CN112736943A - Energy storage power station internal structure optimization method and system for reducing loss capacity - Google Patents
Energy storage power station internal structure optimization method and system for reducing loss capacity Download PDFInfo
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Abstract
The invention relates to an energy storage power station internal structure optimization method and system for reducing loss capacity, wherein the method comprises the following steps: acquiring an optimal arrangement scheme of storage batteries in the energy storage power station by taking the minimum loss capacity of the energy storage power station as a target; arranging the storage batteries in the energy storage power station by using the optimal arrangement scheme of the storage batteries in the energy storage power station; according to the technical scheme provided by the invention, under the condition of considering the failure probability model of each unit of the energy storage power station, the arrangement structure of each element in the energy storage power station is optimized, so that the aim of minimizing the overall loss capacity of the energy storage power station is fulfilled, and the problem of other system failures caused by the loss capacity of the energy storage power station is greatly reduced.
Description
Technical Field
The invention relates to the field of internal structure arrangement of energy storage power stations, in particular to an internal structure optimization method and system for an energy storage power station, which can reduce loss capacity.
Background
With the continuous development of energy storage technology, the advantages of energy storage power stations, such as flexible output adjustment, artificial control of response speed of energy storage power stations, and bidirectional charging and discharging, are gradually revealed, and with the gradual increase of the grid-connected capacity of various forms of energy storage power stations in a power grid, the energy storage power stations play an important role on the power supply side. However, as a new technology, especially for an energy storage power station using a storage battery as a main power source, there is a risk that a failure rate is uncertain, that is, inherent failure rates of storage batteries, converters and cable connection elements inside the power station will bring a great challenge to power supply reliability of the power station, which may cause a problem that a loss power supply capacity of the energy storage power station cannot be guaranteed and other system failures are brought.
At present, the research on the structural optimization of the energy storage power station at home and abroad usually focuses on the research on the optimization design of the whole capacity of the energy storage power station and the optimization of the site selection thereof, but the understanding of the failure rate of the energy storage power station is less, namely, the fault rate modeling and fault identification are only limited to single elements such as storage batteries or cables and the like in the energy storage power station, the modeling analysis of the integral fault rate of the energy storage power station is lacked, moreover, aiming at the control problem of the overall failure rate of the energy storage power station, no effective technical improvement or optimization scheme is provided for reducing the overall loss capacity of the energy storage power station, the arrangement structure of the internal elements of the energy storage power station can generate great influence on the loss capacity of the energy storage power station, the detailed arrangement requirement on the internal elements of the power station is lacked at present, that is, how to reduce the loss capacity by optimizing the structure of the energy storage power station body is not considered.
Disclosure of Invention
Aiming at the defects of the prior art, the invention aims to provide an energy storage power station internal structure optimization method for reducing loss capacity, which can achieve the aim of minimizing the overall loss capacity of an energy storage power station by optimizing the arrangement structure of each element in the energy storage power station under the condition of considering a failure probability model of each unit of the energy storage power station, and greatly alleviate the problem of other system failures caused by the loss capacity of the energy storage power station.
The purpose of the invention is realized by adopting the following technical scheme:
the invention aims to provide an energy storage power station internal structure optimization method for reducing loss capacity, and the improvement is that the method comprises the following steps:
acquiring an optimal arrangement scheme of storage batteries in the energy storage power station by taking the minimum loss capacity of the energy storage power station as a target;
arranging the storage batteries in the energy storage power station by using the optimal arrangement scheme of the storage batteries in the energy storage power station;
wherein the arrangement scheme comprises: the number of the arranged rows and the number of the arranged columns of the battery units and the number of the batteries in each battery unit.
Preferably, the obtaining of the optimal arrangement scheme of the storage batteries in the energy storage power station with the minimum loss capacity of the energy storage power station as a target includes:
establishing an optimization model of an arrangement scheme of storage batteries in the energy storage power station by taking the minimum loss capacity of the energy storage power station as a target;
and solving the configuration scheme optimization model of the storage batteries in the energy storage power station to obtain the optimal configuration scheme of the storage batteries in the energy storage power station.
