A distributed new energy consumption capacity calculation method, device, equipment and medium

Abstract

The present invention discloses a method, device, equipment and medium for calculating the capacity of absorbing distributed new energy, including obtaining the information of units that can participate in balancing the power fluctuation of distributed new energy, and calculating the first distributed new energy access limit value under the constraint of the unit regulation capacity; obtaining the information of the transmission channel transformer on the target subnet with distributed power access, and calculating the second distributed new energy access limit value under the constraint of transformer capacity; establishing an optimization model with the maximum absorption of distributed new energy in the distribution network as the objective function, and solving the optimization model under the premise of satisfying the voltage range and current carrying capacity constraints of the distribution network, and obtaining the third distributed new energy access limit value constrained by the voltage range and current carrying capacity of the distribution network; selecting the minimum value as the current distributed new energy access limit value of the power grid. This scheme takes into account multiple constraints such as system peak regulation, transformer capacity, power and electricity balance, and distribution network flow, and has the advantages of fast calculation speed and high accuracy.

Description

Technical Field

[0001] The present invention belongs to the technical field of distributed renewable energy power generation in power systems, and specifically relates to a method, device, equipment and medium for calculating the absorption capacity of distributed renewable energy. Background Art

[0002] The main forms of new energy access to the grid are centralized access through convergence and decentralized distributed access. With the development of new power generation technologies including renewable energy such as wind power and photovoltaics, as well as efficient and clean fuels, distributed power generation systems are becoming an effective way to meet load growth, reduce environmental pollution, improve energy comprehensive utilization efficiency and power supply reliability, and are widely used in distribution networks. However, the grid connection of distributed power sources has also brought some problems to the safety and reliability of the power system, becoming a constraint factor limiting the absorption of new energy. The current power system grid structure is not enough to support such a large-scale and high-proportion new energy access. The scale of new energy installed capacity has exceeded the limit level that the current system can absorb. The phenomenon of new energy abandonment is frequent, and wind and light resources are seriously wasted. Therefore, in order to reduce the abandonment rate of new energy, it is necessary to consider multiple constraints of the power grid, accurately evaluate the system's new energy absorption capacity, guide the planning and development of new energy and future power systems, and promote the safe, reliable and economical operation of the power grid.

[0003] At present, there are three common methods for evaluating the absorption capacity of new energy sources: typical day method, random production simulation method, and time series simulation method. When this method is calculated online, it is necessary to perform network equivalent calculations for each load node, which requires a large amount of calculations and a long time, so new methods are needed. The scheduling method proposed based on the typical day method is a relatively conservative method. It usually considers the balance of new energy under the most serious circumstances. The calculation results of this method are conservative. The random production simulation method also cannot consider factors such as climbing performance and peak load capacity, and has certain limitations. The time series production simulation method is widely used in the evaluation of the absorption capacity of new energy sources, but it requires a large amount of calculations, takes a long time, and has low calculation efficiency. Summary of the invention

[0004] The purpose of the present invention is to provide a distributed new energy absorption capacity calculation method, device, equipment and medium to solve the problem of low calculation efficiency of new energy absorption capacity evaluation methods in the prior art.

[0005] In order to achieve the above object, the present invention adopts the following technical solution:

[0006] In a first aspect, the present invention provides a method for calculating the capacity of a distributed new energy source, comprising the following steps:

[0007] Obtain information about units that can participate in balancing the power fluctuations of distributed renewable energy;

[0008] Based on the unit information, a first distributed new energy access limit value under the unit regulation capacity constraint is calculated;

[0009] Obtain the information of the transmission channel transformer on the target subnet where the distributed power source is connected;

[0010] Based on the transmission channel transformer information of the target subnet, a second distributed new energy access limit value under the transformer capacity constraint is calculated;

[0011] An optimization model is established with the maximum consumption of distributed renewable energy in the distribution network as the objective function. The optimization model is solved under the premise of satisfying the voltage range and current carrying capacity constraints of the distribution network to obtain the third distributed renewable energy access limit value constrained by the voltage range and current carrying capacity of the distribution network.

