CN113507120A - Method and device for calculating bearing capacity and electronic equipment - Google Patents
Method and device for calculating bearing capacity and electronic equipment Download PDFInfo
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Abstract
The invention provides a method, a device and electronic equipment for calculating bearing capacity, wherein the method comprises the following steps: acquiring a power grid data set in a target time period from a power grid dispatching automation system based on a data interface; converting the power grid data set into target power grid data of a plurality of target devices in a format supported by the distributed photovoltaic bearing capacity computing system, and inputting the target power grid data into the distributed photovoltaic bearing capacity computing system; and determining the bearing capacity of the target equipment according to the calculation result of the distributed photovoltaic bearing capacity calculation system. By the method, the device and the electronic equipment for calculating the bearing capacity, manual data input is not needed, the working difficulty is greatly reduced, the working time consumption is shortened, the calculation efficiency can be greatly improved, and the problem of calculation errors caused by manual errors can be solved.
Description
Technical Field
The invention relates to the technical field of bearing capacity calculation, in particular to a method and a device for calculating bearing capacity, electronic equipment and a computer readable storage medium.
Background
The bearing capacity in the power grid is also called as bearing capacity, refers to the bearing capacity for power supply and load fluctuation, and generally refers to the maximum capacity of the power supply and load which can be borne by the power grid under the conditions that equipment or nodes are not overloaded continuously and the voltage, short-circuit current and harmonic waves are not overproof.
For Distributed power systems, the corresponding load capacity can be determined based on a Distributed photovoltaic load capacity computing system (DPCCS). However, because there are many devices in the power grid and data of a certain period of time needs to be operated to calculate the bearing capacity, the amount of data required by the DPCCS to calculate the bearing capacity is large, and it is difficult to calculate the bearing capacity quickly.
Disclosure of Invention
In order to solve the existing technical problem, embodiments of the present invention provide a method and an apparatus for calculating a bearing capacity, an electronic device, and a computer-readable storage medium.
In a first aspect, an embodiment of the present invention provides a method for calculating a load bearing capacity, including:
acquiring a power grid data set in a target time period from a power grid dispatching automation system based on a data interface;
converting the power grid data set into target power grid data of a plurality of target devices in a format supported by a distributed photovoltaic bearing capacity calculation system, and inputting the target power grid data into the distributed photovoltaic bearing capacity calculation system;
and determining the bearing capacity of the target equipment according to the calculation result of the distributed photovoltaic bearing capacity calculation system.
In one possible implementation, the converting the grid data set into target grid data of a plurality of target devices in a format supported by a distributed photovoltaic capacity computing system includes:
determining the subordination relation among the devices in the power grid according to a preset power grid topological structure;
converting the power grid data set into intermediate power grid data of intermediate equipment in a format supported by the distributed photovoltaic bearing capacity computing system;
and determining the intermediate equipment belonging to the target equipment according to the subordination relation, and calculating the target power grid data of the target equipment according to the intermediate power grid data of all the intermediate equipment belonging to the target equipment.
In one possible implementation, the converting the grid data set into intermediate grid data of an intermediate device in a format supported by a distributed photovoltaic bearing capacity computing system includes:
extracting historical power grid data of the intermediate equipment from the power grid data set;
data element d of historical grid data of intermediate devicei,jData element d 'as the intermediate device'k(ii) a Wherein the data element di,jFor the data element in the ith row and the jth column in the historical power grid data of the intermediate equipment, i belongs to [1, m ∈]，j∈[1,n]And k is i × n + j-n, k ∈ [1, m × n ∈]；
All the data elements d 'of the intermediate device'kSequentially arranging intermediate grid data d 'forming the intermediate device'1,d'2,…,d'k,…,d'm×n。
In one possible implementation, the extracting historical grid data of the intermediate device from the grid data set includes:
sorting the power grid data sets for the first time according to date fields, and then sorting the power grid data sets for the second time according to equipment name fields, wherein the second sorting adopts a bubbling sorting method;
and taking the n rows of data corresponding to the equipment name field of the intermediate equipment in the power grid data set as historical power grid data of the intermediate equipment.
In one possible implementation, after determining the bearing capacity of the target device according to the calculation result of the distributed photovoltaic bearing capacity calculation system, the method further includes:
determining a grade to which the bearing capacity of the target equipment belongs, and determining a color corresponding to the grade;
and updating the color of the line corresponding to the target device in the power grid topological structure to be the color corresponding to the grade.