Further, an objective function in an optimization model of the arrangement scheme of the storage batteries in the energy storage power station is determined according to the following formula:
in the above formula, B is the loss capacity of the energy storage power station, FsumIs the failure rate of the battery system components, lambda is the failure rate of the cable components,
is the failure rate of the transformer element, SvFor presetting the total capacity, S, of the energy storage power stationcIs the total capacity of the battery system components.
Further, the failure rate F of the battery system components is determined as followssum：
Fsum＝[1-(1-e-στ)a]b
In the above equation, σ is a failure rate of a single battery, τ is a failure time interval of a single battery, e is a natural constant, a is the number of rows of the battery cells arranged, and b is the number of columns of the battery cells arranged.
Further, the failure rate λ of the cable element is determined according to the following formula:
in the above formula, λNNumber of faults of cable, TeTo expose time of the faulty line, l is the length of the cable.
Further, the failure rate of the transformer element is determined as follows
In the above formula, Ps(t) is the number of failures of the transformer in the period t, Ps(T +1) is the failure frequency of the transformer in the T +1 time period, delta T is the time interval of the adjacent time periods, T is the total time period, and T belongs to [1, T ∈]。
Further, the constraint conditions in the internal structure optimization model of the energy storage power station include:
determining the capacity constraint condition of the energy storage power station according to the following formula:
in the above formula, SvFor presetting the total capacity, S, of the energy storage power stationiThe capacity of the ith battery in the battery system element is represented by a, b and k, wherein a is the number of the arranged rows of the battery cells, k is the number of the batteries in each battery cell, and i belongs to [1, abk ]]；
Determining battery system component output constraints as follows:
Pmin≤P≤Pmax
in the above formula, PminLower limit of output of battery system components, PmaxThe output limit of the storage battery is P, and the output of the storage battery system element is P;
the cable transmission power constraint is determined as follows:
Qmin≤Q≤Qmax
in the above formula, QminFor lower limits of cable transmission power, QmaxAnd Q is the power transmitted by the cable.
Preferably, the arranging the storage batteries in the energy storage power station by using the optimal arrangement scheme of the storage batteries in the energy storage power station includes:
respectively connecting the tail ends of the feeder cables in the a' storage battery unit branches to a grid connection point of an energy storage power station;
the branch of the storage battery units consists of b' storage battery units connected to a feeder cable;
the battery cell includes: k' storage batteries and corresponding ac/dc converters and isolation transformers;
the k storage batteries are respectively connected with the low-voltage alternating current end of the isolation transformer through the corresponding ac/dc converters, and the medium-voltage alternating current end of the isolation transformer is connected into a feeder cable;
a ' is the number of the arrangement rows of the storage battery units in the optimal arrangement scheme, b ' is the number of the arrangement columns of the storage battery units in the optimal arrangement scheme, and k ' is the number of the storage batteries in each storage battery unit in the optimal arrangement scheme.
Based on the same inventive concept, the invention also provides an energy storage power station internal structure optimization system for reducing loss capacity, and the improvement is that the system comprises:
an acquisition module: the method comprises the steps of obtaining an optimal arrangement scheme of storage batteries in the energy storage power station by taking the minimum loss capacity of the energy storage power station as a target;
an arrangement module: the system is used for arranging the storage batteries in the energy storage power station by using the optimal arrangement scheme of the storage batteries in the energy storage power station;
wherein the arrangement scheme comprises: the number of the arranged rows and the number of the arranged columns of the battery units and the number of the batteries in each battery unit.
Preferably, the obtaining module is specifically configured to:
establishing an optimization model of an arrangement scheme of storage batteries in the energy storage power station by taking the minimum loss capacity of the energy storage power station as a target;
and solving the configuration scheme optimization model of the storage batteries in the energy storage power station to obtain the optimal configuration scheme of the storage batteries in the energy storage power station.