[0012] The minimum value among the first distributed new energy access limit value, the second distributed new energy access limit value and the third distributed new energy access limit value is selected as the current power grid distributed new energy access limit value.

[0013] Furthermore, the first distributed new energy access limit value S Ua The calculation method is as follows:

[0014] S Ua =S adj +S bal

[0015] Among them, S adj The distributed renewable energy consumption capacity considering the regulation capacity constraints of local units; S bal It is the distributed renewable energy consumption capacity that takes into account the regulation capacity constraints of adjacent external power grid units.

[0016] Furthermore, the distributed renewable energy consumption capacity S considering the local unit regulation capacity constraints adj The calculation is as follows:

[0017]

[0018] Among them, P ps,max is the maximum regulation capacity of the power grid; j is the number of local units that can participate in balancing the fluctuation of distributed renewable energy power; m is the total number of local units that can participate in balancing the fluctuation of distributed renewable energy power; P max,j is the maximum output of the jth unit; P min,j is the minimum output of the jth unit; A ps,j is the adjustment amplitude of the jth unit.

[0019] Furthermore, the distributed new energy consumption capacity S considering the regulation capacity constraints of adjacent external power grid units bal The calculation is as follows:

[0020]

[0021] Wherein, μ is the maximum power fluctuation coefficient of distributed renewable energy; P ls It is the spare capacity of the external adjacent power grid units used to support the target power grid during the operation year.

[0022] Furthermore, the spare capacity P of the external adjacent power grid units used to support the target power grid in the operation year is ls Calculate as follows:

[0023] P ls =λ*P ic

[0024] Among them, P ic is the total installed capacity of the external adjacent power grid in the operating year, and λ is the unit's reserve capacity factor.

[0025] Furthermore, the second distributed new energy access limit value S under the transformer capacity constraint Tran The calculation is as follows:

[0026]

[0027] Where i = 1, ..., n represents the i-th target subnet with distributed power access; n represents the number of target subnets with distributed power access; P DG,max is the maximum grid-connected capacity of distributed power sources; P trans,i P is the capacity of the transmission channel transformer on the i-th target subnet to which the distributed generation is connected; disLoad,i is the load value of the i-th target subnet to which the distributed generation is connected; P disLoss,i It is the network loss of the i-th target subnet to which the distributed generation is connected.

[0028] Furthermore, the objective function and constraint conditions of the distributed renewable energy consumption in the distribution network are as follows:

[0029]

[0030]

[0031] Wherein, Z=1,…,k represents the Zth target subnet with distributed power access; k represents the number of target subnets with distributed power access; B represents the Zth target subnet node set, E represents the Zth target subnet branch set; P G,Z,j is the active power of the distributed generation at the Zth target subnet node j; V Z,i 、V Z,j represents the voltage amplitude of the Zth target subnet node i, j; P Z,ij , QZ,ij represents the active and reactive power of the Zth target subnet branch i and j; l Z,ij 、u Z,j is the intermediate variable; P Z,Gi , Q Z,Gi is the active and reactive output of generator i in the Zth target subgrid; P Z,Di , Q Z,Di is the active and reactive loads of the Zth target subnet node i; θ i is the voltage phase angle of the Zth target subnet node i; θ Z,ij =θ Z,i -θ Z,j ; G Z,ij , B Z,ij is the real and imaginary parts of the element in the i-th row and j-th column of the Z-th target subnet node admittance matrix; They represent the upper and lower limits of the voltage amplitude of the Zth target subnet node j respectively; represents the maximum allowable current of the Zth target subnet branch i, j; P Z,Gi are the upper and lower bounds of the active output of the Zth target subnet power supply respectively; Q Z,Gi are the upper and lower bounds of the reactive power output of the Zth target subnet power supply.

