A power supply control method and system for distribution network

Abstract

The present invention relates to the technical field of electric power supply systems. The present invention provides a power supply control method and system for a distribution network, which obtains power grid operation, equipment status, load and meteorological data, and stores renewable energy electricity based on historical data. A deep learning model is used to predict future power grid power consumption, and the power supply strategy is adjusted according to the prediction results. When the power supply is insufficient, regional indirect power supply is adopted to ensure power supply to key areas. The present invention provides a power supply control method and system for a distribution network, which includes power supply, energy storage, power-consuming equipment, and a power grid and background control terminal. Through real-time monitoring and intelligent scheduling, the stable operation of the power grid is guaranteed, solving the problem of difficult power scheduling during peak hours.

Description

Technical Field

[0001] The present invention relates to the technical field of electric power supply systems, and in particular to a power supply control method and system for a power distribution network. Background Art

[0002] With the continuous development of the power system, the power supply control technology of the distribution network is also continuously improving. Traditional power supply control methods mainly rely on mechanical switchgear and manual operation, but with the development of science and technology, especially the introduction of automation technology and the concept of smart grid, power supply control methods are developing in a more intelligent and automated direction. In the existing power supply control method of the distribution network, the power supply control system of the distribution network collects data such as voltage, current, power factor, etc. through sensors distributed at key nodes of the power grid, and then transmits it to the central control unit. The central control unit adjusts the switch state, transformer tap position and switching of reactive compensation equipment in real time according to the preset algorithm and optimization strategy to maintain the voltage stability and power balance of the power grid. In addition, the power supply control system of the distribution network also has fault detection and isolation functions. Once a fault occurs, it can quickly locate and isolate the fault area, reduce the scope and time of power outages, and improve power supply reliability.

[0003] Although the existing distribution network power supply control technology has made significant progress, there are still the following technical pain points:

[0004] With the improvement of living standards, modern electrical appliances such as refrigerators, color TVs, and air conditioners are becoming increasingly popular. In the summer, electrical equipment works almost simultaneously, resulting in a huge demand for household electricity, which increases the burden on the distribution network during peak hours. The number of entertainment venues in cities has increased, and summer is the peak season for entertainment activities, which further increases the load on the power grid during the peak electricity consumption period in summer. Although existing technologies such as distributed eight-port low-voltage flexible DC interconnection systems have been applied to power coordination and mutual assistance, during peak electricity consumption, if electricity consumption suddenly increases again, the distribution network will still face the problem of scheduling difficulties and insufficient power supply in a short period of time. Summary of the invention

[0005] In view of the deficiencies in the prior art, the present invention provides a power supply control method and system for a distribution network, which solves the problem that if the power consumption suddenly increases during peak hours, the distribution network will still face scheduling difficulties and power shortages in a short period of time.

[0006] In order to solve the above technical problems, the specific technical solutions of the present invention are as follows:

[0007] In a first aspect, the present invention provides a power supply control method for a distribution network, comprising:

[0008] Step S101, acquiring power grid operation data, power grid equipment status information, power grid load data and meteorological environment data;

[0009] Step S102, retrieving historical data of the power grid from a database, the historical data of the power grid including historical power consumption data of the power grid, setting the highest power consumption value in the historical power consumption data of the power grid as the maximum electric energy storage value, storing electric energy of the wind power generation equipment and the photovoltaic power generation equipment, and stopping energy storage when the electric energy stored in the wind power generation equipment and the photovoltaic power generation equipment reaches the maximum electric energy storage value;

[0010] Step S103, monitoring power grid operation data, power grid equipment status information, power grid load data and meteorological environment data to obtain a real-time monitoring data set, the real-time monitoring data set including real-time power grid operation data, real-time power grid equipment status information, real-time power grid load data and real-time meteorological environment data;

[0011] Step S104, determining the characteristics of the predicted power grid load, the characteristics of the predicted power grid load include the characteristics of the ambient temperature, the characteristics of the power grid power supply, the characteristics of the power grid load, and the characteristics of the power grid equipment status, and training the characteristics of the predicted power grid load and the real-time monitoring data set through a deep learning model to obtain a model for predicting power grid power consumption;

[0012] Step S105, substituting the real-time data of power grid operation, the real-time information of power grid equipment status, the real-time data of power grid load and the real-time data of meteorological environment into the power grid power consumption prediction model to obtain the power grid power consumption estimated for the next period, comparing the power grid power consumption estimated for the next period with the real-time power supply of the power grid to obtain the power grid power consumption prediction comparison result, the power grid power consumption prediction comparison result includes the power grid meeting the power grid power consumption estimated and the power supply of the power grid not meeting the power grid power consumption estimated;

[0013] Step S106, setting a regional indirect power supply strategy. When the power supply of the power grid does not meet the power grid's expected power consumption, the pre-stored electric energy is called up to supply power to the power grid according to the regional indirect power supply strategy. When the power grid meets the power grid's expected power consumption, the original power supply strategy continues to be executed.

[0014] Furthermore, the power supply control method for a distribution network provided by the present invention includes, in step 102:

[0015] Establish communication connection with wind power generation equipment and photovoltaic power generation equipment to obtain operation data of wind power generation equipment and photovoltaic power generation equipment;

[0016] When the wind power generation equipment and the photovoltaic power generation equipment generate electric energy, the electric power at the energy storage end is detected. If the electric power at the energy storage end is lower than the preset minimum energy storage value, the electric energy generated by the wind power generation equipment and the photovoltaic power generation equipment is received and stored at the energy storage end;

[0017] Based on the meteorological environment data, the meteorological environment data for the next 7 days is obtained. The meteorological environment data includes light intensity and wind intensity. The actual daily consumption of the real-time energy storage power of the energy storage end is detected, and the power consumption of the energy storage end in the next 7 days is predicted. If the power of the energy storage end in the next 7 days is lower than the preset minimum energy storage value, then during the period when the light intensity and wind intensity meet the operation of wind power generation equipment and photovoltaic power generation equipment, the electric energy with light intensity and wind intensity is received and stored.