Compared with the closest prior art, the invention has the following beneficial effects:
the technical scheme provided by the invention provides an energy storage power station internal structure optimization method and system for reducing loss capacity, and the method comprises the following steps of firstly, obtaining an optimal arrangement scheme of storage batteries in an energy storage power station by taking the minimum loss capacity of the energy storage power station as a target; then, the storage batteries in the energy storage power station are arranged by using the optimal arrangement scheme of the storage batteries in the energy storage power station; according to the scheme, under the condition that a fault probability model of each unit of the energy storage power station is considered, the arrangement structure of each element in the energy storage power station is optimized, the purpose of minimizing the overall loss capacity of the energy storage power station is achieved, and the problem of other system faults caused by the loss capacity of the energy storage power station is greatly reduced.
Drawings
FIG. 1 is a flow chart of a method for optimizing an internal structure of an energy storage power station for reducing loss capacity, provided by the invention;
FIG. 2 is a topological diagram of an internal structure of an energy storage power station in the embodiment of the invention;
FIG. 3 is a Wien diagram of an energy storage plant lost capacity objective function in an embodiment of the invention;
FIG. 4 is a schematic diagram of energy storage plant lost capacity as a function of parameters and time in an embodiment of the present invention;
fig. 5 is a schematic structural diagram of an internal structure optimization system of an energy storage power station for reducing loss capacity provided by the invention.
Detailed Description
The following describes embodiments of the present invention in further detail with reference to the accompanying drawings.
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Aiming at the defects of single fault rate modeling and fault identification, incapability of ensuring the loss capacity of the energy storage power station, high fault rate occurrence and the like in the prior art, the invention provides an internal structure optimization method of the energy storage power station for reducing the loss capacity, which comprises the steps of firstly sequentially establishing the internal structure of the energy storage power station and a, b, k and parameters to be optimized, selecting the model of each element to obtain an independent fault rate model of each element of the energy storage power station, and taking the minimum loss capacity of the energy storage power station as a target, establishing an energy storage power station loss capacity objective function related to a parameter a, a parameter b and a parameter k according to the idea of calculating the area of a Wien diagram, and referring to the constraint conditions, completing the modeling of an internal structure optimization model of the energy storage power station, finally calling a matlab/fmincon function to the optimization model for solving, and obtaining a final optimal a, b, k parameter result to complete the optimization design, specifically as shown in fig. 1, the method includes:
the method comprises the following steps that (1) an optimal arrangement scheme of storage batteries in the energy storage power station is obtained by taking the minimum loss capacity of the energy storage power station as a target;
arranging the storage batteries in the energy storage power station by using the optimal arrangement scheme of the storage batteries in the energy storage power station;
specifically, in the step (1), firstly, an optimization model of an arrangement scheme of storage batteries in the energy storage power station is established by taking the minimum loss capacity of the energy storage power station as a target;
in reality, when a certain single battery breaks down in energy storage power station battery system component, can make the total power output of energy storage power station battery system component reduce, when energy storage power station cable component breaks down, can make the battery that the cable is connected break off, thereby lead to the power output of energy storage power station battery system component to reduce, when energy storage power station grid connection point transformer component breaks down, can make the energy storage power station interrupt the power output of battery system component, from this it can to see, the change of the loss capacity of energy storage power station is relevant with the power output volume of energy storage power station battery system component, therefore, when each component of energy storage power station breaks down, the fault rate of each component has decided the size of energy storage power station total loss capacity.
In the embodiment provided by the invention, as shown in fig. 2, the loss capacity of the energy storage power station comprises the failure rates of three parts of elements, the failure rates of all the parts of elements are independent, and the minimization of the total loss capacity of the energy storage power station is the minimization of the area of a wien diagram. Based on the Weinn diagram, the overlapping Weinn diagram area of each element in the corresponding energy storage power station is calculated on the basis of an independent event according to the principle of probability addition and multiplication, then the overlapping Weinn diagram area is multiplied by the preset total capacity of the energy storage power station and the total capacity of the storage battery system elements respectively, and finally the minimum loss capacity of the energy storage power station can be obtained by adding.
