An automatic running capacity configuration method, system, terminal device and storage medium

Abstract

The application is suitable for the technical field of micro-grid, and provides an automatic operation capacity configuration method, system, terminal equipment and storage medium, the method comprises the following steps: obtaining capacity data of a power grid system; based on the capacity data, calculating power failure analysis data of a user in each monitoring period and storing the power failure analysis data as a first data group; based on the capacity data, calculating voltage qualification rate and voltage overrun times in each monitoring period, and storing the voltage qualification rate and the voltage overrun times as a second data group; based on the capacity data, calculating equipment utilization rate and line loss rate in each monitoring period, and storing the equipment utilization rate and the line loss rate as a third data group; based on the first data group, the second data group and the third data group, calculating an optimal capacity configuration set, and recommending online operation of the power system based on the optimal capacity configuration set. The method of the application can consider economy and technical constraints to form an optimal deployment and control mode.

Description

Technical Field

[0001] This application belongs to the field of microgrid technology, and in particular relates to an automatic operation capacity configuration method, system, terminal equipment and storage medium. Background Technology

[0002] The future power grid will become increasingly complex and massive in scale. Numerous distributed power electronic devices, including new energy sources and energy storage, will be continuously integrated into the power system. How to make optimal decisions and deployments within such a system, considering economic efficiency, technological constraints, and policy support, has become a significant challenge.

[0003] The existing automatic operation control of the power grid is mainly set based on the experience of dispatchers. However, human resources are ultimately limited, making it difficult to truly take into account economic, technical constraints and policy support to form the optimal deployment and control method. Summary of the Invention

[0004] To overcome the problems existing in related technologies, embodiments of this application provide an automatic capacity configuration method, system, terminal device and storage medium that can take into account economic and technical constraints to form an optimal deployment and control method.

[0005] This application is achieved through the following technical solution:

[0006] In a first aspect, embodiments of this application provide an automatic capacity configuration method, comprising: acquiring capacity data of the power grid system; calculating user outage analysis data for each monitoring cycle based on the capacity data, and storing the user outage analysis data as a first data group; calculating voltage compliance rate and voltage over-limit count for each monitoring cycle based on the capacity data, and storing the voltage compliance rate and voltage over-limit count as a second data group; calculating equipment utilization rate and line loss rate for each monitoring cycle based on the capacity data, and storing the equipment utilization rate and line loss rate as a third data group; calculating an optimal capacity configuration set based on the first data group, the second data group, and the third data group, and making online operation recommendations for the power system based on the optimal capacity configuration set.

[0007] In one possible implementation of the first aspect, acquiring the capacity data of the power grid system includes:

[0008] Set the monitoring cycle for the sensor to collect current and historical capacity data;

[0009] During each monitoring cycle, the current capacity data collected by the monitored sensors is summarized, and the current capacity data and historical capacity data are stored in the capacity data.

[0010] Acquire capacity data, and based on the capacity data, obtain the total installed capacity of new energy and the total energy of interactive load.

[0011] In one possible implementation of the first aspect, based on capacity data, power outage analysis data for users within each monitoring cycle is calculated, and the user power outage analysis data is stored as a first data set, including:

[0012] Based on capacity data, power outage analysis data for users within each monitoring period is calculated. The power outage analysis data includes the average power outage duration per user in each monitoring period, the number of power outages per user per year in the corresponding year of each monitoring period, and the average total operating time per user in each monitoring period.

[0013] The average power outage duration per household, the number of power outages per user per year, and the average total operating time per user are stored in the first data group according to different monitoring cycles.

[0014] In one possible implementation of the first aspect, based on capacity data, the voltage compliance rate and the number of voltage over-limit occurrences within each monitoring cycle are calculated, and the voltage compliance rate and the number of voltage over-limit occurrences are stored as a second data set, including:

[0015] Based on capacity data, calculate the voltage compliance rate for each monitoring cycle;

[0016] Based on capacity data, voltage over-limit information is obtained, and based on capacity data and voltage over-limit information, the number of voltage over-limit occurrences in each monitoring cycle is extracted;

[0017] The voltage pass rate and the number of times the voltage exceeded the limit were stored in the second data group according to different monitoring cycles.

