Parallel operation capacity increase control method and system of high-voltage variable-frequency power supply and electronic equipment

Abstract

The invention relates to a parallel operation capacity increasing control method and system for high-voltage variable-frequency power sources and electronic equipment, and belongs to the technical field of power source control. According to the capacity characteristic data of each high-voltage variable-frequency power supply, obtaining the high-voltage variable-frequency power supply meeting the requirement, and obtaining the position information of the power supply in the target area, and finally obtaining the geographic position information of the high-voltage variable-frequency power supply meeting the requirement. And according to the position information of the power supply in the target area and the geographical position information of the high-voltage variable-frequency power supply meeting the requirements, obtaining an optimal parallel-operation capacity-increasing power storage combination. The optimal energy storage combination is selected by estimating the capacity characteristic data of the high-voltage variable-frequency power supply and the power supply data information of the target area, the energy storage plan of the target area is optimized, and the energy storage rationality of the energy storage device is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of equipment control, and in particular to a parallel capacity increasing control method, system and electronic equipment for high-voltage variable frequency power supplies. Background Art

[0002] With economic development and social progress, urban and rural production and people's livelihood electricity consumption is also rising year by year, and the demand for electricity is showing a diversified trend, and users have higher and higher requirements for power supply quality. For intermittent high-power loads such as fast charging piles and seasonal pumps, if the transformer capacity is directly increased or even new transformers are invested, this will not only increase the construction cost of the distribution network, but also reduce the utilization rate of distribution transformers and line equipment, increase the network loss rate, and further increase the power supply cost. With the rapid development of urban areas, there are more and more constraints on the construction of pole-mounted transformers in urban areas. Some areas facing the street can no longer build new distribution transformers. At the same time, the grid structure in many rural areas is weak, and the guarantee of power supply is still a prominent problem. Some substations no longer have the objective conditions for building new distribution transformers. At present, most rural power grids have low annual power load rates, and peak power consumption is periodic or seasonal. The peak load is prominent in a specific period, which often causes the distribution transformers in the substations to be overloaded, which may cause power outages in some areas and affect the normal production and life of people in rural areas. After a long period of research, it was found that traditional means of improving low voltage, such as expanding transformer capacity or installing reactive power compensation devices, have low asset utilization or overvoltage problems in the back-end area during peak power consumption periods. Therefore, adopting energy storage devices to achieve flexible capacity expansion of distribution transformers, assist in providing the required active and reactive power to users in the substation area during peak power consumption periods, and achieve flexible adjustment of voltage in urban and rural substation areas is a solution. However, the prior art does not take into account that after a certain number of years of use, the power capacity of the energy storage device will decrease, which will cause abnormalities in the high-voltage variable-frequency power supply during the parallel capacity expansion process, so that the capacity of the high-voltage variable-frequency power supply cannot meet the predetermined requirements, and thus cannot meet the actual power supply needs. Summary of the invention

[0003] The present invention overcomes the deficiencies of the prior art and provides a parallel capacity increasing control method, system and electronic equipment for a high voltage variable frequency power supply.

[0004] To achieve the above object, the technical solution adopted by the present invention is:

[0005] A first aspect of the present invention provides a method for controlling the parallel operation and capacity increase of multiple high-voltage variable-frequency power supplies, comprising the following steps:

[0006] Acquire power supply data information of a target area, and obtain a power supply status analysis result by identifying and analyzing the power supply status of the power supply data information of the target area;

[0007] Acquire historical capacity change characteristic data of the high-voltage variable-frequency power supply, and construct a capacity characteristic prediction model of the high-voltage variable-frequency power supply based on the historical capacity change characteristic data of the high-voltage variable-frequency power supply;

[0008] Predicting the capacity characteristic data of each high-voltage variable-frequency power supply by the capacity characteristic prediction model of the high-voltage variable-frequency power supply, obtaining a high-voltage variable-frequency power supply that meets the requirements according to the capacity characteristic data of each high-voltage variable-frequency power supply, and obtaining the location information of the power supply in the target area;

[0009] The geographical location information of the high-voltage variable frequency power supply that meets the requirements is obtained, and the optimal parallel capacity increase and power storage combination is obtained according to the location information of the power supply in the target area and the geographical location information of the high-voltage variable frequency power supply that meets the requirements.

[0010] Furthermore, in this method, power supply data information of the target area is obtained, and power supply status analysis results are obtained by identifying and analyzing the power supply data information of the target area, specifically:

[0011] Acquire power supply data information of a target area, set a power supply data threshold, and determine whether the power supply data information of the target area is greater than the power supply data threshold;

[0012] When the power supply data information of the target area is greater than the power supply data threshold, a state signal that meets the power supply demand is generated, and a power supply state analysis result is generated according to the state signal that meets the power supply demand;

[0013] When the power supply data information of the target area is not greater than the power supply data threshold, a status signal indicating that power supply demand is not met is generated, and a power supply status analysis result is generated according to the status signal indicating that power supply demand is not met.

