Method and device for cooperatively regulating and controlling energy of multiple transformer areas of power distribution network based on soft switching

Abstract

The embodiment of the invention discloses a soft switching-based power distribution network multi-transformer-area energy coordinated regulation and control method and device. The method comprises the following steps: acquiring power distribution network information and historical regulation and control data corresponding to a power distribution network to be regulated and controlled; determining a power distribution network coordinated regulation model corresponding to the power distribution network to be regulated based on the power distribution network information; determining reference regulation and control data corresponding to the power distribution network to be regulated and controlled based on the historical regulation and control data and a pre-trained prediction network model; and based on the reference regulation and control data and the power distribution network coordinated regulation and control model, determining a target regulation and control strategy corresponding to the to-be-regulated and controlled power distribution network. Through the technical scheme of the embodiment of the invention, the target regulation and control strategy can be accurately and conveniently determined, so that the flow of active power and reactive power is accurately controlled, the operation cost is reduced, and the risks of short circuit and the like caused by frequent switching actions are avoided.

Description

Technical Field

[0001] The embodiments of the present invention relate to the technical field of energy coordinated regulation and control, and in particular to a method and device for coordinated regulation and control of multiple energy zones in a distribution network based on soft switches. Background Art

[0002] Traditional power dispatching methods focus more on meeting power demand and controlling power generation costs, but often ignore the impact of internal switch operations on line short circuits.

[0003] Short circuits in distribution networks can cause many challenges to the power system, such as regional power outages leading to economic impacts, production stagnation, and poor grid stability. Therefore, how to ensure the continuous and stable development of the power system and achieve environmental protection, economic benefits, and system stability under the premise of low carbon and low cost has become a technical problem that needs to be solved urgently. Summary of the invention

[0004] The embodiments of the present invention provide a method and device for coordinated energy control of multiple distribution areas in a distribution network based on soft switches, so as to accurately and conveniently determine the target control strategy, thereby precisely controlling the flow of active power and reactive power, reducing operating costs, and avoiding the risk of short circuits caused by frequent switching actions.

[0005] In a first aspect, an embodiment of the present invention provides a method for coordinated energy control of multiple distribution areas in a distribution network based on soft switching, comprising:

[0006] Obtain the distribution network information and historical regulation data corresponding to the distribution network to be regulated;

[0007] Determine a distribution network collaborative control model corresponding to the distribution network to be controlled based on the distribution network information;

[0008] Determine reference control data corresponding to the distribution network to be controlled based on the historical control data and the pre-trained prediction network model;

[0009] Based on the reference control data and the distribution network collaborative control model, a target control strategy corresponding to the distribution network to be regulated is determined.

[0010] Optionally, the method also includes: the distribution network collaborative control model includes: a maximum operating cost control sub-model and a distribution system dynamic power supply recovery sub-model; the maximum operating cost control sub-model is used to control the maximum operating cost of each substation in the distribution network; the distribution system dynamic power supply recovery sub-model is used to generate a sequential action strategy for switching lines using soft switches.

[0011] Optionally, the method further includes: the maximum operating cost control sub-model takes the maximum total operating cost of the distribution network as an objective function; the objective function is expressed as the maximum value of the sum of the power loss cost and the switch action cost.

[0012] Optionally, the method further includes: the power loss cost is expressed as: Where T represents the total time period; b represents the total number of all lines; N represents the total number of distribution network nodes; R ij is the resistance value of branch ij; P ij,t and Q ij,t They represent the active power and reactive power flowing through branch ij in period t respectively; U i , t is the voltage amplitude of node i in period t; C L and C sop They represent network loss costs and soft switch operating costs respectively.

[0013] Optionally, the method further includes: the switching action cost is expressed as: Among them, B is the total number of switches, C S The cost of one switch operation; ij,t Indicates the on / off state of the switch on line ij during period t.

[0014] Optionally, the method further includes: the constraint conditions of the objective function include node power constraint conditions, operation safety constraint conditions and switching number constraint conditions.

[0015] Optionally, the method further includes: the node power constraint condition is expressed as: Where ψ(i) represents the set of end nodes of the node branch starting with node i; δ(i) represents the set of beginning nodes of the node branch ending with node i; R ki , X ki Respectively represent the resistance and reactance of feeder ki; I ki,t represents the current value flowing through feeder ki at time t; P i,t , Q i,t They represent the active power and reactive power injected into node i at time t respectively.