[0018] Furthermore, the power supply control method for a distribution network provided by the present invention further includes, in step 103:

[0019] The grid operation data includes the grid voltage, grid current, and grid frequency operation parameters;

[0020] By real-time monitoring of the status of power grid equipment such as transformers, circuit breakers, and switches, the status information of power grid equipment can be obtained;

[0021] The grid load data includes active power and reactive power. The grid load data is used to display the load status of the grid and is also used for load management and data analysis to predict future load trends.

[0022] Meteorological environment data include light intensity, temperature, humidity, and wind speed.

[0023] Furthermore, the power supply control method for a distribution network provided by the present invention includes, in step 105:

[0024] Collect real-time data on power grid operation, real-time information on power grid equipment status, and real-time data on meteorological environment. Real-time data on power grid operation includes voltage, current, and power factor. Real-time information on power grid equipment status includes transformer operation data and circuit breaker operation data.

[0025] Obtain real-time grid load data, which is used to monitor the real-time load status of the grid;

[0026] Preprocess the real-time data of power grid load, power grid operation, power grid equipment status and meteorological environment, and substitute the preprocessed real-time data of power grid operation, equipment status, load and meteorological environment into the power grid power consumption prediction model;

[0027] Run the prediction model of power grid electricity consumption, obtain the predicted value of the power grid's expected electricity consumption in the next period, obtain the data of the real-time power supply of the power grid, compare and analyze the predicted power grid consumption in the next period with the real-time power supply of the power grid, and judge whether the power grid can meet the predicted electricity consumption demand in the next period based on the comparison results.

[0028] Furthermore, the power supply control method for a distribution network provided by the present invention includes, in step 106:

[0029] Set up a regional indirect power supply strategy. When the power supply of the power grid does not meet the expected power consumption of the power grid, set the power supply time for each power supply partition in turn according to the power supply partition label, and supply power to each power supply partition in turn according to the power supply partition label in a step-by-step manner;

[0030] When the electric energy at the energy storage end is fully stored or the grid function meets the expected power consumption of the grid, the stepped power supply to each power supply partition is stopped.

[0031] In a second aspect, the present invention provides a power supply control system for a distribution network, a power supply device end, an energy storage end, a power consumption device end, a power grid control end and a background control end, the power grid control end establishes a communication connection with the energy storage end, the power supply device end, the power consumption device end and the background control end, the power grid control end is used to process and analyze the data of the power supply device end, the power consumption device end and the background control end, obtain the power grid power supply adjustment command, and transmit the power grid power supply adjustment command to the energy storage end and the power supply device end, the energy storage end and the power supply device end execute the power grid power supply adjustment command, and adjust the power supply of the power grid, and the power grid control end includes:

[0032] A data acquisition unit, which acquires power grid operation data, power grid equipment status information, power grid load data, and meteorological environment data;

[0033] The energy storage unit retrieves historical data of the power grid from a database, wherein the historical data of the power grid includes historical power consumption data of the power grid, sets the highest power consumption value in the historical power consumption data of the power grid as the maximum power storage value, stores the power of the wind power generation equipment and the photovoltaic power generation equipment, and stops storing the power when the power of the stored wind power generation equipment and the photovoltaic power generation equipment reaches the maximum power storage value;

[0034] A monitoring unit monitors power grid operation data, power grid equipment status information, power grid load data, and meteorological environment data to obtain a real-time monitoring data set, wherein the real-time monitoring data set includes real-time power grid operation data, real-time power grid equipment status information, real-time power grid load data, and real-time meteorological environment data;

[0035] Assess future risks and determine the characteristics of the predicted grid load. The characteristics of the predicted grid load include ambient temperature characteristics, grid power supply characteristics, grid load characteristics, and grid equipment status characteristics. The characteristics of the predicted grid load and the real-time monitoring data set are trained through a deep learning model to obtain a model for predicting grid power consumption.

[0036] The power supply capacity evaluation unit of the power grid substitutes the real-time data of the power grid operation, the real-time information of the power grid equipment status, the real-time data of the power grid load and the real-time data of the meteorological environment into the power grid power consumption prediction model to obtain the power grid power consumption estimated in the next period, and compares the power grid power consumption estimated in the next period with the real-time power supply of the power grid to obtain the power grid power consumption prediction comparison result, which includes whether the power grid meets the power grid power consumption estimated and whether the power supply of the power grid does not meet the power grid power consumption estimated;

[0037] Scheduling matching, setting regional indirect power supply strategy. When the power supply of the power grid does not meet the power grid's expected power consumption, the pre-stored electric energy is called up to supply power to the power grid according to the regional indirect power supply strategy. When the power grid meets the power grid's expected power consumption, the original power supply strategy continues to be implemented.

[0038] Furthermore, the power supply control system and energy storage unit for a power distribution network provided by the present invention include:

[0039] Establish communication connection with wind power generation equipment and photovoltaic power generation equipment to obtain operation data of wind power generation equipment and photovoltaic power generation equipment;

[0040] When the wind power generation equipment and the photovoltaic power generation equipment generate electric energy, the electric power at the energy storage end is detected. If the electric power at the energy storage end is lower than the preset minimum energy storage value, the electric energy generated by the wind power generation equipment and the photovoltaic power generation equipment is received and stored at the energy storage end;

[0041] Based on the meteorological environment data, the meteorological environment data for the next 7 days is obtained. The meteorological environment data includes light intensity and wind intensity. The actual daily consumption of the real-time energy storage power of the energy storage end is detected, and the power consumption of the energy storage end in the next 7 days is predicted. If the power of the energy storage end in the next 7 days is lower than the preset minimum energy storage value, then during the period when the light intensity and wind intensity meet the operation of wind power generation equipment and photovoltaic power generation equipment, the electric energy with light intensity and wind intensity is received and stored.