[0014] Furthermore, in this method, historical capacity change characteristic data of the high-voltage variable frequency power supply is obtained, and the capacity characteristic prediction model of the high-voltage variable frequency power supply is constructed based on the historical capacity change characteristic data of the high-voltage variable frequency power supply, which specifically includes:

[0015] Acquire historical capacity change characteristic data of the high-voltage variable-frequency power supply through big data, construct a characteristic matrix based on the historical capacity change characteristic data of the high-voltage variable-frequency power supply, and construct a capacity characteristic prediction model of the high-voltage variable-frequency power supply based on a neural network;

[0016] Inputting the feature matrix into the capacity feature prediction model of the high-voltage variable-frequency power supply for training, and processing the feature matrix through an attention mechanism to focus on the capacity feature data;

[0017] When the model parameters of the capacity characteristic prediction model of the high-voltage variable frequency power supply meet the preset requirements, the model parameters of the capacity characteristic prediction model of the high-voltage variable frequency power supply are saved, and the capacity characteristic prediction model of the high-voltage variable frequency power supply is output.

[0018] Furthermore, in the present method, predicting the capacity characteristic data of each high-voltage variable-frequency power supply by using the capacity characteristic prediction model of the high-voltage variable-frequency power supply specifically includes:

[0019] Acquire capacity characteristic data of the high-voltage variable-frequency power supply within a preset time, and input the capacity characteristic data of the high-voltage variable-frequency power supply within the preset time into a capacity characteristic prediction model of the high-voltage variable-frequency power supply for prediction;

[0020] By prediction, the capacity characteristic data of each high-voltage variable-frequency power supply within the next preset time is obtained, and the capacity characteristic data of each high-voltage variable-frequency power supply within the next preset time is output.

[0021] Furthermore, in this method, a high-voltage variable-frequency power supply that meets the requirements is obtained according to the capacity characteristic data of each high-voltage variable-frequency power supply, specifically:

[0022] Setting a capacity characteristic threshold of the high-voltage variable-frequency power supply, and determining whether the capacity characteristic data of each high-voltage variable-frequency power supply is greater than the capacity characteristic threshold of the high-voltage variable-frequency power supply;

[0023] When the capacity characteristic data is greater than the capacity characteristic threshold of the high-voltage variable-frequency power supply, the high-voltage variable-frequency power supply corresponding to the capacity characteristic data greater than the capacity characteristic threshold of the high-voltage variable-frequency power supply is regarded as a high-voltage variable-frequency power supply that meets the requirements;

[0024] When the capacity characteristic data is not greater than the capacity characteristic threshold of the high-voltage variable frequency power supply, the high-voltage variable frequency power supply corresponding to the capacity characteristic threshold of the high-voltage variable frequency power supply whose capacity characteristic data is not greater than the capacity characteristic threshold of the high-voltage variable frequency power supply is regarded as a high-voltage variable frequency power supply that does not meet the requirements.

[0025] Furthermore, in this method, the geographical location information of the high-voltage variable frequency power supply that meets the requirements is obtained, and the optimal parallel capacity increase and power storage combination is obtained according to the location information of the power supply in the target area and the geographical location information of the high-voltage variable frequency power supply that meets the requirements, specifically:

[0026] Obtain the geographical location information of the high-voltage variable-frequency power supply that meets the requirements, and obtain the grid layout information in the target area and the geographical location of the power supply energy;

[0027] Calculate the transmission distance information of the power supply line based on the geographical location information of the high-voltage variable frequency power supply that meets the requirements, the power grid layout information in the target area, and the geographical location of the power supply energy source;

[0028] Obtaining estimated loss information for each transmission distance through big data, and calculating power supply loss information based on the transmission distance information of the power supply wire and the estimated loss information for each transmission distance;

[0029] A particle swarm algorithm is introduced to calculate the optimal parallel-machine capacity-increasing power-storage combination according to the power supply loss information, and the optimal parallel-machine capacity-increasing power-storage combination is output.

[0030] Furthermore, in this method, a particle swarm algorithm is introduced, and the particle swarm algorithm is used to calculate the optimal parallel machine capacity increase and power storage combination according to the power loss information, and output the optimal parallel machine capacity increase and power storage combination, which specifically includes:

[0031] A particle swarm algorithm is introduced, the number of iterations is set based on the particle swarm algorithm, and an optimal parallel-machine capacity-increasing power storage combination is constructed, and a high-voltage variable-frequency power supply that meets the requirements is randomly selected from the optimal parallel-machine capacity-increasing power storage combination;

[0032] Obtain estimated power loss information based on the high-voltage variable-frequency power supply that meets the requirements and the power loss information in the optimal parallel-machine capacity-increasing power storage combination, set power loss threshold data, and determine whether the power loss information is greater than the power loss threshold data;

[0033] When the power loss information is not greater than the power loss threshold data, the optimal parallel capacity increase and power storage combination is output, and the parallel capacity increase and energy storage are performed according to the optimal parallel capacity increase and power storage combination;

[0034] When the power supply loss information is greater than the power supply loss threshold data, the optimal parallel capacity increase and power storage combination is iterated based on the number of iterations, and a high-voltage variable frequency power supply that meets the requirements is reselected until it is no greater than the power supply loss threshold data.

[0035] A second aspect of the present invention provides a parallel capacity expansion control system for multiple high-voltage variable-frequency power supplies, the system comprising a memory and a processor, the memory comprising a parallel capacity expansion control method program for multiple high-voltage variable-frequency power supplies, and when the parallel capacity expansion control method program for multiple high-voltage variable-frequency power supplies is executed by the processor, the steps of any one of the parallel capacity expansion control methods for multiple high-voltage variable-frequency power supplies are implemented.

