Automatic voltage control method and device for transformer area substation, and electronic equipment

Abstract

The invention discloses an automatic voltage control method and device for a transformer area substation and electronic equipment, and relates to the technical field of automatic voltage control or other related fields. Obtaining load flow calculation results of the power distribution network model, the transformer low-voltage side model and the target power distribution network from a power grid energy management system; topology analysis is carried out based on the power distribution network model, the transformer low-voltage side model and the load flow calculation result, a feeder line area and a transformer area in the feeder line area are obtained, and the transformer area comprises transformers and distributed new energy equipment; obtaining active power prediction data of distributed new energy equipment in the transformer region, and determining an active power change trend of the transformer in the target time period; and generating a voltage control strategy in the target time period based on the active power change trend of the transformer. According to the invention, the technical problem that the voltage fluctuation of the power grid is easily caused after the distributed new energy is accessed to the power grid in the related technology is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of automatic voltage control, and in particular to an automatic voltage control method and device, and electronic equipment for a transformer substation. Background Art

[0002] In the power system, the automatic voltage control capability and effect of the transmission network substation directly affect the overall control result of the automatic voltage control of the power system. The substation is equipped with discrete reactive equipment (capacitors, reactors) of a certain capacity. The switching of capacitors and reactors is mainly used to eliminate bus voltage over-limit, and also to increase the voltage level of the substation to reduce the network loss of the system. The distribution network is at the end of the entire power system, and its voltage quality is directly related to whether the user's electrical equipment can operate stably. When the system provides a voltage lower than the rated voltage of the user's electrical equipment, the user's electrical equipment will not be able to operate normally. On the contrary, when the system provides a voltage higher than the rated voltage of the user's electrical equipment, it will shorten the service life of the user's electrical equipment and even cause damage to the electrical equipment.

[0003] Distributed new energy is the end of the distribution network, which refers to small renewable energy power generation equipment scattered on the user side or the grid side, such as solar photovoltaic, wind power, biomass energy, etc. Most of them are connected to the grid through the transformer of the distribution network, and belong to the end power generation equipment of the entire grid. With the energy transformation and the popularization of renewable energy, distributed new energy has been rapidly developed and widely used around the world.

[0004] In recent years, distributed new energy technologies have been continuously innovated and broken through. The cost of solar photovoltaic and wind power generation technologies has been continuously reduced, and the efficiency has been continuously improved, making the power generation cost of distributed new energy gradually more competitive. At the same time, with the development of energy storage technology, distributed new energy can better coordinate with the power grid and improve the flexibility and reliability of the power grid. With the development and application of renewable energy, the importance of distributed new energy in the power grid has become increasingly prominent, and it has also had an impact on the power grid that cannot be ignored.

[0005] In the traditional central power generation mode, the voltage control of the power grid is relatively stable, because the power station can adjust the output voltage according to the change of load. After the introduction of a large number of distributed new energy, there will be uncertainty in the power generation, which may cause large voltage fluctuations in the power grid and affect the stability of the power grid. Specifically, there are many nodes in the power grid that need to maintain a constant voltage level, and the access of distributed new energy will change the voltage distribution of these nodes. When distributed new energy is concentrated in a certain node, it may cause the voltage of the node to increase, while the voltage of other nodes may decrease. This voltage imbalance will affect the normal operation of the power grid; distributed new energy equipment usually uses an inverter to convert DC power into AC power and connect it to the power grid. The working principle of the inverter will produce certain voltage fluctuations, especially when some inverters with smaller capacity are working, which may cause instantaneous changes in voltage, thereby affecting the voltage stability of the power grid. When the installed capacity of distributed new energy is too large, it may cause overload of the power grid, which in turn causes voltage drop. Especially in high-risk scenarios, such as when a power grid failure or sudden abnormal situation occurs, the access of distributed new energy may aggravate the overload of the power grid, causing voltage drop and affecting the safe operation of the power grid.

[0006] The biggest problem with the access of distributed renewable energy to the power grid is its discontinuous and intermittent characteristics. The present invention aims to alleviate the impact of this problem on the power grid voltage. By using information such as meteorological data and historical power generation data, an accurate distributed renewable energy power generation prediction model can be established, so that the fluctuation of distributed renewable energy power generation can be predicted in advance. According to the distributed renewable energy active power prediction results and the power grid load conditions, the power grid dispatch optimization is carried out. Through the substation AVC system deployed in the substation area where renewable energy is connected to the grid, the static and dynamic reactive resource adjustment planning of the substation area is reasonably planned, and a variety of reactive resources are effectively used to achieve the stable operation of the regional power grid voltage, thereby reducing the voltage fluctuation of the power grid.

[0007] To address the above-mentioned problems, no effective solution has been proposed yet. Summary of the invention

[0008] The embodiments of the present invention provide an automatic voltage control method and device for a transformer substation, and electronic equipment, so as to at least solve the technical problem in the related art that the grid voltage fluctuation is easily caused after the distributed renewable energy is connected to the grid.

[0009] According to one aspect of an embodiment of the present invention, there is provided an automatic voltage control method for a substation in a substation area, comprising: when a target time is reached, obtaining a distribution network model, a transformer low-voltage side model and a power flow calculation result of a target distribution network from a power grid energy management system; performing a topological analysis based on the distribution network model, the transformer low-voltage side model and the power flow calculation result to obtain a feeder area and a transformer area in the feeder area, wherein the transformer area includes a transformer and F distributed new energy devices connected to a low-voltage side connection point of the transformer, where F is a positive integer; obtaining active power prediction data of the distributed new energy devices in the transformer area, and determining an active power change trend of the transformer within a target time period based on all the active power prediction data; and generating a voltage control strategy within the target time period based on the active power change trend of the transformer.

[0010] Furthermore, the distribution network model is used to record the physical structure information of the target distribution network, and the transformer low-voltage side model is used to record the electrical structure information of the distributed new energy equipment connected to each low-voltage side node of the transformer, wherein the physical structure information at least includes: equipment parameters and a first equipment connection method of each distribution equipment in the target distribution network, the first equipment connection method refers to the connection method between each distribution equipment and other distribution equipment, and the electrical structure information at least includes: electrical parameters and a second equipment connection method of the distributed new energy equipment, the second equipment connection method refers to the connection method between the distributed new energy equipment and the distribution equipment of the target distribution network.

[0011] Furthermore, the power flow calculation results of the target distribution network include: the low-voltage side node voltage, active power data and reactive power data of the transformer, the active power data and reactive power data of the distributed new energy, and the circuit breaker status, disconnector status, capacitor status and reactor status in the target distribution network.

[0012] Furthermore, a topological analysis is performed based on the distribution network model, the transformer low-voltage side model and the power flow calculation result to obtain the feeder area and the transformer area in the feeder area, including: performing a topological analysis on the distribution network model according to the power flow calculation result and the transformer low-voltage side model to obtain a first topological analysis result, and extracting D feeder areas from the first topological analysis result, wherein the feeder area is composed of feeder segments and transformers in the target distribution network, and D is a positive integer; for each feeder area, performing a topological analysis on the feeder area based on the distribution network model and the transformer low-voltage side model to obtain a second topological analysis result, and extracting T transformer areas based on the T transformers recorded in the second topological analysis result, wherein T is a positive integer.