[0042] Furthermore, the power supply control system and monitoring unit for a power distribution network provided by the present invention include:

[0043] The grid operation data includes the grid voltage, grid current, and grid frequency operation parameters;

[0044] By real-time monitoring of the status of power grid equipment such as transformers, circuit breakers, and switches, the status information of power grid equipment can be obtained;

[0045] The grid load data includes active power and reactive power. The grid load data is used to display the load status of the grid and is also used for load management and data analysis to predict future load trends.

[0046] Meteorological environment data include light intensity, temperature, humidity, and wind speed.

[0047] Furthermore, the power supply control system for a power distribution network provided by the present invention, and the power supply capacity evaluation unit of the power distribution network include:

[0048] Collect real-time data on power grid operation, real-time information on power grid equipment status, and real-time data on meteorological environment. Real-time data on power grid operation includes voltage, current, and power factor. Real-time information on power grid equipment status includes transformer operation data and circuit breaker operation data.

[0049] Obtain real-time grid load data, which is used to monitor the real-time load status of the grid;

[0050] Preprocess the real-time data of power grid load, power grid operation, power grid equipment status and meteorological environment, and substitute the preprocessed real-time data of power grid operation, equipment status, load and meteorological environment into the power grid power consumption prediction model;

[0051] Run the prediction model of power grid electricity consumption, obtain the predicted value of the power grid's expected electricity consumption in the next period, obtain the data of the real-time power supply of the power grid, compare and analyze the predicted power grid consumption in the next period with the real-time power supply of the power grid, and judge whether the power grid can meet the predicted electricity consumption demand in the next period based on the comparison results.

[0052] Furthermore, the power supply control system and power supply adjustment unit for a power distribution network provided by the present invention include:

[0053] Set up a regional indirect power supply strategy. When the power supply of the power grid does not meet the expected power consumption of the power grid, set the power supply time for each power supply partition in turn according to the power supply partition label, and supply power to each power supply partition in turn according to the power supply partition label in a step-by-step manner;

[0054] When the electric energy at the energy storage end is fully stored or the grid function meets the expected power consumption of the grid, the stepped power supply to each power supply partition is stopped.

[0055] Beneficial effects of the present invention:

[0056] The present invention provides a power supply control method and system for a distribution network, which improves the power supply reliability of the power grid and reduces the time and scope of power outages through real-time monitoring and intelligent management. Secondly, the distribution of electric energy is optimized, and the pre-stored electric energy can be intelligently dispatched when the power supply of the power grid is insufficient, giving priority to ensuring the power supply of key areas and important users. In addition, the use of deep learning models improves the accuracy of power grid power consumption forecasts and provides powerful decision-making support for power grid operators. At the same time, by setting a regional indirect power supply strategy and retrieving pre-stored electric energy, the resilience of the power grid and its ability to respond to emergencies are enhanced. In addition, the present invention also promotes the use of renewable energy and helps promote a green and low-carbon energy structure. Finally, through precise prediction and intelligent management, energy utilization efficiency is improved and the operating cost of the power grid is reduced. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] In order to more clearly illustrate the technical solution of the present invention, the following briefly introduces the drawings required for use in the embodiments. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0058] Figure 1 A schematic diagram of a method flow chart provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0059] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described in conjunction with the specific embodiments of the present invention and the corresponding drawings. 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 are within the scope of protection of the present invention. The technical solutions provided by the embodiments of the present invention are described in detail below in conjunction with the drawings.

[0060] In order to better understand the purpose of the present invention, the present invention is described in further detail below.

[0061] In a first aspect, the present invention provides a power supply control method for a distribution network, comprising:

[0062] Step S101, acquiring power grid operation data, power grid equipment status information, power grid load data and meteorological environment data;

[0063] Grid operation data reflects the overall operation status of the grid, including but not limited to parameters such as voltage, current, power factor, frequency, etc. These parameters are crucial for evaluating the stability, efficiency and security of the grid.

[0064] The power grid equipment status information provides real-time status information of key equipment in the power grid (such as transformers, circuit breakers, switches, etc.). The equipment's working status, temperature, pressure, oil level and other indicators are important bases for evaluating the health status of the equipment and predicting maintenance needs.

[0065] Grid load data reflects the real-time power consumption in various areas of the grid, including active power, reactive power and apparent power. It is not only used to monitor the current load level, but also serves as the basis for predicting future load trends and formulating load management strategies.

[0066] Meteorological and environmental data: Meteorological conditions have a significant impact on grid operation and load. Meteorological and environmental data such as temperature, humidity, wind speed, sunshine or light intensity are factors in predicting grid load and formulating power supply strategies to cope with extreme weather.

[0067] Step S102, retrieving historical data of the power grid from a database, the historical data of the power grid including historical power consumption data of the power grid, setting the highest power consumption value in the historical power consumption data of the power grid as the maximum electric energy storage value, storing electric energy of the wind power generation equipment and the photovoltaic power generation equipment, and stopping energy storage when the electric energy stored in the wind power generation equipment and the photovoltaic power generation equipment reaches the maximum electric energy storage value;

[0068] Step S102 involves the retrieval of historical data of the power grid, the setting of the maximum electric energy storage value, and the storage of electric energy of wind power and photovoltaic power generation equipment.

[0069] The historical data of the power grid retrieved from the database contains the power consumption of the power grid in the past, which is the basis for analyzing the power consumption pattern of the power grid and predicting future power demand. Find the highest power consumption value from the historical power consumption data of the power grid, and set this value as the maximum power storage value. The setting is based on the consideration of the historical power consumption peak to ensure that the system has sufficient power reserves to cope with possible power supply needs during peak power consumption periods. Start storing the power generated by wind power generation equipment and photovoltaic power generation equipment. Wind and photovoltaic power generation are important sources of renewable energy. By storing the power generated by these devices, additional power support can be provided during peak power consumption periods or when the power supply of the power grid is insufficient.

[0070] Finally, when the stored electrical energy reaches the previously set maximum electrical energy storage value, energy storage is stopped to avoid the potential safety hazards and waste of resources caused by excessive energy storage, while also ensuring the efficient use of electrical energy reserves.

