtains including N3The combine scenes set of a combine scenes.Fluctuation probability-distribution function is established according to the historical data,
And scene reduction is carried out to the combine scenes set according to the fluctuation probability-distribution function, obtain the revised scene
Set.It is appreciated that mixing load, photovoltaic and the probabilistic scene collection of wind power output can be generated according to historical data
It closes.Random scene can be generated using Latin Hypercube Sampling technology in one of the embodiments, pass through interval prediction method
It solves the problems, such as uncertain optimization, establishes Robust Optimization Model, then cut down algorithm using synchronous back substitution and scene is reduced to M
Feature is relatively significant and the biggish data scene of probability.It can sample to be formed using Monte Carlo in one of the embodiments,
Photovoltaic power generation whole year power scene, total M, and fluctuating power data are formed in annual data.Composite phase-change storage is generated respectively
Load, photovoltaic and the wind power output of energy microgrid whole year fluctuates scene, wherein any three loads, photovoltaic and wind power output wave
Dynamic scene composition can be formed including N3The data scene of a combine scenes.Finally scene is carried out using synchronous back substitution technology for eliminating
It cuts down, obtains revised scene set.Wherein, wind-power electricity generation scene generates cutting method and can generate with photovoltaic power generation scene
Cutting method is identical.
It is described in one of the embodiments, that the historical data is sampled using the monte carlo method, it obtains
To the scene set for going out activity of force including the composite phase change energy-storing microgrid whole year, comprising: use the Monte Carlo side
Method is sampled the historical data, obtains the annual power number of the wind-power electricity generation, the photovoltaic power generation and the load
According to.According to the annual power data, the fluctuating power of the wind-power electricity generation, the photovoltaic power generation and the load is calculated
Data, wherein the fluctuating power data meet accumulated probability distribution function.According to the fluctuating power data, calculate described multiple
Conjunction phase-change accumulation energy microgrid whole year goes out activity of force, obtains the scene set.
Photovoltaic power generation whole year 8760h power (P is formed using the Monte Carlo methods of sampling in one of the embodiments,1,
P2,...,P8760) scene, and fluctuating power data are formed in annual data, and fluctuating power data meet accumulated probability distribution
Function Pr(), specifically:
Pit=Pt+ΔPit=Pt+F-1[Pr(ΔPit)] (8)
Wherein, N PrThe quantity that () divides.It can be in one of the embodiments, 100 according to big number principle N.PitWith
ΔPitIt respectively indicates photovoltaic power generation and goes out activity of force and generated output undulating value.F-1[Pr(ΔPit)] indicate to negate function.PtWhen for t
Section photovoltaic power generation prediction power, ritFor the random number between 0~1.In PrI-th part is extracted in N part that () divides, and is formed
8760 random numbers, then available random scene i is (Pi1,Pi2,...,Pi8760)。
The method of the fluctuation probability-distribution function is established in one of the embodiments, comprising: according to the history number
According to, the probability density distribution that the wind-power electricity generation, the photovoltaic power generation and the load fluctuate is described using beta distribution,
Obtain the fluctuation probability-distribution function.It is appreciated that beta distribution description load, wind-force or the probability of photovoltaic power generation fluctuation are close
Degree distribution:
Wherein, P is the contextual data of load, wind-force or photovoltaic power generation, can be obtained by grid dispatching center and Meteorological Center.
PmaxIt is the maximum contextual data of load, wind-force or photovoltaic power generation, is normalized for contextual data.Γ (α) indicates gamma letter
Number；α, β are probability density function form parameter, can be obtained by concrete shape parameter fitting.
Scene is carried out to the combine scenes set according to the fluctuation probability-distribution function in one of the embodiments,
It cuts down, the method for obtaining the revised scene set, comprising: the combination is calculated according to the fluctuation probability-distribution function
It is two the smallest to obtain diversity factor in the combine scenes set for scene diversity factor in scene set between any two scene
Scene.The smallest two scenes of diversity factor in the combine scenes set are merged, the combined field after being merged
Scape set.Above-mentioned two step is repeated, until the scene number in the combine scenes set is reduced to preset value, is repaired
The scene set after just.
