DC power supply intelligent sharing system and method for substation

Abstract

The present invention discloses a DC power intelligent sharing system and method for a substation, which relates to the technical field of substations. The system comprises: installing sensors at each load end of the substation to obtain monitoring data; determining the load type; configuring parallel DC power supplies; establishing a load distribution node according to the load processing capacity and the remaining load capacity; configuring distribution rules based on the load type; distributing the load request capacity, determining the distribution relationship between the load request capacity and the load distribution node; and performing shared distribution of the parallel DC power supplies. The system solves the technical problem that the DC power supply of the existing substation is equipped with multiple independent DC power supplies at multiple load ends, which makes it difficult to cope with large load fluctuations and easily causes power supply overload, thereby leading to poor stability and reliability of the substation and low resource utilization efficiency. The system realizes the intelligent sharing of DC power supplies and achieves the technical effect of improving resource utilization efficiency and the stability and reliability of the substation.

Description

Technical Field

[0001] The present application relates to the technical field related to substations, and in particular to a system and method for intelligently sharing a DC power supply for substations. Background Art

[0002] Therefore, in the current substation DC power supply related technologies, there are technical problems such as multiple load ends are equipped with independent DC power supplies, which makes it difficult to cope with large load fluctuations and easily causes power supply overload, thereby leading to poor stability and reliability of the substation and low resource utilization efficiency. Summary of the Invention

[0003] The present application provides a DC power supply intelligent sharing system and method for substations, thereby solving the technical problem that the DC power supply of existing substations is equipped with multiple independent DC power supplies at multiple load ends, which makes it difficult to cope with large load fluctuations and easily causes power supply overload, thereby leading to poor stability and reliability of the substation and low resource utilization efficiency. The application realizes the intelligent sharing of DC power supply and achieves the technical effect of improving resource utilization efficiency and the stability and reliability of the substation.

[0004] The present application provides a DC power intelligent sharing system for a substation, the system comprising: a monitoring data acquisition module for installing sensors at each load end of the substation to obtain monitoring data, including monitoring current and power fluctuations; a load type determination module for identifying load characteristics based on the monitoring data and determining the load type, the load type including continuous load and intermittent load, and using the load type to generate a type label to identify the load at each load end; a parallel DC power configuration module for configuring parallel DC power supplies, the parallel DC power supply including multiple DC power supplies, and obtaining the load processing capacity and remaining load capacity of each DC power supply; a load distribution node establishment module for determining the load processing capacity and remaining load capacity of each DC power supply according to the monitoring data ... The load processing capacity and remaining load of each DC power supply are used to establish a load distribution node, where the load distribution node corresponds to the parallel position of the DC power supply, and the load of the load distribution node corresponds to the remaining load; a distribution rule configuration module is used to obtain the load request amount of the load end and configure the distribution rule based on the load type of the load request amount; a distribution relationship determination module is used to distribute the load request amount based on the distribution rule according to the remaining load amount of the load distribution node, and determine the distribution relationship between the load request amount and the load distribution node; a parallel DC power supply sharing distribution module is used to perform shared distribution of parallel DC power supplies according to the distribution relationship.

[0005] In a possible implementation, the load type determination module further performs the following processing: extracting a load data set based on the monitoring data; calculating the mean, variance, peak value and frequency characteristics of the load data set; extracting the continuous interval characteristics of the load based on the calculation results of the mean, variance, peak value and frequency characteristics, and setting the load type based on the continuous interval characteristics.

[0006] In a possible implementation, the load type determination module also performs the following processing: extracting the core frequency component based on the frequency characteristics; determining the duty cycle of the load signal based on the core frequency component; reconstructing the time domain information through inverse Fourier transform based on the core frequency component to determine the working time and interval time of the load signal within the duty cycle; calculating the continuous time mean, continuous time variance, interval time mean, and interval time variance based on the working time and interval time respectively using the mean and variance; identifying the ratio relationship between the continuous time and the interval time based on the continuous time mean, continuous time variance, interval time mean, and interval time variance to determine the load type, wherein the continuous load is a continuous time mean that is greater than the interval time mean, and the variance of the continuous working time and the interval time is small.

[0007] In a possible implementation, the allocation rule configuration module further performs the following processing: configuring an allocation priority according to the load type, wherein the continuous load priority is greater than the intermittent load priority; when the remaining load amount does not meet the load request amount, activating the energy storage system for supplying power to the intermittent load; when the remaining load amount meets the continuous load and there is a surplus, dividing the supply of the intermittent load, wherein a part of the division is supplied through the energy storage system, and a part shares the DC power supply with the continuous load.

[0008] In a possible implementation, the distribution relationship determination module also performs the following processing: setting a load synchronization window based on the remaining load of the load distribution node, and the load synchronization window is used to synchronously meet all loads in the window; identifying the load type based on the load request amount, and extracting the load amount of the continuous load type; using the load synchronization window to traverse the load amount of the continuous load type, and determine the synchronization window matching relationship; identifying the window load amount based on the synchronization window matching relationship, and the window load amount is the load balance of the synchronization window; performing synchronization window segmentation based on the window load amount, and using the segmented window to perform intermittent load traversal distribution, and determining the matching relationship of the segmented window.