[0036] A third aspect of the present invention provides an electronic device, comprising:

[0037] A power supply status analysis module is used to obtain power supply data information of a target area, and obtain a power supply status analysis result by identifying and analyzing the power supply data information of the target area;

[0038] A capacity characteristic prediction module is used to obtain historical capacity change characteristic data of the high-voltage variable-frequency power supply, and to construct a capacity characteristic prediction model of the high-voltage variable-frequency power supply based on the historical capacity change characteristic data of the high-voltage variable-frequency power supply;

[0039] A data analysis module, which predicts the capacity characteristic data of each high-voltage variable-frequency power supply through the capacity characteristic prediction model of the high-voltage variable-frequency power supply, obtains a high-voltage variable-frequency power supply that meets the requirements according to the capacity characteristic data of each high-voltage variable-frequency power supply, and obtains the location information of the power supply in the target area;

[0040] The output module obtains the geographical location information of the high-voltage variable frequency power supply that meets the requirements, and obtains the optimal parallel capacity increase and power storage combination according to the location information of the power supply in the target area and the geographical location information of the high-voltage variable frequency power supply that meets the requirements.

[0041] A fourth aspect of the present invention provides a computer-readable storage medium, which includes a parallel capacity expansion control method program for multiple high-voltage variable-frequency power supplies. When the parallel capacity expansion control method program for multiple high-voltage variable-frequency power supplies is executed by a processor, the steps of any one of the parallel capacity expansion control methods for multiple high-voltage variable-frequency power supplies are implemented.

[0042] The present invention solves the defects existing in the background technology and has the following beneficial effects:

[0043] The present invention obtains the power supply data information of the target area, identifies and analyzes the power supply status of the power supply data information of the target area, obtains the power supply status analysis result, and then obtains the historical capacity change characteristic data of the high-voltage variable frequency power supply, and constructs the capacity characteristic prediction model of the high-voltage variable frequency power supply based on the historical capacity change characteristic data of the high-voltage variable frequency power supply, thereby predicting the capacity characteristic data of each high-voltage variable frequency power supply through the capacity characteristic prediction model of the high-voltage variable frequency power supply, obtaining the high-voltage variable frequency power supply that meets the requirements according to the capacity characteristic data of each high-voltage variable frequency power supply, and obtaining the location information of the power supply in the target area, and finally obtaining the geographical location information of the high-voltage variable frequency power supply that meets the requirements, and obtaining the optimal parallel capacity increase power storage combination according to the location information of the power supply in the target area and the geographical location information of the high-voltage variable frequency power supply that meets the requirements. The present invention selects the optimal energy storage combination by estimating the capacity characteristic data of the high-voltage variable frequency power supply and the power supply data information of the target area, optimizes the energy storage plan of the target area, and improves the rationality of energy storage for the energy storage device. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, drawings of other embodiments can be obtained based on these drawings without paying creative work.

[0045] Figure 1 The overall flow chart of the parallel capacity increase control method of multiple high-voltage variable-frequency power supplies is shown;

[0046] Figure 2 A partial flow chart of a method for controlling the parallel operation and capacity increase of multiple high-voltage variable-frequency power supplies is shown;

[0047] Figure 3 The system block diagram of the parallel capacity increase control system of multiple high-voltage variable-frequency power supplies is shown;

[0048] Figure 4 A device diagram showing an electronic device. DETAILED DESCRIPTION

[0049] In order to more clearly understand the above-mentioned purpose, features and advantages of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that the embodiments of the present application and the features in the embodiments can be combined with each other without conflict.

[0050] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Therefore, the protection scope of the present invention is not limited to the specific embodiments disclosed below.

[0051] like Figure 1 As shown, the first aspect of the present invention provides a parallel capacity increase control method for multiple high-voltage variable-frequency power supplies, comprising the following steps:

[0052] S102: Acquire power supply data information of the target area, and obtain power supply status analysis results by identifying and analyzing the power supply data information of the target area;

[0053] S104: Acquire historical capacity change characteristic data of the high-voltage variable-frequency power supply, and construct a capacity characteristic prediction model of the high-voltage variable-frequency power supply based on the historical capacity change characteristic data of the high-voltage variable-frequency power supply;

[0054] S106: predicting the capacity characteristic data of each high-voltage variable-frequency power supply through the capacity characteristic prediction model of the high-voltage variable-frequency power supply, obtaining a high-voltage variable-frequency power supply that meets the requirements according to the capacity characteristic data of each high-voltage variable-frequency power supply, and obtaining the location information of the power supply in the target area;

[0055] S108: Obtain geographical location information of high-voltage variable-frequency power supplies that meet the requirements, and obtain the optimal parallel-connection capacity-increasing power storage combination based on the location information of the power supply in the target area and the geographical location information of the high-voltage variable-frequency power supplies that meet the requirements.

[0056] It should be noted that the present invention selects the optimal energy storage combination by estimating the capacity characteristic data of the high-voltage variable-frequency power supply and the power supply data information of the target area, thereby optimizing the energy storage plan of the target area and improving the rationality of energy storage of the energy storage device.