[0016] In a second aspect, an embodiment of the present invention further provides a distribution network multi-zone energy coordinated control device based on soft switches, the device comprising:

[0017] An information acquisition module is used to obtain distribution network information and historical control data corresponding to the distribution network to be regulated;

[0018] A model determination module, used to determine a distribution network collaborative control model corresponding to the distribution network to be controlled based on the distribution network information;

[0019] A reference control data determination module, used to determine reference control data corresponding to the distribution network to be regulated based on the historical control data and a pre-trained prediction network model;

[0020] The target control strategy determination module is used to determine the target control strategy corresponding to the distribution network to be regulated based on the reference control data and the distribution network collaborative control model.

[0021] In a third aspect, an embodiment of the present invention further provides an electronic device, the electronic device comprising:

[0022] one or more processors;

[0023] A memory for storing one or more programs;

[0024] When the one or more programs are executed by the one or more processors, the one or more processors implement the method for coordinated energy control of multiple distribution areas in a distribution network based on soft switches as provided in any embodiment of the present invention.

[0025] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements a method for coordinated energy control of multiple distribution network areas based on soft switches as provided in any embodiment of the present invention.

[0026] In a fifth aspect, an embodiment of the present invention provides a computer program product, including a computer program, which, when executed by a processor, implements a method for coordinated energy control of multiple distribution areas in a distribution network based on soft switches as provided in any embodiment of the present invention.

[0027] The technical solution of the embodiment of the present invention obtains the distribution network information and historical control data corresponding to the distribution network to be regulated; determines the distribution network collaborative control model corresponding to the distribution network to be regulated based on the distribution network information; determines the reference control data corresponding to the distribution network to be regulated based on the historical control data and the pre-trained prediction network model; determines the target control strategy corresponding to the distribution network to be regulated based on the reference control data and the distribution network collaborative control model, so as to accurately control the flow of active power and reactive power, reduce operating costs, and avoid the risk of short circuit caused by frequent switching actions. In addition, the load transfer capacity of the soft switch is brought into play by regulating the distribution network to be regulated through the soft switch, and the power supply of the substation is mutually regulated to re-energize the affected area, thereby improving the recovery capacity of the power system, and effectively preventing short circuit phenomena according to the soft switch cost data, thereby improving the user's power experience.

[0028] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0030] Figure 1 It is a flow chart of a method for coordinated energy control of multiple distribution areas in a distribution network based on soft switches provided in the first embodiment of the present invention;

[0031] Figure 2 This is a schematic diagram of recording data of an SOP active power time period involved in the first embodiment of the present invention;

[0032] Figure 3 This is a schematic diagram of recording data of a SOP reactive power time period involved in the first embodiment of the present invention;

[0033] Figure 4 It is a structural schematic diagram of a distribution network multi-zone energy coordinated control device based on soft switches provided in the second embodiment of the present invention;

[0034] Figure 5 It is a structural schematic diagram of an electronic device for implementing the method for coordinated energy control of multiple areas in a distribution network based on soft switches according to an embodiment of the present invention. DETAILED DESCRIPTION

[0035] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0036] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0037] Embodiment 1

[0038] Figure 1 A flowchart of a method for coordinated energy control of multiple distribution areas in a distribution network based on soft switches is provided for the first embodiment of the present invention. This embodiment is applicable to the case of determining a target control strategy. The method can be executed by a device for coordinated energy control of multiple distribution areas in a distribution network based on soft switches. The device for coordinated energy control of multiple distribution areas in a distribution network based on soft switches can be implemented in the form of hardware and / or software. The device for coordinated energy control of multiple distribution areas in a distribution network based on soft switches can be configured in an electronic device. Figure 1 As shown, the method includes:

[0039] S110. Obtain distribution network information and historical regulation data corresponding to the distribution network to be regulated.