In a second aspect, an embodiment of the present invention further provides a device for calculating a bearing capacity, including:
the data acquisition module is used for acquiring a power grid data set in a target time period from the power grid dispatching automation system based on the data interface;
the data conversion module is used for converting the power grid data set into target power grid data of a plurality of target devices in a format supported by the distributed photovoltaic bearing capacity calculation system and inputting the target power grid data into the distributed photovoltaic bearing capacity calculation system;
and the data calculation module is used for determining the bearing capacity of the target equipment according to the calculation result of the distributed photovoltaic bearing capacity calculation system.
In one possible implementation, the data conversion module converting the grid data set into target grid data of a plurality of target devices in a format supported by a distributed photovoltaic load-bearing computing system includes:
determining the subordination relation among the devices in the power grid according to a preset power grid topological structure;
converting the power grid data set into intermediate power grid data of intermediate equipment in a format supported by the distributed photovoltaic bearing capacity computing system;
and determining the intermediate equipment belonging to the target equipment according to the subordination relation, and calculating the target power grid data of the target equipment according to the intermediate power grid data of all the intermediate equipment belonging to the target equipment.
In one possible implementation, the data conversion module converting the grid data set into intermediate grid data of an intermediate device in a format supported by a distributed photovoltaic load-bearing computing system includes:
extracting historical power grid data of the intermediate equipment from the power grid data set;
data element d of historical grid data of intermediate devicei,jData element d 'as the intermediate device'k(ii) a Wherein the data element di,jFor the data element in the ith row and the jth column in the historical power grid data of the intermediate equipment, i belongs to [1, m ∈]，j∈[1,n]And k is i × n + j-n, k ∈ [1, m × n ∈]；
All the data elements d 'of the intermediate device'kSequentially arranging intermediate grid data d 'forming the intermediate device'1,d'2,…,d'k,…,d'm×n。
In a third aspect, an embodiment of the present invention provides an electronic device, which includes a bus, a transceiver, a memory, a processor, and a computer program stored on the memory and executable on the processor, where the transceiver, the memory, and the processor are connected via the bus, and when the computer program is executed by the processor, the steps in any one of the above methods for calculating a load capacity are implemented.
In a fourth aspect, the embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the steps in the method for calculating a load power described in any one of the above.
According to the method, the device, the electronic equipment and the computer readable storage medium for calculating the bearing capacity, which are provided by the embodiment of the invention, the required power grid data set is obtained from the power grid dispatching automation system, and the power grid data set is converted into the target power grid data of the target equipment in the format supported by the distributed photovoltaic bearing capacity calculation system, so that the bearing capacity of the target equipment can be conveniently calculated based on the distributed photovoltaic bearing capacity calculation system. According to the method, manual data input is not needed, the work difficulty is greatly reduced, the work time consumption is shortened, the calculation efficiency can be greatly improved, and the problem of calculation errors caused by manual errors can be avoided.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments or the background art of the present invention, the drawings required to be used in the embodiments or the background art of the present invention will be described below.
Fig. 1 is a flowchart illustrating a method for calculating a load bearing capacity according to an embodiment of the present invention;
fig. 2 is a schematic diagram illustrating a power grid topology in a method for calculating a load according to an embodiment of the present invention;
FIG. 3 is a schematic structural diagram of an apparatus for calculating a load bearing capacity according to an embodiment of the present invention;
fig. 4 shows a schematic structural diagram of an electronic device for performing a method for calculating a load bearing capacity according to an embodiment of the present invention.
Detailed Description
The embodiments of the present invention will be described below with reference to the drawings.
Fig. 1 shows a flowchart of a method for calculating a load bearing capacity according to an embodiment of the present invention. As shown in fig. 1, the method includes:
step 101: and acquiring a power grid data set in the target time period from the power grid dispatching automation system based on the data interface.
The power grid dispatching automation system, such as the IES600, is an open power control center application integration platform that adopts domestic and foreign electronic information technologies and various system technologies, and supports a component system structure based on a middleware technology, including a Common Information Model (CIM) -based information organization mode, a Component Interface Specification (CIS) -based data access, and the like. Because the power grid dispatching automation system can collect power grid data such as current, voltage and the like generated in the power grid operation process, the embodiment of the invention obtains the original data for calculating the bearing capacity, namely the power grid data set, from the power grid dispatching automation system.
