CN115549213A - Distributed power supply access scale determination method, device, electronic device, storage medium, and program product - Google Patents
Distributed power supply access scale determination method, device, electronic device, storage medium, and program product 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
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
- H02J3/466—Scheduling the operation of the generators, e.g. connecting or disconnecting generators to meet a given demand
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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
- H02J3/003—Load forecast, e.g. methods or systems for forecasting future load demand
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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
- H02J3/004—Generation forecast, e.g. methods or systems for forecasting future energy generation
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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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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
- H02J2300/20—The dispersed energy generation being of renewable origin
Abstract
The invention discloses a method and a device for determining the access scale of a distributed power supply, electronic equipment, a storage medium and a program product. The distributed power supply access scale determining method provided by the embodiment of the invention considers the load characteristics, calculates the distributed power supply access scale on the basis of reading load data such as maximum load, average load, load demand and the like, and judges whether the grid has the distributed power supply access expansion capacity, so that the problem that the bearing capacity of a power distribution network cannot be considered by the conventional planning method is solved; the distributed power supply access scale determining method provided by the embodiment of the invention is based on the grid division mode, namely based on the difference between the city land area division and the land function positioning, and divides the city land into different grids for data reading and relevant model calculation, so that the requirement on planning year data and the complexity of a calculation model thereof are effectively reduced.
Description
Technical Field
The present invention relates to the field of power distribution network technologies, and in particular, to a method and an apparatus for determining a distributed power supply access scale, an electronic device, a storage medium, and a program product.
Background
Due to randomness and uncertainty of low-voltage distributed power supply access and power generation behaviors, a plurality of factors need to be comprehensively considered when the low-voltage distributed power supply is accessed, the urban development needs need to be considered, the urban functional area division and functional positioning need to be considered, and the regional power grid characteristics such as the bearing capacity of a regional power distribution network and the load needs to be considered for comprehensive layout.
However, the existing low-voltage distributed power access planning methods are mainly divided into two categories: one type of method is a ratio extrapolation method, such as a transformer capacity proportioning model; another type of approach is an optimization model-based approach.
The collaborative planning of the power distribution network by the current low-voltage distributed power access planning method is less in consideration, and on one hand, a simple model cannot consider core elements such as the bearing capacity of the power distribution network and the functions of urban functional areas; on the other hand, the complex refined model has huge calculation amount, high requirements on data quality and the like, and the calculation process is very arduous.
Disclosure of Invention
The invention provides a method and a device for determining the access scale of a distributed power supply, electronic equipment, a storage medium and a program product, solves the problem that the bearing capacity of a power distribution network cannot be considered in the conventional planning method, and effectively reduces the requirement on planning annual data and the complexity of a calculation model thereof.
According to an aspect of the present invention, there is provided a method for determining a distributed power access size, including:
acquiring grid data, load data, distributed power supply data and distribution transformation data of a power distribution network;
counting the grid type, the coverage area, the annual maximum load and the annual maximum network power of the distributed power supply of each grid according to the grid data, the load data, the distributed power supply data and the distribution transformation data;
determining the residual capacity density of each voltage class of each grid connected with other grids and the annual maximum internet power density of the distributed power supply in each grid, according to the grid type, the coverage geographical area, the annual maximum load and the annual maximum internet power of the distributed power supply of each grid;
according to the annual maximum internet power generation power density of the distributed power sources in each grid and the coverage area of the grid, the annual maximum internet power generation power density of each distributed power source in the grid at the same time rate is calculated for different types of grids;
and determining the access scale of the distributed power supplies of each grid in the planning year according to the difference value between the annual maximum internet power generation power density and the residual capacity density of each distributed power supply in the grid under the synchronous rate and the coverage geographical area of the grid.