When each element of the energy storage power station fails, the failure rate of each element determines the total loss capacity of the energy storage power station, so that the storage batteries in the energy storage power station need to be arranged according to the optimal a, b and k parameter arrangement scheme, the failure rate change of each element of the energy storage power station is minimum, and the purpose of minimizing the loss capacity of the energy storage power station is achieved.
Through the analysis, an objective function in an optimization model of the configuration scheme of the storage batteries in the energy storage power station can be obtained.
In the embodiment provided by the invention, the objective function in the optimization model of the arrangement scheme of the storage batteries in the energy storage power station can be determined according to the following formula:
in the above formula, B is the loss capacity of the energy storage power station, FsumIs the failure rate of the battery system components, lambda is the failure rate of the cable components,
is the failure rate of the transformer element, SvFor presetting the total capacity, S, of the energy storage power stationcIs the total capacity of the battery system components.
The invention providesIn an embodiment, the objective function in the optimization model of the arrangement scheme of the storage batteries in the energy storage power station is based on a probability theory addition principle and a multiplication principle, (F)sum+λ-Fsumλ)·SvRepresenting only the capacity lost in the event of a failure of the storage battery system components of the energy storage plant and of the cable components connected to the storage battery system components,
the sum of the formulas represents the lost capacity of the energy storage power station grid-connected point transformer, the storage battery system element and the cable element connected with the storage battery system element when the power station grid-connected point transformer, the storage battery system element and the cable element are in fault, and means that the total lost capacity of the energy storage power station changes along with the fault rate of each element in the energy storage power station.
Further, the failure rate F of the battery system components is determined as followssum：
Fsum＝[1-(1-e-στ)a]b
In the above equation, σ is a failure rate of a single battery, τ is a failure time interval of a single battery, e is a natural constant, a is the number of rows of the battery cells arranged, and b is the number of columns of the battery cells arranged.
The failure rate λ of the cable element is determined as follows:
in the above formula, λNNumber of faults of cable, TeTo expose time of the faulty line, l is the length of the cable.
Determining the failure rate of a transformer element by
In the above formula, Ps(t) is the transformer at tNumber of failures of a segment, Ps(T +1) is the failure frequency of the transformer in the T +1 time period, delta T is the time interval of the adjacent time periods, T is the total time period, and T belongs to [1, T ∈]。
In the embodiment provided by the invention, the constraint conditions in the internal structure optimization model of the energy storage power station comprise:
determining the capacity constraint condition of the energy storage power station according to the following formula:
in the above formula, SvFor presetting the total capacity, S, of the energy storage power stationiThe capacity of the ith battery in the battery system element is represented by a, b and k, wherein a is the number of the arranged rows of the battery cells, k is the number of the batteries in each battery cell, and i belongs to [1, abk ]]；
In the embodiment provided by the invention, for a specific energy storage power station, capacity size constraint exists, that is, the total capacity of the storage batteries contained in the specific energy storage power station is required to meet the total capacity requirement of the energy storage power station, so that the formula shows that the total capacity of the storage batteries arranged according to a multiplied by b multiplied by k is required to be equal to the set total capacity of the energy storage power station, and the constraint is equality constraint.
Determining battery system component output constraints as follows:
Pimin≤Pi≤Pimax
in the above formula, PiminLower limit of output of battery system components, PimaxIs the upper limit of the battery output, PiIs the output of a battery system component;
the cable transmission power constraint is determined as follows:
Qimin≤Qi≤Qimax
in the above formula, QiminFor lower limits of cable transmission power, QimaxUpper limit of cable transmission power, QiPower is transmitted for the cable.
In the embodiment provided by the invention, the transmission power of each line of the energy storage power station has a limit value, and each storage battery has upper and lower output limit constraints, so that the constraint conditions of the upper and lower output limits of the storage battery and the constraint conditions of the upper and lower cable transmission power limits can be obtained.