[0040] Among them, the distribution network to be regulated may refer to a distribution network that needs to be regulated. The distribution network includes multiple substations. In the power system, the substation may refer to the power supply range or area of ​​a transformer. Distribution network information may refer to information containing the distribution network collaborative system architecture. For example, distribution network information may include but is not limited to a distribution network line topology, the total number of all distribution network lines, the total number of distribution network nodes, the resistance value of each branch, and the total number of soft switches (soft open point, SOP). The distribution network line topology may include line topology, node topology, and soft switch topology. Historical control data may refer to control data obtained based on historical control strategy control. For example, historical control data may include but is not limited to active power and reactive power flowing through the branch during the historical period, voltage amplitude of the node during the historical period, network loss cost during the historical period, soft switch operation cost during the historical period, and the disconnection state of the switch on the line during the historical period.

[0041] Specifically, the control center can obtain the distribution network information corresponding to the distribution network to be regulated according to the soft switch installed in the distribution network, and obtain the recorded historical regulation data. The soft switch can control at least one substation.

[0042] S120. Determine a distribution network collaborative control model corresponding to the distribution network to be controlled based on the distribution network information.

[0043] Among them, the distribution network coordinated control model can be used to control the maximum operating cost of each substation in the distribution network and generate a sequential action strategy for switching lines using soft switches.

[0044] Based on the above technical scheme, the distribution network coordinated control model includes: a maximum operating cost control sub-model and a distribution system dynamic power supply recovery sub-model; the maximum operating cost control sub-model is used to control the maximum operating cost of each substation in the distribution network; the distribution system dynamic power supply recovery sub-model is used to generate a sequential action strategy for switching lines using soft switches.

[0045] Specifically, a maximum operating cost regulation submodel of the intelligent soft switch is constructed based on the distribution network information to determine the soft switch control mode. The soft switch control mode is regulated according to the maximum operating cost. Cost regulation may include but is not limited to factors such as power calculation and electricity price. When the maximum operating cost of a substation exceeds a preset threshold, the soft switch is controlled to disconnect to prevent economic damage or short circuit in the distribution network. A dynamic power supply recovery submodel of the distribution system is established based on the distribution network information, and a sequential action strategy that can be used to switch lines using soft switches is generated. When the soft switch control mode is used to shut down the substation, it can be shut down at intervals, and the sequential action strategy may include starting gradually from the minimum power received by the soft switch to prevent short circuits in the distribution network, effectively protect the entire device, and prevent large-scale power outages.

[0046] On the basis of the above technical solution, the maximum operating cost control sub-model takes the maximum total operating cost of the distribution network as the objective function; the objective function is expressed as the maximum value of the sum of the power loss cost and the switch action cost.

[0047] Among them, the maximum total operating cost is taken as the objective function. The total operating cost of the distribution network consists of two parts: power loss cost and switch action cost, which is expressed as max(W L +W S ), where W L represents the power loss cost, W S Represents the switching operation cost.

[0048] Based on the above technical solution, the power loss cost is expressed as: Where T represents the total time period; b represents the total number of all lines; N represents the total number of distribution network nodes; R ij is the resistance value of branch ij; P ij,t and Q ij,t They represent the active power and reactive power flowing through branch ij in period t respectively; U i, t is the voltage amplitude of node i in period t; C L and C sop They represent network loss costs and soft switch operating costs respectively.

[0049] Among them, the power loss cost W S Including network loss cost and soft switching power transmission loss cost, the total power loss cost is expressed as Where T represents the total time period; b represents the total number of all lines; N represents the total number of distribution network nodes; R ij is the resistance value of branch ij; P ij,t and Q ij,t They represent the active power and reactive power flowing through branch ij in period t respectively; U i , t is the voltage amplitude of node i in period t; C L and C sop They represent network loss costs and soft switch operating costs respectively.

[0050] Based on the above technical solution, the switching action cost is expressed as: Among them, B is the total number of switches, C S The cost of one switch operation; ij,t Indicates the on / off state of the switch on line ij during period t.

[0051] Among them, the switching cost W S Expressed as B is the total number of switches, C S The cost of one switch operation; ij,t represents the on / off state of the switch on line ij during period t, a ij,t =1, indicating the switch is closed, a ij,t =0, indicating the switch is off.

[0052] S130. Determine reference control data corresponding to the distribution network to be controlled based on historical control data and a pre-trained prediction network model.

[0053] The prediction network model can predict future data based on historical data. The reference control data can refer to control data in a period when the event did not occur.