[0009] In a possible implementation, the allocation rule configuration module also performs the following processing: constructing an optimization objective function of the energy storage system with the operating cost minimized; obtaining the charging and discharging power of the energy storage system to meet the balance constraint condition of the DC power supply capacity; performing optimization based on the balance constraint condition and the optimization objective function to determine the energy supply timing chain of the energy storage system; extracting the load timing relationship based on the demand time and interval time of the intermittent load, optimizing the allocation with the goal of minimizing the waiting time of the intermittent load, and determining the load supply demand timing chain; configuring the weight coefficients of the energy supply timing chain and the load supply demand timing chain, wherein the weight coefficient of the energy supply timing chain is greater than the weight coefficient of the load supply demand timing chain; based on the weight coefficients, using the Nash equilibrium algorithm to perform equilibrium optimization on the energy supply timing chain and the load supply demand timing chain to determine the supply relationship between the energy storage system and the intermittent load.

[0010] In a possible implementation, the allocation rule configuration module further performs the following processing: the optimization objective function expression is: Among them, C e (t) is the operating cost of the energy storage system at time t, P e (t) is the discharge power of the energy storage system at time t, P c (t) is the charging power of the energy storage system at time t, φ is the charging and discharging efficiency of the energy storage system, and T is the total time period.

[0011] The present application also provides a method for intelligent sharing of DC power supplies for substations, the method comprising: installing sensors at each load end of the substation to obtain monitoring data, including monitoring current and power fluctuations; identifying load characteristics based on the monitoring data to determine the load type, the load type including continuous load and intermittent load, and using the load type to generate a type label to identify the load at each load end; configuring parallel DC power supplies, the parallel DC power supplies including multiple DC power supplies, and obtaining the load processing capacity and remaining load of each DC power supply; establishing a load distribution node based on the load processing capacity and remaining load of each DC power supply, the load distribution node corresponding to the parallel position of the DC power supply, and the load of the load distribution node corresponding to the remaining load; obtaining the load request amount of the load end, and configuring a distribution rule based on the load type of the load request amount; distributing the load request amount based on the distribution rule according to the remaining load amount of the load distribution node, and determining the distribution relationship between the load request amount and the load distribution node; and sharing the parallel DC power supplies according to the distribution relationship.

[0012] The proposed system and method for intelligent sharing of DC power supply for substations will install sensors at each load end of the substation to obtain monitoring data; determine the load type; configure parallel DC power supplies; establish load distribution nodes based on the load processing capacity and the remaining load; configure distribution rules based on the load type; distribute the load request amount and determine the distribution relationship between the load request amount and the load distribution node; and share the parallel DC power supply. This solves the technical problem that the existing DC power supply of substations, where multiple load ends are equipped with independent DC power supplies, are unable to cope with large load fluctuations, easily causing power supply overload, and thus leading to poor stability and reliability of the substation and low resource utilization efficiency, realizes intelligent sharing of DC power supply, and achieves the technical effect of improving resource utilization efficiency and the stability and reliability of the substation. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] To more clearly illustrate the technical solutions of the embodiments of the present disclosure, the accompanying drawings of the embodiments of the present disclosure are briefly introduced below. Flowcharts are used in this application to illustrate the operations performed by the systems according to the embodiments of the present application. It should be understood that the preceding or following operations are not necessarily performed in precise order. Instead, various steps may be processed in reverse order or simultaneously as needed. Furthermore, other operations may be added to these processes, or one or more operations may be removed from these processes.

[0014] Figure 1 A schematic diagram of the structure of a DC power supply intelligent sharing system for a substation provided in an embodiment of the present application;

[0015] Figure 2 A flow chart of a method for intelligent sharing of DC power supply for a substation provided in an embodiment of the present application.

[0016] Explanation of the accompanying drawings: monitoring data acquisition module 10, load type determination module 20, parallel DC power supply configuration module 30, load distribution node establishment module 40, distribution rule configuration module 50, distribution relationship determination module 60, parallel DC power supply sharing distribution module 70. DETAILED DESCRIPTION

[0017] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below.

[0018] In order to make the purpose, technical solutions and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings. The described embodiments should not be regarded as limiting this application. All other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0019] In the following description, reference is made to “some embodiments”, which describes a subset of all possible embodiments, but it will be understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict, and the terms “first\second” involved are merely used to distinguish similar objects and do not represent a specific ordering of the objects. The terms “including” and “having” and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, system, product, or server 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 modules that are not clearly listed or that are inherent to these processes, products, or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this application belongs. The terms used herein are for the purpose of describing the embodiments of this application only.

[0020] The embodiment of the present application provides a DC power intelligent sharing system for a substation, such as Figure 1 As shown, the system includes:

[0021] The monitoring data acquisition module 10 is configured to install sensors at each load terminal of the substation to acquire monitoring data, including current and power fluctuations. Based on the characteristics and installation conditions of the loads, appropriate sensors are installed at each load terminal of the substation to acquire monitoring data, including current and power fluctuations. Sensors are installed at each load terminal of the substation to monitor the operating status of each load in real time and acquire key operating data, thereby ensuring stable operation of the substation and reasonable power distribution. The acquired monitoring data includes current and power fluctuations. Specifically, current is an important parameter that characterizes the operating status of the load. By monitoring the load current value in real time through sensors, the load's real-time power consumption and whether it is in normal operating condition can be understood. For current measurement of high-voltage circuits, insulating clamps are required to ensure measurement accuracy and safety. The monitored current data can be used to determine the load type, such as continuous load or intermittent load. Power fluctuation reflects the dynamic changes of the load during operation. By monitoring power fluctuation, the load's stability and power quality requirements can be understood. The monitored power fluctuation data can be used to assess the stability and reliability of the power supply system and determine whether the power distribution strategy needs to be adjusted to cope with load changes.