[0013] Furthermore, the steps of obtaining active power prediction data of the distributed new energy equipment in the station transformer area, and determining the active power change trend of the station transformer within the target time period based on all the active power prediction data include: for each station transformer area, extracting active power prediction data of F distributed new energy equipment in the station transformer area within the target time period from the data center system to obtain F active power prediction sequences, wherein the active power prediction sequence includes N active power prediction data, each active power prediction data corresponds to a unique prediction time point, and N is a positive integer; calculating N overall active power prediction data of the station transformer area within the target time period based on the N prediction time points and the active power prediction sequence of the distributed new energy equipment; calculating the active power peak-to-valley difference of the station transformer area within the target time period based on the N overall active power prediction data, and comparing the active power peak-to-valley difference with a preset peak-to-valley threshold value to obtain a comparison result; determining the active power change trend of the station transformer within the target time period based on the comparison result.

[0014] Further, the step of determining the active power change trend of the transformer within the target time period based on the comparison result includes: when the comparison result indicates that the active power peak-valley difference is less than the preset peak-valley threshold value, confirming that it is temporarily not necessary to perform voltage control operation on the transformer within the target time period; or, when the comparison result indicates that the active power peak-valley difference is greater than or equal to the preset peak-valley threshold value, reading the active power data of the transformer at the current moment from the power flow calculation result of the target distribution network; based on the active power data of the transformer at the current moment and N overall active power prediction data of the transformer area within the target time period, determining the active power change trend of the transformer.

[0015] Furthermore, the step of generating a voltage control strategy within the target time period based on the active power change trend of the transformer comprises: when the active power change trend indicates that the target time period is a period of active power growth of the transformer, determining the voltage control strategy as voltage downshifting and / or capacitor removal; when the active power change trend indicates that the target time period is a period of active power reduction of the transformer, determining the voltage control strategy as voltage upshifting and / or capacitor input.

[0016] According to another aspect of an embodiment of the present invention, an automatic voltage control device for a substation in a substation area is also provided, comprising: an acquisition unit, for acquiring a distribution network model, a transformer low-voltage side model and a power flow calculation result of a target distribution network from a power grid energy management system when a target time is reached; an analysis unit, for performing a topological analysis based on the distribution network model, the transformer low-voltage side model and the power flow calculation result to obtain a feeder area and a transformer area in the feeder area, wherein the transformer area includes a transformer and F distributed new energy devices connected to a low-voltage side connection point of the transformer, and F is a positive integer; a determination unit, for acquiring active power prediction data of the distributed new energy devices in the transformer area, and determining an active power change trend of the transformer within a target time period based on all the active power prediction data; a generation unit, for generating a voltage control strategy within the target time period based on the active power change trend of the transformer.

[0017] Furthermore, the distribution network model is used to record the physical structure information of the target distribution network, and the transformer low-voltage side model is used to record the electrical structure information of the distributed new energy equipment connected to each low-voltage side node of the transformer, wherein the physical structure information at least includes: equipment parameters and a first equipment connection method of each distribution equipment in the target distribution network, the first equipment connection method refers to the connection method between each distribution equipment and other distribution equipment, and the electrical structure information at least includes: electrical parameters and a second equipment connection method of the distributed new energy equipment, the second equipment connection method refers to the connection method between the distributed new energy equipment and the distribution equipment of the target distribution network.

[0018] Furthermore, the power flow calculation results of the target distribution network include: the low-voltage side node voltage, active power data and reactive power data of the transformer, the active power data and reactive power data of the distributed new energy, and the circuit breaker status, disconnector status, capacitor status and reactor status in the target distribution network.

[0019] Furthermore, the analysis unit includes: a first analysis module, used to perform a topological analysis on the distribution network model based on the power flow calculation result and the transformer low-voltage side model to obtain a first topological analysis result, and extract D feeder areas from the first topological analysis result, wherein the feeder area is composed of feeder segments and transformers in the target distribution network, and D is a positive integer; a second analysis module, used to perform a topological analysis on each feeder area based on the distribution network model and the transformer low-voltage side model to obtain a second topological analysis result, and extract T transformer areas based on the T transformers recorded in the second topological analysis result, wherein T is a positive integer.

[0020] Further, the determination unit includes: an extraction module, which is used to extract the active power prediction data of F distributed new energy devices in the station change area in the target time period from the data center system for each station change area, and obtain F active power prediction sequences, wherein the active power prediction sequence contains N active power prediction data, each active power prediction data corresponds to a unique prediction time point, and N is a positive integer; a calculation module, which is used to calculate N overall active power prediction data of the station change area in the target time period based on the N prediction time points and the active power prediction sequence of the distributed new energy equipment; a comparison module, which is used to calculate the active power peak-valley difference of the station change area in the target time period based on the N overall active power prediction data, and compare the active power peak-valley difference with a preset peak-valley threshold value to obtain a comparison result; a first determination module, which is used to determine the active power change trend of the station change in the target time period based on the comparison result.

[0021] Further, the first determination module includes: a confirmation submodule, which is used to confirm that it is not necessary to perform voltage control operation on this transformer within the target time period when the comparison result indicates that the active power peak-valley difference is less than the preset peak-valley threshold value; a reading submodule, which is used to read the active power data of this transformer at the current moment from the power flow calculation result of the target distribution network when the comparison result indicates that the active power peak-valley difference is greater than or equal to the preset peak-valley threshold value; and a determination submodule, which is used to determine the active power change trend of the transformer based on the active power data of the transformer at the current moment and N overall active power prediction data of the transformer area within the target time period.

[0022] Further, the generating unit includes: a second determining module, for determining that the voltage control strategy is voltage downshifting and / or capacitor removal when the active power variation trend indicates that the target time period is an active power growth period of the transformer; a second determining module, for determining that the voltage control strategy is voltage upshifting and / or capacitor input when the active power variation trend indicates that the target time period is an active power reduction period of the transformer.

[0023] According to another aspect of an embodiment of the present invention, a computer-readable storage medium is also provided, wherein the computer-readable storage medium includes a stored computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute any of the above-mentioned automatic voltage control methods for a substation in a substation area.

[0024] According to another aspect of an embodiment of the present invention, there is also provided an electronic device, comprising one or more processors and a memory, wherein the memory is used to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement any one of the above-mentioned automatic voltage control methods for a substation in a substation area.

[0025] The present invention proposes an automatic voltage control method for a transformer substation. When a target time is reached, a distribution network model, a transformer low-voltage side model and a power flow calculation result of a target distribution network are first obtained from a power grid energy management system. Then, a topological analysis is performed based on the distribution network model, the transformer low-voltage side model and the power flow calculation result to obtain a feeder area and a transformer area in the feeder area, wherein the transformer area includes a transformer and F distributed new energy devices connected to a low-voltage side connection point of the transformer, where F is a positive integer. Then, active power prediction data of the distributed new energy devices in the transformer area is obtained, and the active power change trend of the transformer in the target time period is determined based on all active power prediction data. Finally, a voltage control strategy in the target time period is generated based on the active power change trend of the transformer.