[0057] Furthermore, in this method, power supply data information of the target area is obtained, and power supply status analysis results are obtained by identifying and analyzing the power supply data information of the target area, specifically:

[0058] Obtaining power supply data information of the target area, setting a power supply data threshold, and determining whether the power supply data information of the target area is greater than the power supply data threshold;

[0059] When the power supply data information of the target area is greater than the power supply data threshold, a state signal that meets the power supply demand is generated, and a power supply state analysis result is generated according to the state signal that meets the power supply demand;

[0060] When the power supply data information of the target area is not greater than the power supply data threshold, a state signal indicating that the power supply demand is not met is generated, and a power supply state analysis result is generated according to the state signal indicating that the power supply demand is not met.

[0061] It should be noted that the power supply data information includes descriptions such as the power supply amount required within the target time period, the power supply power within a unit time, and the power supply power required within the target time period.

[0062] Furthermore, in this method, historical capacity change characteristic data of the high-voltage variable frequency power supply is obtained, and a capacity characteristic prediction model of the high-voltage variable frequency power supply is constructed based on the historical capacity change characteristic data of the high-voltage variable frequency power supply, specifically including:

[0063] The historical capacity change characteristic data of the high-voltage variable-frequency power supply is obtained through big data, and a characteristic matrix is ​​constructed based on the historical capacity change characteristic data of the high-voltage variable-frequency power supply, and a capacity characteristic prediction model of the high-voltage variable-frequency power supply is constructed based on a neural network;

[0064] The feature matrix is ​​input into the capacity feature prediction model of the high-voltage variable-frequency power supply for training, and the feature matrix is ​​processed through the attention mechanism to focus on the capacity feature data;

[0065] When the model parameters of the capacity characteristic prediction model of the high-voltage variable frequency power supply meet the preset requirements, the model parameters of the capacity characteristic prediction model of the high-voltage variable frequency power supply are saved, and the capacity characteristic prediction model of the high-voltage variable frequency power supply is output.

[0066] It should be noted that the capacity characteristic data is a description of the amount of electricity stored, the amount of electric energy stored, etc. After the high-voltage variable-frequency power supply has been used for a certain number of years, the capacity characteristic data will become smaller due to the degradation of parts. Through this method, a capacity characteristic prediction model of the high-voltage variable-frequency power supply can be obtained, thereby predicting the capacity characteristic data of each high-voltage variable-frequency power supply within the next preset time.

[0067] Furthermore, in the present method, the capacity characteristic data of each high-voltage variable-frequency power supply is predicted by the capacity characteristic prediction model of the high-voltage variable-frequency power supply, specifically including:

[0068] Acquire capacity characteristic data of the high-voltage variable-frequency power supply within a preset time, and input the capacity characteristic data of the high-voltage variable-frequency power supply within the preset time into a capacity characteristic prediction model of the high-voltage variable-frequency power supply for prediction;

[0069] By prediction, the capacity characteristic data of each high-voltage variable-frequency power supply within the next preset time is obtained, and the capacity characteristic data of each high-voltage variable-frequency power supply within the next preset time is output.

[0070] Furthermore, in this method, a high-voltage variable-frequency power supply that meets the requirements is obtained according to the capacity characteristic data of each high-voltage variable-frequency power supply, specifically:

[0071] Setting a capacity characteristic threshold of the high-voltage variable-frequency power supply, and determining whether the capacity characteristic data of each high-voltage variable-frequency power supply is greater than the capacity characteristic threshold of the high-voltage variable-frequency power supply;

[0072] When the capacity characteristic data is greater than the capacity characteristic threshold of the high-voltage variable-frequency power supply, the high-voltage variable-frequency power supply corresponding to the capacity characteristic data greater than the capacity characteristic threshold of the high-voltage variable-frequency power supply is regarded as a high-voltage variable-frequency power supply that meets the requirements;

[0073] When the capacity characteristic data is not greater than the capacity characteristic threshold of the high-voltage variable frequency power supply, the high-voltage variable frequency power supply corresponding to the capacity characteristic threshold of the high-voltage variable frequency power supply whose capacity characteristic data is not greater than the capacity characteristic threshold of the high-voltage variable frequency power supply is regarded as a high-voltage variable frequency power supply that does not meet the requirements.

[0074] Furthermore, in this method, the geographical location information of the high-voltage variable frequency power supply that meets the requirements is obtained, and the optimal parallel capacity increase and power storage combination is obtained according to the location information of the power supply in the target area and the geographical location information of the high-voltage variable frequency power supply that meets the requirements, specifically:

[0075] Obtain the geographical location information of the high-voltage variable-frequency power supply that meets the requirements, and obtain the grid layout information in the target area and the geographical location of the power supply energy;

[0076] Calculate the transmission distance information of the power supply line based on the geographical location information of the high-voltage variable frequency power supply that meets the requirements, the power grid layout information in the target area, and the geographical location of the power supply energy;

[0077] Obtain estimated loss information for each transmission distance through big data, and calculate power supply loss information based on the transmission distance information of the power supply wire and the estimated loss information for each transmission distance;

[0078] The particle swarm algorithm is introduced to calculate the optimal parallel-machine capacity-increasing power-storage combination according to the power supply loss information, and output the optimal parallel-machine capacity-increasing power-storage combination.