[0022] The load type determination module 20 is used to identify the load characteristics based on the monitoring data and determine the load type. The load types include continuous load and intermittent load. The load type is used to generate a type label to identify the load of each load terminal. Load characteristic identification is to classify the working characteristics of each load terminal in the substation based on the monitoring data, that is, to determine the load type based on the detected current and power fluctuations. Specifically, based on the collected monitoring data, the characteristics of the load are identified, and key characteristics such as the load current change pattern and power fluctuation range are analyzed. According to the results of load characteristic identification, the load is divided into different types, mainly including continuous load and intermittent load. Continuous load refers to a load that operates continuously and stably with small current and power fluctuations, such as some constant production equipment; intermittent load refers to a load that frequently starts and stops during operation and has large current and power fluctuations, such as some intermittent equipment. Using the identified load type, a corresponding type label is generated for each load terminal to identify and distinguish the working characteristics of different loads.

[0023] The parallel DC power supply configuration module 30 is used to configure a parallel DC power supply, wherein the parallel DC power supply includes multiple DC power supplies and obtains the load processing capacity and residual load of each DC power supply. A parallel DC power supply refers to connecting the positive and negative poles of multiple DC power supplies together to form an integrated power supply system. By connecting in parallel, the total voltage (when the voltage is the same) or the total current (when the current is the same) can be increased, thereby meeting the power supply needs of more loads. Specifically, when configuring the parallel DC power supply, the voltage, current, power and other parameters of each DC power supply are considered to match. Usually, multiple DC power supplies with the same voltage, current and power are selected for parallel connection to ensure the stability and reliability of the power supply system. During the configuration process, the capacity and safety of the power supply system must also be considered to ensure that the system can meet the power supply needs of various loads. Load handling capacity refers to the amount of load a DC power supply can handle within a specific timeframe. This is calculated by measuring the DC power supply's output current, voltage, and other parameters, combined with the load's power requirements. For example, if a DC power supply can handle a load power of 1000W within one hour, its load handling capacity is 1000W / h. Remaining load capacity refers to the amount of load the DC power supply can still handle within a specific timeframe. This is calculated by subtracting the already handled load from the DC power supply's total capacity. For example, if a DC power supply has a total capacity of 2000W / h and has already handled a load of 1000W / h, its remaining load capacity is 1000W / h. In a parallel DC power supply system, the output data of each DC power supply can be collected in real time through a monitoring system. This data is then calculated and analyzed based on a preset algorithm to determine the load handling capacity and remaining load of each DC power supply.

[0024] The load distribution node establishment module 40 is used to establish a load distribution node based on the load processing capacity and residual load of each DC power supply. The load distribution node corresponds to the parallel position of the DC power supply, and the load of the load distribution node corresponds to the residual load. The load distribution node is used to distribute the load according to the residual load of the DC power supply to ensure that the load is evenly distributed among multiple DC power supplies. Specifically, the module analyzes the collected data to understand the working status and performance of each DC power supply, identifies DC power supplies with a large residual load and DC power supplies with a small residual load, and formulates a load distribution strategy based on the difference in residual load to achieve a balanced distribution of load among multiple DC power supplies. At the same time, the module fully utilizes the residual load of each DC power supply to establish load distribution nodes. These load distribution nodes correspond to the parallel position of the DC power supply to ensure that the load can be correctly distributed to each DC power supply. That is, according to the load distribution strategy, a corresponding load is set for each load distribution node. The load should correspond to the residual load of each DC power supply to ensure the rationality and effectiveness of load distribution.

[0025] The allocation rule configuration module 50 is used to obtain the load request amount of the load end and configure the allocation rules based on the load type of the load request amount. The load request amount refers to the amount of electricity that the load end (such as a device, system or application) needs to process or consume within a specific time. The load current, power and other parameters are collected in real time by sensors or other monitoring devices installed at the load end, and the load request amount is then calculated. According to the characteristics of the load request amount (such as continuity, intermittency, peak value, etc.), the load is divided into different types, such as continuous load, intermittent load, peak load, etc. Different types of loads have different impacts and requirements on the power supply system. According to the load type and the actual situation of the system, corresponding allocation rules are formulated, that is, allocation rules are configured. For example, for continuous loads, stable power can be allocated first; for intermittent loads, power distribution can be dynamically adjusted according to their working cycle and peak value.