[0026] The present invention realizes effective control of voltage fluctuations through intelligent analysis and prediction. The distribution network model, transformer low-voltage side model and power flow calculation results obtained from the power grid energy management system provide a basis for subsequent topological analysis. The feeder area and the transformer area therein can be accurately located by deeply analyzing the power grid structure and operation status. In particular, the number F of distributed new energy equipment in the transformer area is dynamic. The step of predicting the active power of distributed new energy equipment helps to timely understand the active power change trend of the transformer in the target time period. This key step to solve the voltage fluctuation problem is directly related to the impact of the power output of the new energy equipment on the grid voltage. Finally, a voltage control strategy for the target time period is generated according to the obtained active power change trend. The power supply and demand of the grid are balanced through the intelligent regulation of the new energy equipment, thereby suppressing the voltage fluctuation at the source and ensuring the power quality and stable operation of the grid. The above process covers the closed-loop control logic from data acquisition, analysis and prediction to strategy generation, which significantly improves the voltage management level after the distributed new energy is connected to the grid, thereby solving the technical problem in the related technology that the distributed new energy is easy to cause grid voltage fluctuation after the grid is connected. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0028] Figure 1is a flow chart of an optional automatic voltage control method for a transformer substation according to an embodiment of the present invention;

[0029] Figure 2 is a schematic diagram of an optional coordinated control area of ​​a transformer and distributed new energy according to an embodiment of the present invention;

[0030] Figure 3 is a schematic diagram of an optional automatic voltage control device for a substation in a substation area according to an embodiment of the present invention;

[0031] Figure 4 The present invention is a hardware structure block diagram of an electronic device (or mobile device) for an automatic voltage control method for a transformer substation according to an embodiment of the present invention. DETAILED DESCRIPTION

[0032] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0033] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0034] To facilitate those skilled in the art to understand the present invention, some terms or nouns involved in the embodiments of the present invention are explained below:

[0035] The Automatic Voltage Control (AVC) system is an important means to achieve safe (improving voltage stability margin), economic (reducing network losses), and high-quality (improving voltage qualification rate) operation of the power grid. The AVC system is based on the power grid energy management system (EMS). It can use the real-time operation data of the power grid to scientifically decide the best reactive voltage adjustment plan from the perspective of global optimization of the transmission network, and automatically send it to power plants, substations, and lower-level power grid dispatching organizations for execution.

[0036] The following embodiments of the present invention can be applied to various systems / applications / equipment that require voltage fluctuation control and grid dispatch optimization, and can implement an effective voltage fluctuation control method based on intelligent analysis and prediction. The present invention acquires the grid model and flow data in real time, analyzes the feeder and transformer area, and then reads the active power forecast of distributed renewable energy in the area and predicts the trend of active power change of transformer. When rapid power fluctuations are detected, the transformer tap or capacitor is automatically adjusted to ensure regional voltage stability, avoid voltage limit violations caused by renewable energy fluctuations, and improve the grid voltage quality.

[0037] The present invention is described in detail below in conjunction with various embodiments.

[0038] Embodiment 1

[0039] According to an embodiment of the present invention, an embodiment of an automatic voltage control method for a substation is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0040] The implementation subject of the embodiment of the present invention can be a power grid dispatching automation system or the automatic voltage control system therein, including obtaining a complete distribution network model and power flow calculation results from the power grid EMS system, performing topological analysis on the model to form feeder and transformer areas, and calculating the change trend based on the active power forecast data for a specified time period in the future. When the active power of the transformer changes rapidly, the transformer tap or capacitor is preferentially adjusted to maintain voltage stability. This is suitable for quickly responding to changes in distributed renewable energy, ensuring the voltage quality of the distribution network, and improving the operation efficiency of the power grid.

[0041] The embodiment of the present invention is described in detail below in combination with the above steps.

[0042] Figure 1 is a flow chart of an optional automatic voltage control method for a substation in a substation area according to an embodiment of the present invention, such as Figure 1 As shown, the method comprises the following steps:

[0043] Step S101, when the target time is reached, the distribution network model, the transformer low-voltage side model and the power flow calculation results of the target distribution network are obtained from the power grid energy management system.

[0044] Specifically, when confirming whether the target moment has been reached, the calculation cycle Q can be set first. The starting point of the calculation cycle is the time point for performing automatic voltage control (AVC) analysis and adjustment. The target moment here specifically refers to the moment when each calculation cycle begins. When the target moment is reached, the automatic voltage control method is automatically started and a series of subsequent analysis and control steps are executed.

[0045] Specifically, whether the target time is reached can be determined by whether the number of minutes at the current time T is divisible by the calculation period Q. For example, if Q=15 minutes, the subsequent steps will be automatically started at the beginning of every 15 minutes.

[0046] An optional embodiment, regarding the data acquisition method, in addition to reading data directly from the EMS system, the required information can also be obtained from different data sources (such as smart meters, remote terminal units RTU, distribution automation systems, etc.) through real-time communication interfaces such as Modbus, DNP3 or IEC 61850 and other protocols, which can improve the real-time and accuracy of the data.

[0047] Another optional method, regarding the update of the distribution network model, the embodiment of the present invention can adopt a real-time update mechanism, that is, automatically checking and updating the distribution network model in each calculation cycle to reflect any changes in the grid structure (such as increase or decrease of equipment, reconstruction of lines, etc.). The specific implementation method can be achieved by integration with GIS (geographic information system) or SCADA (supervisory control and data acquisition system).

[0048] In addition, before analyzing the power flow calculation results, the data can be preprocessed (such as outlier detection, missing value filling, equipment status verification, etc.) to ensure the accuracy of subsequent analysis. For example, intelligent algorithms (such as machine learning) can be used to predict potential failures of circuit breakers or disconnectors and take them into account in the calculation.

[0049] In the embodiment of the present invention, an enhanced power flow calculation method can also be adopted, and advanced analysis methods (such as fast decoupling method or Newton-Raphson iteration method) are introduced to improve calculation efficiency and accuracy, consider nonlinear factors and dynamic characteristics in the power grid, such as load changes, fluctuations in new energy output, etc., and use a dynamic power flow calculation model to more accurately reflect the real-time status of the distribution network.

[0050] Optionally, the distribution network model is used to record the physical structure information of the target distribution network, and the transformer low-voltage side model is used to record the electrical structure information of the distributed new energy equipment connected to the low-voltage side node of each transformer, wherein the physical structure information at least includes: equipment parameters of each distribution equipment in the target distribution network and a first equipment connection method, the first equipment connection method refers to the connection method between each distribution equipment and other distribution equipment, and the electrical structure information at least includes: electrical parameters of the distributed new energy equipment and a second equipment connection method, the second equipment connection method refers to the connection method between the distributed new energy equipment and the distribution equipment of the target distribution network.