[0018] In one possible implementation of the first aspect, based on capacity data, the equipment utilization rate and line loss rate are calculated for each monitoring cycle, and the equipment utilization rate and line loss rate are stored as a third data set, including:

[0019] Based on capacity data and rated installed capacity, calculate the equipment utilization rate for each monitoring cycle;

[0020] Calculate the line loss rate of the monitored area in each monitoring cycle based on capacity data;

[0021] Equipment utilization rate and line loss rate are stored in a third data set according to different monitoring cycles.

[0022] In one possible implementation of the first aspect, the optimal capacity configuration set is calculated based on the first data set, the second data set, and the third data set, including:

[0023] Based on the first data set, the first economic index is calculated; the first economic index is used to assess the impact of power outages on capacity allocation.

[0024] Based on the second data set, a second economic index is calculated; the second economic index is used to characterize the impact of voltage crossing on capacity configuration.

[0025] Based on the third data set, the third economic index is calculated; the third economic index is used to characterize the impact of power utilization on capacity allocation.

[0026] Calculate economic indicators based on the first, second, and third economic indices;

[0027] Based on the total installed capacity of new energy sources, the total energy of interactive loads, and economic indicators, the corrected economic indicators are calculated.

[0028] Capacity data that meets preset conditions is filtered from the capacity data and stored as a set of supporting operating capacity;

[0029] Based on the revised economic indicators, the optimal capacity configuration set within the supporting operational capacity set is calculated. In one possible implementation of the first aspect, the expression for the first economic index X1 is:

[0030] X1=A×B÷T ALL

[0031] Where A represents the average power outage duration per household, B represents the number of power outages per user per year, and T represents the average power outage duration per household. ALL Average total runtime per user;

[0032] The expression for the second economic index X2 is:

[0033] X2 = 1 - H Y

[0034] Where H is the voltage pass rate and Y is the number of times the voltage exceeds the limit;

[0035] The expression for the third economic index X3 is:

[0036] X3 = L × (1 - S)

[0037] Where L is the equipment utilization rate and S is the line loss rate;

[0038] Economic Indicator X A The expression is:

[0039] X A =K3X3-K1X1-K2X2

[0040] Among them, K1, K2 and K3 are the first economic coefficient, the second economic coefficient and the third economic coefficient, respectively;

[0041] Revised economic indicator X L The expression is:

[0042] X L =X A ×(1+b1P new +b2W F )

[0043] Among them, P new For the total installed capacity of new energy, W F b1 is the conversion factor for the total installed capacity of new energy sources, and b2 is the conversion factor for the interactive load subsidy.

[0044] The expression for the optimal capacity configuration set P is:

[0045] P = Arg max(X) L ), P∈J H

[0046] Where, Arg max(X L J is the function that extracts the optimal P. H To support the set of operational capacity.

[0047] Secondly, embodiments of this application provide an automatic capacity configuration system, including:

[0048] The periodic acquisition module is used to acquire capacity data;

[0049] The power outage analysis module is used to calculate the power outage analysis data of users in each monitoring cycle based on capacity data, and store the power outage analysis data of users as the first data group;

[0050] The voltage analysis module is used to calculate the voltage compliance rate and the number of voltage over-limits in each monitoring cycle based on capacity data, and store the voltage compliance rate and the number of voltage over-limits as a second data set;

[0051] The utilization rate analysis module is used to calculate the equipment utilization rate and line loss rate in each monitoring cycle based on capacity data, and store the equipment utilization rate and line loss rate as a third data group;

[0052] The online capacity allocation and control module is used to calculate the optimal capacity configuration set based on the first data set, the second data set, and the third data set, and to make online operation recommendations for the power system based on the optimal capacity configuration set.

[0053] Thirdly, embodiments of this application provide a terminal device, including a memory and a processor, wherein the memory stores a computer program that can run on the processor, characterized in that the processor, when executing the computer program, implements the automatic capacity configuration method as described in any of the first aspects.

[0054] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program, characterized in that the computer program, when executed by a processor, implements the automatic capacity configuration method as described in any of the first aspects.

[0055] The beneficial effects of the embodiments in this application compared with the prior art are:

[0056] In this embodiment, by combining capacity data and considering power outages, voltage overruns, and utilization rates, an optimal set of operational deployment controls that meets technical constraints is obtained, thereby achieving efficient, economical, and reliable automatic operation control.

[0057] It is understood that the beneficial effects of the second and third aspects mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here.

[0058] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this specification. Attached Figure Description

[0059] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0060] Figure 1 This is a schematic flowchart of an automatic capacity configuration method provided in an embodiment of this application;

[0061] Figure 2 This is a schematic diagram of the automatic operation capacity configuration system structure provided in one embodiment of this application;

[0062] Figure 3 This is a schematic diagram of the structure of a terminal device provided in an embodiment of this application. Detailed Implementation

[0063] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0064] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.