According to another aspect of the present invention, there is provided a distributed power supply access size determining apparatus, including:
the power grid data acquisition module is used for acquiring grid data, load data, distributed power supply data and distribution transformation data of the power distribution network;
the grid data statistics module is used for carrying out statistics on the grid type, the coverage area, the annual maximum load and the annual maximum network power of the distributed power supply of each grid according to the grid data, the load data, the distributed power supply data and the distribution transformation data;
the first calculation module is used for determining the residual capacity density of each voltage class of each grid connected with other grids and the annual maximum internet power density of the distributed power supply in each grid, which is externally connected with a distribution transformer, according to the grid type, the coverage geographical area, the annual maximum load and the annual maximum internet power of the distributed power supply of each grid;
the second calculation module is used for calculating the annual maximum internet power generation power density of each distributed power supply in the grids at the same time rate aiming at different types of grids according to the annual maximum internet power generation power density of the distributed power supply in each grid and the coverage area of the grid;
and the distributed power access determining module is used for determining the access scale of the distributed power of each grid in the planning year according to the difference value between the annual maximum internet power generation power density and the residual capacity density of each distributed power in the grid at the same time rate and the coverage geographical area of the grid.
According to another aspect of the present invention, there is provided an electronic apparatus including:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores a computer program executable by the at least one processor, the computer program being executable by the at least one processor to enable the at least one processor to perform the distributed power access dimensioning method of any of the embodiments of the invention.
According to another aspect of the present invention, there is provided a computer-readable storage medium storing computer instructions for causing a processor to implement the distributed power access size determination method according to any one of the embodiments of the present invention when executed.
According to another aspect of the invention, there is provided a computer program product comprising a computer program which, when executed by a processor, implements the distributed power access dimensioning method of any one of the embodiments of the invention.
According to the technical scheme of the embodiment of the invention, grid data, load data, distributed power supply data and distribution transformation data of a power distribution network are obtained; counting the grid type, the coverage area, the annual maximum load and the annual maximum network power of the distributed power supply of each grid according to the grid data, the load data, the distributed power supply data and the distribution transformation data; determining the residual capacity density of each voltage class of each grid connected with other grids and the annual maximum internet power density of the distributed power supply in each grid, according to the grid type, the coverage geographical area, the annual maximum load and the annual maximum internet power of the distributed power supply of each grid; according to the annual maximum internet power generation power density of the distributed power sources in each grid and the coverage area of the grids, calculating the annual maximum internet power generation power density of each distributed power source in the grids at the same time rate aiming at different types of grids; and determining the access scale of the distributed power supplies of each grid in the planning year according to the difference value between the annual maximum internet power generation power density and the residual capacity density of each distributed power supply in the grid under the synchronous rate and the coverage geographical area of the grid. The distributed power supply access scale determining method provided by the embodiment of the invention considers the load characteristics, calculates the distributed power supply access scale on the basis of reading load data such as maximum load, average load and load demand and the like, and judges whether the grid has the distributed power supply access expansion capacity, so that the problem that the bearing capacity of a power distribution network cannot be considered by the conventional planning method is solved; the distributed power supply access scale determining method provided by the embodiment of the invention divides the urban land into different grids for data reading and related model calculation based on the grid division mode, namely based on the difference between the urban land area division and the land function positioning, so that the requirement on planning year data and the complexity of a calculation model thereof are effectively reduced.
It should be understood that the statements in this section do not necessarily identify key or critical features of the embodiments of the present invention, nor do they necessarily limit the scope of the invention. Other features of the present invention will become apparent from the following description.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a flowchart of a method for determining a distributed power access scale according to an embodiment of the present invention.
Fig. 2 is a flowchart of a method for determining a distributed power access size according to a second embodiment of the present invention.
Fig. 3 is a schematic structural diagram of a distributed power supply access scale determining apparatus according to a third embodiment of the present invention.
Fig. 4 is a schematic structural diagram of an electronic device according to a fourth embodiment of the present invention, where the method for determining a distributed power supply access scale is provided.
Detailed Description
In order to make the technical solutions of the present invention better understood, 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 only a part of the embodiments of the present invention, and not all of the embodiments. 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.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Example one
Fig. 1 is a flowchart of a method for determining a distributed power access size according to an embodiment of the present invention. The present embodiment is applicable to the case of optimizing the scale planning of the low-voltage distributed power access distribution network, and the method may be executed by a distributed power access scale determining apparatus, where the distributed power access scale determining apparatus may be implemented in a form of hardware and/or software, and the distributed power access scale determining apparatus may be configured in any electronic device having a network communication function. As shown in fig. 1, the method comprises the steps of:
and S110, acquiring grid data, load data, distributed power supply data and distribution transformation data of the power distribution network.