The calculation method of the scene diversity factor in one of the embodiments, comprising: to the fluctuation probability distribution letter
Number is integrated, and probability of occurrence of any two scene in the combine scenes set is obtained.It is general to calculate the appearance
The product of Euclidean distance between rate and any two scene obtains the scene diversity factor.It is appreciated that for above-mentioned
The N that embodiment is formed3The combine scenes set of a combine scenes carries out scene reduction, forms desired M scene.Firstly, can
In N3Scene diversity factor S is found in a combine scenesijThe smallest combine scenes i and j, wherein diversity factor SijCalculation formula
Are as follows:
Wherein, pjProbability of occurrence of the combine scenes j in all combine scenes is indicated, by probability density function
Integrate available probability of occurrence.si、sjWhere the position for indicating combine scenes i, j, it can be used for calculating European between scene
Distance.It finds out the diversity factor in combine scenes set the smallest combine scenes i, j to merge, and has pj=pi+pj, guarantee institute
There is the probability of combine scenes and for 1.It constantly repeats the above steps, until cutting down combine scenes number to M.
The overall life cycle cost includes all kinds of in the composite phase change energy-storing microgrid sets in one of the embodiments,
Standby installation cost, maintenance cost, operating cost and transaction cost, wherein the equipment installed in the composite phase change energy-storing microgrid
Including wind-driven generator, photovoltaic generator, non-renewable energy resources generator and phase-change accumulation energy system.It is appreciated that compound
The overall life cycle cost C of phase-change accumulation energy microgrid is objective function, can obtain objective function most by existing optimization method
Small value.It in above process, can be constraint with the configuration condition of composite phase change energy-storing microgrid and service condition.One wherein
In embodiment, constraint condition may include the sale of electricity constraint of composite phase-change microgrid, power-balance constraint, plant capacity constraint and
System operation constraint.
Wherein, composite phase change energy-storing microgrid purchase sale of electricity constraint are as follows:
Wherein, Ug,tFor [0,1] Boolean variable, composite phase change energy-storing microgrid, which can be constrained, cannot buy electricity simultaneously and sell electricity.Pg
For the upper limit of the power of composite phase change energy-storing microgrid and interconnecting ties.The power-balance constraint of composite phase change energy-storing microgrid are as follows:
Wherein, Pwi、Ppi、Psi、PdiFor the specified function of wind-power electricity generation, photovoltaic power generation, phase-change energy-storage units and diesel-driven generator
Rate.Psci,t、Psdi,tRespectively the heat pump of phase-change energy-storage units absorbs electrical power and release electrical power.Composite phase change energy-storing microgrid
It is related with equipment switched amount and power output bound that interior equipment goes out activity of force, therefore the plant capacity of composite phase change energy-storing microgrid is about
Beam are as follows:
Wherein,For wind power plant contribute the upper limit,WithThe upper limit is contributed under for photovoltaic power generation equipment
Limit；WithFor diesel generation machine equipment power output upper and lower bound.S is integer variable, indicates the number to put into operation.
Remaining physical quantity can refer to other embodiments, and details are not described herein.
The overall life cycle cost according to the composite phase change energy-storing microgrid in one of the embodiments,
It establishes the microgrid Optimized model and is arranged before the constraint condition, comprising: establish oneself of the composite phase change energy-storing microgrid
Balance figureofmerit, redundancy figureofmerit and renewable energy utilization rate index.It is appreciated that the application can be referred to by self-balancing amount
Mark α ', redundancy figureofmerit β ', renewable energy utilization rate index γ ' Lai Tixian composite phase change energy-storing microgrid capacity configuration it is specific
Performance.Wherein, self-balancing figureofmerit can indicate are as follows:
Wherein, Pl,tFor load microgrid demand, Pbuy,tElectrical power is bought to power grid for composite phase change energy-storing microgrid, T indicates annual
Time.Redundancy figureofmerit can indicate are as follows:
Wherein, Psell,tElectrical power is sold to power grid for composite phase change energy-storing microgrid.Renewable energy utilization rate index can be with
It indicates are as follows:
Wherein, Pwi,tAnd Ppi,tThe respectively output power of t moment wind-power electricity generation machine and photovoltaic battery panel,WithRespectively the output power upper limit of t moment wind-power electricity generation machine and photovoltaic battery panel, WT and PV respectively indicate wind-power electricity generation
The magnitude-set of machine and photovoltaic battery panel.