In the embodiment of the invention, a data interface for acquiring data is developed in advance, and the data interface can receive data in a specified date from a power grid dispatching automation system; in addition, optionally, because the data generated by the power grid dispatching automation system is numerous and complex, and only part of the data is needed when the bearing capacity is calculated, the data interface can also set the required data type, that is, the power grid dispatching automation system only returns the power grid data of the data type specified by the data interface. In the embodiment of the invention, the data stored in the power grid dispatching automation system is the generated power grid data, so the data is called historical power grid data in the embodiment, and each device corresponds to the historical power grid data. When the bearing capacity needs to be calculated, the required time, namely the target time period is specified, and historical power grid data of the devices in the target time period are combined into a power grid data set.
Step 102: and converting the power grid data set into target power grid data of a plurality of target devices in a format supported by the distributed photovoltaic bearing capacity calculation system, and inputting the target power grid data into the distributed photovoltaic bearing capacity calculation system.
Step 103: and determining the bearing capacity of the target equipment according to the calculation result of the distributed photovoltaic bearing capacity calculation system.
In the embodiment of the invention, a large amount of historical power grid data can be conveniently and quickly acquired from the power grid dispatching automation system through the data interface, so that the efficiency of acquiring the power grid data can be improved; however, the distributed photovoltaic bearing capacity calculation system DPCCS needs data in a specific format when calculating the bearing capacity, which is different from the format output by the power grid dispatching automation system, so that the embodiment of the present invention needs to convert the power grid data set into data in a specific format.
Specifically, the grid data set includes historical grid data of a plurality of devices, and some or all of the devices may be used as target devices to calculate the bearing capacity of the target devices; generally, a transformer, a breaker, a transformer, a bus and the like can be selected as target equipment. Accordingly, the corresponding historical grid data in the grid data set can be converted into grid data of the target device, that is, target grid data, and the target grid data conforms to a format supported by the distributed photovoltaic load capacity computing system. And then target power grid data of the target equipment can be input into the distributed photovoltaic bearing capacity calculation system, and the bearing capacity of the target equipment can be calculated by utilizing the function of calculating the bearing capacity of the distributed photovoltaic bearing capacity calculation system.
According to the method for calculating the bearing capacity, the required power grid data set is obtained from the power grid dispatching automation system, and the power grid data set is converted into the target power grid data of the target devices in the format supported by the distributed photovoltaic bearing capacity calculation system, so that the bearing capacity of the target devices can be conveniently calculated based on the distributed photovoltaic bearing capacity calculation system. According to the method, manual data input is not needed, the work difficulty is greatly reduced, the work time consumption is shortened, the calculation efficiency can be greatly improved, and the problem of calculation errors caused by manual errors can be avoided.
On the basis of the foregoing embodiment, the step 102 "converting the grid data set into target grid data of a plurality of target devices in a format supported by the distributed photovoltaic bearing capacity computing system" may specifically include:
step A1: and determining the subordination relation among the devices in the power grid according to a preset power grid topological structure.
In the embodiment of the invention, the power grid is provided with a corresponding topological structure in advance, namely a power grid topological structure, so as to represent the connection relation among all devices in the power grid. On the basis of the power grid topology, the dependencies between the devices in the power grid can be determined, i.e. to which device a device belongs, or to which device a device is a superordinate device, etc. A schematic diagram of a power grid topology structure can be seen from fig. 2, taking a bus "110 kV longport west station 110kVI bus" and transformers "longport west station #1 main transformer" and "longport west station #2 main transformer" in fig. 2 as an example, based on the power grid topology structure, two transformers "longport west station #1 main transformer" and "longport west station #2 main transformer" are subordinate to the bus "110 kV longport west station 110kVI bus", that is, they are subordinate devices of the bus "110 kV longport west station 110kVI bus"; or, the bus "110 kV longport west station 110kVI bus" is the superior device of the transformer "longport west station #1 main transformer" and "longport west station #2 main transformer".
Step A2: and converting the power grid data set into intermediate power grid data of the intermediate equipment in a format supported by the distributed photovoltaic bearing capacity calculation system.
Step A3: and determining the intermediate equipment belonging to the target equipment according to the subordination relation, and calculating the target power grid data of the target equipment according to the intermediate power grid data of all the intermediate equipment belonging to the target equipment.
In the embodiment of the present invention, the intermediate device is a device included in the power grid data set, that is, the power grid data set includes historical power grid data of the intermediate device. If the grid data set does not include the target device, the embodiment first determines the intermediate grid data of the intermediate device, and then determines the target grid data of the corresponding target device according to the dependency relationship. Still taking the example shown in fig. 2, if the target device is the bus "110 kV longport west station 110kVI mother", the intermediate devices belonging to the target device include the "longport west station #1 main transformer" and the "longport west station #2 main transformer", so that the target grid data of the target device can be calculated based on the intermediate grid data of the "longport west station #1 main transformer" and the "longport west station #2 main transformer". For example, the sum of the active power of the two transformers is the active power of the target device.