The grid can be specifically understood as dividing the urban land into different grids based on the difference between the urban land area division and the land function positioning; distributed power is understood in particular to be applied to new energy power generation devices in power systems, for example photovoltaic power plants, wind power plants, fuel cells, etc.
Specifically, basic information such as grid data of grid number, grid attributes and the like of a grid planning year of a related power distribution network, load data of maximum load, average load and the like, distributed power data of distributed power sources such as installed capacity and power generation on the internet and the like, distribution and transformation data of low-voltage distribution and transformation capacity, voltage levels and the like is read, and basic data is provided for subsequent calculation work.
And S120, counting the grid type, the coverage area, the annual maximum load and the annual maximum network power of the distributed power supply of each grid according to the grid data, the load data, the distributed power supply data and the distribution transformation data.
Specifically, basic information such as grid types, coverage areas, annual maximum loads, annual maximum network power of the distributed power supplies and the like of each grid in historical years is counted, and basic data are provided for subsequent calculation work.
S130, determining the residual capacity density of external connection distribution transformation of each voltage class of each grid connected with other grids and the annual maximum internet power density of the distributed power supply in each grid according to the grid type, the coverage geographical area, the annual maximum load and the annual maximum internet power of the distributed power supply of each grid.
The external contact can be specifically understood as the use condition of the load connected in the power distribution network; distribution transformer is a short term distribution transformer, which is understood to be a static electrical appliance in a distribution system that transfers ac power by transforming ac voltage and current according to the law of electromagnetic induction. The distribution transformer generally refers to a power transformer which runs in a power distribution network, has the voltage grade of 10-35kV (mostly 10kV and below), and the capacity of 6300KVA and below and directly supplies power to end users; the annual maximum internet power generation density of the distributed power supply can be specifically understood as annual maximum internet power generation of the distributed power supply in the grid under a unit area, and does not include power generation power corresponding to a self-use part of the distributed power supply.
Specifically, according to the grid type, the coverage geographical area, the annual maximum load and the annual maximum internet power of the distributed power supply of each grid, the difference between the sum of the external connection distribution transformation capacity of each grid and the annual maximum power load value in each grid is divided by the coverage geographical area of each grid, the residual capacity density of the external connection distribution transformation of each voltage grade of each grid connected with other grids is determined, and the annual maximum internet power generation power density of the distributed power supply in each grid is determined according to the ratio of the annual maximum internet power generation power of the distributed power supply of each grid to the coverage geographical area of each grid.
And S140, calculating the annual maximum internet power density of each distributed power supply in the grids at the same time rate according to the annual maximum internet power density of the distributed power supply in each grid and the coverage area of the grids.
The concurrency rate can be specifically understood as the probability of starting and using electricity of similar electricity utilization objects at the same time, and is used for describing the degree of mutual overlapping electricity utilization of the similar electricity utilization objects.
Specifically, the annual maximum internet power generation power density of each distributed power supply in each grid is calculated according to the annual maximum internet power generation power density of the distributed power supply in each grid and the coverage area of the grid, based on load characteristics and considering the load power consumption condition, namely the probability of starting up and power consumption of similar power consumption objects at the same time for different types of grids.
S150, determining the access scale of the distributed power supplies of each grid in planning year according to the difference value between the annual maximum on-line power generation density and the residual capacity density of each distributed power supply in the grid under the condition of the same time rate and the coverage geographical area of the grid
Specifically, whether the grid has the expansion capability of the distributed power sources is judged according to the difference value between the annual maximum internet power generation power density and the residual capacity density of each distributed power source in the grid at the same time rate, namely according to the density value of the expandable distributed power sources of the grid, if the difference value between the annual maximum internet power generation power density and the residual capacity density of each distributed power source in the grid at the same time rate is larger than 0, namely the density value of the expandable distributed power sources of the grid is larger than 0, the access scale of the distributed power sources of each grid in the planning year is further determined according to the density of the expandable distributed power sources of the grid and the geographic area covered by the grid, and the planned annual grid planning of each city and whole province is summarized to form the whole planning scale; and if the difference between the annual maximum online generated power density and the residual capacity density of each distributed power supply in the grid under the same rate =0, namely the density value of the expandable distributed power supply of the grid =0, the grid does not have the expansion capability of the distributed power supply.