[0051] It should be noted that the distribution network model records the equipment parameters of all distribution equipment (such as transformers, lines, circuit breakers, etc.) and the connection methods between them. The equipment parameters may include: rated voltage, rated capacity, impedance, etc. of the equipment. The first equipment connection method describes how the various devices in the power grid are connected to each other through lines to form a network structure.

[0052] Another thing that needs to be explained is that the low-voltage side model of the transformer is used to record the electrical structure information of the distributed new energy equipment connected to the low-voltage side node of each transformer (the transformer connecting the high-voltage distribution network and the low-voltage user power grid). The electrical parameters may include: the rated voltage, rated power, power factor, etc. of the equipment, and the second device connection mode is used to describe how the distributed new energy equipment is connected to the low-voltage side node of the transformer.

[0053] Optionally, the power flow calculation results of the target distribution network include: the low-voltage side node voltage, active power data and reactive power data of the transformer, the active power data and reactive power data of distributed new energy, the circuit breaker status, disconnector status, capacitor status and reactor status in the target distribution network.

[0054] It should be noted that power flow calculation is a commonly used calculation method in power systems. It is used to analyze the power flow of the power grid at a certain moment, including the voltage of each node, the active power and reactive power entering and leaving the node, and the status of circuit breakers, disconnectors, capacitors and reactors. The above power flow data reflects the real-time operating status of the power grid and is crucial for voltage control.

[0055] Step S102, performing a topological analysis based on the distribution network model, the transformer low-voltage side model and the power flow calculation results to obtain the feeder area and the transformer area in the feeder area, wherein the transformer area includes the transformer and F distributed new energy devices connected to the low-voltage side connection point of the transformer, where F is a positive integer.

[0056] Step S102 determines the feeder area in the distribution network and the transformer area in each feeder area through topological analysis based on the real-time model of the distribution network, the transformer low-voltage side model and the power flow calculation results. The purpose is to more accurately identify which transformers and distributed new energy equipment need to be included in the same control area for subsequent effective automatic voltage control.

[0057] It should be noted that in the topology analysis step based on the distribution network model and the flow calculation results, the distribution network model contains the physical structure information of the power grid, such as the location and connection relationship of lines, transformers, circuit breakers, etc., and the flow calculation results reflect the operating status of the power grid at a certain point in time, including the voltage, current and power distribution of each node. Through joint topology analysis, the electrically connected areas, namely the feeder areas, can be identified.

[0058] From the comprehensive analysis of the distribution network model and the power flow calculation results, D feeder areas consisting of feeder segments and transformers are extracted. For each feeder area, the topological structure is further analyzed to identify the T transformers connected to it and the distributed new energy equipment connected to the low-voltage side of these transformers, thereby obtaining T transformer areas.

[0059] It should be noted that the feeder area is divided according to the physical connection and electrical characteristics of the power grid. Each area represents a set of electrically closely connected equipment. The definition of the transformer area is more detailed, focusing on a certain transformer and the collection of distributed new energy equipment connected to it, which is crucial for precise control and regulation of reactive power and voltage.

[0060] In the process of topological analysis, traditional topological analysis may be based on traditional relational databases, but when dealing with complex power grid topologies, graph databases (such as Neo4j or JanusGraph) may provide more efficient and intuitive solutions, which can better manage the node and edge relationships in the power grid and quickly identify feeder areas and transformer areas.

[0061] Considering that the distribution network model may be very large, the embodiments of the present invention may also use a distributed computing framework (such as Apache Spark or Hadoop) to accelerate the topology analysis process, which can make the analysis of large-scale power grid models faster, especially in real-time or quasi-real-time scenarios.

[0062] In addition, the embodiments of the present invention can also use machine learning models (such as deep learning networks) to predict grid topology changes in advance when extracting feeder areas and transformer areas, thereby giving priority to areas that may experience larger power fluctuations in the next few hours in the topology analysis, thereby improving the pertinence and effectiveness of control.

[0063] Optionally, step S102 includes: performing a topological analysis on the distribution network model based on the power flow calculation results and the transformer low-voltage side model to obtain a first topological analysis result, and extracting D feeder areas from the first topological analysis result, wherein the feeder area consists of feeder segments and transformers in the target distribution network, and D is a positive integer; for each feeder area, performing a topological analysis on the feeder area based on the distribution network model and the transformer low-voltage side model to obtain a second topological analysis result, and extracting T transformer areas based on the T transformers recorded in the second topological analysis result, wherein T is a positive integer.

[0064] The above steps effectively identify D feeder areas and T transformer areas by performing a detailed topological analysis on the distribution network model, greatly improving the accuracy and response speed of the control system. The flow calculation results and the transformer low-voltage side model can accurately capture the real-time operating status and electrical connection characteristics of the distribution network, thereby generating the first and second topological analysis results to ensure an accurate understanding of the grid structure.

[0065] In-depth analysis of the power grid structure helps the system quickly locate key transformers and feeder segments, providing a solid foundation for subsequent voltage control strategies. In particular, the extraction of transformer areas helps to manage the access of distributed renewable energy in a targeted manner, effectively prevent voltage fluctuations and ensure stable operation of the power grid, thereby improving the overall efficiency and reliability of the power system.

[0066] Step S103, obtaining active power prediction data of distributed new energy equipment in the transformer area, and determining the active power change trend of the transformer within the target time period based on all active power prediction data.

[0067] Optionally, step S103 includes: for each station-changing area, extracting active power prediction data of F distributed new energy devices in the station-changing area in the target time period from the data center system to obtain F active power prediction sequences, wherein the active power prediction sequence includes N active power prediction data, each active power prediction data corresponds to a unique prediction time point, and N is a positive integer; based on the N prediction time points and the active power prediction sequence of the distributed new energy devices, N overall active power prediction data of the station-changing area in the target time period are calculated; based on the N overall active power prediction data, the active power peak-valley difference of the station-changing area in the target time period is calculated, and the active power peak-valley difference is compared with a preset peak-valley threshold value to obtain a comparison result; based on the comparison result, the active power change trend of the station-changing area in the target time period is determined.

[0068] It should be noted that the above steps first obtain the active power prediction data of the distributed new energy equipment in each transformer area from the data middle station system (a platform for centralized processing and storage of power grid data) to form an active power prediction sequence, wherein the active power prediction sequence is composed of N active power prediction data, each of which corresponds to a specific time point in the target time period, where the size of N depends on the resolution of the prediction and the length of the target time period, for example, in a 4-hour prediction with a prediction interval of 15 minutes, N = 16. Then the active power prediction sequences of F distributed new energy devices are merged to calculate the total predicted active power value of the entire transformer area at each prediction time point, which is essentially to accumulate the active power at the time point to form a sequence reflecting the active power dynamics of the entire area.