[0026] The distribution relationship determination module 60 is used to distribute the load request according to the remaining load of the load distribution node based on the distribution rules, and determine the distribution relationship between the load request and the load distribution node. The remaining load of the load distribution node represents the load that the node can still handle in the current time period. The load request is distributed according to the distribution rules. During the distribution process, the best distribution plan is determined based on factors such as the type, size and time of the load request, as well as the remaining load and processing capacity of each node. For example, the load is preferentially distributed to nodes with larger remaining load to fully utilize system resources; for continuous load, it is preferentially distributed to nodes with higher stability; for intermittent load, it is dynamically distributed according to the processing capacity of the node and the load fluctuation; during the distribution process, one or more target load distribution nodes are determined for each load request. These nodes will be responsible for processing the load request, that is, the distribution relationship between the load request and the load distribution node is determined.

[0027] The parallel DC power supply sharing distribution module 70 is configured to share and distribute the parallel DC power supplies according to the distribution relationship. After determining the load distribution relationship, the load request amount is distributed to the parallel DC power supplies according to the distribution relationship. Specifically, based on the distribution relationship, the DC power supply to which each load request amount is to be allocated is determined. Based on the allocated load request amount, the output current or voltage of the target DC power supply is adjusted to ensure that the power supply output parameters meet the load requirements. During the load distribution process, the status and load of each power supply are monitored in real time. If a power supply is found to be overloaded or underloaded, optimization is performed by adjusting the distribution relationship or increasing or decreasing the number of parallel power supplies to ultimately achieve load balancing, that is, ensuring that each power supply bears an appropriate amount of load to improve the overall performance and stability of the system.

[0028] The intelligent DC power sharing system for a substation according to an embodiment of the present invention is designed to address the technical problem that existing substation DC power supplies, where multiple load terminals are equipped with independent DC power supplies, are unable to cope with large load fluctuations, easily causing power supply overload, and thus leading to poor stability and reliability of the substation and low resource utilization efficiency. The intelligent DC power sharing system for a substation includes: a monitoring data acquisition module 10, a load type determination module 20, a parallel DC power supply configuration module 30, a load distribution node establishment module 40, an allocation rule configuration module 50, an allocation relationship determination module 60, and a parallel DC power supply sharing allocation module 70.

[0029] Below, the specific configuration of the load type determination module 20 will be described in detail. The load type determination module 20 can further include: extracting a load data set based on the monitoring data. Extracting a load data set for analysis from the original monitoring data includes the changes in the load over a period of time. It also includes calculating the mean, variance, peak and frequency characteristics based on the load data set. The load data mean is the sum of the load data of each load end divided by the total number of load ends, which identifies the overall level of the load; the load data variance is the sum of the squares of the difference between the load data of each load end and the load mean and then divided by the total number of load ends, which indicates the discreteness or fluctuation of the load data; the load peak is to find the maximum value of the load data in the load data set, which is used to indicate the maximum processing capacity or demand of the load; the frequency characteristic refers to analyzing the frequency of load changes in the load data set, that is, the speed or frequency of the load switching between different values.

[0030] The load type determination module 20 also includes extracting the continuous interval characteristics of the load based on the calculation results of the mean, variance, peak and frequency characteristics, and setting the load type based on the continuous interval characteristics. Based on the previously calculated mean, variance, peak and frequency characteristics, combined with the time series analysis method, continuous high-load or low-load intervals in the load data set are identified, and the duration and intervals of these intervals are calculated, that is, the continuous interval characteristics of the load are extracted. Based on the extracted continuous interval characteristics, combined with the actual application scenarios and business needs of the load, appropriate thresholds and conditions are set to determine the load type. For example, if a load maintains a high load state for most of the time, and the intervals between continuous high-load intervals are very short, it can be determined as a continuous load; if the load frequently switches between high load and low load, and the switching intervals are short, it can be determined as an intermittent load.

[0031] The specific configuration of the load type determination module 20 will be described in detail below. The load type determination module 20 may further include extracting core frequency components based on the frequency characteristics. In the frequency domain, a load signal may contain multiple frequency components. Core frequency components are those frequencies that contribute most to the signal, i.e., the main components of the signal. This is determined by searching for peaks in the spectrum. The module also includes determining the duty cycle of the load signal based on the core frequency components. The inverse of the core frequency component is typically equal to the duty cycle. For example, if the core frequency is 1 Hz, the duty cycle is 1 second. The duty cycle is the time required for the signal to complete a full cycle. The module also includes reconstructing time domain information from the core frequency components using an inverse Fourier transform to determine the duty cycle and interval time of the load signal within a duty cycle. By reconstructing the time domain information of the core frequency components through an inverse Fourier transform, analyzing the temporal changes of the signal, and detecting the transition points where the signal changes from a low level to a high level (or vice versa), the duty cycle and interval time of the load signal can be determined.

[0032] The load type determination module 20 further includes calculating the continuous time mean, continuous time variance, interval time mean, and interval time variance based on the working time and interval time, respectively, using the mean and variance. The continuous time mean refers to calculating the average value of all working time periods; the continuous time variance refers to calculating the average value of the squares of the deviations of all working time periods from their mean; the interval time mean refers to calculating the average value of all interval time periods; and the interval time variance refers to calculating the average value of the squares of the deviations of all interval time periods from their mean. The module also includes identifying the ratio of continuous time to interval time based on the continuous time mean, continuous time variance, interval time mean, and interval time variance, and determining the load type. A continuous load is defined as a load in which the continuous time mean is greater than the interval time mean, and the variance of the continuous working time and interval time is small. By comparing the continuous time mean and the interval time mean, as well as their variance, the load type can be identified. If the continuous time mean is greater than the interval time mean, and the variance of the continuous working time and the interval time is small, the load can be identified as a continuous load, because the continuous load usually maintains a continuous working state for a long time when working, and the interval time is relatively short and stable; on the contrary, the intermittent load has a short working time, a long interval time, and a large variance of the working time and the interval time.