It should be noted that the historical grid data, the intermediate grid data, and the target grid data are all grid-related data, but differences may exist between them. For example, the historical grid data is raw data collected by the grid dispatching automation system, and mainly includes voltage, current, and the like, while the intermediate grid data and the target grid data are processed data, which may include voltage, current, active power, reactive power, and the like that need to be calculated, and specifically, data included in the intermediate grid data and the target grid data may be determined based on which data is needed by the DPCCS to calculate the bearing capacity.
Optionally, the step a2 "converting the grid data set into the intermediate grid data of the intermediate device in the format supported by the distributed photovoltaic bearing capacity calculation system" specifically includes:
step A21: historical grid data of the intermediate device is extracted from the grid data set.
In the embodiment of the invention, the power grid data set comprises data of a plurality of intermediate devices, namely historical power grid data, and the historical power grid data of the intermediate devices can be directly extracted from the power grid data set.
Optionally, a problem of data misalignment may exist in a power grid data set generated by the power grid dispatching automation system, in this embodiment, the power grid data set is sorted first, and then, historical power grid data of each intermediate device is extracted in a unified manner. Specifically, the step a21 "extracting historical grid data of the intermediate device from the grid data set" may specifically include: the power grid data sets are sorted for the first time according to the date field, then the power grid data sets are sorted for the second time according to the equipment name field, and the second sorting adopts a bubble sorting method; and taking the n rows of data corresponding to the equipment name field of the intermediate equipment in the power grid data set as historical power grid data of the intermediate equipment.
In the embodiment of the invention, the power grid dispatching automation system sequentially generates data according to the time sequence, and the numerical values in the date fields are set from small to large according to the time sequence. And then, performing second sequencing according to the equipment name fields, so that the power grid data with the same equipment name (namely the same value of the equipment name fields) can be ensured to be arranged together, and the power grid data in a matrix form, namely historical power grid data, is formed. And a bubble sorting method is adopted during the second sorting, and for the power grid data with the same equipment name, the time sequence is not interfered by the second sorting, so that the multiple lines of power grid data determined after the second sorting are also arranged according to the time sequence, and the historical power grid data arranged according to the time can be directly extracted in blocks based on the equipment name.
Step A22: data element d of historical grid data of intermediate devicei,jData element d 'as an intermediate device'k(ii) a Wherein the data element di,jFor the data element in the ith row and the jth column in the historical power grid data of the intermediate equipment, i belongs to [1, m ∈]，j∈[1,n]And k is i × n + j-n, k ∈ [1, m × n ∈]。
Step A23: all data elements d 'of the intermediate device'kIntermediate network data d 'forming intermediate devices are arranged in sequence'1,d'2,…,d'k,…,d'm×n。
Since the power grid data set collected from the power grid dispatching automation system is in a specific format, that is, the historical power grid data of the intermediate device conforms to the format supported by the power grid dispatching automation system, it needs to be converted into the data in the DPCCS supported format, that is, the intermediate power grid data. In the embodiment of the present invention, the historical grid data of the intermediate device is essentially data in a matrix form, for example, data in m rows and n columns, and the embodiment converts the historical grid data into data in an array form supported by the DPCCS. Specifically, a data element d of historical grid datai,jData element d 'as an intermediate device'kI.e. d'k＝di,jIs thus based on a plurality of data elements d'kCombined to form intermediate grid data d'1,d'2,…,d'k,…,d'm×n. And k is i × n + j-n, so as to ensure that the time sequence of the data elements in the intermediate power grid data is the same as that of the data elements in the historical power grid data.
In the embodiment of the invention, more complete target power grid data of the target equipment can be determined through the power grid topological structure; data element d of historical power grid datai,jData element d 'as an intermediate device'kFormat conversion can be realized rapidly; and k is i × n + j-n, the time sequence of data elements in the intermediate power grid data can be ensured to be the same as that of data elements in the historical power grid data, and the converted target power grid data can be conveniently and directly input to the DPCCS to calculate the bearing capacity.
Optionally, after the step 103 "determining the bearing capacity of the target device according to the calculation result of the distributed photovoltaic bearing capacity calculation system", the method further includes:
step B1: and determining the grade to which the bearing capacity of the target equipment belongs, and determining the color corresponding to the grade.
