CN114243678B - Comprehensive energy storage configuration scheme generation method and system for photovoltaic power station - Google Patents
Comprehensive energy storage configuration scheme generation method and system for photovoltaic power station Download PDFInfo
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/28—Arrangements for balancing of the load in a network by storage of energy
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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
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- 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
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- G06Q10/06312—Adjustment or analysis of established resource schedule, e.g. resource or task levelling, or dynamic rescheduling
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- G—PHYSICS
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
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- 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
- H02J3/008—Circuit arrangements for ac mains or ac distribution networks involving trading of energy or energy transmission rights
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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
- H02J3/32—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/381—Dispersed generators
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02S—GENERATION OF ELECTRIC POWER BY CONVERSION OF INFRARED RADIATION, VISIBLE LIGHT OR ULTRAVIOLET LIGHT, e.g. USING PHOTOVOLTAIC [PV] MODULES
- H02S10/00—PV power plants; Combinations of PV energy systems with other systems for the generation of electric power
- H02S10/20—Systems characterised by their energy storage means
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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
- 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
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- 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]
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- H—ELECTRICITY
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- 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
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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- 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
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- Y02E40/00—Technologies for an efficient electrical power generation, transmission or distribution
- Y02E40/70—Smart grids as climate change mitigation technology in the energy generation sector
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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
The invention belongs to the technical field of photovoltaic power generation and energy storage, and provides a comprehensive energy storage configuration scheme generation method and system for a photovoltaic power station. The method comprises the steps of obtaining parameters of a photovoltaic power station; the photovoltaic power station parameters comprise distributed virtual energy storage parameters, centralized energy storage parameters, distributed virtual energy storage compensation parameters and supplementary power interval values; based on the obtained photovoltaic power station parameters, the energy overflow rate and the energy storage annual average cost are used as an optimized objective function, the limitation of the normal operation rate of the centralized energy storage in the normal operation state of the centralized energy storage in the whole year is measured, the energy storage configuration of the photovoltaic power station is optimized by adopting an immune algorithm, and a centralized and distributed virtual energy storage collaborative configuration scheme of the photovoltaic power station is obtained.
Description
Technical Field
The invention belongs to the technical field of photovoltaic power generation and energy storage, and particularly relates to a comprehensive energy storage configuration scheme generation method and system of a photovoltaic power station.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
In the grid system, the increase of photovoltaic power stations brings challenges to the stability of grid dispatching and the smoothness of power curves. Corresponding energy storage devices can be selectively added in the photovoltaic power station, so that the target requirements of the temperature property and the power curve smoothness of power grid dispatching can be met.
For the configuration method of energy storage in the photovoltaic power station, the inventor finds that the existing configuration method generally adopts a centralized energy storage device near the station to realize the configuration scheme, takes reliability as a limiting condition and takes economy as a configuration target, mainly focuses on the economy of the final configuration scheme, does not consider the functions exerted by virtual energy storage such as controllable load and the like, and does not consider the coordination of energy storage in different forms, thus the cost of the energy storage configuration scheme of the photovoltaic power station is high, and only economic operation is considered, but only tiny deviation of the reliability is ignored, so that the impact can be caused to the power grid, and the stable operation of the power grid is influenced.
Disclosure of Invention
In order to solve the technical problems in the background art, the invention provides a method and a system for generating a comprehensive energy storage configuration scheme of a photovoltaic power station, which comprehensively consider the synergistic effect of centralized and distributed virtual energy storage, can reduce the cost of the energy storage configuration scheme and improve the stable operation of a power grid.