[0033] The specific configuration of the allocation rule configuration module 50 will be described in detail below. The allocation rule configuration module 50 may further include configuring allocation priorities based on the load type, where the priority of continuous loads is higher than the priority of intermittent loads. Since continuous loads typically require a continuous and stable power supply, their priority is set higher than that of intermittent loads. Intermittent loads may not require power during certain time periods or their operating cycles may include long periods of idle time. Therefore, when resources are limited, intermittent loads may have a relatively low priority.

[0034] The allocation rule configuration module 50 further includes, when the remaining load does not meet the load request, activating the energy storage system to supply power to the intermittent load. The remaining load is compared with the load request to determine how to allocate power. When the remaining load does not meet the requests of all loads (including continuous loads and intermittent loads), the system will prioritize meeting the needs of the continuous load and activate the energy storage system to provide power to the intermittent load, ensuring stable operation of the continuous load while minimizing the impact on the intermittent load. The energy storage system (such as a battery, supercapacitor, etc.) is used to provide power during peak power demand or when power supply is insufficient.

[0035] The allocation rule configuration module 50 further includes, when the remaining load quantity satisfies the continuous load and there is a surplus, dividing the supply of the intermittent load, wherein a portion of the supply is supplied by the energy storage system, and a portion shares the DC power supply with the continuous load. When the remaining load quantity satisfies the needs of the continuous load and there is still a surplus, the power supply of the intermittent load is divided, and a portion of the power demand of the intermittent load is supplied by the energy storage system, which can reduce the burden of the DC power supply and extend the service life of the energy storage system; the other portion of the intermittent load shares the DC power supply with the continuous load. It is necessary to reasonably allocate the power supply of the DC power supply according to the operating characteristics and needs of the intermittent load while ensuring the stable operation of the continuous load.

[0036] Below, the specific configuration of the distribution relationship determination module 60 will be described in detail. The distribution relationship determination module 60 may further include: setting a load synchronization window according to the remaining load of the load distribution node, and the load synchronization window is used to synchronously meet all loads in the window. The size of the load synchronization window is set according to the remaining load of the load distribution node. The more the remaining load, the larger the synchronization window may be; conversely, the synchronization window may be smaller, wherein the load synchronization window is a window of time or electrical energy, which is used to ensure that all loads in the window can be met within the same time period. It also includes load type identification based on the load request amount, and extracting the load amount of the continuous load type. According to the working characteristics of the load, identify which loads belong to the continuous load type, and extract the specific load amount of the continuous load type, that is, the electrical energy required by these loads within a period of time.

[0037] The distribution relationship determination module 60 also includes using the load synchronization window to traverse the load amount of the continuous load type and determine the synchronization window matching relationship. Using the set load synchronization window, the load amount of the continuous load type is traversed to determine which continuous loads can be satisfied in the current synchronization window, that is, the size of the synchronization window matches the load amount of these loads. It also includes identifying the window load amount according to the synchronization window matching relationship, and the window load amount is the load balance of the synchronization window. The window load amount refers to the load amount remaining after matching in the synchronization window, that is, the load balance of the synchronization window. This balance may be caused by the synchronization window being greater than the load amount of certain continuous loads, or it may be caused by the fact that certain continuous loads cannot be satisfied in the current synchronization window and remain. It also includes splitting the synchronization window based on the window load amount, using the split window to perform intermittent load traversal distribution, and determining the matching relationship of the split window. According to the identified window load, the original synchronization window is divided into multiple smaller split windows, and these split windows are used to traverse and distribute the intermittent load. Similar to the continuous load, it is determined which intermittent load loads can be satisfied within these split windows, and the matching relationship between each split window and the intermittent load is determined, that is, which intermittent loads can be satisfied within which split windows.

[0038] The specific configuration of the allocation rule configuration module 50 will be described in detail below. The allocation rule configuration module 50 may further include: constructing an optimization objective function for the energy storage system based on minimizing operating costs. This optimization objective function is constructed, and the energy storage system is configured to minimize the overall operating costs of the energy storage system. This also includes obtaining a balance constraint condition for the charge and discharge power of the energy storage system that satisfies the DC power supply capacity. Based on the charge and discharge characteristics of the energy storage system and the power supply capacity of the DC power supply, a power balance equation is established that incorporates factors such as the charge and discharge power of the energy storage system, the power supply of the DC power supply, and the power demand of the load. This balance constraint condition is obtained to ensure that the charge and discharge power of the energy storage system remains balanced with the DC power supply capacity. This also includes performing an optimization search based on the balance constraint condition and the optimization objective function to determine an energy supply time chain for the energy storage coefficient. This search is performed using an optimization method (such as linear programming, integer programming, genetic algorithm, etc.) to find an energy storage coefficient and energy supply time chain that satisfies the balance constraint condition and optimizes the objective function. Specifically, the charge and discharge state and power output of the energy storage system in different time periods are determined to form an energy supply time chain.