[0065] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0066] As used in this application specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if detected [the described condition or event]" may be interpreted, depending on the context, as meaning "once determined," "in response to determination," "once detected [the described condition or event]," or "in response to detection [the described condition or event]."

[0067] Furthermore, in the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0068] The phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this application specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0069] To enable those skilled in the art to better understand the present invention, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the accompanying drawings and specific implementation methods.

[0070] Figure 1 This is a flowchart illustrating an embodiment of the automatic capacity configuration method provided in this application, with reference to... Figure 1 The automatic capacity configuration method includes:

[0071] In step 101, the capacity data of the power grid system is obtained.

[0072] For example, acquiring power grid system capacity data includes: setting a monitoring cycle for sensors to collect current and historical capacity data of the power grid system. Within each monitoring cycle, the current capacity data collected by the monitored sensors is summarized, and the current and historical capacity data are stored in the capacity data. The capacity data is then acquired, and based on this data, the total installed capacity of new energy sources and the total energy of interactive loads are obtained.

[0073] For example, the capacity data of a power grid system may include all current capacity data and all historical capacity data.

[0074] For example, by setting the monitoring cycle of sensor data collection, the data collection information of all sensors in the monitored and automatically controlled power grid system area is summarized to obtain all real-time data, making the obtained data more comprehensive and timely, and making the final optimal automatic operation configuration more reliable.

[0075] In step 102, based on the capacity data, the power outage analysis data of the users in each monitoring cycle is calculated, and the power outage analysis data of the users is stored as the first data group.

[0076] For example, based on capacity data, power outage analysis data for users within each monitoring period is calculated, and the user power outage analysis data is stored in a first data group. This includes: calculating user power outage analysis data for each monitoring period based on capacity data; the power outage analysis data includes the average power outage duration per household for each monitoring period, the number of power outages per user per year for the corresponding year of each monitoring period, and the average total operating time per user for each monitoring period. The average power outage duration per household, the number of power outages per user per year, and the average total operating time per user are stored in the first data group according to different monitoring periods.

[0077] For example, the number of annual power outages per user is obtained according to the year corresponding to each monitoring period. If the monitoring period spans two years, the average number of annual power outages per user over the two years is taken as the number of annual power outages per user.

[0078] For example, the average power outage duration per household, the number of power outages per user per year, and the average total operating time per user for all monitoring periods 'a' are stored in the first data group, and the average power outage duration per household, the number of power outages per user per year, and the average total operating time per user for all monitoring periods 'b' are also stored in the first data group. Here, 'a' and 'b' represent different time lengths; for example, 'a' can be 1 year, and 'b' can be 2 years. Power outage analysis data with a monitoring period of 1 year are stored together, and power outage analysis data with a monitoring period of 2 years are stored together.

[0079] For example, by analyzing the impact of power outages, specific economic indicators can be better determined, thereby ultimately obtaining the optimal capacity configuration that takes into account economic indicators.

[0080] In step 103, based on the capacity data, the voltage compliance rate and the number of voltage over-limits are calculated for each monitoring cycle, and the voltage compliance rate and the number of voltage over-limits are stored as a second data set.

[0081] For example, based on capacity data, the voltage compliance rate and the number of voltage over-limit occurrences are calculated for each monitoring cycle, and the voltage compliance rate and the number of voltage over-limit occurrences are stored as a second data group. This includes: calculating the voltage compliance rate for each monitoring cycle based on capacity data; obtaining voltage over-limit information based on capacity data; and extracting the number of voltage over-limit occurrences for each monitoring cycle based on capacity data and voltage over-limit information; and storing the voltage compliance rate and the number of voltage over-limit occurrences in the second data group according to different monitoring cycles.

[0082] For example, overvoltage can cause voltage transformers and electricity meters to burn out due to severe overheating. Overvoltage can also accelerate the aging of power equipment. By focusing on the voltage-related impacts, specific economic indicators can be better determined.

[0083] In step 104, based on the capacity data, the equipment utilization rate and line loss rate are calculated for each monitoring cycle, and the equipment utilization rate and line loss rate are stored as a third data set.