[0032] In a second aspect, the present invention provides a distributed new energy consumption capacity calculation device, comprising:

[0033] The first acquisition module is used to obtain the unit information that can participate in balancing the power fluctuation of distributed new energy;

[0034] A first calculation module is used to calculate a first distributed new energy access limit value under the constraint of the unit regulation capability based on the unit information;

[0035] The second acquisition module is used to obtain the information of the transmission channel transformer on the target subnet where the distributed power source is connected;

[0036] A second calculation module is used to calculate a second distributed new energy access limit value under the transformer capacity constraint based on the transmission channel transformer information on the target subnet;

[0037] The model solving module is used to establish an optimization model with the maximum consumption of distributed renewable energy in the distribution network as the objective function, and solve the optimization model under the premise of satisfying the voltage range and current carrying capacity constraints of the distribution network to obtain the third distributed renewable energy access limit value constrained by the voltage range and current carrying capacity of the distribution network;

[0038] The comparison module is used to select the minimum value among the first distributed new energy access limit value, the second distributed new energy access limit value and the third distributed new energy access limit value as the current power grid distributed new energy access limit value.

[0039] In a third aspect, the present invention provides an electronic device, comprising a processor and a memory, wherein the processor is used to execute a computer program stored in the memory to implement the above-mentioned distributed new energy absorption capacity calculation method.

[0040] In a fourth aspect, the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores at least one instruction, and when the at least one instruction is executed by a processor, the above-mentioned distributed new energy absorption capacity calculation method is implemented.

[0041] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0042] The distributed new energy consumption capacity calculation method proposed in the present invention considers multiple constraints of the transmission and distribution network, and calculates the first distributed new energy access limit value under the constraint of the group adjustment capacity and the second distributed new energy access limit value under the constraint of the transformer capacity; establishes an optimization model with the maximum consumption of distributed new energy in the distribution network as the objective function, and solves the optimization model under the premise of satisfying the voltage range and current carrying capacity constraints of the distribution network to obtain the third distributed new energy access limit value constrained by the voltage range and current carrying capacity of the distribution network; selects the minimum value of the first distributed new energy access limit value, the second distributed new energy access limit value and the third distributed new energy access limit value as the current distributed new energy access limit value of the power grid. Considering multiple constraints such as system peak regulation, transformer capacity, power and electricity balance, and distribution network flow, it has the advantages of fast calculation speed and high accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The drawings constituting a part of the present application are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0044] Figure 1 A schematic diagram of a flow chart of a method for calculating the absorption capacity of distributed new energy in the present invention;

[0045] Figure 2 This is a structural block diagram of a distributed new energy consumption capacity calculation device of the present invention;

[0046] Figure 3 The present invention is a structural block diagram of an electronic device. DETAILED DESCRIPTION

[0047] The present invention will be described in detail below with reference to the accompanying drawings and in combination with embodiments. It should be noted that the embodiments and features in the embodiments of the present application can be combined with each other without conflict.

[0048] The following detailed description is an exemplary description, which is intended to provide further detailed description of the present invention. Unless otherwise specified, all technical terms used in the present invention have the same meaning as those generally understood by those skilled in the art to which the present application belongs. The terms used in the present invention are only for describing specific embodiments, and are not intended to limit exemplary embodiments according to the present invention.

[0049] Example 1

[0050] like Figure 1 As shown, the present invention provides a method for calculating the capacity of a distributed new energy source, comprising the following steps:

[0051] S1. Obtaining information on units that can participate in balancing the power fluctuations of distributed renewable energy;

[0052] Specifically, in this scheme, the information of units that can participate in balancing the power fluctuations of distributed renewable energy is provided by a pre-built integrated digital model of the transmission and distribution network. The target grid range to be studied is selected, and the information of local units that can participate in balancing the power fluctuations of distributed renewable energy is extracted.