[0039] The allocation rule configuration module 50 also includes extracting load timing relationships based on the demand time and interval time of the intermittent loads, optimizing allocation with the goal of minimizing the waiting time of the intermittent loads, and determining the load supply demand timing chain. The specific demand time of each intermittent load is clarified, i.e., the start and end time when the load requires power supply. The interval time of the intermittent load is considered, i.e., the idle time between two consecutive demand times. Based on these demand times and interval times, the timing relationships of all intermittent loads are extracted to form a demand sequence on the timeline. The optimization goal is to reduce the waiting time of the intermittent loads. The waiting time refers to the time difference between the load sending a demand signal and the actual receipt of power supply. To achieve this goal, the load supply is reasonably arranged to ensure that the waiting time of the intermittent loads is minimized while ensuring the stable supply of continuous loads. Based on the extracted load timing relationships, an optimized allocation strategy is formulated. For example, intermittent loads with earlier demand times and shorter interval times are prioritized to reduce their waiting time. At the same time, the optimized allocation strategy is continuously adjusted according to actual conditions. For example, when the demand for continuous loads suddenly increases, it may be necessary to temporarily reduce the supply to intermittent loads to ensure the stability of the power system. The load supply demand timing chain is finally determined, and detailed information such as the demand time, supply time, and corresponding supply power of each intermittent load is recorded. This helps to better understand the load demand situation, ensure the stable operation of the power system, and optimize operating costs.

[0040] The allocation rule configuration module 50 also includes configuring the weight coefficients of the energy supply timing chain and the load supply demand timing chain, wherein the weight coefficient of the energy supply timing chain is greater than the weight coefficient of the load supply demand timing chain. The weight coefficient is used to represent the relative importance of different factors or indicators in the overall system, and can help determine which timing chains should be given priority when making decisions. The energy supply timing chain represents the entire process from energy production to supply, including energy generation, transmission, storage and distribution. Since the stability and reliability of energy supply are crucial to the operation of the entire system, its weight coefficient is usually set to a higher value. A higher weight coefficient means that in the optimization and decision-making process, the energy supply timing chain will be given priority to ensure a stable supply of energy; the load supply demand timing chain describes the energy demand of the load at different time points. In some cases, such as when the energy supply is tight or the system stability is threatened, it may be necessary to temporarily sacrifice some load demand to ensure the overall operation of the system. Therefore, the weight coefficient of the load supply demand timing chain is usually set to a lower value than that of the energy supply timing chain.

[0041] The allocation rule configuration module 50 also includes, based on the weight coefficient, using the Nash equilibrium algorithm to balance and optimize the energy supply timing chain and the load supply demand timing chain, and determine the supply relationship between the energy storage system and the intermittent load. The Nash equilibrium algorithm is used to balance and optimize the energy supply timing chain and the load supply demand timing chain. Specifically, a Nash equilibrium model is constructed. In this model, the energy storage system is a participant, and its goal is to make the best energy allocation decision based on the current energy supply timing chain and the load supply demand timing chain. The strategy of the energy storage system includes deciding when to charge, discharge, and the amount of discharge to meet the load demand while optimizing energy use. The benefit function is the benefit obtained by the participant based on the result of the strategy selection, such as energy supply cost, load satisfaction (related to waiting time), system stability and other dimensions. Using the Nash equilibrium algorithm, through an iterative method Find a strategy combination under which no participant can increase their benefits by unilaterally changing their strategy. For example, initialize the energy storage system's strategy (such as the time and amount of charging and discharging). Based on the current strategy combination, calculate the benefits of each participant. Participants adjust their strategies based on the benefits to maximize their benefits. Repeat until a Nash equilibrium is reached, that is, no participant can increase their benefits by unilaterally changing their strategy. After reaching the Nash equilibrium, determine the optimal supply relationship between the energy storage system and the intermittent load, including the charging and discharging status of the energy storage system at different time points and the amount of power supplied to the load.

[0042] The specific configuration of the allocation rule configuration module 50 will be described in detail below. The allocation rule configuration module 50 may further include: the optimization objective function expression is: Among them, C e (t) is the operating cost of the energy storage system at time t, P e (t) is the discharge power of the energy storage system at time t, P c (t) is the charging power of the energy storage system at time t, φ is the charging and discharging efficiency of the energy storage system, and T is the total time period.

[0043] In the above, refer to Figure 1 The DC power intelligent sharing system for substations according to an embodiment of the present invention is described in detail. Figure 2 A method for intelligently sharing direct current power supply for a substation according to an embodiment of the present invention is described.

[0044] Intelligent sharing method of DC power supply for substations, such as Figure 2As shown, the method includes: installing sensors at each load end of the substation to obtain monitoring data, including monitoring current and power fluctuations; identifying load characteristics based on the monitoring data to determine the load type, the load type including continuous load and intermittent load, and using the load type to generate a type label to identify the load of each load end; configuring parallel DC power supplies, the parallel DC power supplies including multiple DC power supplies, obtaining the load processing capacity and remaining load of each DC power supply; establishing a load distribution node based on the load processing capacity and remaining load of each DC power supply, the load distribution node corresponding to the parallel position of the DC power supply, and the load of the load distribution node corresponding to the remaining load; obtaining the load request amount of the load end, and configuring a distribution rule based on the load type of the load request amount; distributing the load request amount based on the distribution rule according to the remaining load of the load distribution node, and determining the distribution relationship between the load request amount and the load distribution node; and performing shared distribution of the parallel DC power supplies according to the distribution relationship.