[0071] Step S103, monitoring power grid operation data, power grid equipment status information, power grid load data and meteorological environment data to obtain a real-time monitoring data set, the real-time monitoring data set including real-time power grid operation data, real-time power grid equipment status information, real-time power grid load data and real-time meteorological environment data;

[0072] Continuously monitor the grid operation data, grid equipment status information, grid load data and meteorological environment data. These data are obtained in real time, which improves the timeliness and accuracy of the information.

[0073] Real-time monitoring of the grid's voltage, current, power and other operating parameters to assess the grid's stability and performance. Continuously track the status of key equipment in the grid, such as transformers and switches, to identify potential problems and prevent failures in a timely manner.

[0074] Real-time monitoring of the power load in each area, understanding the current power demand and distribution, and collecting meteorological information such as temperature, humidity, and wind speed, which directly affect the power grid load and power supply efficiency. Through this step, a real-time monitoring data set is obtained, which contains all the above categories of real-time data.

[0075] Real-time monitoring ensures that the power grid management system obtains the latest status of the power grid at the first time, so as to respond quickly. By continuously monitoring the status of equipment, the system can promptly detect abnormalities or signs of failure of equipment, and then arrange preventive maintenance to reduce the occurrence of sudden failures. Based on real-time load data and meteorological information, the power grid management system can more effectively dispatch and distribute loads to ensure the stability and efficiency of power supply. Based on real-time and accurate data, power grid operators can make decisions to meet various power grid operation challenges.

[0076] Step S104, determining the characteristics of the predicted power grid load, the characteristics of the predicted power grid load include the characteristics of the ambient temperature, the characteristics of the power grid power supply, the characteristics of the power grid load, and the characteristics of the power grid equipment status, and training the characteristics of the predicted power grid load and the real-time monitoring data set through a deep learning model to obtain a model for predicting power grid power consumption;

[0077] Determine the characteristics of the predicted grid load, including the characteristics of ambient temperature, grid power supply, grid load, and grid equipment status. These characteristics are selected based on their impact on grid load changes. Determining the characteristics of the predicted grid load is the basis for building an accurate prediction model.

[0078] The characteristics of the predicted power grid load are combined with the real-time monitoring data set and trained through a deep learning model. The deep learning model has the ability to learn and represent, and can capture the complex relationship between these characteristics and power grid power consumption. Through continuous training and optimization, the model can gradually improve the accuracy of the prediction.

[0079] The predicted grid power consumption model obtained through training can be used to predict grid power consumption in the future. The model can comprehensively consider multiple factors, such as ambient temperature, grid power supply, grid load, and grid equipment status, to provide more accurate and comprehensive prediction results. By comprehensively considering multiple characteristics that affect grid load and combining real-time monitoring data for training, a more accurate prediction model can be obtained, which helps grid operators better understand future power demand and make more reasonable scheduling and allocation decisions.

[0080] Accurate forecast results can help grid operators prepare in advance and adjust power supply strategies to meet power demand in different time periods. This can not only improve the operational efficiency of the grid, but also reduce problems such as resource waste or power shortages caused by imbalanced supply and demand. By predicting grid power consumption, grid operators can promptly identify potential load peaks or troughs and take appropriate measures to balance supply and demand. This helps maintain the stability of the grid and reduce failures or accidents caused by load fluctuations.

[0081] In summary, step S104 obtains a model that can accurately predict power consumption of the power grid by determining key features and training using a deep learning model. The model provides powerful decision support for power grid operators, helps optimize the operation and management of the power grid, and improves the stability of the power grid.

[0082] Step S105, substituting the real-time data of power grid operation, the real-time information of power grid equipment status, the real-time data of power grid load and the real-time data of meteorological environment into the power grid power consumption prediction model to obtain the power grid power consumption estimated for the next period, comparing the power grid power consumption estimated for the next period with the real-time power supply of the power grid to obtain the power grid power consumption prediction comparison result, the power grid power consumption prediction comparison result includes the power grid meeting the power grid power consumption estimated and the power supply of the power grid not meeting the power grid power consumption estimated;

[0083] The real-time data of power grid operation, real-time information on power grid equipment status, real-time data on power grid load, and real-time data on meteorological environment are substituted into the predictive power grid electricity consumption model previously trained by the deep learning model. These data are used as the input of the model. After calculation and processing by the model, the expected power grid electricity consumption for the next period is output.

[0084] Comparing this predicted power consumption with the real-time power supply of the power grid, there are two possible results: one is that the power supply of the power grid can meet the predicted power consumption, and the other is that the power supply of the power grid does not meet the predicted power consumption. This comparison result provides important information about the future balance of power supply and demand for power grid operators.

[0085] By substituting real-time monitoring data into the forecasting model, grid operators can accurately understand the expected electricity consumption in the next period. This helps them plan and manage power resources in advance to meet future needs. By comparing the expected electricity consumption and the real-time power supply, grid operators can promptly detect potential imbalances between supply and demand. If the expected electricity consumption is higher than the real-time power supply, operators can take corresponding measures, such as increasing power generation or adjusting load distribution, to ensure the stable operation of the power grid. Accurate forecasting and comparison results can help grid operators allocate power resources more reasonably and avoid waste or shortage of resources. This can not only improve the operational efficiency of the power grid, but also reduce operating costs. By predicting and comparing in advance, grid operators can better respond to emergencies or abnormal situations, such as equipment failures, weather changes, etc. This helps to enhance the resilience and reliability of the power grid and reduce power outages or failures caused by unforeseen factors.

[0086] In summary, step S105 provides valuable prediction and decision support information for power grid operators by comparing the prediction model with the real-time monitoring data. This not only helps to optimize the resource allocation and operation management of the power grid, but also improves the stability and reliability of the power grid, thereby better meeting the power demand of the society.

[0087] Step S106, setting a regional indirect power supply strategy. When the power supply of the power grid does not meet the power grid's expected power consumption, the pre-stored electric energy is called up to supply power to the power grid according to the regional indirect power supply strategy. When the power grid meets the power grid's expected power consumption, the original power supply strategy continues to be executed.