[0069] Then, the peak-to-valley difference of the active power in the transformer area during the target time period is calculated, that is, the difference between the highest predicted active power value and the lowest predicted active power value, which is used to measure the degree of fluctuation of the active power and then determine whether voltage control is needed to cope with possible fluctuations.

[0070] Finally, the calculated active power peak-to-valley difference is compared with the preset peak-to-valley threshold value. If the difference is less than the threshold value, it means that the fluctuation of active power is within an acceptable range and there is no need to perform voltage control operation immediately. On the contrary, if the difference is greater than or equal to the threshold value, the next step is entered to analyze the current active power status of the transformer and the predicted data to determine the specific change trend.

[0071] Optionally, in addition to obtaining forecast data from the data middle-end system, an embodiment of the present invention can also extract active power forecast information from a dedicated weather forecast service, historical data analysis, or a comprehensive forecast model combined with real-time meteorological data.

[0072] In addition, a rolling window can be used to calculate the peak-to-valley difference, that is, to calculate the difference between the maximum and minimum values ​​in the past m time points at each time point, so as to monitor the fluctuation of active power more carefully, and the preset peak-to-valley threshold value can be adjusted dynamically. For example, a more appropriate threshold value can be adaptively set based on the analysis of historical data or the real-time grid operation status to better adapt to different grid conditions and operating environments.

[0073] Optionally, the step of determining the active power change trend of the transformer within the target time period based on the comparison result includes: when the comparison result indicates that the active power peak-valley difference is less than a preset peak-valley threshold value, confirming that it is temporarily not necessary to perform voltage control operation on the transformer within the target time period; or, when the comparison result indicates that the active power peak-valley difference is greater than or equal to the preset peak-valley threshold value, reading the active power data of the transformer at the current moment from the power flow calculation result of the target distribution network; based on the active power data of the transformer at the current moment and N overall active power prediction data of the transformer area within the target time period, determining the active power change trend of the transformer.

[0074] Step S104: generating a voltage control strategy within a target time period based on the active power variation trend of the transformer.

[0075] Optionally, step S104 includes: when the active power change trend indicates that the target time period is an active power growth period of the transformer, determining the voltage control strategy as voltage downshift processing and / or capacitor removal; when the active power change trend indicates that the target time period is an active power reduction period of the transformer, determining the voltage control strategy as voltage upshift processing and / or capacitor input.

[0076] Step S104 analyzes the predicted active power change trend and formulates a voltage control strategy in advance to ensure the voltage stability and economic operation of the power grid. Specifically, if the forecast shows that the active power of the transformer will enter a growth period within the target time period (such as the next hour), the control strategy may focus on voltage downshifting and / or removing capacitors to prevent excessive voltage; conversely, if the active power will enter a reduction period, the control strategy may focus on voltage upshifting and / or adding capacitors to avoid excessive voltage.

[0077] In addition to the preset fixed thresholds (such as α, peak-to-valley difference thresholds), in the embodiments of the present invention, dynamic thresholds can be introduced to adjust the control strategy according to the current load conditions, voltage levels, and seasonal demand changes. For example, in high-load summer, even if the active power change rate is small, a more aggressive voltage control strategy may be required.

[0078] In addition to capacitors, energy storage systems (such as battery storage) can also be considered in the control strategy. During the period of active power growth, the energy storage system can absorb additional power to prevent excessive voltage increase; during the period of active power reduction, the energy storage system can release the stored power to support the voltage level.

[0079] Through the above steps S101 to S104, when the target time is reached, the distribution network model, the transformer low-voltage side model and the power flow calculation results of the target distribution network can be first obtained from the power grid energy management system, and then a topological analysis is performed based on the distribution network model, the transformer low-voltage side model and the power flow calculation results to obtain the feeder area and the transformer area in the feeder area, wherein the transformer area includes the transformer and F distributed new energy devices connected to the low-voltage side connection point of the transformer, and F is a positive integer, and then the active power prediction data of the distributed new energy devices in the transformer area is obtained, and the active power change trend of the transformer in the target time period is determined based on all the active power prediction data, and finally the voltage control strategy in the target time period is generated based on the active power change trend of the transformer.

[0080] The embodiment of the present invention realizes effective control of voltage fluctuations through intelligent analysis and prediction. The distribution network model, transformer low-voltage side model and power flow calculation results obtained from the power grid energy management system provide a basis for subsequent topological analysis. The feeder area and the transformer area therein can be accurately located by deeply analyzing the power grid structure and operation status. In particular, the number of distributed new energy devices F in the transformer area is dynamic. The step of predicting the active power of distributed new energy devices helps to timely understand the active power change trend of the transformer in the target time period. This key step to solve the voltage fluctuation problem is directly related to the impact of the power output of the new energy device on the grid voltage. Finally, a voltage control strategy for the target time period is generated according to the obtained active power change trend. The power supply and demand of the grid are balanced through the intelligent regulation of the new energy device, thereby suppressing the voltage fluctuation at the source and ensuring the power quality and stable operation of the grid. The above process covers the closed-loop control logic from data acquisition, analysis and prediction to strategy generation, which significantly improves the voltage management level after the distributed new energy is connected to the grid, thereby solving the technical problem in the related technology that the distributed new energy is easy to cause grid voltage fluctuation after the grid is connected.

[0081] The present invention is described below in conjunction with another specific implementation manner.

[0082] The embodiment of the present invention proposes an automatic voltage control method for a substation in a substation area based on the prediction of distributed renewable energy, automatically generates the connection relationship between the substation of the distribution network and the distributed renewable energy, and merges the active power prediction result of the distributed renewable energy into the change trend of the active power on the substation. When the active power of the substation changes rapidly in a short period of time, the substation of the substation or the capacitor mounted on the substation is adjusted preferentially to give the substation area sufficient reactive power and voltage margin, stabilize the voltage level in the area, and avoid voltage limit violations or drastic voltage fluctuations caused by power fluctuations of renewable energy.

[0083] The specific control steps include the following:

[0084] S1, pre-set the calculation period Q, generally set Q = 15 minutes.

[0085] S2, the current time is T. If the number of minutes at time T is divisible by Q, the calculation starts, and the complete distribution network and the model, connection relationship and power flow calculation result data of the distributed renewable energy in the substation area are obtained from the power grid EMS system, thereby forming a connection relationship between the substation and the distributed renewable energy, including:

[0086] In the complete distribution network model, the circuit breakers and disconnectors in the split state are deleted according to the results of the power flow;

[0087] Perform topological analysis on the retained distribution network model to form several feeder areas, each of which includes several grid devices that are electrically connected together;

[0088] Check all feeder areas in turn. One or more 10kV line segments in a loop form a feeder area. Total D Articles, defined as: in, Refers to 10kV line segments, i.e. multiple 10kV distribution network feeder line segments connected from 10kV outgoing lines, whose ends are connected to the upper 10kV lines or other line segments, totaling S lines, T t 10 Refers to the transformer at the end of the feeder, which is the substation transformer. It is the key equipment connecting the 10kV high-voltage distribution network and the 380V low-voltage user network. It is referred to as substation transformer. There are T in total. One end is connected to a 10kV line segment node, and the other end is connected to the line end of the 380V distributed new energy grid on the low-voltage side. This connection method means that the substation transformer is not only responsible for supplying power from the high-voltage power grid to low-voltage users, but also can accept power input from distributed new energy (such as solar photovoltaic panels, wind turbines), and integrate the power of these new energy into the power grid;

[0089] The topology analysis of the distributed renewable energy under each transformer is carried out. The integrated control terminals of multiple distributed renewable energy can be connected to the 380V terminal of the transformer through different line segments for grid connection. Each transformer connected to each distributed renewable energy can be called the transformer area T t 10 , and added to the feeder area Among them, the station changes area T t 10 It can be defined as: in, It refers to the distributed renewable energy connected in each transformer area. The distributed renewable energy is connected to the nodes on the 380V side of the transformer, totaling F.