[0084] For example, based on capacity data, the equipment utilization rate and line loss rate are calculated for each monitoring period, and stored as a third data set. This includes: calculating the equipment utilization rate for each monitoring period based on capacity data and rated installed capacity; calculating the line loss rate of the monitored area for each monitoring period based on capacity data; and storing the equipment utilization rate and line loss rate in the third data set according to different monitoring periods.

[0085] For example, by focusing on the impact of energy utilization rates, taking into account equipment utilization and line loss rates, specific economic indicators can be better determined.

[0086] In step 105, based on the first data set, the second data set, and the third data set, the optimal capacity configuration set is calculated, and an online operation recommendation for the power system is made based on the optimal capacity configuration set.

[0087] For example, based on the first data group, the second data group, and the third data group, the optimal set of capacity configurations is calculated, including:

[0088] Step 1051: Based on the first data set, calculate the first economic index, which is used to characterize the impact of power outages on capacity allocation.

[0089] Step 1052: Based on the second data set, calculate the second economic index, which is used to characterize the impact of voltage crossing on capacity configuration.

[0090] Step 1053: Based on the third data set, calculate the third economic index, which is used to characterize the impact of power utilization on capacity configuration.

[0091] Step 1054: Calculate economic indicators based on the first economic index, the second economic index, and the third economic index.

[0092] Step 1055: Calculate the corrected economic indicators based on the total installed capacity of new energy sources, the total energy of interactive loads, and economic indicators.

[0093] Step 1056: Select capacity data that meets preset conditions from the capacity data and store it as a set of supporting operating capacity.

[0094] Step 1057: Based on the revised economic indicators, calculate the optimal capacity configuration set in the supporting operational capacity set.

[0095] Specifically, in step 1051, the expression for the first economic index X1 is:

[0096] X1=A×B÷T ALL (1)

[0097] Where A represents the average power outage duration per household, B represents the number of power outages per user per year, and T represents the average power outage duration per household. ALL This represents the average total runtime for users.

[0098] Specifically, in step 1052, the expression for the second economic index X2 is:

[0099] X2 = 1 - H Y (2)

[0100] Where H is the voltage pass rate and Y is the number of times the voltage exceeds the limit.

[0101] Specifically, in step 1053, the expression for the third economic index X3 is:

[0102] X3=L×(1-S) (3)

[0103] Where L is the equipment utilization rate and S is the line loss rate.

[0104] Specifically, in step 1054, the economic indicator X A The expression is:

[0105] X A =K3X3-K1X1-K2X2 (4)

[0106] Among them, K1, K2 and K3 are the first economic coefficient, the second economic coefficient and the third economic coefficient, respectively.

[0107] For example, K1, K2 and K3 are the first, second and third economic coefficients, respectively, preferably 1. When it is 1, the actual economic indicators obtained take into account the comprehensive impact of power outages, voltage overpasses and power utilization on the capacity configuration method in proportion.

[0108] Specifically, in step 1055, the corrected economic indicator X L The expression is:

[0109] X L =X A ×(1+b1P new +b2W F (5)

[0110] Among them, P new For the total installed capacity of new energy, W F b1 represents the total energy of the interactive load, b2 represents the conversion factor of the total installed capacity of new energy, and b2 represents the conversion factor of the interactive load subsidy.

[0111] For example, b1P new and b2W F All of these are unitless numbers, which can be determined based on the specific policy subsidy ratio.

[0112] Specifically, in step 1056, the expression for the aforementioned preset condition is:

[0113]

[0114] Where M1 is the margin of the load energy storage power supply ratio, M0 is the margin of the energy storage deployment ratio, and P E For the rated power of a single load, w i Let T be the total capacity provided by the energy storage device for the i-th load during the monitoring period, n be the total number of monitored devices, and p be the total capacity provided by the energy storage device for the i-th load. c The proportion of the power supplied to the monitored load that is provided by energy storage.

[0115] For example, a set of capacity data that meets preset conditions is combined into a support capacity set. In actual execution, scheduling is set based on experience and each time period. Then, the optimal capacity configuration set P is extracted from the support capacity set.

[0116] Specifically, in step 1057, the expression for the optimal capacity configuration set P is:

[0117] P = Arg max (X) L ), P∈J H (7)

[0118] Where, Arg max(X LJ is the function that extracts the optimal P. H To support the set of operational capacity.

[0119] For example, online operation recommendations based on the optimal capacity control set specifically include: obtaining the optimal capacity control set and sequentially extracting reference values ​​for the optimal operating capacity at the current moment. These values ​​are then sent to the scheduler for reference, and the scheduler selects the corresponding reference value for automatic operation control based on operational needs.