Step B2: and updating the color of the line corresponding to the target equipment in the power grid topological structure to be the color corresponding to the grade.
In the embodiment of the invention, a plurality of bearing capacity grades are preset, and corresponding colors are set for each grade. For example, four levels are set, and the colors are set for the levels in order from high to low in bearing capacity: green, orange, yellow, red. After the grade corresponding to the target equipment is determined, the color of the target equipment can be determined, and the line corresponding to the target equipment in the power grid topological structure is displayed in the color, so that a user can quickly locate the line with possible problems based on the power grid topological structure. As shown in fig. 2, if the target device is "110 kV longport west station 110kVI parent", and the bearing capacity of the target device is the highest level, the color of the line corresponding to the target device is green, and the line from "110 kV longport west station 110kVI parent" to "longport west station #1 main transformer" and "longport west station #2 main transformer" can be set to green.
The method for calculating bearing capacity according to the embodiment of the present invention is described above in detail, and the method may also be implemented by a corresponding apparatus.
Fig. 3 shows a schematic structural diagram of an apparatus for calculating a bearing capacity according to an embodiment of the present invention. As shown in fig. 3, the apparatus for calculating a load-bearing capacity includes:
the data acquisition module 31 is configured to acquire a power grid data set in a target time period from a power grid dispatching automation system based on a data interface;
a data conversion module 32, configured to convert the power grid data set into target power grid data of a plurality of target devices in a format supported by a distributed photovoltaic bearing capacity calculation system, and input the target power grid data into the distributed photovoltaic bearing capacity calculation system;
and the data calculation module 33 is configured to determine the bearing capacity of the target device according to a calculation result of the distributed photovoltaic bearing capacity calculation system.
On the basis of the foregoing embodiment, the converting, by the data conversion module 32, the grid data set into target grid data of a plurality of target devices in a format supported by the distributed photovoltaic bearing capacity computing system includes:
determining the subordination relation among the devices in the power grid according to a preset power grid topological structure;
converting the power grid data set into intermediate power grid data of intermediate equipment in a format supported by the distributed photovoltaic bearing capacity computing system;
and determining the intermediate equipment belonging to the target equipment according to the subordination relation, and calculating the target power grid data of the target equipment according to the intermediate power grid data of all the intermediate equipment belonging to the target equipment.
On the basis of the foregoing embodiment, the converting, by the data conversion module 32, the grid data set into intermediate grid data of an intermediate device in a format supported by the distributed photovoltaic bearing capacity computing system includes:
extracting historical power grid data of the intermediate equipment from the power grid data set;
data element d of historical grid data of intermediate devicei,jData element d 'as the intermediate device'k(ii) a Wherein the data element di,jFor the data element in the ith row and the jth column in the historical power grid data of the intermediate equipment, i belongs to [1, m ∈]，j∈[1,n]And k is i × n + j-n, k ∈ [1, m × n ∈]；
All the data elements d 'of the intermediate device'kSequentially arranging intermediate grid data d 'forming the intermediate device'1,d'2,…,d'k,…,d'm×n。
On the basis of the foregoing embodiment, the extracting, by the data conversion module 32, the historical grid data of the intermediate device from the grid data set includes:
sorting the power grid data sets for the first time according to date fields, and then sorting the power grid data sets for the second time according to equipment name fields, wherein the second sorting adopts a bubbling sorting method;
and taking the n rows of data corresponding to the equipment name field of the intermediate equipment in the power grid data set as historical power grid data of the intermediate equipment.
On the basis of the above embodiment, the device further comprises a display module;
after determining the bearing capacity of the target device according to the calculation result of the distributed photovoltaic bearing capacity calculation system, the display module is configured to:
determining a grade to which the bearing capacity of the target equipment belongs, and determining a color corresponding to the grade;
and updating the color of the line corresponding to the target device in the power grid topological structure to be the color corresponding to the grade.
In addition, an embodiment of the present invention further provides an electronic device, which includes a bus, a transceiver, a memory, a processor, and a computer program stored in the memory and capable of running on the processor, where the transceiver, the memory, and the processor are connected via the bus, respectively, and when the computer program is executed by the processor, the processes in the embodiment of the method for calculating a load bearing capability are implemented, and the same technical effect can be achieved, and details are not described here to avoid repetition.
Specifically, referring to fig. 4, an embodiment of the present invention further provides an electronic device, which includes a bus 1110, a processor 1120, a transceiver 1130, a bus interface 1140, a memory 1150, and a user interface 1160.