[0090] S3, First, set d = 1. area to be calculated.

[0091] S4, in the area In, T t 10 ,t=1...T, first set t=1, change area T t 10 Perform calculations.

[0092] S5, station change area T t 10 Including distributed new energy Read the station change area T from the data center system t 10 The active power prediction data of the f distributed renewable energy sources in The prediction data interval is 15 minutes, and the data of 16 moments in the next 4 hours starting from the current moment is read, which is the ultra-short-term power prediction of the distributed renewable energy. The new energy prediction data of the f distributed renewable energy in the substation area at the next 16 moments is represented by a matrix: Among them, P f Represents the active power forecast data of the fth distributed renewable energy source in the next 4 hours, It represents the predicted active power value of the fth distributed renewable energy at the kth moment, where f=1...F, k=1...16.

[0093] S6, change the station to area T t 10 For example, the active power forecast data of the f distributed renewable energy sources in the 4-hour period is accumulated at each moment, and the station transformer area T is obtained. t 10 The active power forecast data for 16 moments in the next 4 hours is expressed in a matrix as follows:

[0094]

[0095] Among them, G t Represents the tth station change area T t 10 Active power forecast data for the next 4 hours, Represents the active power prediction data of the t-th transformer area at the k-th moment, where k=1...16.

[0096] S7, in the prediction data of 16 moments, the current moment T is set as the 0th moment, and the station change area T t 10The reactive voltage is pre-regulated based on the change trend of active power at 16 moments in the next 4 hours. First, the change trend is determined. According to the station transformer area T obtained in step 6 t 10 Active power forecast data for the next 4 hours G t , make a determination, including:

[0097] In G t In the example, the current time T corresponds to the 0th time point, and the active power prediction value corresponding to the 1st time point of the next 15 minutes is The predicted active power value at the second moment is The predicted active power value at the 16th moment is

[0098] Determine the peak-to-valley difference of the 16 time points of the next 4 hours. t The maximum value is set to The minimum value is set to right These 16 numbers are judged cyclically: set the initial value a = 1, if but if but Let a=a+1, if a≤16, continue looping, otherwise exit the loop, and get and The peak-to-valley difference is

[0099] Set the peak-to-valley difference threshold to ΔG t ,if Then continue to the next step, if Then t=t+1, and the process returns to S4 to determine the next station change area;

[0100] Set the change rate threshold α to continuously judge the data of the four time points in the next hour from the current time, including: reading the current real-time active power of the current substation from the flow data Set the variable initial value L I =0,L D =0,L I A counter for determining the active power trend rising time, L D To determine the counter of the active power trend decline time, set the initial value b = 1, and determine the change rate between the current moment and the previous moment. The formula is in is the rate of change of active power at time b relative to the previous time. If And satisfy Then L I=L I +1 if and Then L D =L D +1, let b=b+1, if a<=4, then continue to judge at the next moment, otherwise exit the loop and get L I and L D , if L I ≥3, it is considered that the area will enter a period of rapid active power growth in the next hour. D ≥3, it is considered that the substation will enter a period of rapid active power reduction in the next hour.

[0101] S8, if the substation is about to enter a period of rapid active power growth, the voltage at the end of the substation will also increase significantly. Therefore, the substation AVC system needs to downshift or remove the capacitor to provide the voltage with a sufficient reactive power support range to cope with the rapid increase and fluctuation of active power.

[0102] If the substation is about to enter a period of rapid reduction in active power, the voltage at the end of the substation will drop significantly. Therefore, the substation AVC system needs to be upgraded or capacitors need to be put into use to ensure that the reduction in active power does not cause the voltage to drop rapidly below the safety limit.

[0103] S9, set t=t+1, if t<=T, then enter S4 to continue to determine the next station change area; if t>T, set d=d+1 and enter S3 to determine the next feeder area. If d>D, it means that all feeder areas have been determined.

[0104] S10, when the next cycle arrives, return to S2 to start a new round of calculation.

[0105] Figure 2 is a schematic diagram of an optional coordinated control area of ​​a transformer and distributed new energy according to an embodiment of the present invention, such as Figure 2 As shown in the figure, the distribution network in this area includes: 10kV distribution network line, capacitors connected to the line and transformer, and F distributed new energy equipment connected to the 380V end of the transformer ( Figure 2 (In the figure, F=3 is taken as an example).

[0106] The automatic voltage control method for substations in a substation area based on distributed renewable energy prediction proposed in the embodiment of the present invention belongs to the technical field of automatic voltage control of power systems. The method reads the complete transmission and distribution network model, the model of the low-voltage side of the transformer and the flow calculation results at the arrival of each calculation cycle, automatically generates the connection relationship between the transformer and the distributed renewable energy in the distribution network, and calculates the active power prediction change trend of the transformer according to the active power prediction results of the distributed renewable energy read from the transformer system in the data. When it is monitored that the active power of the transformer changes rapidly in a short period of time, the transformer's branch or the mounted capacitor on the transformer is adjusted preferentially to leave sufficient reactive power and voltage margin to stabilize the voltage level in the area, avoid voltage exceeding the limit or drastic voltage fluctuation caused by power fluctuation of renewable energy, thereby improving the voltage stability and voltage quality of the transmission and distribution network, and also ensuring the economical operation of the power grid.

[0107] The present invention is described below in conjunction with another optional embodiment.

[0108] Embodiment 2

[0109] The automatic voltage control device for a transformer substation provided in this embodiment includes a plurality of implementation units, each of which corresponds to each implementation step in the above-mentioned first embodiment.

[0110] Figure 3 is a schematic diagram of an optional automatic voltage control device for a substation in a substation area according to an embodiment of the present invention, such as Figure 3 As shown, the device may include: an acquisition unit 31, an analysis unit 32, a determination unit 33, and a generation unit 34.

[0111] The acquisition unit 31 is used to acquire the distribution network model, the transformer low-voltage side model and the power flow calculation results of the target distribution network from the power grid energy management system when the target time is reached.