[0120] For example, the determined optimal capacity control set is the control reference value used for each control operation, which is finally confirmed. In this way, a global optimal control state of the current power grid can be achieved by considering the overall situation and combining economic efficiency and performance indicators.

[0121] As can be seen, this invention analyzes power outages, voltage overruns, and power utilization to form three types of indicators: the first type is economic indicators, the second type is technical constraints, and the third type is policy indicators. It then selects the optimal capacity configuration method from the capacity data as the optimal automatic operation configuration method recommended to the dispatcher at the current moment. In this way, it obtains a set of optimal operation deployment controls that meet technical constraints, thereby achieving efficient, economical, reliable, and policy-supported automatic operation control.

[0122] It should be understood that the sequence number of each step does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0123] This application provides an automatic capacity configuration system based on an automatic capacity configuration method, referring to... Figure 2 , Figure 2 This is a schematic diagram of the structure of an automatic capacity allocation system provided in an embodiment of this application. The automatic capacity allocation system includes: a periodic acquisition module 201, a power outage analysis module 202, a voltage analysis module 203, a utilization rate analysis module 204, and an online capacity allocation and control module 205.

[0124] The periodic acquisition module 201 is used to acquire capacity data.

[0125] The power outage analysis module 202 is used to calculate the power outage analysis data of users in each monitoring cycle based on capacity data, and store the power outage analysis data of users as the first data group.

[0126] The voltage analysis module 203 is used to calculate the voltage compliance rate and the number of voltage over-limits in each monitoring cycle based on capacity data, and to store the voltage compliance rate and the number of voltage over-limits as a second data set.

[0127] The utilization analysis module 204 is used to calculate the equipment utilization rate and line loss rate in each monitoring cycle based on capacity data, and store the equipment utilization rate and line loss rate as a third data group.

[0128] The online capacity allocation and control module 205 is used to calculate the optimal capacity configuration set based on the first data set, the second data set, and the third data set, and to make online operation recommendations for the power system based on the optimal capacity configuration set.

[0129] For example, the periodic acquisition module 201 is used to acquire capacity data of the power grid system, including: setting a monitoring period for sensors to collect current and historical capacity data. Within each monitoring period, the current capacity data collected by the monitored sensors is summarized, and the current and historical capacity data are stored in the capacity data. The capacity data is acquired, and based on the capacity data, the total installed capacity of new energy sources and the total energy of interactive loads are obtained.

[0130] For example, the power outage analysis module 202 is used to calculate power outage analysis data for users within each monitoring period based on capacity data, and to store the user power outage analysis data into a first data group. This includes: calculating user power outage analysis data for each monitoring period based on capacity data; the power outage analysis data includes the average power outage duration per household for each monitoring period, the number of power outages per user per year for the corresponding year of each monitoring period, and the average total operating time per user for each monitoring period. The average power outage duration per household, the number of power outages per user per year, and the average total operating time per user are stored in the first data group according to different monitoring periods.

[0131] For example, the voltage analysis module 203 is used to calculate the voltage compliance rate and the number of voltage over-limit occurrences in each monitoring cycle based on capacity data, and store the voltage compliance rate and the number of voltage over-limit occurrences in a second data group, including: calculating the voltage compliance rate in each monitoring cycle based on capacity data; obtaining voltage over-limit information based on capacity data, and extracting the number of voltage over-limit occurrences in each monitoring cycle based on capacity data and voltage over-limit information; and storing the voltage compliance rate and the number of voltage over-limit occurrences in the second data group according to different monitoring cycles.

[0132] For example, the utilization analysis module 204 is used to calculate the equipment utilization rate and line loss rate for each monitoring cycle based on capacity data, and store the equipment utilization rate and line loss rate as a third data set, including: calculating the equipment utilization rate for each monitoring cycle based on capacity data and rated installed capacity; calculating the line loss rate of the monitored area for each monitoring cycle based on capacity data; and storing the equipment utilization rate and line loss rate into the third data set according to different monitoring cycles.

[0133] Based on the first, second, and third data sets, the optimal capacity configuration set is calculated, and online operation recommendations for the power system are made based on the optimal capacity configuration set.