The constraint condition includes microgrid configuration constraint in one of the embodiments, and the microgrid configuration constraint is institute
State the lower limit constraint of self-balancing figureofmerit, the redundancy figureofmerit and the renewable energy utilization rate index.It is appreciated that multiple
Closing phase-change accumulation energy microgrid configuration constraint can refer to for self-balancing figureofmerit α ', redundancy figureofmerit β ' and renewable energy utilization rate
Mark γ ' constrains the configuration of composite phase change energy-storing microgrid place capacity:
Wherein, α 'design、β'design、γ'designRespectively self-balancing figureofmerit lower limit requires, redundancy figureofmerit lower limit is wanted
It asks, renewable energy utilization rate index lower limit requirement.
The constraint condition includes the operation constraint of microgrid phase-change accumulation energy system, the microgrid in one of the embodiments,
The operation constraint of phase-change accumulation energy system are as follows:
Wherein, HbtEnthalpy for the phase-change accumulation energy system in period t, HbFor the full enthalpy of the phase-change accumulation energy system,WithThe charging and discharging power of the phase-change accumulation energy system heat pump respectively, ηcAnd ηdThe respectively described heat pump electricity turns heat
Efficiency and the heat pump radiating efficiency, Δ t are time interval, and φ is the phase-change accumulation energy system from heat liberation rate, heat release rate,SOCWithThe minimum and maximum heat accumulation state of the respectively described phase-change accumulation energy system, SOC are the phase-change accumulation energy system in period t
Heat accumulation state.
In one of the embodiments.Composite phase change energy-storing microgrid configuration method include: first from grid dispatching center and
Meteorological Center obtains whole year 8760h wind speed, illumination and demand history data, referring to fig. 2-Fig. 4.In one of the embodiments,
Annual 8760h wind-power electricity generation, photovoltaic power generation and load fluctuation data can be directly acquired from grid dispatching center, or according to figure
Wind-power electricity generation, photovoltaic power generation and load fluctuation data are calculated in the data of 2- Fig. 4.It is generated according to accumulated probability density function
Wind-power electricity generation, photovoltaic power generation and load fluctuation data.Establish the composite phase-change that target is minimised as with overall life cycle cost
Energy storage microgrid allocation models, wherein it is 2.6 that the heat pump electricity of phase-change accumulation energy system, which turns the thermal efficiency, and heat pump radiating efficiency is 0.9.It is multiple
The net purchase electricity price and sale of electricity electricity price for closing phase-change accumulation energy microgrid and power grid are respectively 1.0 yuan/kWh and 0.8 yuan/kWh.
Table 1
Composite phase change energy-storing microgrid equipment operating parameter is as shown in table 1 in one of the embodiments, then establishes the life-cycle
Life cycle costing C can be expressed as formula (1), and include in formula (1) composite phase change energy-storing microgrid installation cost, maintenance at
Originally, operating cost and transaction cost can be expressed as formula (2), (3), (4) and (5).Constraint condition can be expressed as public affairs
Formula (11), (12), (13), (14), (15), (19) and (20).Wherein, dominant eigenvalues upper limit PgIt can be 2000kW,
WithSOCIt can be respectively 0.9 and 0.1 for phase-change accumulation energy system SOC capacity peak and minimum.
According to the historical data of wind-power electricity generation, photovoltaic power generation and load, generate N=100 scene respectively, then any three
Wind-power electricity generation, photovoltaic power generation and the symbiosis of load fluctuation scene are at 1000000 combine scenes.Technology is cut down using synchronous back substitution to contract
Reduce to M=10 representative combine scenes.It specifically includes: it is poor to find scene first in 1000000 data scenes
Different degree SijThe smallest scene i and j, wherein SijCalculation formula be formula (10).Scene i the smallest to diversity factor, j are closed
And i.e. pj=pi+pj, and all scene probability and be 1.It repeats the above steps until combine scenes number is cut down to M=10.Base
Combine scenes after reduction form 10 wind-power electricity generations, photovoltaic power generation and load fluctuation combine scenes and carry out composite phase change energy-storing
The configuration of microgrid place capacity.