In order to achieve the above purpose, the present invention adopts the following technical scheme:
a first aspect of the present invention provides a method for generating a comprehensive energy storage configuration scheme of a photovoltaic power plant, comprising:
acquiring parameters of a photovoltaic power station; the photovoltaic power station parameters comprise distributed virtual energy storage parameters, centralized energy storage parameters, distributed virtual energy storage compensation parameters and supplementary power interval values;
based on the obtained photovoltaic power station parameters, the energy overflow rate and the energy storage annual average cost are used as an optimized objective function, the limitation of the normal operation rate of the centralized energy storage in the normal operation state of the centralized energy storage in the whole year is measured, the energy storage configuration of the photovoltaic power station is optimized by adopting an immune algorithm, and a centralized and distributed virtual energy storage collaborative configuration scheme of the photovoltaic power station is obtained.
A second aspect of the present invention provides a comprehensive energy storage configuration scheme generation system for a photovoltaic power plant, comprising:
the parameter acquisition module is used for acquiring parameters of the photovoltaic power station; the photovoltaic power station parameters comprise distributed virtual energy storage parameters, centralized energy storage parameters, distributed virtual energy storage compensation parameters and supplementary power interval values;
the energy storage collaborative configuration module is used for measuring the limitation of the normal working rate of the centralized energy storage in the normal working state of the centralized energy storage in the whole year by taking the energy overflow rate and the average cost of the energy storage year as the optimized objective function based on the acquired parameters of the photovoltaic power station, optimizing the energy storage configuration of the photovoltaic power station by adopting an immune algorithm, and obtaining a centralized and distributed virtual energy storage collaborative configuration scheme of the photovoltaic power station.
A third aspect of the invention provides a computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps in a method of generating a comprehensive energy storage configuration scheme for a photovoltaic power plant as described above.
A fourth aspect of the invention provides a computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps in a method of generating a comprehensive energy storage configuration scheme for a photovoltaic power plant as described above when the program is executed.
Compared with the prior art, the invention has the beneficial effects that:
(1) Based on the existing centralized energy storage configuration, the invention introduces a related strategy of distributed virtual energy storage, replaces part of centralized energy storage capacity configuration, further reduces the cost of the energy storage configuration scheme, and simultaneously improves the management efficiency of the load side due to the distributed virtual energy storage.
(2) According to the invention, in the scheme optimizing process, the target function considers the energy overflow rate, the constraint condition uses the centralized energy storage normal working rate of the centralized energy storage in a normal working state all the year round, so that the photovoltaic power station can ensure good working condition when the energy storage is set and put into operation, but the impact on the power grid possibly caused by small deviation of the reliability is ignored by considering only economic operation, and the stable operation of the power grid is ensured.
Additional aspects of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the invention.
FIG. 1 is a virtual energy storage based on a power spring in accordance with an embodiment of the present invention;
FIG. 2 is a schematic diagram of an optical storage combination system according to an embodiment of the present invention;
FIG. 3 is a flowchart of an immunization algorithm according to an embodiment of the invention;
FIG. 4 is a graph comparing performance before and after a distributed virtual energy storage input according to an embodiment of the present invention;
FIG. 5 (a) is a graph comparing the normal operating rate of centralized energy storage with and without the distributed virtual energy storage scheme according to the embodiment of the present invention;
fig. 5 (b) is a graph comparing the energy overflow rate of a scheme taking into account distributed virtual energy storage with a scheme not taking into account distributed energy storage according to an embodiment of the present invention.
Detailed Description
The invention will be further described with reference to the drawings and examples.
It should be noted that the following detailed description is illustrative and is intended to provide further explanation of the invention. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the present invention. As used herein, the singular is also intended to include the plural unless the context clearly indicates otherwise, and furthermore, it is to be understood that the terms "comprises" and/or "comprising" when used in this specification are taken to specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof.
Example 1
In this embodiment, the centralized energy storage is a real battery energy storage device. The distributed virtual energy storage is a distributed controllable load. The distributed controllable load comprises electric elements of illumination facilities, ovens, dish washers, dryers and the like in residential areas, which are dispersed with each other and have no energy storage effect, but can achieve the effect similar to a part of energy storage structure through regulation and control, so the distributed controllable load is regarded as distributed virtual energy storage, and the distributed virtual energy storage is shown in the figure 2.