And based on the configuration scheme optimization model of the storage batteries in the energy storage power station, solving the configuration scheme optimization model of the storage batteries in the energy storage power station to obtain the optimal configuration scheme of the storage batteries in the energy storage power station.
In the embodiment provided by the invention, the optimal arrangement scheme of the storage batteries in the energy storage power station given by the step (1) considers the failure probability of each unit of the energy storage power station, and gives the optimal parameter selection of a, b and k, the step (2) in the technical scheme provided by the invention arranges the internal structure of the energy storage power station based on the optimal arrangement scheme, as shown in figure 3, firstly, the connection form of k groups of storage batteries and converters in each storage battery-converter unit is formed to realize the inversion output of electric energy, secondly, each storage battery-converter unit is arranged into the basic structure of a row and b columns in a row and column mode, then, the inversion output side of the storage battery-converter units of the a row and b columns is boosted through a transformer and then is sent to the energy storage power station grid connection point through a feeder cable, and finally, the boosting is sent to a high-voltage alternating-current transmission, specifically, the step (2) may include:
respectively connecting the tail ends of the feeder cables in the a' storage battery unit branches to a grid connection point of an energy storage power station;
the branch of the storage battery units consists of b' storage battery units connected to a feeder cable;
the battery cell includes: k' storage batteries and corresponding ac/dc converters and isolation transformers;
the k storage batteries are respectively connected with the low-voltage alternating current end of the isolation transformer through the corresponding ac/dc converters, and the medium-voltage alternating current end of the isolation transformer is connected into a feeder cable;
a ' is the number of the arrangement rows of the storage battery units in the optimal arrangement scheme, b ' is the number of the arrangement columns of the storage battery units in the optimal arrangement scheme, and k ' is the number of the storage batteries in each storage battery unit in the optimal arrangement scheme.
In the embodiment provided by the invention, the scheme can be verified in an application scene shown in fig. 4, and a schematic diagram of the change of the loss capacity of the energy storage power station along with the parameters a, b and time is given by taking k as an example to illustrate the advantages and meanings of the invention. In fig. 4, the vertical axis shows that the energy storage power station fault loss capacity is directly proportional to the total fault rate of the energy storage power station, and by taking the example that the lowest fault loss capacity is obtained when the optimization result a is 50 and b is 2, the optimal parameter combination can be obtained, and the maximum quantity of the fault loss capacity reduction percentage in the previous four years reaches 55.56%.
In summary, the method for optimizing the internal structure of the energy storage power station for reducing the loss capacity provided by the invention can optimize the arrangement structure of each element in the energy storage power station under the condition of considering the fault probability model of each unit of the energy storage power station, so that the aim of minimizing the overall loss capacity of the energy storage power station is fulfilled, and the problem of other system faults caused by the loss capacity of the energy storage power station is greatly reduced.
Based on the same inventive concept, the invention also provides an energy storage power station internal structure optimization system for reducing loss capacity, as shown in fig. 5, the system comprises:
an acquisition module: the method comprises the steps of obtaining an optimal arrangement scheme of storage batteries in the energy storage power station by taking the minimum loss capacity of the energy storage power station as a target;
an arrangement module: the system is used for arranging the storage batteries in the energy storage power station by using the optimal arrangement scheme of the storage batteries in the energy storage power station;
wherein the arrangement scheme comprises: the number of the arranged rows and the number of the arranged columns of the battery units and the number of the batteries in each battery unit.
Preferably, the obtaining module is specifically configured to:
establishing an optimization model of an arrangement scheme of storage batteries in the energy storage power station by taking the minimum loss capacity of the energy storage power station as a target;
and solving the configuration scheme optimization model of the storage batteries in the energy storage power station to obtain the optimal configuration scheme of the storage batteries in the energy storage power station.