[0112] The analysis unit 32 is used to perform topological analysis based on the distribution network model, the transformer low-voltage side model and the flow calculation results to obtain the feeder area and the transformer area in the feeder area, wherein the transformer area includes the transformer and F distributed new energy devices connected to the low-voltage side connection point of the transformer, where F is a positive integer.

[0113] The determination unit 33 is used to obtain the active power prediction data of the distributed new energy equipment in the transformer area, and determine the active power change trend of the transformer within the target time period based on all the active power prediction data.

[0114] The generating unit 34 is used to generate a voltage control strategy within a target time period based on the active power variation trend of the transformer.

[0115] The automatic voltage control device of the above-mentioned substation area can reach the target time. First, the acquisition unit 31 is used to obtain the distribution network model, the transformer low-voltage side model and the power flow calculation results of the target distribution network from the power grid energy management system. Then, the analysis unit 32 performs topological analysis based on the distribution network model, the transformer low-voltage side model and the power flow calculation results to obtain the feeder area and the transformer area in the feeder area, wherein the transformer area includes the transformer and F distributed new energy devices connected to the low-voltage side connection point of the transformer, and F is a positive integer. Then, the active power prediction data of the distributed new energy devices in the transformer area is obtained by the determination unit 33, and the active power change trend of the transformer in the target time period is determined based on all the active power prediction data. Finally, the voltage control strategy in the target time period is generated based on the active power change trend of the transformer by the generation unit 34.

[0116] In the embodiment of the present invention, effective control of voltage fluctuation is achieved through intelligent analysis and prediction. The distribution network model, transformer low-voltage side model and power flow calculation results obtained from the power grid energy management system provide a basis for subsequent topological analysis. The feeder area and the transformer area therein can be accurately located by deeply analyzing the power grid structure and operation status. In particular, the number of distributed new energy devices F in the transformer area is dynamic. The step of predicting the active power of distributed new energy devices helps to timely understand the active power change trend of the transformer in the target time period. This key step to solve the voltage fluctuation problem is directly related to the impact of the power output of the new energy device on the grid voltage. Finally, a voltage control strategy for the target time period is generated according to the obtained active power change trend. The power supply and demand of the grid are balanced through the intelligent regulation of the new energy device, thereby suppressing the voltage fluctuation at the source and ensuring the power quality and stable operation of the grid. The above process covers the closed-loop control logic from data acquisition, analysis and prediction to strategy generation, which significantly improves the voltage management level after the distributed new energy is connected to the grid, thereby solving the technical problem in the related technology that the distributed new energy is easy to cause grid voltage fluctuation after the grid is connected.

[0117] Optionally, the distribution network model is used to record the physical structure information of the target distribution network, and the transformer low-voltage side model is used to record the electrical structure information of the distributed new energy equipment connected to the low-voltage side node of each transformer, wherein the physical structure information at least includes: equipment parameters of each distribution equipment in the target distribution network and a first equipment connection method, the first equipment connection method refers to the connection method between each distribution equipment and other distribution equipment, and the electrical structure information at least includes: electrical parameters of the distributed new energy equipment and a second equipment connection method, the second equipment connection method refers to the connection method between the distributed new energy equipment and the distribution equipment of the target distribution network.

[0118] Optionally, the power flow calculation results of the target distribution network include: the low-voltage side node voltage, active power data and reactive power data of the transformer, the active power data and reactive power data of distributed new energy, the circuit breaker status, disconnector status, capacitor status and reactor status in the target distribution network.

[0119] Optionally, the analysis unit includes: a first analysis module, used to perform a topological analysis on the distribution network model based on the power flow calculation results and the transformer low-voltage side model to obtain a first topological analysis result, and extract D feeder areas from the first topological analysis result, wherein the feeder area consists of feeder segments and transformers in the target distribution network, and D is a positive integer; a second analysis module, used to perform a topological analysis on each feeder area based on the distribution network model and the transformer low-voltage side model to obtain a second topological analysis result, and extract T transformer areas based on the T transformers recorded in the second topological analysis result, wherein T is a positive integer.

[0120] Optionally, the determination unit includes: an extraction module, which is used to extract the active power prediction data of F distributed new energy devices in the station change area in the target time period from the data center system for each station change area, and obtain F active power prediction sequences, wherein the active power prediction sequence contains N active power prediction data, each active power prediction data corresponds to a unique prediction time point, and N is a positive integer; a calculation module, which is used to calculate N overall active power prediction data of the station change area in the target time period based on the N prediction time points and the active power prediction sequence of the distributed new energy equipment; a comparison module, which is used to calculate the active power peak-valley difference of the station change area in the target time period based on the N overall active power prediction data, and compare the active power peak-valley difference with a preset peak-valley threshold value to obtain a comparison result; a first determination module, which is used to determine the active power change trend of the station change in the target time period based on the comparison result.

[0121] Optionally, the first determination module includes: a confirmation submodule, which is used to confirm that it is not necessary to perform voltage control operation on this transformer within the target time period when the comparison result indicates that the active power peak-valley difference is less than the preset peak-valley threshold value; a reading submodule, which is used to read the active power data of this transformer at the current moment from the flow calculation result of the target distribution network when the comparison result indicates that the active power peak-valley difference is greater than or equal to the preset peak-valley threshold value; and a determination submodule, which is used to determine the active power change trend of the transformer based on the active power data of the transformer at the current moment and N overall active power prediction data of the transformer area within the target time period.

[0122] Optionally, the generating unit includes: a second determination module, used to determine that the voltage control strategy is voltage downshifting and / or capacitor removal when the active power change trend indicates that the target time period is an active power growth period of the transformer; a second determination module, used to determine that the voltage control strategy is voltage upshifting and / or capacitor input when the active power change trend indicates that the target time period is an active power reduction period of the transformer.

[0123] The automatic voltage control device of the above-mentioned substation area may also include a processor and a memory. The above-mentioned acquisition unit 31, analysis unit 32, determination unit 33, generation unit 34, etc. are all stored in the memory as program units, and the processor executes the above-mentioned program units stored in the memory to realize the corresponding functions.

[0124] The processor includes a kernel, which retrieves the corresponding program unit from the memory. One or more kernels can be set, and the active power prediction data of the distributed new energy equipment in the transformer area can be obtained by adjusting the kernel parameters, and the active power change trend of the transformer in the target time period is determined based on all the active power prediction data, and the voltage control strategy in the target time period is generated based on the active power change trend of the transformer.

[0125] The above-mentioned memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one storage chip.

[0126] The present application also provides a computer program product, which, when executed on a data processing device, is suitable for executing a program that is initialized with the following method steps: when the target time is reached, obtaining the distribution network model, the transformer low-voltage side model and the power flow calculation results of the target distribution network from the power grid energy management system; performing a topological analysis based on the distribution network model, the transformer low-voltage side model and the power flow calculation results to obtain the feeder area and the transformer area in the feeder area, wherein the transformer area includes the transformer and F distributed new energy devices connected to the low-voltage side connection point of the transformer, and F is a positive integer; obtaining the active power prediction data of the distributed new energy devices in the transformer area, and determining the active power change trend of the transformer within the target time period based on all the active power prediction data; and generating a voltage control strategy within the target time period based on the active power change trend of the transformer.