[0053] The integrated digital model of the transmission and distribution network includes the models of the transmission and distribution network components and the equipment operating limit parameters. The models of the transmission and distribution network components include the transmission line parameters (resistance, reactance, conductance, susceptance), transformer parameters (leakage reactance, ratio, tap position), generator node parameters (active and reactive output values), load node parameters (active and reactive values); generator and reserve capacity data;

[0054] The equipment operating limit parameters include: line rated current, transformer rated capacity, and generator maximum output (maximum active output and maximum reactive output).

[0055] S2. Based on the unit information, calculate and obtain the first distributed new energy access limit value S under the unit regulation capacity constraint. Ua ; Specifically, the first distributed new energy access limit value S Ua The calculation method is as follows:

[0056]

[0057] Among them, S adj is the distributed renewable energy consumption capacity considering the regulation capacity constraints of local units; P ps,maxis the maximum regulation capacity of the power grid; j is the number of local units that can participate in balancing the fluctuation of distributed renewable energy power; m is the total number of local units that can participate in balancing the fluctuation of distributed renewable energy power; P max,j is the maximum output of the jth unit; P min,j is the minimum output of the jth unit; A ps,j is the adjustment amplitude of the jth unit.

[0058] According to the total installed capacity of the external adjacent power grid in the operating year, the spinning reserve capacity that the adjacent external power grid can use to balance the power fluctuation of the distributed generation of the target power grid is calculated:

[0059] P ls =λ*P ic (2)

[0060] Among them, P ic P is the total installed capacity of the external adjacent power grid in the operating year; ls is the spare capacity of the units in the external adjacent power grid used to support the target power grid in the operating year; λ is the unit spare capacity coefficient, which is generally 5% according to engineering experience, or is adjusted according to the actual power grid.

[0061] Calculate the distributed renewable energy consumption capacity considering the regulation capacity constraints of adjacent external power grid units:

[0062]

[0063] Among them, μ is the maximum power fluctuation coefficient of distributed renewable energy; S bal It is the distributed renewable energy consumption capacity that takes into account the regulation capacity constraints of adjacent external power grid units.

[0064] Therefore, the distributed renewable energy consumption capacity S that comprehensively considers the regulation capacity constraints of the internal and external units of the target power grid is Ua The calculation is as follows:

[0065] S Ua =S adj +S bal (4)

[0066] Among them, S adj The distributed renewable energy consumption capacity considering the regulation capacity constraints of local units; S bal It is the distributed renewable energy consumption capacity that takes into account the regulation capacity constraints of adjacent external power grid units.

[0067] S3, obtaining the information of the transmission channel transformer on the target subnet where the distributed power source is connected;

[0068] Specifically, in this solution, the information of the transmission channel transformer on the target subnet with distributed power generation access is provided by the above-mentioned pre-built integrated digital model of the transmission and distribution network. Based on the integrated digital model, the target grid range to be connected to the distributed power generation is selected, and the capacity of the transmission channel transformer on the target subnet with distributed power generation access in the target grid is extracted.

[0069] S4. Based on the target subnet transmission channel transformer information, calculate the second distributed new energy access limit value S under the transformer capacity constraint. Tran Specifically, the second distributed new energy access limit value S under the transformer capacity constraint Tran The calculation is as follows:

[0070]

[0071] Where i=1,…,n represents the i-th target subnet with distributed power access (the target subnet is part of the target power grid); n represents the number of target subnets with distributed power access; P DG,max is the maximum grid-connected capacity of distributed power sources; P trans,i P is the capacity of the transmission channel transformer on the i-th target subnet to which the distributed generation is connected; disLoad,i is the load value of the i-th target subnet to which the distributed generation is connected; P disLoss,i It is the network loss of the i-th target subnet to which the distributed generation is connected.