In an embodiment of the present invention, the electronic device further includes: a computer program stored on the memory 1150 and executable on the processor 1120, the computer program, when executed by the processor 1120, implementing the various processes of the above-described method of computing a load capacity embodiment.
A transceiver 1130 for receiving and transmitting data under the control of the processor 1120.
In embodiments of the invention in which a bus architecture (represented by bus 1110) is used, bus 1110 may include any number of interconnected buses and bridges, with bus 1110 connecting various circuits including one or more processors, represented by processor 1120, and memory, represented by memory 1150.
Bus 1110 represents one or more of any of several types of bus structures, including a memory bus, and memory controller, a peripheral bus, an Accelerated Graphics Port (AGP), a processor, or a local bus using any of a variety of bus architectures. By way of example, and not limitation, such architectures include: an Industry Standard Architecture (ISA) bus, a Micro Channel Architecture (MCA) bus, an Enhanced ISA (EISA) bus, a Video Electronics Standards Association (VESA), a Peripheral Component Interconnect (PCI) bus.
The bus 1110 may also connect various other circuits such as peripherals, voltage regulators, or power management circuits to provide an interface between the bus 1110 and the transceiver 1130, as is well known in the art. Therefore, the embodiments of the present invention will not be further described.
The transceiver 1130 may be one element or may be multiple elements, such as multiple receivers and transmitters, providing a means for communicating with various other apparatus over a transmission medium. For example: the transceiver 1130 receives external data from other devices, and the transceiver 1130 transmits data processed by the processor 1120 to other devices. Depending on the nature of the computer system, a user interface 1160 may also be provided, such as: touch screen, physical keyboard, display, mouse, speaker, microphone, trackball, joystick, stylus.
It is to be appreciated that in embodiments of the invention, the memory 1150 may further include memory located remotely with respect to the processor 1120, which may be coupled to a server via a network. One or more portions of the above-described networks may be an ad hoc network (ad hoc network), an intranet (intranet), an extranet (extranet), a Virtual Private Network (VPN), a Local Area Network (LAN), a Wireless Local Area Network (WLAN), a Wide Area Network (WAN), a Wireless Wide Area Network (WWAN), a Metropolitan Area Network (MAN), the Internet (Internet), a Public Switched Telephone Network (PSTN), a plain old telephone service network (POTS), a cellular telephone network, a wireless fidelity (Wi-Fi) network, and combinations of two or more of the above. For example, the cellular telephone network and the wireless network may be a global system for Mobile Communications (GSM) system, a Code Division Multiple Access (CDMA) system, a Worldwide Interoperability for Microwave Access (WiMAX) system, a General Packet Radio Service (GPRS) system, a Wideband Code Division Multiple Access (WCDMA) system, a Long Term Evolution (LTE) system, an LTE Frequency Division Duplex (FDD) system, an LTE Time Division Duplex (TDD) system, a long term evolution-advanced (LTE-a) system, a Universal Mobile Telecommunications (UMTS) system, an enhanced Mobile Broadband (eMBB) system, a mass Machine Type Communication (mtc) system, an Ultra Reliable Low Latency Communication (urrllc) system, or the like.
It is to be understood that the memory 1150 in embodiments of the present invention can be either volatile memory or nonvolatile memory, or can include both volatile and nonvolatile memory. Wherein the nonvolatile memory includes: Read-Only Memory (ROM), Programmable ROM (PROM), Erasable PROM (EPROM), Electrically Erasable PROM (EEPROM), or Flash Memory.
The volatile memory includes: random Access Memory (RAM), which acts as an external cache. By way of example, and not limitation, many forms of RAM are available, such as: static random access memory (Static RAM, SRAM), Dynamic random access memory (Dynamic RAM, DRAM), Synchronous Dynamic random access memory (Synchronous DRAM, SDRAM), Double Data Rate Synchronous Dynamic random access memory (Double Data Rate SDRAM, DDRSDRAM), Enhanced Synchronous DRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), and Direct memory bus RAM (DRRAM). The memory 1150 of the electronic device described in the embodiments of the invention includes, but is not limited to, the above and any other suitable types of memory.
In an embodiment of the present invention, memory 1150 stores the following elements of operating system 1151 and application programs 1152: an executable module, a data structure, or a subset thereof, or an expanded set thereof.