[0054] Specifically, the historical control data is input into a pre-trained prediction network model for data prediction, and the reference control data corresponding to the distribution network to be regulated is determined based on the output of the prediction network model. If there are multiple types of historical control data, the historical control data of each type can be combined into a data matrix, and the historical control data matrix is ​​input into the prediction network model to determine the reference control data corresponding to the distribution network to be regulated. Alternatively, there is a prediction sub-model for each data type in the prediction network model. When the historical control data is input into the prediction network model, the data category is first determined, and the prediction sub-model to be input is determined based on the determined data type, so as to determine the reference control data corresponding to the historical control data of this type based on the output of the prediction sub-model.

[0055] For example, take the soft switch cost data as an example. Set up edge nodes, set up intelligent terminal collection devices at the lower layer of the edge nodes, monitor and collect soft switch cost data (equivalent to historical control data) through the intelligent terminal collection devices, and pre-process the soft switch cost data. The pre-processing may include parsing and storing the soft switch cost data, and using a fully connected convolutional neural network (equivalent to a pre-trained prediction network model) to perform preliminary calculations on the parsed soft switch cost data. The fully connected convolutional neural network is:

[0056]

[0057] Where b is the deviation, Z l represents the convolution input of the lth layer, Z l+1 represents the convolution output of the l+1th layer, L is the batch size of Z, K is the total number of convolution input and output times in the edge node, k is the number of channels of total convolution input and output, i is the equipment monitoring data of one channel, j is the soft switching cost data of one channel, ω is the correction constant, and T is the time coefficient.

[0058] Specifically, the soft switching cost data is input into a fully connected convolutional neural network, and a preliminary calculation result (equivalent to the reference control data) is obtained based on the output of the next layer of the fully connected convolutional neural network.

[0059] Exemplarily, the intelligent terminal acquisition device uploads the preliminary calculation results to the upper layer of the edge node, and the edge node returns the preliminary calculation results and soft switch cost data to the control center.

[0060] The preliminary calculation results are output by the fully connected convolutional neural network and uploaded to the upper edge nodes in the form of messages through optical fiber, 5G and other communication technologies. The edge nodes return the calculation results to the control center. The control center can refer to the preliminary calculation results of the edge nodes.

[0061] Exemplarily, the training process of the fully connected convolutional neural network includes: training on both prediction efficiency and prediction accuracy.

[0062] Among them, the training for prediction efficiency mainly includes: the user analyzes the algorithm used in the preliminary calculation results according to the time complexity and space complexity of the algorithm to determine whether the algorithm meets the preset time complexity and preset space complexity. If at least one indicator is not met, the algorithm is improved until all indicators are met, and an algorithm that meets the calculation requirements of the distribution network coordinated control model is obtained.

[0063] The training for prediction accuracy mainly includes: the soft switch cost data is the power transmission loss cost data collected and pre-processed by the soft switch, and the preliminary calculation result is the result of the preliminary calculation of the soft switch cost data by the control center. If it is detected that the soft switch power transmission loss cost data is greater than the proportional preliminary calculation value, indicating that the preliminary calculation result is unreasonable, the soft switch disconnection process is carried out in time, and the algorithm is adjusted manually.

[0064] Among them, the proportion is obtained by weighting the number of times all soft switches are opened (equivalent to disconnection) and closed (equivalent to closure). The first weighting coefficient is obtained by weighting the number of times the opening is performed according to the first weight, and the second weighting coefficient is obtained by weighting the number of times the closing is performed according to the second weight. The first weight must be greater than the second weight. It can be understood that the first weight is a preset ratio value, such as 7 / 10. The second weight is a preset ratio value, such as 3 / 10. The first weighting coefficient is the product of the value of the number of openings and the value of the first weight. For example, when the number of openings is 20 and the number of closings is 10, the first weight is 7 / 10 and the second weight is 3 / 10, so that the first weighting coefficient is 20×7 / 10=14 and the second weighting coefficient is 10×3 / 10=3.

[0065] S140. Determine a target control strategy corresponding to the distribution network to be controlled based on the reference control data and the distribution network coordinated control model.

[0066] The target control strategy may refer to an effective control strategy that meets the control requirements of the distribution network to be regulated.

[0067] Specifically, the reference control data is input into the distribution network collaborative control model, and the target control strategy corresponding to the distribution network to be controlled is determined based on the output of the distribution network collaborative control model.