In order to improve the operation strategy of the centralized energy storage after the configuration scheme, reduce unnecessary charge and discharge times, avoid the phenomenon of overcharge and overdischarge, and fully utilize the advantages of both the centralized energy storage and the distributed controllable load virtual energy storage. The configuration scheme introduces the concept of a power spring, namely a concept distributed virtual energy storage concept, and combines the concept with centralized battery energy storage as shown in fig. 1, so that the comprehensive energy storage configuration scheme generation method of the photovoltaic power station is provided.
Specifically, the embodiment provides a method for generating a comprehensive energy storage configuration scheme of a photovoltaic power station, which specifically comprises the following steps:
step 1: acquiring parameters of a photovoltaic power station; the photovoltaic power station parameters comprise distributed virtual energy storage parameters, centralized energy storage parameters, distributed virtual energy storage compensation parameters and supplementary power interval values.
Wherein, photovoltaic power plant parameters are as shown in table 1:
table 1 photovoltaic power plant parameters
In specific implementation, data of a certain Qinghai photovoltaic power station actually operated for one year is used as sample data, and an actual scheme of energy storage configuration is calculated. The values of the above photovoltaic power plant parameters are shown in table 2:
table 2 photovoltaic power plant parameter assignment
Step 2: based on the obtained photovoltaic power station parameters, the energy overflow rate and the energy storage annual average cost are used as an optimized objective function, the limitation of the normal operation rate of the centralized energy storage in the normal operation state of the centralized energy storage in the whole year is measured, the energy storage configuration of the photovoltaic power station is optimized by adopting an immune algorithm, and a centralized and distributed virtual energy storage collaborative configuration scheme of the photovoltaic power station is obtained.
The distributed virtual energy storage is essentially a controllable load at the load end, and is regarded as the distributed virtual energy storage because of its distributed form and controllable size, and the specific structure is shown in fig. 2.
The non-critical load is a load with lower requirement on voltage quality, and can bear voltage fluctuation to a certain extent, including lighting facilities, ovens, dish washers, dryers and the like; the control loop calculates and obtains the modulation signal V of the inverter according to the dispatching requirement of the upper level ES-order The method comprises the steps of carrying out a first treatment on the surface of the The voltage source type rectifier is responsible for converting bus voltage into stable direct current voltage; the voltage source type inverter is responsible for the voltage according to V ES-order Converting DC voltage into power spring output voltage V ES ；C d A direct current side capacitor of the power spring; l (L) f And C f The filter inductance and the filter capacitance are respectively; i ES Outputting current for the power spring; v (V) NC Is a non-critical load voltage.
In this embodiment, the functions that the distributed virtual energy storage can play are embodied (equivalently, how large-scale the centralized battery energy storage is), and the mathematical modeling of the power spring is as follows:
wherein P' is the power consumed by the virtual energy storage unit when the virtual energy storage control loop is started; p is the power consumed by the virtual energy storage unit when the virtual energy storage control loop is not started;is the impedance angle; ΔP is the active output model, ΔP>0 represents virtual energy storage charging, ΔP<0 represents a virtual energy storage discharge; z is Z NC Is a non-critical load impedance; v (V) ES Outputting voltage for the power spring when the virtual energy storage control loop is not started; v (V) NC Is the voltage of the critical load, which should be equal to the bus voltage V S 。
With energy overflow rate (Energy Spill Rate, ESR) and annual average cost of energy storage (Levelized Cost of Using Storage of Year, LCUS) Y ) As an objective function of optimization, a weighted centralized energy storage (such as: battery) is limited by the normal operating rate (Battery Normal Operation Rate, BNOPR) of the centralized energy storage that is in normal operation throughout the year.