Specifically, the operating system 1151 includes various system programs such as: a framework layer, a core library layer, a driver layer, etc. for implementing various basic services and processing hardware-based tasks. Applications 1152 include various applications such as: media Player (Media Player), Browser (Browser), for implementing various application services. A program implementing a method of an embodiment of the invention may be included in application program 1152. The application programs 1152 include: applets, objects, components, logic, data structures, and other computer system executable instructions that perform particular tasks or implement particular abstract data types.
In addition, an embodiment of the present invention further provides a computer-readable storage medium, where a computer program is stored, and when the computer program is executed by a processor, the computer program implements each process of the above method for calculating a load bearing capability, and can achieve the same technical effect, and in order to avoid repetition, details are not repeated here.
The computer-readable storage medium includes: permanent and non-permanent, removable and non-removable media may be tangible devices that retain and store instructions for use by an instruction execution apparatus. The computer-readable storage medium includes: electronic memory devices, magnetic memory devices, optical memory devices, electromagnetic memory devices, semiconductor memory devices, and any suitable combination of the foregoing. The computer-readable storage medium includes: phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), non-volatile random access memory (NVRAM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic tape cartridge storage, magnetic tape disk storage or other magnetic storage devices, memory sticks, mechanically encoded devices (e.g., punched cards or raised structures in a groove having instructions recorded thereon), or any other non-transmission medium useful for storing information that may be accessed by a computing device. As defined in embodiments of the present invention, the computer-readable storage medium does not include transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission medium (e.g., optical pulses traveling through a fiber optic cable), or electrical signals transmitted through a wire.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus, electronic device and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the modules or units is only one logical division, and there may be other divisions in actual implementation, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may also be an electrical, mechanical or other form of connection.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one position, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to solve the problem to be solved by the embodiment of the invention.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the embodiments of the present invention may be substantially or partially contributed by the prior art, or all or part of the technical solutions may be embodied in a software product stored in a storage medium and including instructions for causing a computer device (including a personal computer, a server, a data center, or other network devices) to execute all or part of the steps of the methods of the embodiments of the present invention. And the storage medium includes various media that can store the program code as listed in the foregoing.
In the description of the embodiments of the present invention, it should be apparent to those skilled in the art that the embodiments of the present invention can be embodied as methods, apparatuses, electronic devices, and computer-readable storage media. Thus, embodiments of the invention may be embodied in the form of: entirely hardware, entirely software (including firmware, resident software, micro-code, etc.), a combination of hardware and software. Furthermore, in some embodiments, embodiments of the invention may also be embodied in the form of a computer program product in one or more computer-readable storage media having computer program code embodied in the medium.
The computer-readable storage media described above may take any combination of one or more computer-readable storage media. The computer-readable storage medium includes: an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of the computer-readable storage medium include: a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only Memory (ROM), an erasable programmable read-only Memory (EPROM), a Flash Memory, an optical fiber, a compact disc read-only Memory (CD-ROM), an optical storage device, a magnetic storage device, or any combination thereof. In embodiments of the invention, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, device, or apparatus.
The computer program code embodied on the computer readable storage medium may be transmitted using any appropriate medium, including: wireless, wire, fiber optic cable, Radio Frequency (RF), or any suitable combination thereof.
Computer program code for carrying out operations for embodiments of the present invention may be written in assembly instructions, Instruction Set Architecture (ISA) instructions, machine related instructions, microcode, firmware instructions, state setting data, integrated circuit configuration data, or in one or more programming languages, including an object oriented programming language, such as: java, Smalltalk, C + +, and also include conventional procedural programming languages, such as: c or a similar programming language. The computer program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be over any of a variety of networks, including: a Local Area Network (LAN) or a Wide Area Network (WAN), which may be connected to the user's computer, may be connected to an external computer.
The method, the device and the electronic equipment are described through the flow chart and/or the block diagram.
It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer-readable program instructions. These computer-readable program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks.
These computer-readable program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing apparatus to function in a particular manner. Thus, the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means which implement the function/act specified in the flowchart and/or block diagram block or blocks.
The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide processes for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks.
The above description is only a specific implementation of the embodiments of the present invention, but the scope of the embodiments of the present invention is not limited thereto, and any person skilled in the art can easily conceive of changes or substitutions within the technical scope of the embodiments of the present invention, and all such changes or substitutions should be covered by the scope of the embodiments of the present invention. Therefore, the protection scope of the embodiments of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. A method of calculating a load bearing force, comprising:
acquiring a power grid data set in a target time period from a power grid dispatching automation system based on a data interface;
converting the power grid data set into target power grid data of a plurality of target devices in a format supported by a distributed photovoltaic bearing capacity calculation system, and inputting the target power grid data into the distributed photovoltaic bearing capacity calculation system;
and determining the bearing capacity of the target equipment according to the calculation result of the distributed photovoltaic bearing capacity calculation system.