[0072] The maximum absorption capacity of distributed renewable energy constrained by transformer capacity corresponds to the following scenario: The distributed power capacity of the i-th target subnet meets the local load P of the i-th target subnet. disLoad,i and network loss P disLoss,i On the other hand, the power is returned to the upper grid through the upper transmission channel transformer. At this time, the maximum power returned to the upper grid is limited by the transmission channel transformer capacity P on the i-th target subnet. trans,i At this time, the maximum absorption value of distributed new energy is the transformer capacity P trans,i +i-th target subnet load P disLoad,i + the network loss of the i-th target subnet P disLoss,i .

[0073] S5. Establish an optimization model with the maximum consumption of distributed renewable energy in the distribution network as the objective function, and solve the optimization model under the premise of satisfying the voltage range and current carrying capacity constraints of the distribution network to obtain the third distributed renewable energy access limit value S constrained by the voltage range and current carrying capacity of the distribution network. Opt ;

[0074] Considering the voltage range constraints of the target power grid, the maximum allowable current constraints of the branches, the power flow balance constraints, and the output limitations of the generator nodes, the power grid's ability to absorb distributed renewable energy is evaluated.

[0075] The objective function and constraints for accommodating distributed renewable energy in the distribution network are established as shown in the following formula:

[0076]

[0077]

[0078] In the above model, (6-2) to (6-5) are equality constraints, (6-6) to (6-9) are inequality constraints, and the variables are explained as follows:

[0079] Z=1,…,k represents the Zth target subnet with distributed power access; k represents the number of target subnets with distributed power access; B represents the Zth target subnet node set, E represents the Zth target subnet branch set; P G,Z,j is the active power of the distributed generation at the Zth target subnet node j; V Z,i 、V Z,j represents the voltage amplitude of the Zth target subnet node i, j; P Z,ij , Q Z,ij represents the active and reactive power of the Zth target subnet branch i and j; l Z,ij 、u Z,j is the intermediate variable; P Z,Gi , Q Z,Gi is the active and reactive output of generator i in the Zth target subgrid; P Z,Di , Q Z,Di is the active and reactive loads of the Zth target subnet node i; θ i is the voltage phase angle of the Zth target subnet node i; θ Z,ij =θ Z,i -θ Z,j ; G Z,ij , B Z,ij is the real and imaginary parts of the element in the i-th row and j-th column of the Z-th target subnet node admittance matrix; They represent the upper and lower limits of the voltage amplitude of the Zth target subnet node j respectively; represents the maximum allowable current of the Zth target subnet branch i, j; P Z,Gi are the upper and lower bounds of the active output of the Zth target subnet power supply respectively; Q Z,Gi are the upper and lower bounds of the reactive power output of the Zth target subnet power supply.

[0080] Solve the optimization model to obtain the new energy access limit value S constrained by the voltage range and current carrying capacity of the distribution networkOpt .

[0081]

[0082] The meanings of the variables in Formula 7 are consistent with those in Formula 6.

[0083] S6. Comparison S Ua , S Tran , S Opt , select the minimum value among the first distributed new energy access limit value, the second distributed new energy access limit value and the third distributed new energy access limit value as the current power grid distributed new energy access limit value.

[0084] According to the above calculation results, the access limit value S of distributed new energy in the target grid to be studied can be obtained: DG , as shown below:

[0085] S DG =min(S Ua ,S Tran ,S Opt ) (8)

[0086] Example 2

[0087] like Figure 2 As shown, in a second aspect, the present invention provides a distributed new energy consumption capacity calculation device, comprising:

[0088] The first acquisition module is used to obtain the unit information that can participate in balancing the power fluctuation of distributed new energy;

[0089] A first calculation module is used to calculate a first distributed new energy access limit value under the constraint of the unit regulation capability based on the unit information;

[0090] In the first calculation module, the first distributed new energy access limit value S Ua The calculation method is as follows:

[0091] S Ua =S adj +S bal

[0092] Among them, S adj The distributed renewable energy consumption capacity considering the regulation capacity constraints of local units; S bal It is the distributed renewable energy consumption capacity that takes into account the regulation capacity constraints of adjacent external power grid units.