Further, an objective function in an optimization model of the arrangement scheme of the storage batteries in the energy storage power station is determined according to the following formula:
in the above formula, B is the loss capacity of the energy storage power station, FsumIs the failure rate of the battery system components, lambda is the failure rate of the cable components,
is the failure rate of the transformer element, SvFor presetting the total capacity, S, of the energy storage power stationcIs the total capacity of the battery system components.
Further, the failure rate F of the battery system components is determined as followssum：
Fsum＝[1-(1-e-στ)a]b
In the above equation, σ is a failure rate of a single battery, τ is a failure time interval of a single battery, e is a natural constant, a is the number of rows of the battery cells arranged, and b is the number of columns of the battery cells arranged.
Further, the failure rate λ of the cable element is determined according to the following formula:
in the above formula, λNNumber of faults of cable, TeTo expose time of the faulty line, l is the length of the cable.
Further, the failure rate of the transformer element is determined as follows
In the above formula, Ps(t) is the number of failures of the transformer in the period t, Ps(T +1) is the failure frequency of the transformer in the T +1 time period, delta T is the time interval of the adjacent time periods, T is the total time period, and T belongs to [1, T ∈]。
Further, the constraint conditions in the internal structure optimization model of the energy storage power station include:
determining the capacity constraint condition of the energy storage power station according to the following formula:
in the above formula, SvFor presetting the total capacity, S, of the energy storage power stationiThe capacity of the ith battery in the battery system element is represented by a, b and k, wherein a is the number of the arranged rows of the battery cells, k is the number of the batteries in each battery cell, and i belongs to [1, abk ]]；
Determining battery system component output constraints as follows:
Pmin≤P≤Pmax
in the above formula, PminLower limit of output of battery system components, PmaxThe output limit of the storage battery is P, and the output of the storage battery system element is P;
the cable transmission power constraint is determined as follows:
Qmin≤Q≤Qmax
in the above formula, QminFor lower limits of cable transmission power, QmaxAnd Q is the power transmitted by the cable.
Preferably, the arrangement module is specifically configured to:
respectively connecting the tail ends of the feeder cables in the a' storage battery unit branches to a grid connection point of an energy storage power station;
the branch of the storage battery units consists of b' storage battery units connected to a feeder cable;
the battery cell includes: k' storage batteries and corresponding ac/dc converters and isolation transformers;
the k storage batteries are respectively connected with the low-voltage alternating current end of the isolation transformer through the corresponding ac/dc converters, and the medium-voltage alternating current end of the isolation transformer is connected into a feeder cable;
a ' is the number of the arrangement rows of the storage battery units in the optimal arrangement scheme, b ' is the number of the arrangement columns of the storage battery units in the optimal arrangement scheme, and k ' is the number of the storage batteries in each storage battery unit in the optimal arrangement scheme.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams 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.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting the same, and although the present invention is described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: modifications and equivalents may be made to the embodiments of the invention without departing from the spirit and scope of the invention, which is to be covered by the claims.
Claims (10)
1. A method for optimizing the internal structure of an energy storage power station with reduced loss capacity, the method comprising:
acquiring an optimal arrangement scheme of storage batteries in the energy storage power station by taking the minimum loss capacity of the energy storage power station as a target;
arranging the storage batteries in the energy storage power station by using the optimal arrangement scheme of the storage batteries in the energy storage power station;
wherein the arrangement scheme comprises: the number of the arranged rows and the number of the arranged columns of the battery units and the number of the batteries in each battery unit.
2. The method of claim 1, wherein the obtaining the optimal arrangement of the storage batteries in the energy storage power station with the goal of minimizing the loss capacity of the energy storage power station comprises:
establishing an optimization model of an arrangement scheme of storage batteries in the energy storage power station by taking the minimum loss capacity of the energy storage power station as a target;
and solving the configuration scheme optimization model of the storage batteries in the energy storage power station to obtain the optimal configuration scheme of the storage batteries in the energy storage power station.