According to the technical scheme of the embodiment of the invention, grid data, load data, distributed power supply data and distribution transformation data of a power distribution network are obtained; counting the grid type, the coverage area, the annual maximum load and the annual maximum network power of the distributed power supply of each grid according to the grid data, the load data, the distributed power supply data and the distribution transformation data; determining the residual capacity density of each voltage class of each grid connected with other grids and the annual maximum internet power density of the distributed power supply in each grid, according to the grid type, the coverage geographical area, the annual maximum load and the annual maximum internet power of the distributed power supply of each grid; according to the annual maximum internet power generation power density of the distributed power sources in each grid and the coverage area of the grid, the annual maximum internet power generation power density of each distributed power source in the grid at the same time rate is calculated for different types of grids; and determining the access scale of the distributed power supplies of each grid in the planning year according to the difference value between the annual maximum internet power generation power density and the residual capacity density of each distributed power supply in the grid under the synchronous rate and the coverage geographical area of the grid. The distributed power supply access scale determining method provided by the embodiment of the invention considers the load characteristics, calculates the distributed power supply access scale on the basis of reading load data such as maximum load, average load and load demand and the like, and judges whether the grid has the distributed power supply access expansion capacity, so that the problem that the bearing capacity of a power distribution network cannot be considered by the conventional planning method is solved; the distributed power supply access scale determining method provided by the embodiment of the invention divides the urban land into different grids for data reading and related model calculation based on the grid division mode, namely based on the difference between the urban land area division and the land function positioning, so that the requirement on planning year data and the complexity of a calculation model thereof are effectively reduced.
Example two
Fig. 2 is a flowchart of a method for determining an access scale of a distributed power supply according to a second embodiment of the present invention, where this embodiment further optimizes, on the basis of the foregoing embodiment, a residual capacity density of an external connection distribution change of each voltage class of connection between each grid and another grid in each grid, an annual maximum internet power generation density of a distributed power supply in each grid, an annual maximum internet power generation density of each distributed power supply in a grid at a same time rate, and a calculation process for planning an access scale of each grid distributed power supply in each year. As shown in fig. 2, the method may include the steps of:
s210, acquiring grid data, load data, distributed power supply data and distribution transformation data of the power distribution network.
The grid can be specifically understood as dividing the urban land into different grids based on the difference between the urban land area division and the land function positioning; distributed power is understood in particular to be applied to new energy power plants in power systems, for example photovoltaic power stations, wind power plants, fuel cells, etc.
Specifically, basic information such as grid data of grid number, grid attributes and the like of a grid planning year of a related power distribution network, load data such as maximum load, average load and the like, distributed power supply data such as installed capacity of a distributed power supply, power generation power on the internet and the like, distribution and transformation data such as low-voltage distribution and transformation capacity, voltage level and the like is read, and basic data is provided for subsequent calculation work.
And S220, counting the grid type, the coverage area, the annual maximum load and the annual maximum internet power of the distributed power supply of each grid according to the grid data, the load data, the distributed power supply data and the distribution transformation data.
Specifically, basic information such as grid types, coverage areas, annual maximum loads, annual maximum internet power of distributed power supplies and the like of historical years of each grid are counted, and basic data are provided for subsequent calculation work.
S230, calculating the difference value between the total value of the external contact distribution transformation capacity of the grid and the annual maximum power load value in the grid; determining the residual capacity density of each voltage class of the grid connected with other grids for the external connection distribution transformer according to the difference value between the sum of the external connection distribution transformer capacity of the grid and the annual maximum power load value in the grid and the ratio of the covered geographic area of the grid; and determining the annual maximum internet power generation power density of the distributed power sources in the grids according to the annual maximum internet power of the distributed power sources in the grids divided by the coverage geographical area of the grids.