[0093] The distributed renewable energy consumption capacity S considering the local unit regulation capacity constraints adj The calculation is as follows:

[0094]

[0095] Among them, P ps,max is the maximum regulation capacity of the power grid; j is the number of local units that can participate in balancing the fluctuation of distributed renewable energy power; m is the total number of local units that can participate in balancing the fluctuation of distributed renewable energy power; P max,j is the maximum output of the jth unit; P min,j is the minimum output of the jth unit; A ps,j is the adjustment amplitude of the jth unit.

[0096] The distributed new energy consumption capacity S considering the regulation capacity constraints of adjacent external power grid units bal The calculation is as follows:

[0097]

[0098] Wherein, μ is the maximum power fluctuation coefficient of distributed renewable energy; P ls It is the spare capacity of the external adjacent power grid units used to support the target power grid during the operation year.

[0099] The reserve capacity P of the external adjacent power grid units used to support the target power grid in the operation year ls Calculate as follows:

[0100] P ls =λ*P ic

[0101] Among them, P ic is the total installed capacity of the external adjacent power grid in the operating year, and λ is the unit's reserve capacity factor.

[0102] The second acquisition module is used to obtain the information of the transmission channel transformer on the target subnet where the distributed power source is connected;

[0103] A second calculation module is used to calculate a second distributed new energy access limit value under the transformer capacity constraint based on the transmission channel transformer information on the target subnet;

[0104] In the second calculation module, the second distributed new energy access limit value S under the transformer capacity constraint Tran The calculation is as follows:

[0105]

[0106] Where i = 1, ..., n represents the i-th target subnet with distributed power access; n represents the number of target subnets with distributed power access; P DG,max is the maximum grid-connected capacity of distributed power sources; P trans,i P is the capacity of the transmission channel transformer on the i-th target subnet to which the distributed generation is connected;disLoad,i is the load value of the i-th target subnet to which the distributed generation is connected; P disLoss,i It is the network loss of the i-th target subnet to which the distributed generation is connected.

[0107] The model solving module is used to establish an optimization model with the maximum consumption of distributed renewable energy in the distribution network as the objective function, and solve the optimization model under the premise of satisfying the voltage range and current carrying capacity constraints of the distribution network to obtain the third distributed renewable energy access limit value constrained by the voltage range and current carrying capacity of the distribution network;

[0108] In the model solving module, the objective function and constraints of the distribution network distributed renewable energy consumption are as follows:

[0109]

[0110]

[0111] Wherein, Z=1,…,k represents the Zth target subnet with distributed power access; k represents the number of target subnets with distributed power access; B represents the Zth target subnet node set, E represents the Zth target subnet branch set; P G,Z,j is the active power of the distributed generation at the Zth target subnet node j; V Z,i 、V Z,j represents the voltage amplitude of the Zth target subnet node i, j; P Z,ij , Q Z,ij represents the active and reactive power of the Zth target subnet branch i and j; l Z,ij 、u Z,j is the intermediate variable; P Z,Gi , Q Z,Gi is the active and reactive output of generator i in the Zth target subgrid; P Z,Di , Q Z,Di is the active and reactive loads of the Zth target subnet node i; θ i is the voltage phase angle of the Zth target subnet node i; θ Z,ij =θ Z,i -θ Z,j ; G Z,ij , B Z,ij is the real and imaginary parts of the element in the i-th row and j-th column of the Z-th target subnet node admittance matrix; They represent the upper and lower limits of the voltage amplitude of the Zth target subnet node j respectively; represents the maximum allowable current of the Zth target subnet branch i, j; P Z,Gi are the upper and lower bounds of the active output of the Zth target subnet power supply respectively; QZ,Gi are the upper and lower bounds of the reactive power output of the Zth target subnet power supply.