[0134] For example, the online capacity allocation and control module 205 is used to calculate the optimal capacity configuration set based on a first data set, a second data set, and a third data set, including: calculating a first economic index based on the first data set, which is used to characterize the impact of power outages on capacity configuration; calculating a second economic index based on the second data set, which is used to characterize the impact of voltage exceeding limits on capacity configuration; calculating a third economic index based on the third data set, which is used to characterize the impact of power utilization on capacity configuration; calculating economic indicators based on the first, second, and third economic indices; calculating corrected economic indicators based on the total installed capacity of new energy sources, the total energy of interactive loads, and the economic indicators; selecting capacity data that meets preset conditions from the capacity data and storing it as a set of supporting operating capacity; and calculating the optimal capacity configuration set in the set of supporting operating capacity based on the corrected economic indicators.

[0135] Specifically, the expression for the first economic index X1 is:

[0136] X1=A×B÷T ALL (1)

[0137] Where A represents the average power outage duration per household, B represents the number of power outages per user per year, and T represents the average power outage duration per household. ALL This represents the average total runtime for users.

[0138] Specifically, the expression for the second economic index X2 is:

[0139] X2 = 1 - H Y (2)

[0140] Where H is the voltage pass rate and Y is the number of times the voltage exceeds the limit.

[0141] Specifically, the expression for the third economic index X3 is:

[0142] X3=L×(1-S) (3)

[0143] Where L is the equipment utilization rate and S is the line loss rate.

[0144] Specifically, economic indicator X A The expression is:

[0145] X A =K3X3-K1X1-K2X2 (4)

[0146] Among them, K1, K2 and K3 are the first economic coefficient, the second economic coefficient and the third economic coefficient, respectively.

[0147] Specifically, the revised economic indicator X L The expression is:

[0148] X L =X A ×(1+b1P new +b2W F (5)

[0149] Among them, P new For the total installed capacity of new energy, W F b1 represents the total energy of the interactive load, b2 represents the conversion factor of the total installed capacity of new energy, and b2 represents the conversion factor of the interactive load subsidy.

[0150] Specifically, the expression for the above preset condition is:

[0151]

[0152] Where M1 is the margin of the load energy storage power supply ratio, M0 is the margin of the energy storage deployment ratio, and P E For the rated power of a single load, w i Let T be the total capacity provided by the energy storage device for the i-th load during the monitoring period, n be the total number of monitored devices, and p be the total capacity provided by the energy storage device for the i-th load. c The proportion of the power supplied to the monitored load that is provided by energy storage.

[0153] For example, a set of capacity data that meets preset conditions is combined into a support capacity set. In actual execution, scheduling is set based on experience and each time period. Then, the optimal capacity configuration set P is extracted from the support capacity set.

[0154] Specifically, in step 1057, the expression for the optimal capacity configuration set P is:

[0155] P = Arg max (X) L ), P∈J H (7)

[0156] Where, Arg max(X L J is the function that extracts the optimal P. H To support the set of operational capacity.

[0157] Corresponding to the automatic capacity configuration system in the above embodiments, this application also provides a terminal device, see [link to relevant documentation]. Figure 3The terminal device 300 may include at least one processor 310, a memory 320, and a wireless module 330. The memory 320 stores a computer program 321 that can run on the at least one processor 310. When the processor 310 executes the computer program, it implements the steps in any of the above-described method embodiments, for example... Figure 1 Steps 101 to 105 in the illustrated embodiment.

[0158] For example, a computer program may be divided into one or more modules / units, one or more of which are stored in memory 320 and executed by processor 310 to complete this application. The one or more modules / units may be a series of computer program segments capable of performing specific functions, which describe the execution process of the computer program in terminal device 300.

[0159] Those skilled in the art will understand that Figure 3 This is merely an example of a terminal device and does not constitute a limitation on the terminal device. It may include more or fewer components than shown, or combine certain components, or different components, such as input / output devices, network access devices, buses, etc.

[0160] The processor 310 can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.

[0161] The memory 320 can be an internal storage unit of the terminal device or an external storage device, such as a plug-in hard drive, a smart media card (SMC), a secure digital card (SD), or a flash card. The memory 320 is used to store the computer program and other programs and data required by the terminal device. The memory 320 can also be used to temporarily store data that has been output or will be output.

[0162] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.