[0068] On the basis of the above technical solution, the constraints of the objective function include: node power constraints, operation safety constraints and switching times constraints.

[0069] The node power constraint condition may refer to a constraint condition for node power control. The operation safety constraint condition may refer to a constraint condition for ensuring safe operation of the distribution network. The switching times constraint condition may refer to a constraint condition for limiting the number of soft switch switching times.

[0070] Based on the above technical solution, the node power constraint condition is expressed as: Where ψ(i) represents the set of end nodes of the node branch starting with node i; δ(i) represents the set of beginning nodes of the node branch ending with node i; R ki , X ki Respectively represent the resistance and reactance of feeder ki; I ki,t represents the current value flowing through feeder ki at time t; P i,t , Q i,t They represent the active power and reactive power injected into node i at time t respectively.

[0071] At the same time, in order to ensure the safety of the power grid, further operational safety constraints and switch action times constraints are implemented. Multiple constraints greatly reduce the occurrence of short circuits in the distribution network.

[0072] The operational safety constraints are: in, represents the upper limit of the current of branch ij. The switching times constraint is Among them, N SB 、N B They are the maximum allowable total number of switch operations within the optimization period and the maximum allowable number of operations for a single switch.

[0073] Specifically, under the multiple constraints of node power constraints, operation safety constraints and switching number constraints, the soft switch operation cost is adjusted to solve the objective function, and multiple candidate solutions are obtained. The target solution is determined from the candidate solutions based on the control requirements, thereby obtaining the target control strategy corresponding to the distribution network to be regulated.

[0074] Exemplarily, "determining the target control strategy corresponding to the distribution network to be regulated based on the reference control data and the coordinated control model of the distribution network" may include: determining the control strategy to be selected and the power data corresponding to the control strategy to be selected based on the reference control data and the coordinated control model of the distribution network; determining the target control strategy corresponding to the distribution network to be regulated based on the control requirements for the distribution network to be regulated and the power data corresponding to the control strategy to be selected.

[0075] The power data may refer to the power data predicted for a future period, and may include active power time period data and reactive power time period data. Figure 2 A schematic diagram of SOP active power time period data recording is given. Figure 3A schematic diagram of SOP reactive power time period data recording is given. Figure 2 and Figure 3 Among the three schemes of SOP22, the reactive power corresponding to SOP22-Scheme 3 is higher than the reactive power corresponding to SOP22-Scheme 1 and SOP22-Scheme 2 at all time points. Among the three schemes of SOP22, the active power corresponding to SOP22-Scheme 3 is higher than the active power corresponding to SOP22-Scheme 1 and SOP22-Scheme 2 at most time points. If the control demand for the distribution network to be regulated is that reactive control takes precedence over active control, and the distribution network is relatively stable, the candidate control strategy corresponding to SOP22-Scheme 3 can be selected as the target control strategy corresponding to the distribution network to be regulated.

[0076] It should be noted that the flexible interconnection technology based on soft switching significantly enhances the controllability and flexibility of system operation. Compared with traditional switch operation, SOP can accurately control the flow of active power and reactive power, reduce operating costs, and avoid the risk of short circuit caused by frequent switching actions. SOP can achieve flexible connection between feeders. The application of SOP will significantly promote the economy, flexibility and reliability of active distribution networks.

[0077] The technical solution of the embodiment of the present invention obtains the distribution network information and historical control data corresponding to the distribution network to be regulated; determines the distribution network collaborative control model corresponding to the distribution network to be regulated based on the distribution network information; determines the reference control data corresponding to the distribution network to be regulated based on the historical control data and the pre-trained prediction network model; determines the target control strategy corresponding to the distribution network to be regulated based on the reference control data and the distribution network collaborative control model, so as to accurately control the flow of active power and reactive power, reduce operating costs, and avoid the risk of short circuit caused by frequent switching actions. In addition, the load transfer capacity of the soft switch is brought into play by regulating the distribution network to be regulated through the soft switch, and the power supply of the substation is mutually regulated to re-energize the affected area, thereby improving the recovery capacity of the power system, and effectively preventing short circuit phenomena according to the soft switch cost data, thereby improving the user's power experience.