[0112] The comparison module is used to select the minimum value among the first distributed new energy access limit value, the second distributed new energy access limit value and the third distributed new energy access limit value as the current power grid distributed new energy access limit value.

[0113] Example 3

[0114] like Figure 3 As shown, the present invention also provides an electronic device 100 for implementing a distributed new energy consumption capacity calculation method; the electronic device 100 includes a memory 101, at least one processor 102, a computer program 103 stored in the memory 101 and executable on the at least one processor 102, and at least one communication bus 104. The memory 101 can be used to store the computer program 103, and the processor 102 implements the steps of a distributed new energy consumption capacity calculation method in embodiment 1 by running or executing the computer program stored in the memory 101 and calling the data stored in the memory 101. The memory 101 can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, an application required by at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area can store data (such as audio data) created according to the use of the electronic device 100, etc. In addition, the memory 101 may include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other non-volatile solid-state storage devices.

[0115] At least one processor 102 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The processor 102 may be a microprocessor or any conventional processor, etc. The processor 102 is the control center of the electronic device 100, and uses various interfaces and lines to connect various parts of the entire electronic device 100.

[0116] The memory 101 in the electronic device 100 stores a plurality of instructions to implement a distributed new energy consumption capacity calculation method, and the processor 102 can execute the plurality of instructions to implement:

[0117] Obtain information about units that can participate in balancing the power fluctuations of distributed renewable energy;

[0118] Based on the unit information, a first distributed new energy access limit value under the unit regulation capacity constraint is calculated;

[0119] Obtain the information of the transmission channel transformer on the target subnet where the distributed power source is connected;

[0120] Based on the transmission channel transformer information of the target subnet, a second distributed new energy access limit value under the transformer capacity constraint is calculated;

[0121] An optimization model is established with the maximum consumption of distributed renewable energy in the distribution network as the objective function. The optimization model is solved under the premise of satisfying the voltage range and current carrying capacity constraints of the distribution network to obtain the third distributed renewable energy access limit value constrained by the voltage range and current carrying capacity of the distribution network.

[0122] The minimum value among the first distributed new energy access limit value, the second distributed new energy access limit value and the third distributed new energy access limit value is selected as the current power grid distributed new energy access limit value.

[0123] Example 4

[0124] If the module / unit integrated in the electronic device 100 is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned method embodiments when executed by the processor. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. Computer-readable media may include: any entity or device capable of carrying computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory and read-only memory (ROM, Read-Only Memory).