3. The method of claim 2, wherein the objective function in the optimal model of the layout of the storage batteries in the energy storage plant is determined as follows:
in the above formula, B is the loss capacity of the energy storage power station, FsumIs the failure rate of the battery system components, lambda is the failure rate of the cable components,
is the failure rate of the transformer element, SvFor presetting the total capacity, S, of the energy storage power stationcIs the total capacity of the battery system components.
4. The method of claim 3, wherein the failure rate F of the battery system components is determined as followssum：
Fsum＝[1-(1-e-στ)a]b
In the above equation, σ is a failure rate of a single battery, τ is a failure time interval of a single battery, e is a natural constant, a is the number of rows of the battery cells arranged, and b is the number of columns of the battery cells arranged.
5. A method according to claim 3, characterized in that the failure rate λ of a cable element is determined according to the following equation:
in the above formula, λNNumber of faults of cable, TeTo expose time of the faulty line, l is the length of the cable.
6. The method of claim 3, wherein the failure rate of the transformer element is determined as follows
In the above formula, Ps(t) is the number of failures of the transformer in the period t, Ps(T +1) is the failure frequency of the transformer in the T +1 time period, delta T is the time interval of the adjacent time periods, T is the total time period, and T belongs to [1, T ∈]。
7. The method of claim 3, wherein the constraints in the energy storage plant internal structure optimization model comprise:
determining the capacity constraint condition of the energy storage power station according to the following formula:
in the above formula, SiThe capacity of the ith battery in the battery system element is represented by a, b and k, wherein a is the number of the arranged rows of the battery cells, k is the number of the batteries in each battery cell, and i belongs to [1, abk ]]；
Determining battery system component output constraints as follows:
Pmin≤P≤Pmax
in the above formula, PminLower limit of output of battery system components, PmaxThe output limit of the storage battery is P, and the output of the storage battery system element is P;
the cable transmission power constraint is determined as follows:
Qmin≤Q≤Qmax
in the above formula, QminFor lower limits of cable transmission power, QmaxAnd Q is the power transmitted by the cable.
8. The method of claim 1, wherein the arranging the batteries in the energy storage power station using the optimal arrangement of the batteries in the energy storage power station comprises:
respectively connecting the tail ends of the feeder cables in the a' storage battery unit branches to a grid connection point of an energy storage power station;
the branch of the storage battery units consists of b' storage battery units connected to a feeder cable;
the battery cell includes: k' storage batteries and corresponding ac/dc converters and isolation transformers;
the k storage batteries are respectively connected with the low-voltage alternating current end of the isolation transformer through the corresponding ac/dc converters, and the medium-voltage alternating current end of the isolation transformer is connected into a feeder cable;
a ' is the number of the arrangement rows of the storage battery units in the optimal arrangement scheme, b ' is the number of the arrangement columns of the storage battery units in the optimal arrangement scheme, and k ' is the number of the storage batteries in each storage battery unit in the optimal arrangement scheme.
9. An energy storage power plant internal structure optimization system for reducing lost capacity, the system comprising:
an acquisition module: the method comprises the steps of obtaining an optimal arrangement scheme of storage batteries in the energy storage power station by taking the minimum loss capacity of the energy storage power station as a target;
an arrangement module: the system is used for arranging the storage batteries in the energy storage power station by using the optimal arrangement scheme of the storage batteries in the energy storage power station;
wherein the arrangement scheme comprises: the number of the arranged rows and the number of the arranged columns of the battery units and the number of the batteries in each battery unit.
10. The system of claim 1, wherein the acquisition module is specifically configured to:
establishing an optimization model of an arrangement scheme of storage batteries in the energy storage power station by taking the minimum loss capacity of the energy storage power station as a target;
and solving the configuration scheme optimization model of the storage batteries in the energy storage power station to obtain the optimal configuration scheme of the storage batteries in the energy storage power station.
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| CN113837795B (en) * | 2021-08-27 | 2024-03-22 | 国网江苏省电力有限公司连云港供电分公司 | Method for determining loss cost of energy storage power station |
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