[0088] Set up a regional indirect power supply strategy. The regional indirect power supply strategy is an emergency plan that is activated when the power supply of the power grid does not meet the expected power consumption. It aims to maximize the power demand of each region by optimizing the distribution of power.

[0089] When the power supply of the power grid does not meet the expected power consumption of the power grid, the system will call upon the pre-stored electric energy, which comes from the electric energy of the wind power generation equipment or photovoltaic power generation equipment stored in the previous step. According to the regional indirect power supply strategy, the electric energy will be reasonably distributed to various regions to ensure the power supply of key areas and important loads.

[0090] If the power supply from the power grid meets the expected power consumption, the system will continue to implement the original power supply strategy without making additional adjustments.

[0091] By setting up a regional indirect power supply strategy, the power grid can quickly adjust the power supply mode when the power supply is insufficient to ensure the power supply to key areas and important loads. This improves the resilience and reliability of the power grid and reduces the risk of power outages caused by insufficient power supply.

[0092] The regional indirect power supply strategy allows the grid to distribute power more reasonably when power supply is tight. This can ensure that power resources are used most efficiently and avoid excessive power consumption in some areas and insufficient power in other areas.

[0093] By accessing pre-stored electricity, the grid can use these renewable energy sources when necessary, thereby reducing dependence on traditional energy, reducing energy waste, and reducing the impact on the environment.

[0094] In the case of tight power supply, it is crucial to ensure that the power demand of key services (such as medical care, transportation, etc.) is met. Regional indirect power supply strategy can help the grid prioritize the power supply of these key services under limited resources.

[0095] In summary, step S106 significantly improves the resilience and reliability of the power grid by setting a regional indirect power supply strategy and, when necessary, calling up pre-stored power for power supply adjustment. This not only helps optimize power distribution and reduce energy waste, but also ensures that the power demand of key services is met at critical moments.

[0096] Specifically, the power supply control method for a distribution network provided by the present invention includes, in step 102:

[0097] Establish communication connection with wind power generation equipment and photovoltaic power generation equipment to obtain operation data of wind power generation equipment and photovoltaic power generation equipment;

[0098] When the wind power generation equipment and the photovoltaic power generation equipment generate electric energy, the electric power at the energy storage end is detected. If the electric power at the energy storage end is lower than the preset minimum energy storage value, the electric energy generated by the wind power generation equipment and the photovoltaic power generation equipment is received and stored at the energy storage end;

[0099] Based on the meteorological environment data, the meteorological environment data for the next 7 days is obtained. The meteorological environment data includes light intensity and wind intensity. The actual daily consumption of the real-time energy storage power of the energy storage end is detected, and the power consumption of the energy storage end in the next 7 days is predicted. If the power of the energy storage end in the next 7 days is lower than the preset minimum energy storage value, then during the period when the light intensity and wind intensity meet the operation of wind power generation equipment and photovoltaic power generation equipment, the electric energy with light intensity and wind intensity is received and stored.

[0100] Specifically, the power supply control method for a distribution network provided by the present invention, in step 103, further includes:

[0101] The grid operation data includes the grid voltage, grid current, and grid frequency operation parameters;

[0102] By real-time monitoring of the status of power grid equipment such as transformers, circuit breakers, and switches, the status information of power grid equipment can be obtained;

[0103] The grid load data includes active power and reactive power. The grid load data is used to display the load status of the grid and is also used for load management and data analysis to predict future load trends.

[0104] Meteorological environment data include light intensity, temperature, humidity, and wind speed.

[0105] Specifically, the power supply control method for a distribution network provided by the present invention includes, in step 105:

[0106] Collect real-time data on power grid operation, real-time information on power grid equipment status, and real-time data on meteorological environment. Real-time data on power grid operation includes voltage, current, and power factor. Real-time information on power grid equipment status includes transformer operation data and circuit breaker operation data.

[0107] Obtain real-time grid load data, which is used to monitor the real-time load status of the grid;

[0108] Preprocess the real-time data of power grid load, power grid operation, power grid equipment status and meteorological environment, and substitute the preprocessed real-time data of power grid operation, equipment status, load and meteorological environment into the power grid power consumption prediction model;

[0109] Run the prediction model of power grid electricity consumption, obtain the predicted value of the power grid's expected electricity consumption in the next period, obtain the data of the real-time power supply of the power grid, compare and analyze the predicted power grid consumption in the next period with the real-time power supply of the power grid, and judge whether the power grid can meet the predicted electricity consumption demand in the next period based on the comparison results.

[0110] Specifically, the power supply control method for a distribution network provided by the present invention includes, in step 106:

[0111] Set up a regional indirect power supply strategy. When the power supply of the power grid does not meet the expected power consumption of the power grid, set the power supply time for each power supply partition in turn according to the power supply partition label, and supply power to each power supply partition in turn according to the power supply partition label in a step-by-step manner;

[0112] When the electric energy at the energy storage end is fully stored or the grid function meets the expected power consumption of the grid, the stepped power supply to each power supply partition is stopped.

[0113] In a second aspect, the present invention provides a power supply control system for a distribution network, a power supply device end, an energy storage end, a power consumption device end, a power grid control end and a background control end, the power grid control end establishes a communication connection with the energy storage end, the power supply device end, the power consumption device end and the background control end, the power grid control end is used to process and analyze the data of the power supply device end, the power consumption device end and the background control end, obtain the power grid power supply adjustment command, and transmit the power grid power supply adjustment command to the energy storage end and the power supply device end, the energy storage end and the power supply device end execute the power grid power supply adjustment command, and adjust the power supply of the power grid, and the power grid control end includes:

[0114] A data acquisition unit, which acquires power grid operation data, power grid equipment status information, power grid load data, and meteorological environment data;

[0115] The energy storage unit retrieves historical data of the power grid from a database, wherein the historical data of the power grid includes historical power consumption data of the power grid, sets the highest power consumption value in the historical power consumption data of the power grid as the maximum power storage value, stores the power of the wind power generation equipment and the photovoltaic power generation equipment, and stops storing the power when the power of the stored wind power generation equipment and the photovoltaic power generation equipment reaches the maximum power storage value;

[0116] A monitoring unit monitors power grid operation data, power grid equipment status information, power grid load data, and meteorological environment data to obtain a real-time monitoring data set, wherein the real-time monitoring data set includes real-time power grid operation data, real-time power grid equipment status information, real-time power grid load data, and real-time meteorological environment data;

[0117] Assess future risks and determine the characteristics of the predicted grid load. The characteristics of the predicted grid load include ambient temperature characteristics, grid power supply characteristics, grid load characteristics, and grid equipment status characteristics. The characteristics of the predicted grid load and the real-time monitoring data set are trained through a deep learning model to obtain a model for predicting grid power consumption.