[0079] like Figure 2 As shown, further, in this method, a particle swarm algorithm is introduced, and the particle swarm algorithm is used to calculate the optimal parallel machine capacity increase and power storage combination according to the power supply loss information, and the optimal parallel machine capacity increase and power storage combination is output, which specifically includes:

[0080] S202: Introduce a particle swarm algorithm, set the number of iterations based on the particle swarm algorithm, and construct an optimal parallel-machine capacity-increasing power storage combination, and randomly select a high-voltage variable-frequency power supply that meets the requirements from the optimal parallel-machine capacity-increasing power storage combination;

[0081] S204: obtaining estimated power loss information based on the high-voltage variable-frequency power supply that meets the requirements and the power loss information in the optimal parallel-machine capacity-increasing power storage combination, setting power loss threshold data, and determining whether the power loss information is greater than the power loss threshold data;

[0082] S206: When the power loss information is not greater than the power loss threshold data, the optimal parallel capacity increase and power storage combination is output, and the parallel capacity increase and power storage are performed according to the optimal parallel capacity increase and power storage combination;

[0083] S208: When the power supply loss information is greater than the power supply loss threshold data, the optimal parallel capacity increase and power storage combination is iterated based on the number of iterations, and a high-voltage variable frequency power supply that meets the requirements is reselected until it is not greater than the power supply loss threshold data.

[0084] It should be noted that this method fully considers the transmission energy consumption during energy storage, so as to find the optimal parallel capacity expansion and energy storage combination through the particle swarm algorithm, so as to carry out parallel capacity expansion and energy storage according to the optimal parallel capacity expansion and energy storage combination, thereby improving the rationality of energy storage.

[0085] In addition, the method may further include:

[0086] Building a power demand prediction model based on LSTM (Long Short-Term Memory Network), obtaining power demand information of a target area within a preset time, and inputting the power demand information of the target area within the preset time into the power demand prediction model for training;

[0087] Acquire the trained power demand prediction model through training, and predict the power demand information of the target area within the current preset time through the trained power demand prediction model;

[0088] Acquire the quantity information of the high-voltage variable-frequency power supplies in the target area and the capacity characteristic data of each high-voltage variable-frequency power supply within a preset time, and calculate the total capacity characteristic data based on the quantity information of the high-voltage variable-frequency power supplies in the target area and the capacity characteristic data of each high-voltage variable-frequency power supply within the preset time;

[0089] When the total capacity characteristic data is greater than the power supply demand information of the target area within the current preset time, parallel operation, capacity increase and energy storage are performed according to the optimal parallel operation, capacity increase and energy storage combination;

[0090] When the total capacity characteristic data is not greater than the power supply demand information of the target area within the current preset time, the quantity information of the high-voltage variable-frequency power supply is reinitialized until it is greater than the power supply demand information of the target area within the current preset time, and the optimal parallel capacity increase and power storage combination is replanned.

[0091] It should be noted that the power supply demand is inconsistent in different seasons and weather conditions. This method can further improve the rationality of energy storage.

[0092] like Figure 3 As shown, the second aspect of the present invention provides a parallel capacity expansion control system 3 for multiple high-voltage variable-frequency power supplies. The system includes a memory 31 and a processor 32. The memory 31 includes a parallel capacity expansion control method program for multiple high-voltage variable-frequency power supplies. When the parallel capacity expansion control method program for multiple high-voltage variable-frequency power supplies is executed by the processor 32, any step of the parallel capacity expansion control method for multiple high-voltage variable-frequency power supplies is implemented.

[0093] like Figure 4 As shown, the third aspect of the present invention provides an electronic device, including:

[0094] The power supply status analysis module 10 is responsible for obtaining the power supply data information of the target area, identifying and analyzing the power supply status of the power supply data information of the target area, and obtaining the power supply status analysis result;

[0095] The capacity characteristic prediction module 20 is responsible for obtaining the historical capacity change characteristic data of the high-voltage variable-frequency power supply and constructing a capacity characteristic prediction model of the high-voltage variable-frequency power supply based on the historical capacity change characteristic data of the high-voltage variable-frequency power supply;

[0096] The data analysis module 30 is responsible for predicting the capacity characteristic data of each high-voltage variable-frequency power supply through the capacity characteristic prediction model of the high-voltage variable-frequency power supply, obtaining the high-voltage variable-frequency power supply that meets the requirements according to the capacity characteristic data of each high-voltage variable-frequency power supply, and obtaining the location information of the power supply in the target area;

[0097] The output module 40 is responsible for obtaining the geographical location information of the high-voltage variable frequency power supply that meets the requirements, and obtaining the optimal parallel capacity increase and power storage combination according to the location information of the power supply in the target area and the geographical location information of the high-voltage variable frequency power supply that meets the requirements.

[0098] Furthermore, in this device, power supply data information of the target area is obtained, and power supply status analysis results are obtained by identifying and analyzing the power supply data information of the target area, specifically:

[0099] Obtaining power supply data information of the target area, setting a power supply data threshold, and determining whether the power supply data information of the target area is greater than the power supply data threshold;

[0100] When the power supply data information of the target area is greater than the power supply data threshold, a state signal that meets the power supply demand is generated, and a power supply state analysis result is generated according to the state signal that meets the power supply demand;

[0101] When the power supply data information of the target area is not greater than the power supply data threshold, a state signal indicating that the power supply demand is not met is generated, and a power supply state analysis result is generated according to the state signal indicating that the power supply demand is not met.