[0163] The wireless module 330 is used to receive and transmit electromagnetic waves, realizing the mutual conversion between electromagnetic waves and electrical signals, thereby communicating with communication networks or other devices, such as communicating with base stations based on mobile communication protocols. The wireless module 330 may include various existing circuit elements for performing these functions, such as antennas, radio frequency transceivers, digital signal processors, encryption / decryption chips, user identity module (SIM) cards, memory, etc. The wireless module 330 can communicate with various networks such as the Internet, corporate intranets, and wireless networks, or communicate with other electronic devices through wireless networks. The aforementioned wireless networks may include cellular telephone networks, wireless local area networks (WLANs), or metropolitan area networks (MANs). The aforementioned wireless networks can use various communication standards, protocols, and technologies, including but not limited to WLAN and Bluetooth protocols, and may even include protocols that are not yet developed.

[0164] The automatic capacity configuration method provided in this application can be applied to terminal devices such as computers, tablets, laptops, netbooks, and personal digital assistants (PDAs). This application does not impose any restrictions on the specific type of terminal device.

[0165] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps described in the various embodiments of the automatic capacity configuration method.

[0166] This application provides a computer program product that, when run on a mobile terminal, enables the mobile terminal to execute the steps described in the various embodiments of the automatic capacity configuration method.

[0167] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of this application can be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include at least: any entity or device capable of carrying computer program code to a photographing device / terminal device, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium. Examples include USB flash drives, portable hard drives, magnetic disks, or optical disks. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electrical carrier signals or telecommunication signals.

[0168] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0169] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0170] In the embodiments provided in this application, it should be understood that the disclosed apparatus / network devices and methods can be implemented in other ways. For example, the apparatus / network device embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0171] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0172] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. An automatic capacity configuration method, characterized in that, include: Obtain capacity data of the power grid system; Based on the capacity data, calculate the power outage analysis data of the user in each monitoring cycle, and store the power outage analysis data of the user as a first data group; Based on the capacity data, calculate the voltage compliance rate and the number of voltage over-limits in each monitoring cycle, and store the voltage compliance rate and the number of voltage over-limits as a second data group; Based on the capacity data, calculate the equipment utilization rate and line loss rate in each monitoring cycle, and store the equipment utilization rate and the line loss rate as a third data group; Based on the first data set, the second data set, and the third data set, the optimal capacity configuration set is calculated, and an online operation recommendation for the power system is made based on the optimal capacity configuration set. The acquisition of power grid system capacity data includes: Set the monitoring cycle for the sensor to collect current and historical capacity data; Within each monitoring cycle, the current capacity data collected by the monitored sensors is summarized, and the current capacity data and the historical capacity data are stored in the capacity data. Obtain the capacity data, and based on the capacity data, obtain the total installed capacity of new energy and the total energy of interactive load; Based on the capacity data, the power outage analysis data for each user within each monitoring cycle is calculated, and the power outage analysis data for the user is stored in a first data group, including: Based on the capacity data, power outage analysis data for users within each monitoring period is calculated. The power outage analysis data includes the average power outage duration per household in each monitoring period, the number of power outages per user per year in the corresponding year of each monitoring period, and the average total operating time per user in each monitoring period. The average power outage duration per household, the number of power outages per user per year, and the average total operating time per user are stored in the first data group according to different monitoring cycles; The step of calculating the optimal capacity configuration set based on the first data group, the second data group, and the third data group includes: Based on the first data set, a first economic index is calculated, which is used to characterize the impact of power outages on capacity allocation. Based on the second data set, a second economic index is calculated, which is used to characterize the impact of voltage crossing on capacity configuration. Based on the third data set, a third economic index is calculated, which is used to characterize the impact of power utilization on capacity configuration. Based on the first economic index, the second economic index, and the third economic index, calculate the economic indicators; Based on the total installed capacity of new energy sources, the total energy of interactive loads, and the economic indicators, the corrected economic indicators are calculated. Capacity data that meets preset conditions is selected from the capacity data and stored as a set of supporting operating capacity; Based on the revised economic indicators, the optimal capacity configuration set in the supporting operational capacity set is calculated.

2. The automatic capacity configuration method as described in claim 1, characterized in that, Based on the capacity data, the voltage compliance rate and the number of voltage exceedances within each monitoring cycle are calculated, and the voltage compliance rate and the number of voltage exceedances are stored as a second data group, including: Based on the capacity data, the voltage qualification rate within each monitoring cycle is calculated; Based on the capacity data, voltage over-limit information is obtained, and based on the capacity data and the voltage over-limit information, the number of voltage over-limit occurrences within each monitoring cycle is extracted; The voltage pass rate and the number of voltage exceedances are stored in the second data group according to different monitoring cycles.