[0045] In one possible implementation, the method for intelligent sharing of DC power supply for a substation further includes: extracting a load data set based on the monitoring data; calculating mean, variance, peak, and frequency characteristics of the load data set; extracting continuous interval characteristics of the load based on the calculation results of the mean, variance, peak, and frequency characteristics, and setting the load type based on the continuous interval characteristics.

[0046] In one possible implementation, the method for intelligent sharing of DC power supply for substations also includes: extracting core frequency components based on the frequency characteristics; determining the working cycle of the load signal based on the core frequency components; reconstructing time domain information through inverse Fourier transform based on the core frequency components to determine the working time and interval time of the load signal within the working cycle; calculating the continuous time mean, continuous time variance, interval time mean, and interval time variance based on the working time and interval time respectively using mean and variance; identifying the ratio relationship between continuous time and interval time based on the continuous time mean, continuous time variance, interval time mean, and interval time variance to determine the load type, wherein the continuous load is a continuous time mean that is greater than the interval time mean, and the variance of the continuous working time and interval time is small.

[0047] In one possible implementation, the method for intelligent sharing of DC power supply for a substation further includes: configuring an allocation priority according to the load type, wherein the continuous load priority is greater than the intermittent load priority; when the remaining load amount does not meet the load request amount, activating the energy storage system for supplying power to the intermittent load; when the remaining load amount meets the continuous load and there is a surplus, dividing the supply of the intermittent load, wherein a part of the division is supplied through the energy storage system, and a part shares the DC power supply with the continuous load.

[0048] In one possible implementation, the method for intelligent sharing of DC power supply for substations also includes: setting a load synchronization window based on the remaining load of the load distribution node, and the load synchronization window is used to synchronously meet all loads in the window; identifying the load type based on the load request amount, and extracting the load amount of the continuous load type; using the load synchronization window to traverse the load amount of the continuous load type to determine the synchronization window matching relationship; identifying the window load amount based on the synchronization window matching relationship, and the window load amount is the load balance of the synchronization window; splitting the synchronization window based on the window load amount, using the split window to perform intermittent load traversal distribution, and determining the matching relationship of the split window.

[0049] In one possible implementation, the method for intelligent sharing of DC power supply for substations also includes: constructing an optimization objective function of the energy storage system with the aim of minimizing operating costs; obtaining the charging and discharging power of the energy storage system to meet the balance constraint of the DC power supply capacity; performing optimization based on the balance constraint and the optimization objective function to determine the energy supply timing chain of the energy storage system; extracting the load timing relationship based on the demand time and interval time of the intermittent load, optimizing the allocation with the goal of minimizing the waiting time of the intermittent load, and determining the load supply demand timing chain; configuring the weight coefficients of the energy supply timing chain and the load supply demand timing chain, wherein the weight coefficient of the energy supply timing chain is greater than the weight coefficient of the load supply demand timing chain; based on the weight coefficients, using the Nash equilibrium algorithm to perform equilibrium optimization on the energy supply timing chain and the load supply demand timing chain to determine the supply relationship between the energy storage system and the intermittent load.

[0050] In a possible implementation, the DC power intelligent sharing method for a substation further includes: the optimization objective function expression is: Among them, C e (t) is the operating cost of the energy storage system at time t, P e (t) is the discharge power of the energy storage system at time t, P c (t) is the charging power of the energy storage system at time t, φ is the charging and discharging efficiency of the energy storage system, and T is the total time period.

[0051] The DC power intelligent sharing system for a substation provided by an embodiment of the present invention can execute the DC power intelligent sharing method for a substation provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0052] Although the present application makes various references to certain modules in the system according to the embodiments of the present application, any number of different modules may be used and run on the user terminal and / or server, and the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other and are not used to limit the scope of protection of the present invention.

[0053] The above specific embodiments do not constitute a limitation on the scope of protection of this application. Those skilled in the art should understand that various modifications, combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application shall be included within the scope of protection of this application.