[0127] According to another aspect of an embodiment of the present invention, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute the automatic voltage control method of the substation in the substation area of ​​any one of the above-mentioned embodiments.

[0128] According to another aspect of an embodiment of the present invention, there is also provided an electronic device, comprising one or more processors and a memory, wherein the memory is used to store one or more programs, wherein when the one or more programs are executed by one or more processors, the one or more processors implement the automatic voltage control method of a substation in a substation area according to any one of the above-mentioned embodiments one.

[0129] Figure 4 1 is a hardware structure block diagram of an electronic device (or mobile device) for an automatic voltage control method for a substation in a substation area according to an embodiment of the present invention. Figure 4 As shown, the electronic device may include one or more ( Figure 4 The processor 402 (the processor 402 may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA) and a memory 404 for storing data. In addition, the device may also include: a display, an input / output interface (I / O interface), a universal serial bus (USB) port (which may be included as one of the ports of the I / O interface), a network interface, a keyboard, a power supply and / or a camera. A person skilled in the art will understand that Figure 4 The structure shown is only for illustration and does not limit the structure of the above electronic device. Figure 4 More or fewer components as shown, or with Figure 4 Different configurations shown.

[0130] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0131] In the above embodiments of the present invention, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0132] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of the units can be a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0133] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0134] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0135] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk and other media that can store program codes.

[0136] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. An automatic voltage control method for a substation, characterized in that: include: When the target time is reached, the power flow calculation results of the distribution network model, the transformer low-voltage side model and the target distribution network are obtained from the power grid energy management system; Perform a topological analysis based on the distribution network model, the transformer low-voltage side model and the power flow calculation result to obtain a feeder area and a transformer area in the feeder area, wherein the transformer area includes a transformer and F distributed new energy devices connected to the low-voltage side connection point of the transformer, where F is a positive integer; Acquire active power prediction data of the distributed new energy equipment in the transformer area, and determine the active power change trend of the transformer within a target time period based on all the active power prediction data; A voltage control strategy within the target time period is generated based on the active power variation trend of the transformer.

2. The automatic voltage control method according to claim 1, characterized in that: The distribution network model is used to record the physical structure information of the target distribution network, and the transformer low-voltage side model is used to record the electrical structure information of the distributed new energy equipment connected to each low-voltage side node of the transformer. The physical structure information at least includes: equipment parameters of each power distribution device in the target power distribution network and a first equipment connection mode, wherein the first equipment connection mode refers to a connection mode between each of the power distribution devices and other power distribution devices, The electrical structure information includes at least: electrical parameters of the distributed new energy equipment and a second device connection mode, where the second device connection mode refers to a connection mode between the distributed new energy equipment and a distribution device of the target distribution network.

3. The automatic voltage control method according to claim 2, characterized in that: The power flow calculation results of the target distribution network include: the low-voltage side node voltage, active power data and reactive power data of the transformer, the active power data and reactive power data of the distributed new energy, and the circuit breaker status, disconnector status, capacitor status and reactor status in the target distribution network.

4. The automatic voltage control method according to claim 1, characterized in that: The step of performing topological analysis based on the distribution network model, the transformer low-voltage side model and the power flow calculation result to obtain the feeder area and the transformer area in the feeder area includes: Performing a topological analysis on the distribution network model according to the power flow calculation result and the transformer low-voltage side model to obtain a first topological analysis result, and extracting D feeder areas from the first topological analysis result, wherein the feeder area is composed of feeder segments and transformers in the target distribution network, and D is a positive integer; For each of the feeder areas, a topological analysis is performed on the feeder area based on the distribution network model and the transformer low-voltage side model to obtain a second topological analysis result, and T transformer areas are extracted based on the T transformers recorded in the second topological analysis result, where T is a positive integer.

5. The automatic voltage control method according to claim 1, characterized in that: The steps of obtaining active power prediction data of the distributed new energy equipment in the transformer area, and determining the active power change trend of the transformer within a target time period based on all the active power prediction data, include: For each of the station change areas, extract the active power prediction data of the F distributed new energy devices in the station change area in the target time period from the data station system to obtain F active power prediction sequences, wherein the active power prediction sequence contains N active power prediction data, each of the active power prediction data corresponds to a unique prediction time point, and N is a positive integer; Calculate N overall active power prediction data of the transformer area within the target time period based on the N prediction time points and the active power prediction sequence of the distributed new energy equipment; Calculating the active power peak-to-valley difference of the transformer area in the target time period based on the N overall active power prediction data, and comparing the active power peak-to-valley difference with a preset peak-to-valley threshold value to obtain a comparison result; The active power variation trend of the transformer within the target time period is determined based on the comparison result.

6. The automatic voltage control method according to claim 5, characterized in that: The step of determining the active power change trend of the transformer within the target time period based on the comparison result includes: When the comparison result indicates that the active power peak-to-valley difference is less than the preset peak-to-valley threshold value, confirming that it is not necessary to perform voltage control operation on the transformer within the target time period; or, When the comparison result indicates that the active power peak-to-valley difference is greater than or equal to the preset peak-to-valley threshold value, reading the active power data of the transformer at the current moment from the power flow calculation result of the target distribution network; Based on the active power data of the transformer at the current moment and N overall active power prediction data of the transformer area within a target time period, the active power change trend of the transformer is determined.

7. The automatic voltage control method according to claim 1, characterized in that: The step of generating a voltage control strategy within the target time period based on the active power variation trend of the transformer comprises: When the active power variation trend indicates that the target time period is an active power growth period of the transformer, determining that the voltage control strategy is voltage downshift processing and / or capacitor removal; When the active power variation trend indicates that the target time period is an active power reduction period of the transformer, the voltage control strategy is determined to be a voltage upshift process and / or a capacitor input.

8. An automatic voltage control device for a substation, characterized in that: include: An acquisition unit is used to acquire the distribution network model, the transformer low-voltage side model and the power flow calculation results of the target distribution network from the power grid energy management system when the target time is reached; An analysis unit, configured to perform a topological analysis based on the distribution network model, the transformer low-voltage side model and the power flow calculation result to obtain a feeder area and a transformer area in the feeder area, wherein the transformer area includes a transformer and F distributed new energy devices connected to a low-voltage side connection point of the transformer, where F is a positive integer; A determination unit, configured to obtain active power prediction data of the distributed new energy equipment in the transformer area, and determine an active power change trend of the transformer within a target time period based on all the active power prediction data; A generating unit is used to generate a voltage control strategy within the target time period based on the active power variation trend of the transformer.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored computer program, wherein when the computer program is executed, the device where the computer-readable storage medium is located is controlled to execute the automatic voltage control method for a substation in an area as claimed in any one of claims 1 to 7.

10. An electronic device, characterized in that: It includes one or more processors and a memory, wherein the memory is used to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the automatic voltage control method for a substation in a substation area as described in any one of claims 1 to 7.

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