Specifically, the formula ρ is adopted re,j ＝(E j -L max，j )/V j And calculating the residual capacity density of the external connection distribution transformation of each voltage class of the grid connected with other grids. Wherein E j Communicate to the outside of grid j the total value of the transformation capacity, L max，j The maximum annual power load value in the grid j is obtained by subtracting the maximum annual power load value in the grid j from the total value of the external connection distribution and transformation capacity of the grid j, namely the difference value between the total value of the external connection distribution and transformation capacity of the grid and the maximum annual power load value in the grid, and V is j Is the geographic area covered by grid j. Using the formula rho pv,j ＝D pv，j /V j And calculating the annual maximum internet power generation power density of the distributed power supply in the grid. Wherein D pv，j The annual maximum online generated power of the grid j distributed power supply means that the generated power corresponding to the self-use part of the distributed power supply is not included, V j Is the geographic area covered by grid j; and dividing the annual maximum internet power generation power of the grid j distributed power supply by the coverage geographical area of the grid j to obtain the annual maximum internet power generation power density of the distributed power supply in the grid.
And S240, calculating the annual maximum internet power generation power density of each distributed power supply in the grid at the same time rate.
In particular, using the formula
And calculating the annual maximum internet power generation power density of each distributed power supply in the grid at the same time rate. Wherein P is i The annual maximum online power generation power density of the distributed power sources i is obtained, and eta is the annual maximum online power generation simultaneous rate of each distributed power source in the grid; v j Is the geographic area covered by the grid j.
And S250, calculating the access scale of the programmable distributed power supply of each grid in the planning year.
Specifically, formula a is adopted j ＝ρ re,j -ρ ch,j Calculating the density of the distributed power supply with the extensible grid by adopting a formula a j *V j And calculating the access scale of the programmable distributed power supply of each grid in the planning year. Where ρ is re,j Representing the remaining capacity density of the external connection distribution transformation of the grid j; rho ch,j Representing the annual maximum of grid j distributed powerGrid power generation power density; a is a j The difference value between the residual capacity density of the external connection distribution transformer of the grid j and the annual maximum online power generation power density of the grid j distributed power supply, namely a j Scalable distributed power density for the grid; v j Is the geographic area covered by grid j; if a is j >0, calculating the access scale of the programmable distributed power supply of each grid in the planning year to be a j *V j Furthermore, the planned annual grid planned distributed power supply access scale of various cities and provinces is further summarized to form an overall planned scale; otherwise, the grid has no distributed power source extension capability, i.e. a j ＝0。
According to the technical scheme of the embodiment of the invention, grid data, load data, distributed power supply data and distribution transformation data of a power distribution network are obtained; according to the grid data, the load data, the distributed power supply data and the distribution transformer data, the grid type, the coverage area, the annual maximum load and the annual maximum internet power of the distributed power supply of each grid are counted; determining the residual capacity density of external connection distribution transformation of each voltage grade of each grid connected with other grids and the annual maximum internet power density of the distributed power supply in each grid according to the grid type, the coverage geographical area, the annual maximum load and the annual maximum internet power of the distributed power supply of each grid; according to the annual maximum internet power generation power density of the distributed power sources in each grid and the coverage area of the grid, the annual maximum internet power generation power density of each distributed power source in the grid at the same time rate is calculated for different types of grids; and determining the access scale of the distributed power supplies of each grid in the planning year according to the difference between the annual maximum internet access power density and the residual capacity density of each distributed power supply in the grid at the same time rate and the coverage geographical area of the grid. The distributed power supply access scale determining method provided by the embodiment of the invention considers the load characteristics, calculates the distributed power supply access scale on the basis of reading load data such as maximum load, average load and load demand and the like, and judges whether the grid has the distributed power supply access expansion capacity, so that the problem that the bearing capacity of a power distribution network cannot be considered by the conventional planning method is solved; the distributed power supply access scale determining method provided by the embodiment of the invention is based on the grid division mode, namely based on the difference between the city land area division and the land function positioning, and divides the city land into different grids for data reading and relevant model calculation, so that the requirement on planning year data and the complexity of a calculation model thereof are effectively reduced.