Claims

1. A DC power intelligent sharing system for a substation, characterized in that: The DC power intelligent sharing system for substations includes: The monitoring data acquisition module is used to install sensors at each load end of the substation to obtain monitoring data, including monitoring current and power fluctuations; a load type determination module, configured to identify load characteristics based on the monitoring data, determine the load type, wherein the load type includes continuous load and intermittent load, and generate a type label based on the load type to identify the load at each load end; A parallel DC power supply configuration module is used to configure a parallel DC power supply, wherein the parallel DC power supply includes multiple DC power supplies and obtain the load processing capacity and remaining load capacity of each DC power supply; a load distribution node establishment module, configured to establish a load distribution node based on the load processing capacity and the remaining load of each DC power supply, wherein the load distribution node corresponds to the parallel position of the DC power supply to ensure that the load can be correctly distributed to each DC power supply, and the load of the load distribution node corresponds to the remaining load. The load distribution node is configured to distribute the load based on the remaining load of the DC power supply to ensure that the load is evenly distributed among the multiple DC power supplies; an allocation rule configuration module, configured to obtain a load request amount of the load end and configure an allocation rule based on a load type of the load request amount; a distribution relationship determining module, configured to distribute the load request according to the remaining load of the load distribution node and based on the distribution rule, and determine a distribution relationship between the load request and the load distribution node; A parallel DC power supply sharing and distribution module, configured to perform sharing and distribution of the parallel DC power supplies according to the distribution relationship; The load type determination module performs the following steps: extracting a load data set based on the monitoring data; Calculating the mean, variance, peak value and frequency characteristics respectively according to the load data set; Extracting a continuous interval feature of the load based on the calculation results of the mean, variance, peak value and frequency features, and setting the load type based on the continuous interval feature; The steps performed by the allocation relationship determination module include: Setting a load synchronization window according to the remaining load of the load distribution node, wherein the load synchronization window is used to synchronously satisfy all loads within the window; Identify the load type according to the load request amount, and extract the load amount of the continuous load type; Using the load synchronization window to traverse the load amount of the continuous load type to determine the synchronization window matching relationship; Identifying a window load according to the synchronization window matching relationship, where the window load is a load balance of the synchronization window; Synchronous windows are split based on the window load, intermittent load traversal distribution is performed using the split windows, and a matching relationship between the split windows is determined.

2. The DC power intelligent sharing system for substations according to claim 1, characterized in that: The load type determination module performs the following steps: extracting core frequency components according to the frequency characteristics; determining a duty cycle of a load signal according to the core frequency component; Reconstructing time domain information by inverse Fourier transform according to the core frequency component to determine the working time and interval time of the load signal within one working cycle; Calculate the continuous time mean, the continuous time variance, the interval time mean, and the interval time variance using the mean and variance based on the working time and the interval time respectively; Based on the continuous time mean, continuous time variance, interval time mean, and interval time variance, the ratio relationship between continuous time and interval time is identified to determine the load type, wherein the continuous load is that the continuous time mean is greater than the interval time mean, and the variance of the continuous working time and the interval time is small.

3. The DC power intelligent sharing system for substations according to claim 1, characterized in that: The steps performed by the allocation rule configuration module include: configuring a distribution priority according to the load type, wherein the continuous load priority is greater than the intermittent load priority; When the remaining load amount does not meet the load request amount, activating the energy storage system to supply power to the intermittent load; When the remaining load capacity satisfies the continuous load and there is a surplus, the intermittent load is supplied by splitting, wherein a part of the split is supplied by the energy storage system and a part of the split shares the DC power supply with the continuous load.

4. The DC power intelligent sharing system for substations according to claim 3, characterized in that: The activation of the energy storage system for supplying power to the intermittent load includes: Constructing the optimization objective function of the energy storage system by minimizing the operating cost; Obtaining the charging and discharging power of the energy storage system to meet the balance constraint of the DC power supply capacity; Optimize according to the balance constraint condition and the optimization objective function to determine the energy supply timing chain of the energy storage coefficient; Extract the load timing relationship based on the demand time and interval time of the intermittent load, optimize the allocation with the goal of minimizing the intermittent load waiting time, and determine the load supply demand timing chain; Configuring weight coefficients of the energy supply timing chain and the load supply demand timing chain, wherein the weight coefficient of the energy supply timing chain is greater than the weight coefficient of the load supply demand timing chain; Based on the weight coefficients, a Nash equilibrium algorithm is used to perform equilibrium optimization on the energy supply timing chain and the load supply demand timing chain to determine the supply relationship between the energy storage system and the intermittent load.

5. The DC power intelligent sharing system for substations according to claim 4, characterized in that: The optimization objective function expression is: ,in, is the operating cost of the energy storage system at time t, is the discharge power of the energy storage system at time t, is the charging power of the energy storage system at time t, is the charging and discharging efficiency of the energy storage system, T is the total time period, is the unit power cost.

6. A method for intelligently sharing DC power supply for a substation, characterized in that: The method is applied to the DC power intelligent sharing system for a substation according to claim 1, and the method comprises: Install sensors at each load end of the substation to obtain monitoring data, including monitoring current and power fluctuations; Identify load characteristics based on the monitoring data to determine the load type, where the load type includes continuous load and intermittent load, and use the load type to generate a type label to identify the load at each load end; Configuring a parallel DC power supply, wherein the parallel DC power supply includes multiple DC power supplies, and obtaining a load processing capacity and a remaining load capacity of each DC power supply; Establishing a load distribution node based on the load processing capacity and the remaining load of each DC power supply, wherein the load distribution node corresponds to the parallel position of the DC power supply to ensure that the load can be correctly distributed to each DC power supply, and the load of the load distribution node corresponds to the remaining load. The load distribution node is used to distribute the load based on the remaining load of the DC power supply to ensure that the load is evenly distributed among the multiple DC power supplies; Obtaining a load request amount of the load end, and configuring a distribution rule based on a load type of the load request amount; Allocating the load request amount based on the allocation rule according to the remaining load amount of the load distribution node, and determining an allocation relationship between the load request amount and the load distribution node; The parallel DC power supplies are shared and distributed according to the distribution relationship.

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