[0102] Furthermore, in this device, historical capacity change characteristic data of the high-voltage variable frequency power supply is obtained, and a capacity characteristic prediction model of the high-voltage variable frequency power supply is constructed based on the historical capacity change characteristic data of the high-voltage variable frequency power supply, specifically including:

[0103] The historical capacity change characteristic data of the high-voltage variable-frequency power supply is obtained through big data, and a characteristic matrix is ​​constructed based on the historical capacity change characteristic data of the high-voltage variable-frequency power supply, and a capacity characteristic prediction model of the high-voltage variable-frequency power supply is constructed based on a neural network;

[0104] The feature matrix is ​​input into the capacity feature prediction model of the high-voltage variable-frequency power supply for training, and the feature matrix is ​​processed through the attention mechanism to focus on the capacity feature data;

[0105] When the model parameters of the capacity characteristic prediction model of the high-voltage variable frequency power supply meet the preset requirements, the model parameters of the capacity characteristic prediction model of the high-voltage variable frequency power supply are saved, and the capacity characteristic prediction model of the high-voltage variable frequency power supply is output.

[0106] Furthermore, in the present device, the capacity characteristic data of each high-voltage variable-frequency power supply is predicted by the capacity characteristic prediction model of the high-voltage variable-frequency power supply, specifically including:

[0107] Acquire capacity characteristic data of the high-voltage variable-frequency power supply within a preset time, and input the capacity characteristic data of the high-voltage variable-frequency power supply within the preset time into a capacity characteristic prediction model of the high-voltage variable-frequency power supply for prediction;

[0108] By prediction, the capacity characteristic data of each high-voltage variable-frequency power supply within the next preset time is obtained, and the capacity characteristic data of each high-voltage variable-frequency power supply within the next preset time is output.

[0109] Furthermore, in this device, a high-voltage variable-frequency power supply that meets the requirements is obtained according to the capacity characteristic data of each high-voltage variable-frequency power supply, specifically:

[0110] Setting a capacity characteristic threshold of the high-voltage variable-frequency power supply, and determining whether the capacity characteristic data of each high-voltage variable-frequency power supply is greater than the capacity characteristic threshold of the high-voltage variable-frequency power supply;

[0111] When the capacity characteristic data is greater than the capacity characteristic threshold of the high-voltage variable-frequency power supply, the high-voltage variable-frequency power supply corresponding to the capacity characteristic data greater than the capacity characteristic threshold of the high-voltage variable-frequency power supply is regarded as a high-voltage variable-frequency power supply that meets the requirements;

[0112] When the capacity characteristic data is not greater than the capacity characteristic threshold of the high-voltage variable frequency power supply, the high-voltage variable frequency power supply corresponding to the capacity characteristic threshold of the high-voltage variable frequency power supply whose capacity characteristic data is not greater than the capacity characteristic threshold of the high-voltage variable frequency power supply is regarded as a high-voltage variable frequency power supply that does not meet the requirements.

[0113] Furthermore, in this device, the geographical location information of the high-voltage variable frequency power supply that meets the requirements is obtained, and the optimal parallel capacity increase and power storage combination is obtained according to the location information of the power supply in the target area and the geographical location information of the high-voltage variable frequency power supply that meets the requirements, specifically:

[0114] Obtain the geographical location information of the high-voltage variable-frequency power supply that meets the requirements, and obtain the grid layout information in the target area and the geographical location of the power supply energy;

[0115] Calculate the transmission distance information of the power supply line based on the geographical location information of the high-voltage variable frequency power supply that meets the requirements, the power grid layout information in the target area, and the geographical location of the power supply energy;

[0116] Obtain estimated loss information for each transmission distance through big data, and calculate power supply loss information based on the transmission distance information of the power supply wire and the estimated loss information for each transmission distance;

[0117] The particle swarm algorithm is introduced to calculate the optimal parallel-machine capacity-increasing power-storage combination according to the power supply loss information, and output the optimal parallel-machine capacity-increasing power-storage combination.

[0118] Furthermore, in this device, a particle swarm algorithm is introduced to calculate the optimal parallel capacity increase and power storage combination according to the power loss information, and output the optimal parallel capacity increase and power storage combination, which specifically includes:

[0119] Introduce a particle swarm algorithm, set the number of iterations based on the particle swarm algorithm, and build an optimal parallel-machine capacity-increasing power storage combination, and randomly select a high-voltage variable-frequency power supply that meets the requirements from the optimal parallel-machine capacity-increasing power storage combination;

[0120] Based on the high-voltage variable-frequency power supply that meets the requirements and the power loss information in the optimal parallel-machine capacity-increasing power storage combination, the estimated power loss information is obtained, and the power loss threshold data is set to determine whether the power loss information is greater than the power loss threshold data;

[0121] When the power loss information is not greater than the power loss threshold data, the optimal parallel capacity increase and power storage combination is output, and the parallel capacity increase and energy storage are performed according to the optimal parallel capacity increase and power storage combination;

[0122] When the power supply loss information is greater than the power supply loss threshold data, the optimal parallel capacity increase and power storage combination is iterated based on the number of iterations, and a high-voltage variable frequency power supply that meets the requirements is reselected until it is no greater than the power supply loss threshold data.