EXAMPLE III
Fig. 3 is a schematic structural diagram of a distributed power access scale determining apparatus according to a third embodiment of the present invention, where this embodiment is applicable to a situation where a scale plan of a low-voltage distributed power access distribution network is optimized, the distributed power access scale determining apparatus may be implemented in a form of hardware and/or software, and the distributed power access scale determining apparatus may be configured in any electronic device with a network communication function. As shown in fig. 3, the apparatus includes: a grid data acquisition module 310, a grid data statistics module 320, a first calculation module 330, a second calculation module 340, and a distributed power access determination module 350. Wherein:
the power grid data acquisition module 310 is configured to acquire grid data, load data, distributed power data, and distribution transformation data of the power distribution network;
the grid data statistics module 320 is used for counting the grid type, the coverage area, the annual maximum load and the annual maximum internet power of the distributed power supply of each grid according to the grid data, the load data, the distributed power supply data and the distribution transformation data;
the first calculation module 330 is configured to determine, according to the grid type, the coverage geographical area, the annual maximum load, and the annual maximum grid power of the distributed power source of each grid, a remaining capacity density of each voltage class, which is obtained by connecting each grid to another grid, of the external connection distribution transformer, and an annual maximum grid power generation power density of the distributed power source in each grid;
the second calculating module 340 is configured to calculate, for different types of grids, the annual maximum internet power density of each distributed power source in the grid at the same time rate according to the annual maximum internet power density of the distributed power sources in each grid and the coverage area of the grid;
and the distributed power access determining module 350 is configured to determine an access scale of the distributed power of each grid in a planning year according to a difference between a maximum annual grid power generation power density and a remaining capacity density of each distributed power in the grid at the same time rate and a coverage geographical area of the grid.
On the basis of the foregoing embodiment, optionally, the first calculating module 330 is configured to:
calculating the difference value between the total value of the external contact distribution transformation capacity of the grid and the annual maximum power load value in the grid;
and determining the residual capacity density of each voltage class of the grid connected with other grids for the external connection distribution transformer according to the ratio of the difference value of the sum of the external connection distribution transformer capacity of the grid and the annual maximum power load value in the grid to the covered geographic area of the grid.
And determining the annual maximum internet power generation power density of the distributed power sources in the grids according to the annual maximum internet power of the distributed power sources in the grids divided by the coverage geographical area of the grids.
On the basis of the foregoing embodiment, optionally, the second calculating module 340 is configured to:
calculating the annual maximum online power generation power density rho of each distributed power supply in the grid j under the condition of the same time rate by adopting the following formula ch,j
Wherein P is i The annual maximum online power generation power density of the distributed power supply i is obtained, and eta is the annual maximum online power generation concurrence rate of each distributed power supply in the grid; v j Is the geographic area covered by the grid j.
On the basis of the foregoing embodiment, optionally, the distributed power access determining module 350 is configured to:
calculating a j ＝ρ re,j -ρ ch,j Where ρ is re,j Residual capacity density, ρ, representing the external connection distribution of grid j ch And j represents the annual maximum grid power density of the grid j distributed power supply. Such asFruit a j >0, the difference value of the grid and the grid is the density of the grid extensible distributed power supply; otherwise, the grid has no distributed power expansion capability, i.e. a j ＝0；
The access scale of the programmable distributed power supply of each grid in the planning year is a j *V j 。
Further, determining the access scale of the distributed power supplies of each grid in a planning year according to the difference value between the annual maximum internet power generation power density and the residual capacity density of each distributed power supply in the grid at the same time rate and the coverage geographical area of the grid;
and summarizing the planning annual grids of cities and the whole province to plan the access scale of the distributed power supply so as to form the overall planning scale.