The following specific formulas are given by taking a battery as an example for centralized energy storage:
energy overflow rate ESR:
at the ith time of system operation, battery charge energy ΔE ch (i) The method comprises the following steps:
ΔE ch (i)＝(W PV (i)-Q L (i))γ (2)
w in the formula PV (i) For the energy generated by the photovoltaic power station at the ith moment, Q L (i) The load is at the i-th time, and γ is the charging efficiency of the battery.
After this time, the total energy in the battery is of the size:
E B (i+1)＝ΔE(i)+E B (i) (3)
in E B (i+1)、E B (i) The energy levels of the battery at the i+1 and i times are respectively.
At this time, it is matched with the upper limit value E of the available energy range of the battery B-h Comparison, if E B (i+1)<E B-h The battery is still in charge and instead the battery capacity is full and the energy is lost by the overflow.
In summary, the formula for ESR is:
in the middle ofTo accumulate the symbols, i is accumulated from time 1 to time n, M ESR Is an energy overflow sign.
Annual average of energy storageThe LCUS Y ：
Wherein Y refers to the specified service life, costs initial Refers to the initial construction cost of energy storage, cost operating Refers to the subsequent operation and maintenance cost of energy storage,refers to how much energy is co-released during the operational life of the energy storage device.
It should be noted that the cost calculated here is applicable to any energy storage device, so the energy storage is not replaced by a battery here.
The cost calculation formula designed in the formula is as follows:
considering the time value of funds, costs initial Can be expressed as:
cost initial ＝C(r,n)(C P P ESS +C E E ESS ) (7)
wherein r is a reference discount rate; n is the term (life) of the energy storage operation, C (r, n) is an equal annual coefficient, P ESS 、E ESS Respectively the power and the capacity of energy storage; c (C) P 、C E Unit investment of power and capacity of the stored energy respectively.
To facilitate practical application in engineering, cost operating Generally estimated approximately in proportion to the initial investment, i.e.
cost operating ＝μcost initial (8)
Wherein: μ is the running maintenance cost coefficient of the stored energy.
Battery normal operation rate BNOPR:
at the ith moment, the unbalanced capacity E (i) of the system is:
E(i)＝W PV (i)-Q L (i)+E B (i) (9)
at this time, if E (i) >0, the system power can meet the load demand, and conversely, the optical storage system is in the power failure state and cannot work normally.
M is recorded BNOPR For the working state of the system at this moment, then:
the energy storage device used in this embodiment is a battery for energy storage, and its mathematical model is as follows:
E B (i+1)＝min{E B (i)+[W PV (i)-Q L (i)]γ(i),E B-h } (11)
E B (i+1)＝max{E B (i)+[W PV (i)-Q L (i)]/η out ,0} (12)
in eta out Is the discharge efficiency of the battery.
To take into account the objective function f of distributed energy storage 1 ：
min f 1 ＝φ+C m (13)
Where φ is the penalty function of BNOPR:
wherein beta is a specific value set according to actual running conditions, and is represented by the formula [0,1]Inside (typically greater than 0.5). C (C) m For multi-objective optimization, ESR and LCUS are combined Y The comprehensive consideration is that:
C m ＝ω 1 ESR+ω 2 LCUS Y (15)
omega in 1 、ω 2 Respectively, the energy overflow rate ESR and the energy storage annual average use cost LCUS Y Weight coefficient of (c) in the above-mentioned formula (c).
At the moment, the concept of the power spring is introduced, and the power spring-based distributed virtual energy storage and photo-electricity generation system is established, so that the cooperation of the power spring-based distributed virtual energy storage and photo-electricity generation system and the centralized battery-operated energy storage is considered. The objective function after the introduction of the distributed energy storage is modified as follows:
the optimized objective function is f 2 ：
Wherein phi is a punishment function of the normal working rate of the centralized energy storage; n' B Equivalent battery number for distributed virtual energy storage, E B-h The upper limit value of the energy interval available for centralized energy storage;the final calculation result of (2) is equivalent power; p is p c And compensation is provided for users participating in virtual energy storage regulation.