2. The method of claim 1, wherein converting the grid data set to target grid data for a plurality of target devices in a format supported by a distributed photovoltaic capacity computing system comprises:
determining the subordination relation among the devices in the power grid according to a preset power grid topological structure;
converting the power grid data set into intermediate power grid data of intermediate equipment in a format supported by the distributed photovoltaic bearing capacity computing system;
and determining the intermediate equipment belonging to the target equipment according to the subordination relation, and calculating the target power grid data of the target equipment according to the intermediate power grid data of all the intermediate equipment belonging to the target equipment.
3. The method of claim 2, wherein converting the grid data set to intermediate grid data for an intermediate device in a format supported by a distributed photovoltaic capacity computing system comprises:
extracting historical power grid data of the intermediate equipment from the power grid data set;
data element d of historical grid data of intermediate devicei,jData element d 'as the intermediate device'k(ii) a Wherein the data element di,jFor the data element in the ith row and the jth column in the historical power grid data of the intermediate equipment, i belongs to [1, m ∈]，j∈[1,n]And k is i × n + j-n, k ∈ [1, m × n ∈]；
All the data elements d 'of the intermediate device'kSequentially arranging intermediate grid data d 'forming the intermediate device'1,d'2,…,d'k,…,d'm×n。
4. The method of claim 3, wherein extracting historical grid data for the intermediate device from the grid data set comprises:
sorting the power grid data sets for the first time according to date fields, and then sorting the power grid data sets for the second time according to equipment name fields, wherein the second sorting adopts a bubbling sorting method;
and taking the n rows of data corresponding to the equipment name field of the intermediate equipment in the power grid data set as historical power grid data of the intermediate equipment.
5. The method according to any one of claims 2-4, further comprising, after determining the load bearing capacity of the target device from the calculation of the distributed photovoltaic load bearing capacity calculation system:
determining a grade to which the bearing capacity of the target equipment belongs, and determining a color corresponding to the grade;
and updating the color of the line corresponding to the target device in the power grid topological structure to be the color corresponding to the grade.
6. An apparatus for calculating a load bearing capacity, comprising:
the data acquisition module is used for acquiring a power grid data set in a target time period from the power grid dispatching automation system based on the data interface;
the data conversion module is used for converting the power grid data set into target power grid data of a plurality of target devices in a format supported by the distributed photovoltaic bearing capacity calculation system and inputting the target power grid data into the distributed photovoltaic bearing capacity calculation system;
and the data calculation module is used for determining the bearing capacity of the target equipment according to the calculation result of the distributed photovoltaic bearing capacity calculation system.
7. The apparatus of claim 6, wherein the data conversion module converts the grid data set into target grid data for a plurality of target devices in a format supported by a distributed photovoltaic load bearing computing system comprises:
determining the subordination relation among the devices in the power grid according to a preset power grid topological structure;
converting the power grid data set into intermediate power grid data of intermediate equipment in a format supported by the distributed photovoltaic bearing capacity computing system;
and determining the intermediate equipment belonging to the target equipment according to the subordination relation, and calculating the target power grid data of the target equipment according to the intermediate power grid data of all the intermediate equipment belonging to the target equipment.
8. The apparatus of claim 7, wherein the data conversion module converts the grid data set into intermediate grid data for an intermediate device in a format supported by a distributed photovoltaic capacity computing system comprises:
extracting historical power grid data of the intermediate equipment from the power grid data set;
data element d of historical grid data of intermediate devicei,jData element d 'as the intermediate device'k(ii) a Wherein the data element di,jFor the data element in the ith row and the jth column in the historical power grid data of the intermediate equipment, i belongs to [1, m ∈]，j∈[1,n]And k is i × n + j-n, k ∈ [1, m × n ∈]；
All the data elements d 'of the intermediate device'kSequentially arranging intermediate grid data d 'forming the intermediate device'1,d'2,…,d'k,…,d'm×n。
9. An electronic device comprising a bus, a transceiver, a memory, a processor and a computer program stored on the memory and executable on the processor, the transceiver, the memory and the processor being connected via the bus, characterized in that the computer program realizes the steps in the method of calculating a load power of any of claims 1 to 5 when executed by the processor.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps in the method of calculating a bearing capacity of any one of claims 1 to 5.
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