The distributed power supply access scale determining device provided by the embodiment of the invention can execute the distributed power supply access scale determining method provided by any embodiment of the invention, and has corresponding functional modules and beneficial effects of the executing method.
Example four
FIG. 4 shows a schematic block diagram of an electronic device 10 that may be used to implement an embodiment of the invention. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smart phones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the inventions described and/or claimed herein.
As shown in fig. 4, the electronic device 10 includes at least one processor 11, and a memory communicatively connected to the at least one processor 11, such as a Read Only Memory (ROM) 12, a Random Access Memory (RAM) 13, and the like, wherein the memory stores a computer program executable by the at least one processor, and the processor 11 can perform various suitable actions and processes according to the computer program stored in the Read Only Memory (ROM) 12 or the computer program loaded from a storage unit 18 into the Random Access Memory (RAM) 13. In the RAM 13, various programs and data necessary for the operation of the electronic apparatus 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other via a bus 14. An input/output (I/O) interface 15 is also connected to bus 14.
A number of components in the electronic device 10 are connected to the I/O interface 15, including: an input unit 16 such as a keyboard, a mouse, or the like; an output unit 17 such as various types of displays, speakers, and the like; a storage unit 18 such as a magnetic disk, an optical disk, or the like; and a communication unit 19 such as a network card, modem, wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information/data with other devices via a computer network such as the internet and/or various telecommunication networks.
The processor 11 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various processors running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, or the like. The processor 11 performs the various methods and processes described above, such as the distributed power access dimensioning method.
In some embodiments, the distributed power access dimensioning method may be implemented as a computer program tangibly embodied on a computer readable storage medium, such as the storage unit 18. In some embodiments, part or all of the computer program may be loaded and/or installed onto the electronic device 10 via the ROM 12 and/or the communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the distributed power access dimensioning method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform the distributed power access dimensioning method in any other suitable manner (e.g., by means of firmware).
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuitry, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), system on a chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.
A computer program for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer programs, when executed by the processor, cause the functions/acts specified in the flowchart and/or block diagram block or blocks to be performed. A computer program can execute entirely on a machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of the present invention, a computer-readable storage medium may be a tangible medium that can contain, or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. A computer readable storage medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, the computer readable storage medium may be a machine readable signal medium. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user can provide input to the electronic device. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic, speech, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), blockchain networks, and the internet.
The computing system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also called a cloud computing server or a cloud host, and is a host product in a cloud computing service system, so that the defects of high management difficulty and weak service expansibility in the traditional physical host and VPS service are overcome.
It should be understood that various forms of the flows shown above, reordering, adding or deleting steps, may be used. For example, the steps described in the present invention may be executed in parallel, sequentially, or in different orders, and are not limited herein as long as the desired results of the technical solution of the present invention can be achieved.
The above-described embodiments should not be construed as limiting the scope of the invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A method for determining the access scale of a distributed power supply is characterized by comprising the following steps:
acquiring grid data, load data, distributed power supply data and distribution transform data of a power distribution network;
counting the grid type, the coverage area, the annual maximum load and the annual maximum network power of the distributed power supply of each grid according to the grid data, the load data, the distributed power supply data and the distribution transformation data;
determining the residual capacity density of each voltage class of each grid connected with other grids and the annual maximum internet power generation density of the distributed power supply in each grid according to the grid type, the coverage geographical area, the annual maximum load and the annual maximum internet power of the distributed power supply of each grid;
according to the annual maximum internet power generation power density of the distributed power sources in each grid and the coverage area of the grids, calculating the annual maximum internet power generation power density of each distributed power source in the grids at the same time rate aiming at different types of grids;
and determining the access scale of the distributed power supplies of each grid in the planning year according to the difference value between the annual maximum internet power generation power density and the residual capacity density of each distributed power supply in the grid under the condition of the same time rate and the coverage geographical area of the grid.