[0118] The power supply capacity evaluation unit of the power grid substitutes the real-time data of the power grid operation, the real-time information of the power grid equipment status, the real-time data of the power grid load and the real-time data of the meteorological environment into the power grid power consumption prediction model to obtain the power grid power consumption estimated in the next period, and compares the power grid power consumption estimated in the next period with the real-time power supply of the power grid to obtain the power grid power consumption prediction comparison result, which includes whether the power grid meets the power grid power consumption estimated and whether the power supply of the power grid does not meet the power grid power consumption estimated;

[0119] Scheduling matching, setting regional indirect power supply strategy. When the power supply of the power grid does not meet the power grid's expected power consumption, the pre-stored electric energy is called up to supply power to the power grid according to the regional indirect power supply strategy. When the power grid meets the power grid's expected power consumption, the original power supply strategy continues to be implemented.

[0120] Specifically, the power supply control system and energy storage unit for a power distribution network provided by the present invention include:

[0121] Establish communication connection with wind power generation equipment and photovoltaic power generation equipment to obtain operation data of wind power generation equipment and photovoltaic power generation equipment;

[0122] When the wind power generation equipment and the photovoltaic power generation equipment generate electric energy, the electric power at the energy storage end is detected. If the electric power at the energy storage end is lower than the preset minimum energy storage value, the electric energy generated by the wind power generation equipment and the photovoltaic power generation equipment is received and stored at the energy storage end;

[0123] Based on the meteorological environment data, the meteorological environment data for the next 7 days is obtained. The meteorological environment data includes light intensity and wind intensity. The actual daily consumption of the real-time energy storage power of the energy storage end is detected, and the power consumption of the energy storage end in the next 7 days is predicted. If the power of the energy storage end in the next 7 days is lower than the preset minimum energy storage value, then during the period when the light intensity and wind intensity meet the operation of wind power generation equipment and photovoltaic power generation equipment, the electric energy with light intensity and wind intensity is received and stored.

[0124] Specifically, the power supply control system and monitoring unit for a power distribution network provided by the present invention include:

[0125] The grid operation data includes the grid voltage, grid current, and grid frequency operation parameters;

[0126] By real-time monitoring of the status of power grid equipment such as transformers, circuit breakers, and switches, the status information of power grid equipment can be obtained;

[0127] The grid load data includes active power and reactive power. The grid load data is used to display the load status of the grid and is also used for load management and data analysis to predict future load trends.

[0128] Meteorological environment data include light intensity, temperature, humidity, and wind speed.

[0129] Specifically, the power supply control system for a distribution network provided by the present invention, and the power supply capacity evaluation unit of the power distribution network include:

[0130] Collect real-time data on power grid operation, real-time information on power grid equipment status, and real-time data on meteorological environment. Real-time data on power grid operation includes voltage, current, and power factor. Real-time information on power grid equipment status includes transformer operation data and circuit breaker operation data.

[0131] Obtain real-time grid load data, which is used to monitor the real-time load status of the grid;

[0132] Preprocess the real-time data of power grid load, power grid operation, power grid equipment status and meteorological environment, and substitute the preprocessed real-time data of power grid operation, equipment status, load and meteorological environment into the power grid power consumption prediction model;

[0133] Run the prediction model of power grid electricity consumption, obtain the predicted value of the power grid's expected electricity consumption in the next period, obtain the data of the real-time power supply of the power grid, compare and analyze the predicted power grid consumption in the next period with the real-time power supply of the power grid, and judge whether the power grid can meet the predicted electricity consumption demand in the next period based on the comparison results.

[0134] Specifically, the power supply control system and power supply adjustment unit for a power distribution network provided by the present invention include:

[0135] Set up a regional indirect power supply strategy. When the power supply of the power grid does not meet the expected power consumption of the power grid, set the power supply time for each power supply partition in turn according to the power supply partition label, and supply power to each power supply partition in turn according to the power supply partition label in a step-by-step manner;

[0136] When the electric energy at the energy storage end is fully stored or the grid function meets the expected power consumption of the grid, the stepped power supply to each power supply partition is stopped.

[0137] The technical solution of the present invention solves the problem of scheduling difficulties and insufficient power supply faced by the distribution network in a short period of time if the power consumption suddenly increases during the peak power consumption period through the following technical solutions:

[0138] Data-driven prediction and optimization: By collecting grid operation data, grid equipment status information, grid load data and meteorological environment data, the present invention can establish a model for predicting grid electricity consumption, and can perform training and learning based on a real-time monitoring data set, including real-time grid operation data, real-time information on grid equipment status, real-time grid load data and real-time meteorological environment data, so as to accurately predict the expected grid electricity consumption in the next period of time.

[0139] Utilization of energy storage system: The technical solution of the present invention mentions storing the electric energy of wind power generation equipment and photovoltaic power generation equipment. This means that the system can store excess electric energy during non-peak hours. When the peak of electricity consumption arrives, or the electricity consumption suddenly increases, the stored electric energy can be quickly released to make up for the shortage of power supply from the power grid, thereby solving the problem of scheduling difficulties in a short period of time.