[0125] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0126] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0127] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0128] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0129] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for calculating the capacity of distributing new energy, characterized in that: The steps include: Obtain information about units that can participate in balancing the power fluctuations of distributed renewable energy; Based on the unit information, a first distributed new energy access limit value under the unit regulation capacity constraint is calculated; Obtain the information of the transmission channel transformer on the target subnet where the distributed power source is connected; Based on the transmission channel transformer information of the target subnet, a second distributed new energy access limit value under the transformer capacity constraint is calculated; An optimization model is established with the maximum consumption of distributed renewable energy in the distribution network as the objective function. The optimization model is solved under the premise of satisfying the voltage range and current carrying capacity constraints of the distribution network to obtain the third distributed renewable energy access limit value constrained by the voltage range and current carrying capacity of the distribution network. Selecting the minimum value among the first distributed new energy access limit value, the second distributed new energy access limit value and the third distributed new energy access limit value as the current power grid distributed new energy access limit value; The first distributed new energy access limit value S Ua It is the sum of the distributed renewable energy consumption capacity taking into account the regulation capacity constraints of local units and the distributed renewable energy consumption capacity taking into account the regulation capacity constraints of adjacent external power grid units. The distributed renewable energy consumption capacity S considering the local unit regulation capacity constraints adj The calculation method is as follows: in, The maximum regulation capacity of the power grid; j Number the local units that can participate in balancing the power fluctuations of distributed renewable energy; m is the total number of local units that can participate in balancing the fluctuations in distributed renewable energy power; For the j Maximum output of each unit; For the j Minimum output of each unit; For the j The adjustment range of each unit; The distributed new energy consumption capacity S considering the regulation capacity constraints of adjacent external power grid units bal The calculation is as follows: in, is the maximum power fluctuation coefficient of distributed renewable energy; The reserve capacity of the external adjacent power grid units used to support the target power grid during the operation year; The distribution network distributed new energy consumption objective function and constraint conditions are as follows: in, Z=1,…,k Indicates the number of distributed power sources connected Z target subnet; k Indicates the number of target subnets with distributed generation access; B Indicates Z A set of target subnet nodes, E Indicates Z A target subnet branch set; For the Z Target subnet nodes j Active power of distributed power sources; 、 Indicates Z Target subnet nodes i, j The voltage amplitude; , Indicates Z Target subnet branch i, j Active and reactive power; 、 is an intermediate variable; 、 For the Z Target Subnet Generator i The active and reactive contributions; 、 For the Z Target subnet nodes i Active and reactive loads; ; 、 For the Z The target subnet node admittance array i Line j real and imaginary parts of column elements; , Respectively represent Z Target subnet nodes j The upper and lower limits of the voltage amplitude; Indicates Z Target subnet branch i, j The maximum allowable current; , Respectively Z The upper and lower bounds of active output of the target subnet power supply; , For the Z The upper and lower bounds of reactive power output of the target subnet power supply are set.

2. The method for calculating the capacity of distributing new energy according to claim 1 is characterized in that: The reserve capacity P of the external adjacent power grid units used to support the target power grid in the operation year ls Calculate as follows: in, is the total installed capacity of the external adjacent power grid in the operating year, is the unit reserve capacity factor.

3. The method for calculating the capacity of distributing new energy according to claim 1, characterized in that: The second distributed new energy access limit value S under the transformer capacity constraint Tran The calculation is as follows: in, i=1,…,n Indicates the number of distributed power sources connected i target subnet; n Indicates the number of target subnets with distributed power sources connected; is the maximum grid-connected capacity of distributed power sources; The first distributed power source connected i Transformer capacity of the transmission channel on each target subnet; The first distributed power source connected i target subnet load value; The first distributed power source connected i The target subnet network loss.

4. A distributed new energy consumption capacity calculation device, used to implement the distributed new energy consumption capacity calculation method according to any one of claims 1 to 3, characterized in that: include: The first acquisition module is used to obtain the unit information that can participate in balancing the power fluctuation of distributed new energy; A first calculation module is used to calculate a first distributed new energy access limit value under the constraint of the unit regulation capability based on the unit information; The second acquisition module is used to obtain the information of the transmission channel transformer on the target subnet where the distributed power source is connected; A second calculation module is used to calculate a second distributed new energy access limit value under the transformer capacity constraint based on the transmission channel transformer information on the target subnet; The model solving module is used to establish an optimization model with the maximum consumption of distributed renewable energy in the distribution network as the objective function, and solve the optimization model under the premise of satisfying the voltage range and current carrying capacity constraints of the distribution network to obtain the third distributed renewable energy access limit value constrained by the voltage range and current carrying capacity of the distribution network; The comparison module is used to select the minimum value among the first distributed new energy access limit value, the second distributed new energy access limit value and the third distributed new energy access limit value as the current power grid distributed new energy access limit value.

5. An electronic device, characterized in that: It comprises a processor and a memory, wherein the processor is used to execute a computer program stored in the memory to implement the distributed new energy absorption capacity calculation method as described in any one of claims 1 to 3.

6. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores at least one instruction, and when the at least one instruction is executed by the processor, the distributed new energy absorption capacity calculation method as described in any one of claims 1 to 3 is implemented.

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