3. The automatic capacity configuration method as described in claim 1, characterized in that, Based on the capacity data, the equipment utilization rate and line loss rate are calculated for each monitoring cycle, and the equipment utilization rate and line loss rate are stored as a third data group, including: Based on the capacity data and rated installed capacity, the equipment utilization rate within each monitoring cycle is calculated; Calculate the line loss rate of the monitored area in each monitoring cycle based on the capacity data; The equipment utilization rate and the line loss rate are stored in the third data group according to different monitoring cycles.

4. The automatic capacity configuration method as described in claim 1, characterized in that, The first economic index X The expression for 1 is: X 1= A × B ÷ T ALL in, A The average power outage duration per household is [not specified]. B The number of power outages per year for the user. T ALL The average total runtime for the user; Second economic index X The expression for 2 is: X 2=1- H Y in, H The voltage pass rate, Y The number of times the voltage exceeded the limit; The third economic index X The expression for 3 is: X 3= L ×（1- S ） in, L The utilization rate of the equipment. S The line loss rate is mentioned. The economic indicators X A The expression is: X A = K 3 X 3- K 1 X 1- K 2 X 2 in, K 1. K 2 and K 3 represents the first, second, and third economic coefficients, respectively. The revised economic indicators X L The expression is: X L = X A ×（1+ b 1 P new + b 2 W F ） in, P new The total installed capacity of the aforementioned new energy sources. W F The total energy of the interactive load, b 1 represents the conversion factor for the total installed capacity of the new energy sources. b 2 represents the conversion factor for interactive load subsidies; The optimal capacity configuration set P The expression is: P = Argmax ( X L )， P ∈ J H in, Argmax ( X L To extract the optimal P The function, J H This refers to the set of supporting operating capacities.

5. An automatic capacity configuration system, characterized in that, include: The periodic acquisition module is used to acquire capacity data; The power outage analysis module is used to calculate the power outage analysis data of users in each monitoring cycle based on the capacity data, and store the power outage analysis data of users as a first data group; The voltage analysis module is used to calculate the voltage compliance rate and the number of voltage over-limits in each monitoring cycle based on the capacity data, and to store the voltage compliance rate and the number of voltage over-limits as a second data group; The utilization rate analysis module is used to calculate the equipment utilization rate and line loss rate in each monitoring cycle based on the capacity data, and store the equipment utilization rate and the line loss rate as a third data group; The online capacity allocation and control module is used to calculate the optimal capacity configuration set based on the first data set, the second data set, and the third data set, and to make online operation recommendations for the power system based on the optimal capacity configuration set. The periodic acquisition module is specifically used for: Set the monitoring cycle for the sensor to collect current and historical capacity data; Within each monitoring cycle, the current capacity data collected by the monitored sensors is summarized, and the current capacity data and the historical capacity data are stored in the capacity data. Obtain the capacity data, and based on the capacity data, obtain the total installed capacity of new energy and the total energy of interactive load; The power outage analysis module is specifically used for: Based on the capacity data, power outage analysis data for users within each monitoring period is calculated. The power outage analysis data includes the average power outage duration per household in each monitoring period, the number of power outages per user per year in the corresponding year of each monitoring period, and the average total operating time per user in each monitoring period. The average power outage duration per household, the number of power outages per user per year, and the average total operating time per user are stored in the first data group according to different monitoring cycles; The online capacity allocation and control module is specifically used for: Based on the first data set, a first economic index is calculated, which is used to characterize the impact of power outages on capacity allocation. Based on the second data set, a second economic index is calculated, which is used to characterize the impact of voltage crossing on capacity configuration. Based on the third data set, a third economic index is calculated, which is used to characterize the impact of power utilization on capacity configuration. Based on the first economic index, the second economic index, and the third economic index, calculate the economic indicators; Based on the total installed capacity of new energy sources, the total energy of interactive loads, and the economic indicators, the corrected economic indicators are calculated. Capacity data that meets preset conditions is selected from the capacity data and stored as a set of supporting operating capacity; Based on the revised economic indicators, the optimal capacity configuration set in the supporting operational capacity set is calculated.

6. A terminal device, comprising a memory and a processor, wherein the memory stores a computer program executable on the processor, characterized in that, When the processor executes the computer program, it implements the automatic capacity configuration method as described in any one of claims 1 to 4.

7. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the automatic capacity configuration method as described in any one of claims 1 to 4.

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