[0140] Intelligent scheduling and power supply strategy adjustment: By comparing the estimated power consumption of the power grid with the real-time power supply of the power grid, the power supply adjustment unit can judge the power supply status of the power grid in real time. When it is found that the power grid may not be able to meet the estimated power consumption, the power stored in the energy storage terminal can be called up and intelligent scheduling can be performed according to the regional indirect power supply strategy to give priority to the power supply of key areas and important users.

[0141] Dynamic feedback and strategy adjustment: The power supply regulation unit will also dynamically adjust the power supply strategy according to the actual power supply situation and feedback information. This flexibility enables the system to quickly respond to changes in grid load and fluctuations in user demand, especially in the event of a sudden increase in power consumption, and can make rapid adjustments to ensure the stable operation of the grid.

[0142] In summary, the technical solution of the present invention effectively solves the problem of scheduling difficulties and power supply shortages in the distribution network within a short period of time if the power consumption suddenly increases during peak hours through data-driven prediction and optimization, utilization of energy storage systems, intelligent scheduling and power supply strategy adjustment, and dynamic feedback and strategy adjustment.

[0143] In summary, the specific implementation of the present invention effectively solves the key problems in existing offshore rocket launches and networking communications through innovative system architecture and workflow design, and makes important contributions to technological progress in related fields.

[0144] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations, and the above-mentioned embodiments of the present invention do not constitute a limitation on the scope of protection of the present invention.

Claims

1. A power supply control method for a distribution network, characterized in that: include: Step S101, acquiring power grid operation data, power grid equipment status information, power grid load data and meteorological environment data; Step S102, retrieving historical data of the power grid from a database, the historical data of the power grid including historical power consumption data of the power grid, setting the highest power consumption value in the historical power consumption data of the power grid as the maximum electric energy storage value, storing electric energy of the wind power generation equipment and the photovoltaic power generation equipment, and stopping energy storage when the electric energy stored in the wind power generation equipment and the photovoltaic power generation equipment reaches the maximum electric energy storage value; Step S103, monitoring power grid operation data, power grid equipment status information, power grid load data and meteorological environment data to obtain a real-time monitoring data set, the real-time monitoring data set including real-time power grid operation data, real-time power grid equipment status information, real-time power grid load data and real-time meteorological environment data; Step S104, determining the characteristics of the predicted power grid load, the characteristics of the predicted power grid load include the characteristics of the ambient temperature, the characteristics of the power grid power supply, the characteristics of the power grid load, and the characteristics of the power grid equipment status, and training the characteristics of the predicted power grid load and the real-time monitoring data set through a deep learning model to obtain a model for predicting power grid power consumption; Step S105, substituting the real-time data of power grid operation, the real-time information of power grid equipment status, the real-time data of power grid load and the real-time data of meteorological environment into the power grid power consumption prediction model to obtain the power grid power consumption estimated for the next period, comparing the power grid power consumption estimated for the next period with the real-time power supply of the power grid to obtain the power grid power consumption prediction comparison result, the power grid power consumption prediction comparison result includes the power grid meeting the power grid power consumption estimated and the power supply of the power grid not meeting the power grid power consumption estimated; Step S106, setting a regional indirect power supply strategy. When the power supply of the power grid does not meet the power grid's expected power consumption, the pre-stored electric energy is called up to supply power to the power grid according to the regional indirect power supply strategy. When the power grid meets the power grid's expected power consumption, the original power supply strategy continues to be executed.

2. The power supply control method for a distribution network according to claim 1, characterized in that: In step 102, it includes: Establish communication connection with wind power generation equipment and photovoltaic power generation equipment to obtain operation data of wind power generation equipment and photovoltaic power generation equipment; When the wind power generation equipment and the photovoltaic power generation equipment generate electric energy, the electric power at the energy storage end is detected. If the electric power at the energy storage end is lower than the preset minimum energy storage value, the electric energy generated by the wind power generation equipment and the photovoltaic power generation equipment is received and stored at the energy storage end; Based on the meteorological environment data, the meteorological environment data for the next 7 days is obtained. The meteorological environment data includes light intensity and wind intensity. The actual daily consumption of the real-time energy storage power of the energy storage end is detected, and the power consumption of the energy storage end in the next 7 days is predicted. If the power of the energy storage end in the next 7 days is lower than the preset minimum energy storage value, then during the period when the light intensity and wind intensity meet the operation of wind power generation equipment and photovoltaic power generation equipment, the electric energy with light intensity and wind intensity is received and stored.

3. The power supply control method for a distribution network according to claim 1, characterized in that: In step 103, it also includes: The grid operation data includes the grid voltage, grid current, and grid frequency operation parameters; By real-time monitoring of the status of power grid equipment such as transformers, circuit breakers, and switches, the status information of power grid equipment can be obtained; The grid load data includes active power and reactive power. The grid load data is used to display the load status of the grid and is also used for load management and data analysis to predict future load trends. Meteorological environment data include light intensity, temperature, humidity, and wind speed.

4. The power supply control method for a distribution network according to claim 1, characterized in that: In step 105, it includes: Collect real-time data on power grid operation, real-time information on power grid equipment status, and real-time data on meteorological environment. Real-time data on power grid operation includes voltage, current, and power factor. Real-time information on power grid equipment status includes transformer operation data and circuit breaker operation data. Obtain real-time grid load data, which is used to monitor the real-time load status of the grid; Preprocess the real-time data of power grid load, power grid operation, power grid equipment status and meteorological environment, and substitute the preprocessed real-time data of power grid operation, equipment status, load and meteorological environment into the power grid power consumption prediction model; Run the prediction model of power grid electricity consumption, obtain the predicted value of the power grid's expected electricity consumption in the next period, obtain the data of the real-time power supply of the power grid, compare and analyze the predicted power grid consumption in the next period with the real-time power supply of the power grid, and judge whether the power grid can meet the predicted electricity consumption demand in the next period based on the comparison results.