Please also refer to Fig. 5, in one of the embodiments, the operation that meets M random combine scene and configuration about
Gradually amendment allocation plan under beam.First set the initial value that the equipment installation number of composite phase change energy-storing microgrid is arranged to
Zero.For first scene, optimization obtains the optimal installation number of devices and dominant eigenvalues capacity of composite phase change energy-storing microgrid.
And the installation lower limit constraint using the configuration scheme of first scene as second scenario.One by one for M combine scenes
It is successively iterated optimization, in this process, the allocation plan of the composite phase change energy-storing microgrid obtained every time can be used as next
The installation lower limit constraint of combine scenes optimization, obtains M group prioritization scheme.Therefore, for M group prioritization scheme, every kind of equipment installation
Quantity chooses the upper limit of M group, that is, chooses last group, final configuration of the M group prioritization scheme as composite phase change energy-storing microgrid
Scheme.Can satisfy all scene operations according to the final allocation plan of composite phase change energy-storing microgrid obtained by the above method needs
It asks, is the allocation optimum of composite phase change energy-storing microgrid.In the present embodiment, the allocation optimum of the composite phase change energy-storing microgrid obtained
Scheme may refer to Fig. 6, and wherein TL indicates dominant eigenvalues.
In one of the embodiments, to allocation plan without gradually correcting, directly chooses under 10 scenes and set for every kind
The maximum value of standby installation number can form " the highest configuration " of microgrid installation equipment.Based on wind-power electricity generation, photovoltaic power generation and load
Historical data, directly setting objective function and constraint condition solve, and can form " basic configuration " of microgrid installation equipment.According to
The application composite phase change energy-storing net configuration method can be formed " allocation optimum " of composite phase change energy-storing microgrid, pair of three kinds of configurations
Than as shown in table 2.As shown in Table 2, allocation optimum is reduced with respect to the deployment cost that highest configures, and economy increases, simultaneously
Also it is able to satisfy the operation demand of all scenes, the ability that can make composite phase change energy-storing microgrid that there is stronger resisting risk.
Table 2
| TL/kw | DE/kw | ES/kw | PV/kw | WT/kw | |
| Basic configuration | 81.509 | 100 | 80 | 20 | 420 |
| Allocation optimum | 89.22337 | 100 | 140 | 30 | 480 |
| Highest configuration | 88.4997 | 100 | 340 | 140 | 480 |
Each technical characteristic of embodiment described above can be combined arbitrarily, for simplicity of description, not to above-mentioned reality
It applies all possible combination of each technical characteristic in example to be all described, as long as however, the combination of these technical characteristics is not deposited
In contradiction, all should be considered as described in this specification.
The several embodiments of the application above described embodiment only expresses, the description thereof is more specific and detailed, but simultaneously
The limitation to claim therefore cannot be interpreted as.It should be pointed out that coming for those of ordinary skill in the art
It says, without departing from the concept of this application, various modifications and improvements can be made, these belong to the protection of the application
Range.Therefore, the scope of protection shall be subject to the appended claims for the application patent.
Claims (11)
1. a kind of composite phase change energy-storing microgrid configuration method characterized by comprising
Obtain the historical data of wind-force Generate, Generation, Generator volt power generation and load in composite phase change energy-storing microgrid；
According to the overall life cycle cost of the composite phase change energy-storing microgrid, establishes microgrid Optimized model and constraint condition is set；
According to the historical data, scene set is generated, wherein the scene set includes the composite phase change energy-storing microgrid
Activity of force out；
According to the microgrid Optimized model and the constraint condition, using the configuration scheme of current scene as next field
The installation lower limit of scape constrains, and carries out iteration optimization one by one to each scene in the scene set, obtains the composite phase-change
The allocation optimum scheme of energy storage microgrid.