And according to the comparison result of the equivalent power and the supplementary power interval value, providing corresponding compensation for users participating in virtual energy storage regulation and control in a segmented manner.
Specifically, p c The expression of the compensation provided for the user participating in the virtual energy storage regulation is as follows:
p in the formula 1 、P 2 、P 3 When the total load power participating in virtual energy storage regulation is smaller than P 1 At the time, the compensation price is p c_1 meta/W; when it is between P 1 And P 2 When in between, the compensation price is p c_2 meta/W; when it is between P 2 And P 3 When in between, the compensation price is p c_3 meta/W; when it is greater than P 3 At the time, the compensation price is p c_4 meta/W.
The equivalent total capacity E of the final energy storage configuration is corrected Total (S) The method comprises the following steps:
E′ B +E″ B ＝E total (S) (18)
E″ B ＝N″ B ×E B-h (19)
In E' B For the capacity of centralized battery energy storage E B And the equivalent battery energy storage capacity is realized for distributed virtual energy storage.
Corrected equivalent total power P of final energy storage configuration Total (S) The method comprises the following steps:
P′ B +P″ B ＝P total (S) (20)
In P' B Power stored by centralized battery, P B And (5) equivalent battery energy storage power for distributed virtual energy storage.
It should be noted that the capacity and power provided by the distributed virtual energy storage are only needed to provide a small amount of assistance to the user at a certain scale of controllable load on the load side, and the reason for further reduction of the cost is that.
As shown in fig. 3, the process of optimizing the energy storage configuration of the photovoltaic power station by adopting the immune algorithm is as follows:
step a: determining an optimized objective function based on the energy overflow rate and the average cost of energy storage year to obtain an antigen;
step b: based on the optimized objective function corresponding to the antigen and the obtained photovoltaic power station parameters, obtaining an initial random solution of the optimized objective function, namely generating an initial antibody;
step c: calculating the affinity between the antibodies and the antigen;
antibody-antigen affinity A v
Where F is the minimum value of the objective function value corresponding to v, that is, A v The larger the moreRetention is desirable.
Affinity between antibodies S v,s
Wherein k is v,s Is the number of identical positions of two antibodies v, s, L is the antibody length.
Step d: judging whether a termination condition is met or not based on the affinity of the antibodies and the antigens and the affinity between the antibodies and a corresponding preset threshold value, and if so, obtaining an optimizing configuration result; otherwise, continuing iteration;
antibody concentration Cv
Wherein aff () is the Euclidean distance between antibody vectors, N is the total number of antibody genes, δs is a given specific value, and ab represents the genes on the antibody.
Desired reproduction rate
Wherein a is the weight value and the value range is [0,1].
Step e: and (3) calculating the concentration and the excitation degree of the antibody, performing immune treatment, updating the antibody to form a new population, returning to the step (c), and recalculating the affinity between the antibody and the antigen and the affinity between the antibodies to judge whether the termination condition is met.
And (3) calculating the configuration scheme under the objective function by using the formulated objective function formula (13) without adding the configuration scheme of the distributed virtual energy storage, and comparing the configuration scheme under the objective function with the index parameters in the evaluation system given by the configuration scheme with adding the distributed virtual energy storage, and checking whether the system reliability is basically consistent with the pure centralized battery energy storage after the centralized and distributed virtual energy storage are cooperated.
The algorithm optimization of the energy storage configuration scheme is carried out according to the parameters given in the table, and the configuration result is shown in the table 3:
table 3 optimal configuration scheme (distributed virtual energy storage)
Table 4 optimal configuration scheme (without distributed virtual energy storage)
Performance comparisons before and after addition of the distributed virtual energy storage are shown in fig. 4, 5 (a) and 5 (b). As can be seen from fig. 4, table 3 and table 4, the energy storage cost is obviously reduced under the condition of comparable performance of the scheme taking the distributed virtual energy storage into consideration and the scheme taking no consideration of the distributed energy storage, and it can be proved that the synergy of the centralized virtual energy storage and the distributed virtual energy storage can complete the improvement of the economical aspect under the condition of ensuring the reliability.