5. The power supply control method for a distribution network according to claim 1, characterized in that: In step 106, it includes: Set up a regional indirect power supply strategy. When the power supply of the power grid does not meet the expected power consumption of the power grid, set the power supply time for each power supply partition in turn according to the power supply partition label, and supply power to each power supply partition in turn according to the power supply partition label in a step-by-step manner; When the electric energy at the energy storage end is fully stored or the grid function meets the expected power consumption of the grid, the stepped power supply to each power supply partition is stopped.

6. A power supply control system for a distribution network, applied to the power supply control method for a distribution network as claimed in any one of claims 1 to 5, characterized in that: The power supply equipment end, the energy storage end, the power consumption equipment end, the power grid control end and the background control end establish communication connections with the energy storage end, the power supply equipment end, the power consumption equipment end and the background control end. The power grid control end is used to process and analyze the data of the power supply equipment end, the power consumption equipment end and the background control end, obtain the power supply adjustment command of the power grid, and transmit the power supply adjustment command of the power grid to the energy storage end and the power supply equipment end. The energy storage end and the power supply equipment end execute the power supply adjustment command of the power grid to adjust the power supply of the power grid. The power grid control end includes: A data acquisition unit, which acquires power grid operation data, power grid equipment status information, power grid load data, and meteorological environment data; The energy storage unit retrieves historical data of the power grid from a database, wherein the historical data of the power grid includes historical power consumption data of the power grid, sets the highest power consumption value in the historical power consumption data of the power grid as the maximum power storage value, stores the power of the wind power generation equipment and the photovoltaic power generation equipment, and stops storing the power when the power of the stored wind power generation equipment and the photovoltaic power generation equipment reaches the maximum power storage value; A monitoring unit monitors power grid operation data, power grid equipment status information, power grid load data, and meteorological environment data to obtain a real-time monitoring data set, wherein the real-time monitoring data set includes real-time power grid operation data, real-time power grid equipment status information, real-time power grid load data, and real-time meteorological environment data; Assess future risks and determine the characteristics of the predicted grid load. The characteristics of the predicted grid load include ambient temperature characteristics, grid power supply characteristics, grid load characteristics, and grid equipment status characteristics. The characteristics of the predicted grid load and the real-time monitoring data set are trained through a deep learning model to obtain a model for predicting grid power consumption. The power supply capacity evaluation unit of the power grid substitutes the real-time data of the power grid operation, the real-time information of the power grid equipment status, the real-time data of the power grid load and the real-time data of the meteorological environment into the power grid power consumption prediction model to obtain the power grid power consumption estimated in the next period, and compares the power grid power consumption estimated in the next period with the real-time power supply of the power grid to obtain the power grid power consumption prediction comparison result, which includes whether the power grid meets the power grid power consumption estimated and whether the power supply of the power grid does not meet the power grid power consumption estimated; Scheduling matching, setting regional indirect power supply strategy. When the power supply of the power grid does not meet the power grid's expected power consumption, the pre-stored electric energy is called up to supply power to the power grid according to the regional indirect power supply strategy. When the power grid meets the power grid's expected power consumption, the original power supply strategy continues to be implemented.

7. The power supply control system for a power distribution network according to claim 6, characterized in that: Energy storage unit, including: Establish communication connection with wind power generation equipment and photovoltaic power generation equipment to obtain operation data of wind power generation equipment and photovoltaic power generation equipment; When the wind power generation equipment and the photovoltaic power generation equipment generate electric energy, the electric power at the energy storage end is detected. If the electric power at the energy storage end is lower than the preset minimum energy storage value, the electric energy generated by the wind power generation equipment and the photovoltaic power generation equipment is received and stored at the energy storage end; Based on the meteorological environment data, the meteorological environment data for the next 7 days is obtained. The meteorological environment data includes light intensity and wind intensity. The actual daily consumption of the real-time energy storage power of the energy storage end is detected, and the power consumption of the energy storage end in the next 7 days is predicted. If the power of the energy storage end in the next 7 days is lower than the preset minimum energy storage value, then during the period when the light intensity and wind intensity meet the operation of wind power generation equipment and photovoltaic power generation equipment, the electric energy with light intensity and wind intensity is received and stored.

8. The power supply control system for a power distribution network according to claim 6, characterized in that: The monitoring unit also includes: The grid operation data includes the grid voltage, grid current, and grid frequency operation parameters; By real-time monitoring of the status of power grid equipment such as transformers, circuit breakers, and switches, the status information of power grid equipment can be obtained; The grid load data includes active power and reactive power. The grid load data is used to display the load status of the grid and is also used for load management and data analysis to predict future load trends. Meteorological environment data include light intensity, temperature, humidity, and wind speed.

9. The power supply control system for a power distribution network according to claim 6, characterized in that: Grid power supply capability assessment unit, including: Collect real-time data on power grid operation, real-time information on power grid equipment status, and real-time data on meteorological environment. Real-time data on power grid operation includes voltage, current, and power factor. Real-time information on power grid equipment status includes transformer operation data and circuit breaker operation data. Obtain real-time grid load data, which is used to monitor the real-time load status of the grid; Preprocess the real-time data of power grid load, power grid operation, power grid equipment status and meteorological environment, and substitute the preprocessed real-time data of power grid operation, equipment status, load and meteorological environment into the power grid power consumption prediction model; Run the prediction model of power grid electricity consumption, obtain the predicted value of the power grid's expected electricity consumption in the next period, obtain the data of the real-time power supply of the power grid, compare and analyze the predicted power grid consumption in the next period with the real-time power supply of the power grid, and judge whether the power grid can meet the predicted electricity consumption demand in the next period based on the comparison results.

10. The power supply control system for a power distribution network according to claim 6, characterized in that: A power supply conditioning unit, comprising: Set up a regional indirect power supply strategy. When the power supply of the power grid does not meet the expected power consumption of the power grid, set the power supply time for each power supply partition in turn according to the power supply partition label, and supply power to each power supply partition in turn according to the power supply partition label in a step-by-step manner; When the electric energy at the energy storage end is fully stored or the grid function meets the expected power consumption of the grid, the stepped power supply to each power supply partition is stopped.

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