2. composite phase change energy-storing microgrid configuration method according to claim 1, which is characterized in that described according to the microgrid
Optimized model and the constraint condition, using the configuration scheme of current scene as the installation of next scene
Lower limit constraint carries out iteration optimization one by one to each scene in the scene set, obtains the composite phase change energy-storing microgrid
The allocation optimum scheme, comprising:
Zero is set by the initial value of various kinds of equipment installation number in the composite phase change energy-storing microgrid, wherein the composite phase-change
The equipment installed in energy storage microgrid includes wind-driven generator, photovoltaic generator, non-renewable energy resources generator and phase-change accumulation energy
System；
According to the microgrid Optimized model and the constraint condition, using the configuration scheme of current scene as next scene
Installation lower limit constraint, in the scene set each scene carry out one by one iteration optimization obtain in the scene set
The identical multiple configuration schemes of scene quantity, wherein the configuration scheme includes the various kinds of equipment installation number
Amount and dominant eigenvalues capacity；
According to obtained multiple configuration schemes, the various kinds of equipment installation number and the dominant eigenvalues are determined
The maximum value of capacity obtains the allocation optimum scheme of the composite phase change energy-storing microgrid.
3. composite phase change energy-storing microgrid configuration method according to claim 1, which is characterized in that described according to the history
Data generate the scene set, comprising:
The historical data is sampled using monte carlo method, obtains including going out the composite phase change energy-storing microgrid whole year
The scene set of activity of force, wherein the number of scene is N in the scene set；
Any three scenes in the scene set are combined, obtain including N3The combine scenes set of a combine scenes；
Fluctuation probability-distribution function is established according to the historical data, and according to the fluctuation probability-distribution function to the combination
Scene set carries out scene reduction, obtains the revised scene set.
4. composite phase change energy-storing microgrid configuration method according to claim 3, which is characterized in that described special using the illiteracy
Carlow method is sampled the historical data, obtains including the composite phase change energy-storing microgrid whole year going out the described of activity of force
Scene set, comprising:
The historical data is sampled using the monte carlo method, obtains the wind-power electricity generation, the photovoltaic power generation
With the annual power data of the load；
According to the annual power data, the fluctuation function of the wind-power electricity generation, the photovoltaic power generation and the load is calculated
Rate data, wherein the fluctuating power data meet accumulated probability distribution function；
According to the fluctuating power data, calculating the composite phase change energy-storing microgrid whole year goes out activity of force, obtains the scene collection
It closes.
5. composite phase change energy-storing microgrid configuration method according to claim 3, which is characterized in that establish the fluctuation probability
The method of distribution function, comprising:
According to the historical data, the wind-power electricity generation, the photovoltaic power generation and the load are described using beta distribution and occurred
The probability density distribution of fluctuation obtains the fluctuation probability-distribution function.
6. composite phase change energy-storing microgrid configuration method according to claim 3, which is characterized in that according to the fluctuation probability
Distribution function carries out scene reduction, the method for obtaining the revised scene set to the combine scenes set, comprising:
The scene difference in the combine scenes set between any two scene is calculated according to the fluctuation probability-distribution function
Degree, obtains the smallest two scenes of diversity factor in the combine scenes set；
The smallest two scenes of diversity factor in the combine scenes set are merged, the combine scenes after being merged
Set；
Above-mentioned two step is repeated, until the scene number in the combine scenes set is reduced to preset value, is corrected
The scene set afterwards.
7. composite phase change energy-storing microgrid configuration method according to claim 6, which is characterized in that the scene diversity factor
Calculation method, comprising:
The fluctuation probability-distribution function is integrated, obtains any two scene in the combine scenes set
Probability of occurrence；
The product for calculating the Euclidean distance between the probability of occurrence and any two scene obtains the scene difference
Degree.
8. composite phase change energy-storing microgrid configuration method according to claim 1, which is characterized in that the life cycle management at
This includes installation cost, maintenance cost, operating cost and the transaction cost of various kinds of equipment in the composite phase change energy-storing microgrid,
Described in the equipment installed in composite phase change energy-storing microgrid include wind-driven generator, photovoltaic generator, non-renewable energy resources power generation
Machine and phase-change accumulation energy system.