As can be seen from fig. 4, fig. 5 (a) and fig. 5 (b), under the condition of the same input cost, the relative performance of adding the distributed virtual energy storage is more excellent, and the energy storage configuration scheme of the centralized battery energy storage and the distributed virtual energy storage (namely, the load side controllable load) provided by the patent is proved to be more excellent in performance.
Example two
The embodiment provides a comprehensive energy storage configuration scheme generation system of a photovoltaic power station, which comprises the following components:
the parameter acquisition module is used for acquiring parameters of the photovoltaic power station; the photovoltaic power station parameters comprise distributed virtual energy storage parameters, centralized energy storage parameters, distributed virtual energy storage compensation parameters and supplementary power interval values;
the energy storage collaborative configuration module is used for measuring the limitation of the normal working rate of the centralized energy storage in the normal working state of the centralized energy storage in the whole year by taking the energy overflow rate and the average cost of the energy storage year as the optimized objective function based on the acquired parameters of the photovoltaic power station, optimizing the energy storage configuration of the photovoltaic power station by adopting an immune algorithm, and obtaining a centralized and distributed virtual energy storage collaborative configuration scheme of the photovoltaic power station.
In a specific implementation, in the energy storage collaborative configuration module, the optimized objective function is f 2 ：
C m ＝ω 1 ESR+ω 2 LCUS Y
Wherein phi is a punishment function of the normal working rate of the centralized energy storage; omega 1 、ω 2 Respectively, the energy overflow rate ESR and the energy storage annual average use cost LCUS Y Weight coefficient of (2); n' B Equivalent battery number for distributed virtual energy storage, E B-h The upper limit value of the energy interval available for centralized energy storage;the final calculation result of (2) is equivalent power; p is p c And compensation is provided for users participating in virtual energy storage regulation.
It should be noted that, each module in the embodiment corresponds to each step in the first embodiment one to one, and the implementation process is the same, which is not described here.
Example III
The present embodiment provides a computer-readable storage medium, on which a computer program is stored, which when being executed by a processor, implements the steps in the method for generating a comprehensive energy storage configuration scheme of a photovoltaic power plant as described in the above embodiment one.
Example IV
The present embodiment provides a computer device, including a memory, a processor, and a computer program stored in the memory and capable of running on the processor, where the processor executes the program to implement the steps in the method for generating the comprehensive energy storage configuration scheme of the photovoltaic power plant according to the foregoing embodiment.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of a hardware embodiment, a software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, magnetic disk storage, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Those skilled in the art will appreciate that implementing all or part of the above-described methods in accordance with the embodiments may be accomplished by way of a computer program stored on a computer readable storage medium, which when executed may comprise the steps of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), or the like.
The above description is only of the preferred embodiments of the present invention and is not intended to limit the present invention, but various modifications and variations can be made to the present invention by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (8)
1. The method for generating the comprehensive energy storage configuration scheme of the photovoltaic power station is characterized by comprising the following steps of:
acquiring parameters of a photovoltaic power station; the photovoltaic power station parameters comprise distributed virtual energy storage parameters, centralized energy storage parameters, distributed virtual energy storage compensation parameters and supplementary power interval values;
based on the obtained photovoltaic power station parameters, taking the energy overflow rate and the energy storage annual average cost as an optimized objective function, measuring the limitation of the normal operation rate of the centralized energy storage in the normal operation state of the centralized energy storage all the year round, and adopting an immune algorithm to perform optimizing configuration on the energy storage configuration of the photovoltaic power station to obtain a centralized and distributed virtual energy storage collaborative configuration scheme of the photovoltaic power station;
the optimized objective function is f 2 ：
C m ＝ω 1 ESR+ω 2 LCUS Y
Wherein phi is a punishment function of the normal working rate of the centralized energy storage; omega 1 、ω 2 Respectively, the energy overflow rate ESR and the energy storage annual average use cost LCUS Y Weight coefficient of (2); n' B Equivalent battery number for distributed virtual energy storage, E B-h The upper limit value of the energy interval available for centralized energy storage;the final calculation result of (2) is equivalent power; p is p c And compensation is provided for users participating in virtual energy storage regulation.