2. The method of claim 1, wherein determining the remaining capacity density of each voltage class of each grid connected to other grids and the annual maximum power density of the distributed power sources in each grid according to the grid type, the coverage geographical area, the annual maximum load, and the annual maximum power density of the distributed power sources in each grid comprises:
calculating the difference value between the total value of the external contact distribution transformation capacity of the grid and the annual maximum power load value in the grid;
and determining the residual capacity density of each voltage grade connected with other grids according to the difference value between the sum of the external connection distribution transformer capacity of the grids and the annual maximum power load value in the grids and the ratio of the covered geographic area of the grids.
3. The method of claim 1, wherein determining the remaining capacity density of each voltage class of each grid connected to other grids and the annual maximum power density of the distributed power sources in each grid according to the grid type, the coverage geographical area, the annual maximum load, and the annual maximum power density of the distributed power sources in each grid comprises:
and determining the annual maximum internet power generation power density of the distributed power sources in the grid according to the annual maximum internet power of the distributed power sources in the grid divided by the coverage geographical area of the grid.
4. The method of claim 1, wherein calculating the annual maximum grid power density of each distributed power source in the grid at the same time rate for different types of the grids according to the annual maximum grid power density of the distributed power sources in each grid and the coverage area of the grid comprises calculating the annual maximum grid power density ρ of each distributed power source in the grid j at the same time rate by using the following formula ch,j
Wherein P is i The annual maximum online power generation power density of the distributed power sources i is obtained, and eta is the annual maximum online power generation simultaneous rate of each distributed power source in the grid; v j Is the geographic area covered by the grid j.
5. The method of claim 4, wherein determining the access size of the distributed power sources planning each grid in the year according to the difference between the annual maximum grid power generation power density and the residual capacity density of each distributed power source in the grid at the same time rate and the coverage geographical area of the grid comprises:
calculating a j ＝ρ re,j -ρ ch,j Where ρ is re,j Representing the remaining capacity density, ρ, of the grid j external connection distribution ch,j And the annual maximum network power generation density of the grid j distributed power supply is shown. If a is j If the difference value is greater than 0, the difference value is the density of the grid expandable distributed power supply; otherwise, the grid has no distributed power source extension capability, i.e. a j ＝0；
The access scale of the programmable distributed power supply of each grid in the planning year is a j *V j 。
6. The method according to any one of claims 1 to 5, wherein after determining the access size of the distributed power sources planning each grid in the year according to the difference between the annual maximum grid power generation density and the residual capacity density of each distributed power source in the grid at the same time rate and the coverage geographic area of the grid, the method further comprises:
and summarizing the planning annual grids of cities and provinces in all regions, and planning the access scale of the distributed power supply to form the overall planning scale.
7. A distributed power supply access scale determining apparatus, comprising:
the power grid data acquisition module is used for acquiring grid data, load data, distributed power supply data and distribution transformation data of the power distribution network;
the grid data statistics module is used for carrying out statistics on the grid type, the coverage area, the annual maximum load and the annual maximum network power of the distributed power supply of each grid according to the grid data, the load data, the distributed power supply data and the distribution transformer data;
the first calculation module is used for determining the residual capacity density of each voltage grade of connection between each grid and other grids and the annual maximum internet power density of the distributed power supply in each grid according to the grid type, the coverage geographical area, the annual maximum load and the annual maximum internet power of the distributed power supply in each grid;
the second calculation module is used for calculating the annual maximum internet power generation power density of each distributed power supply in the grids at the same time rate aiming at different types of grids according to the annual maximum internet power generation power density of the distributed power supply in each grid and the coverage area of the grid;
and the distributed power access determining module is used for determining the access scale of the distributed power of each grid in the planning year according to the difference value between the annual maximum internet access power density and the residual capacity density of each distributed power in the grid at the same time rate and the coverage geographical area of the grid.
8. An electronic device, characterized in that the electronic device comprises:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores a computer program executable by the at least one processor, the computer program being executable by the at least one processor to enable the at least one processor to perform the distributed power access size determination method of any one of claims 1-6.
9. A computer-readable storage medium storing computer instructions for causing a processor to implement the distributed power access size determination method of any one of claims 1 to 4 when executed.
10. A computer program product, characterized in that the computer program product comprises a computer program which, when executed by a processor, implements a distributed power access dimensioning method according to any one of claims 1-6.
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