[0123] The fourth aspect of the present invention provides a computer-readable storage medium, which includes a parallel capacity expansion control method program for multiple high-voltage variable-frequency power supplies. When the parallel capacity expansion control method program for multiple high-voltage variable-frequency power supplies is executed by a processor, any step of the parallel capacity expansion control method for multiple high-voltage variable-frequency power supplies is implemented.

[0124] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0125] The units described above as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units; they may be located in one place or distributed on multiple network units; some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0126] In addition, all functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately used as a unit, or two or more units may be integrated into one unit; the above-mentioned integrated units may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0127] A person of ordinary skill in the art can understand that: all or part of the steps of implementing the above method embodiments can be completed by hardware related to program instructions, and the aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it executes the steps of the above method embodiments; and the aforementioned storage medium includes: mobile storage devices, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks or optical disks, and other media that can store program codes.

[0128] Alternatively, if the above-mentioned integrated unit of the present invention is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiment of the present invention can be essentially or partly reflected in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the methods of each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, ROM, RAM, magnetic disks or optical disks.

[0129] The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art who is familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A method for controlling the parallel operation and capacity increase of multiple high-voltage variable-frequency power supplies, characterized in that: The following steps are involved: Acquire power supply data information of a target area, and obtain a power supply status analysis result by identifying and analyzing the power supply status of the power supply data information of the target area; Acquire historical capacity change characteristic data of the high-voltage variable-frequency power supply, and construct a capacity characteristic prediction model of the high-voltage variable-frequency power supply based on the historical capacity change characteristic data of the high-voltage variable-frequency power supply; Predicting the capacity characteristic data of each high-voltage variable-frequency power supply by the capacity characteristic prediction model of the high-voltage variable-frequency power supply, obtaining a high-voltage variable-frequency power supply that meets the requirements according to the capacity characteristic data of each high-voltage variable-frequency power supply, and obtaining the location information of the power supply in the target area; The geographical location information of the high-voltage variable frequency power supply that meets the requirements is obtained, and the optimal parallel capacity increase and power storage combination is obtained according to the location information of the power supply in the target area and the geographical location information of the high-voltage variable frequency power supply that meets the requirements.

2. The method for controlling the parallel operation and capacity increase of multiple high-voltage variable-frequency power supplies according to claim 1, characterized in that: The power supply data information of the target area is obtained, and the power supply status analysis result is obtained by identifying and analyzing the power supply data information of the target area, specifically: Acquire power supply data information of a target area, set a power supply data threshold, and determine whether the power supply data information of the target area is greater than the power supply data threshold; When the power supply data information of the target area is greater than the power supply data threshold, a state signal that meets the power supply demand is generated, and a power supply state analysis result is generated according to the state signal that meets the power supply demand; When the power supply data information of the target area is not greater than the power supply data threshold, a status signal indicating that the power supply demand is not met is generated, and a power supply status analysis result is generated according to the status signal indicating that the power supply demand is not met.

3. The method for controlling the parallel operation and capacity increase of multiple high-voltage variable-frequency power supplies according to claim 1, characterized in that: Acquiring historical capacity change characteristic data of the high-voltage variable-frequency power supply, and constructing a capacity characteristic prediction model of the high-voltage variable-frequency power supply based on the historical capacity change characteristic data of the high-voltage variable-frequency power supply, specifically including: Acquire historical capacity change characteristic data of the high-voltage variable-frequency power supply through big data, construct a characteristic matrix based on the historical capacity change characteristic data of the high-voltage variable-frequency power supply, and construct a capacity characteristic prediction model of the high-voltage variable-frequency power supply based on a neural network; Inputting the feature matrix into the capacity feature prediction model of the high-voltage variable-frequency power supply for training, and processing the feature matrix through an attention mechanism to focus on the capacity feature data; When the model parameters of the capacity characteristic prediction model of the high-voltage variable frequency power supply meet the preset requirements, the model parameters of the capacity characteristic prediction model of the high-voltage variable frequency power supply are saved, and the capacity characteristic prediction model of the high-voltage variable frequency power supply is output.

4. The method for controlling the parallel operation and capacity increase of multiple high-voltage variable-frequency power supplies according to claim 1, characterized in that: Predicting the capacity characteristic data of each high-voltage variable-frequency power supply by using the capacity characteristic prediction model of the high-voltage variable-frequency power supply specifically includes: Acquire capacity characteristic data of the high-voltage variable-frequency power supply within a preset time, and input the capacity characteristic data of the high-voltage variable-frequency power supply within the preset time into a capacity characteristic prediction model of the high-voltage variable-frequency power supply for prediction; By prediction, the capacity characteristic data of each high-voltage variable-frequency power supply within the next preset time is obtained, and the capacity characteristic data of each high-voltage variable-frequency power supply within the next preset time is output.