2. The method for generating the comprehensive energy storage configuration scheme of the photovoltaic power station according to claim 1, wherein corresponding compensation is provided for users participating in virtual energy storage regulation in a segmented manner according to a comparison result of the equivalent power and the supplementary power interval value.
3. The method for generating the comprehensive energy storage configuration scheme of the photovoltaic power station according to claim 1, wherein the process of optimizing the energy storage configuration of the photovoltaic power station by adopting an immune algorithm is as follows:
determining an optimized objective function based on the energy overflow rate and the average cost of energy storage year to obtain an antigen;
based on the optimized objective function corresponding to the antigen and the obtained photovoltaic power station parameters, obtaining an initial random solution of the optimized objective function, namely generating an initial antibody;
calculating the affinity between the antibodies and the antigen;
judging whether a termination condition is met or not based on the affinity of the antibodies and the antigens and the affinity between the antibodies and a corresponding preset threshold value, and if so, obtaining an optimizing configuration result; otherwise, continuing iteration;
and calculating the concentration and the excitation degree of the antibody, performing immune treatment, updating the antibody to form a new population, and recalculating the affinity between the antibody and the antigen and the affinity between the antibodies to judge whether the termination condition is met.
4. The method of generating a comprehensive energy storage configuration scheme for a photovoltaic power plant of claim 1, wherein the centralized energy storage is a real battery energy storage device.
5. The method of generating a comprehensive energy storage configuration scheme for a photovoltaic power plant of claim 1, wherein the distributed virtual energy storage is a distributed controllable load.
6. A comprehensive energy storage configuration scheme generation system for a photovoltaic power plant, comprising:
the parameter acquisition module is used for acquiring parameters of the photovoltaic power station; the photovoltaic power station parameters comprise distributed virtual energy storage parameters, centralized energy storage parameters, distributed virtual energy storage compensation parameters and supplementary power interval values;
the energy storage collaborative configuration module is used for measuring the limitation of the normal working rate of the centralized energy storage in the normal working state of the centralized energy storage in the whole year by taking the energy overflow rate and the average cost of the energy storage year as the optimized objective function based on the acquired parameters of the photovoltaic power station, and optimizing the energy storage configuration of the photovoltaic power station by adopting an immune algorithm to obtain a centralized and distributed virtual energy storage collaborative configuration scheme of the photovoltaic power station;
in the energy storage collaborative configuration module, the optimized objective function is f 2 ：
C m ＝ω 1 ESR+ω 2 LCUS Y
Wherein phi is a punishment function of the normal working rate of the centralized energy storage; omega 1 、ω 2 Respectively, the energy overflow rate ESR and the energy storage annual average use cost LCUS Y Weight coefficient of (2); n' B Equivalent battery number for distributed virtual energy storage, E B-h The upper limit value of the energy interval available for centralized energy storage;the final calculation result of (2) is equivalent power; p is p c And compensation is provided for users participating in virtual energy storage regulation.
7. A computer readable storage medium, on which a computer program is stored, characterized in that the program, when being executed by a processor, realizes the steps in the method for generating a comprehensive energy storage configuration scheme of a photovoltaic power plant according to any one of claims 1-5.
8. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the steps in the method for generating a comprehensive energy storage configuration scheme of a photovoltaic power plant according to any of claims 1-5 when the program is executed.
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