9. composite phase change energy-storing microgrid configuration method according to claim 1, which is characterized in that described according to described compound
The overall life cycle cost of phase-change accumulation energy microgrid is established the microgrid Optimized model and is arranged before the constraint condition,
Include:
Establish the self-balancing figureofmerit, redundancy figureofmerit and renewable energy utilization rate index of the composite phase change energy-storing microgrid.
10. composite phase change energy-storing microgrid configuration method according to claim 9, which is characterized in that the constraint condition packet
Include microgrid configuration constraint, the microgrid configuration constraint is the self-balancing figureofmerit, the redundancy figureofmerit and described renewable
The lower limit of energy utilization rate index constrains.
11. composite phase change energy-storing microgrid configuration method according to claim 1, which is characterized in that the constraint condition packet
Include the operation constraint of microgrid phase-change accumulation energy system, the microgrid phase-change accumulation energy system operation constraint are as follows:
Wherein, HbtEnthalpy for the phase-change accumulation energy system in period t, HbFor the full enthalpy of the phase-change accumulation energy system,
WithThe charging and discharging power of the phase-change accumulation energy system heat pump respectively, ηcAnd ηdThe respectively described heat pump electricity turns the thermal efficiency
With the heat pump radiating efficiency, Δ t is time interval, and φ is the phase-change accumulation energy system from heat liberation rate, heat release rate,SOCWithPoint
Not Wei the phase-change accumulation energy system minimum and maximum heat accumulation state, SOC be the phase-change accumulation energy system period t heat accumulation shape
State.
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| CN113824137A (en) * | 2021-10-09 | 2021-12-21 | 深圳供电局有限公司 | Scheduling method and device of hybrid energy storage system and storage medium |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103715688A (en) * | 2014-01-10 | 2014-04-09 | 国家电网公司 | Grid-connected micro-grid optimizing configuration method and device |
| CN108711868A (en) * | 2018-05-30 | 2018-10-26 | 西安理工大学 | It is a kind of meter and islet operation voltage security GA for reactive power optimization planing method |
| CN108734350A (en) * | 2018-05-17 | 2018-11-02 | 燕山大学 | A kind of independent method for solving with combined dispatching of the power distribution network containing micro-capacitance sensor |
| CN109995082A (en) * | 2019-04-17 | 2019-07-09 | 深圳供电局有限公司 | Meter and the building phase-change accumulation energy electric heating combined scheduling method of scene fluctuation |
| CN110046821A (en) * | 2019-04-19 | 2019-07-23 | 深圳供电局有限公司 | The electric heating combined scheduling method of phase-change accumulation energy wall system |
| CN110046766A (en) * | 2019-04-17 | 2019-07-23 | 广东电网有限责任公司电力调度控制中心 | A kind of cooperative optimization method of virtual plant and power distribution network |
-
2019
- 2019-09-30 CN CN201910942142.2A patent/CN110518637A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103715688A (en) * | 2014-01-10 | 2014-04-09 | 国家电网公司 | Grid-connected micro-grid optimizing configuration method and device |
| CN108734350A (en) * | 2018-05-17 | 2018-11-02 | 燕山大学 | A kind of independent method for solving with combined dispatching of the power distribution network containing micro-capacitance sensor |
| CN108711868A (en) * | 2018-05-30 | 2018-10-26 | 西安理工大学 | It is a kind of meter and islet operation voltage security GA for reactive power optimization planing method |
| CN109995082A (en) * | 2019-04-17 | 2019-07-09 | 深圳供电局有限公司 | Meter and the building phase-change accumulation energy electric heating combined scheduling method of scene fluctuation |
| CN110046766A (en) * | 2019-04-17 | 2019-07-23 | 广东电网有限责任公司电力调度控制中心 | A kind of cooperative optimization method of virtual plant and power distribution network |
| CN110046821A (en) * | 2019-04-19 | 2019-07-23 | 深圳供电局有限公司 | The electric heating combined scheduling method of phase-change accumulation energy wall system |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113824137A (en) * | 2021-10-09 | 2021-12-21 | 深圳供电局有限公司 | Scheduling method and device of hybrid energy storage system and storage medium |
| CN113824137B (en) * | 2021-10-09 | 2024-02-27 | 深圳供电局有限公司 | Scheduling method, device and storage medium of hybrid energy storage system |
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