5. The method for controlling parallel operation and capacity increase of multiple high-voltage variable-frequency power supplies according to claim 1, characterized in that: According to the capacity characteristic data of each high-voltage variable-frequency power supply, a high-voltage variable-frequency power supply that meets the requirements is obtained, specifically: Setting a capacity characteristic threshold of the high-voltage variable-frequency power supply, and determining whether the capacity characteristic data of each high-voltage variable-frequency power supply is greater than the capacity characteristic threshold of the high-voltage variable-frequency power supply; When the capacity characteristic data is greater than the capacity characteristic threshold of the high-voltage variable-frequency power supply, the high-voltage variable-frequency power supply corresponding to the capacity characteristic data greater than the capacity characteristic threshold of the high-voltage variable-frequency power supply is regarded as a high-voltage variable-frequency power supply that meets the requirements; When the capacity characteristic data is not greater than the capacity characteristic threshold of the high-voltage variable frequency power supply, the high-voltage variable frequency power supply corresponding to the capacity characteristic threshold of the high-voltage variable frequency power supply whose capacity characteristic data is not greater than the capacity characteristic threshold of the high-voltage variable frequency power supply is regarded as a high-voltage variable frequency power supply that does not meet the requirements.

6. The method for controlling parallel connection and capacity increase of multiple high-voltage variable-frequency power supplies according to claim 1, characterized in that: Obtain the geographical location information of the high-voltage variable frequency power supply that meets the requirements, and obtain the optimal parallel capacity increase and power storage combination according to the location information of the power supply in the target area and the geographical location information of the high-voltage variable frequency power supply that meets the requirements, specifically: Obtain the geographical location information of the high-voltage variable-frequency power supply that meets the requirements, and obtain the grid layout information in the target area and the geographical location of the power supply energy; Calculate the transmission distance information of the power supply line based on the geographical location information of the high-voltage variable frequency power supply that meets the requirements, the power grid layout information in the target area, and the geographical location of the power supply energy source; Obtaining estimated loss information for each transmission distance through big data, and calculating power supply loss information based on the transmission distance information of the power supply wire and the estimated loss information for each transmission distance; A particle swarm algorithm is introduced to calculate the optimal parallel-machine capacity-increasing power-storage combination according to the power supply loss information, and the optimal parallel-machine capacity-increasing power-storage combination is output.

7. The method for controlling parallel connection and capacity increase of multiple high-voltage variable-frequency power supplies according to claim 6, characterized in that: A particle swarm algorithm is introduced to calculate the optimal parallel-machine capacity-increasing power storage combination according to the power loss information, and output the optimal parallel-machine capacity-increasing power storage combination, specifically including: A particle swarm algorithm is introduced, the number of iterations is set based on the particle swarm algorithm, and an optimal parallel-machine capacity-increasing power storage combination is constructed, and a high-voltage variable-frequency power supply that meets the requirements is randomly selected from the optimal parallel-machine capacity-increasing power storage combination; Obtain estimated power loss information based on the high-voltage variable-frequency power supply that meets the requirements and the power loss information in the optimal parallel-machine capacity-increasing power storage combination, set power loss threshold data, and determine whether the power loss information is greater than the power loss threshold data; When the power loss information is not greater than the power loss threshold data, the optimal parallel capacity increase and power storage combination is output, and the parallel capacity increase and energy storage are performed according to the optimal parallel capacity increase and power storage combination; When the power supply loss information is greater than the power supply loss threshold data, the optimal parallel capacity increase and power storage combination is iterated based on the number of iterations, and a high-voltage variable frequency power supply that meets the requirements is reselected until it is no greater than the power supply loss threshold data.

8. A parallel capacity expansion control system for multiple high-voltage variable-frequency power supplies, characterized in that: The system includes a memory and a processor, wherein the memory includes a parallel capacity expansion control method program for multiple high-voltage variable-frequency power supplies, and when the parallel capacity expansion control method program for multiple high-voltage variable-frequency power supplies is executed by the processor, the steps of the parallel capacity expansion control method for multiple high-voltage variable-frequency power supplies as described in any one of claims 1 to 7 are implemented.

9. An electronic device, characterized in that: include: A power supply status analysis module is used to obtain power supply data information of a target area, and obtain a power supply status analysis result by identifying and analyzing the power supply data information of the target area; A capacity characteristic prediction module is used to obtain historical capacity change characteristic data of the high-voltage variable-frequency power supply, and to construct a capacity characteristic prediction model of the high-voltage variable-frequency power supply based on the historical capacity change characteristic data of the high-voltage variable-frequency power supply; A data analysis module, which predicts the capacity characteristic data of each high-voltage variable-frequency power supply through the capacity characteristic prediction model of the high-voltage variable-frequency power supply, obtains a high-voltage variable-frequency power supply that meets the requirements according to the capacity characteristic data of each high-voltage variable-frequency power supply, and obtains the location information of the power supply in the target area; The output module obtains the geographical location information of the high-voltage variable frequency power supply that meets the requirements, and obtains the optimal parallel capacity increase and power storage combination according to the location information of the power supply in the target area and the geographical location information of the high-voltage variable frequency power supply that meets the requirements.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a parallel capacity expansion control method program for multiple high-voltage variable-frequency power supplies. When the parallel capacity expansion control method program for multiple high-voltage variable-frequency power supplies is executed by a processor, the steps of the parallel capacity expansion control method for multiple high-voltage variable-frequency power supplies as described in any one of claims 1 to 7 are implemented.

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