[0078] It should be noted that the technical solution of the embodiment of the present invention predicts the maximum and minimum output values ​​of the substation based on historical switching data (equivalent to historical control data), and combines the energy regulation rate and energy regulation participation to determine the adjustable energy space for each substation. It provides a flexible adjustment range for subsequent energy correction and scheduling, making energy scheduling more accurate and efficient, and uses soft switches to control the energy space to correct it, thereby obtaining an optimized energy switching sequence (equivalent to the target control strategy), achieving coordinated optimization between soft switches and electric energy, and improving overall energy utilization efficiency. It effectively ensures the stable operation of the power system. When the power system faces emergencies, such as a sudden increase in load or equipment failure, the output plan can be adjusted quickly to ensure continuous power supply and stable operation of the power system.

[0079] The following is an embodiment of a device for coordinated energy control of multiple distribution areas in a distribution network based on soft switches provided in an embodiment of the present invention. The device and the coordinated energy control methods of multiple distribution areas in a distribution network based on soft switches in the above-mentioned embodiments belong to the same inventive concept. For details not fully described in the embodiment of the device for coordinated energy control of multiple distribution areas in a distribution network based on soft switches, reference can be made to the embodiment of the method for coordinated energy control of multiple distribution areas in a distribution network based on soft switches.

[0080] Embodiment 2

[0081] Figure 4 The schematic diagram of the structure of a multi-zone energy coordinated control device for a distribution network based on soft switches provided in the second embodiment of the present invention. Figure 4 As shown, the device includes: an information acquisition module 410, a model determination module 420, a reference control data determination module 430 and a target control strategy determination module 440.

[0082] Among them, the information acquisition module 410 is used to obtain the distribution network information and historical control data corresponding to the distribution network to be regulated; the model determination module 420 is used to determine the distribution network collaborative control model corresponding to the distribution network to be regulated based on the distribution network information; the reference control data determination module 430 is used to determine the reference control data corresponding to the distribution network to be regulated based on the historical control data and a pre-trained prediction network model; the target control strategy determination module 440 is used to determine the target control strategy corresponding to the distribution network to be regulated based on the reference control data and the distribution network collaborative control model.

[0083] The technical solution of the embodiment of the present invention obtains the distribution network information and historical control data corresponding to the distribution network to be regulated; determines the distribution network collaborative control model corresponding to the distribution network to be regulated based on the distribution network information; determines the reference control data corresponding to the distribution network to be regulated based on the historical control data and the pre-trained prediction network model; determines the target control strategy corresponding to the distribution network to be regulated based on the reference control data and the distribution network collaborative control model, so as to accurately control the flow of active power and reactive power, reduce operating costs, and avoid the risk of short circuit caused by frequent switching actions. In addition, the load transfer capacity of the soft switch is brought into play by regulating the distribution network to be regulated through the soft switch, and the power supply of the substation is mutually regulated to re-energize the affected area, thereby improving the recovery capacity of the power system, and effectively preventing short circuit phenomena according to the soft switch cost data, thereby improving the user's power experience.

[0084] Based on the above technical scheme, the distribution network coordinated control model includes: a maximum operating cost control sub-model and a distribution system dynamic power supply recovery sub-model; the maximum operating cost control sub-model is used to control the maximum operating cost of each substation in the distribution network; the distribution system dynamic power supply recovery sub-model is used to generate a sequential action strategy for switching lines using soft switches.

[0085] On the basis of the above technical solution, the maximum operating cost control sub-model takes the maximum total operating cost of the distribution network as the objective function; the objective function is expressed as the maximum value of the sum of the power loss cost and the switch action cost.

[0086] Based on the above technical solution, the power loss cost is expressed as: Where T represents the total time period; b represents the total number of all lines; N represents the total number of distribution network nodes; R ij is the resistance value of branch ij; P ij,t and Q ij,t They represent the active power and reactive power flowing through branch ij in period t respectively; U i , t is the voltage amplitude of node i in period t; C L and C sop They represent network loss costs and soft switch operating costs respectively.

[0087] Based on the above technical solution, the switching action cost is expressed as: Among them, B is the total number of switches, C S The cost of one switch operation; ij,t Indicates the on / off state of the switch on line ij during period t.

[0088] On the basis of the above technical solution, the constraints of the objective function include: node power constraints, operation safety constraints and switching times constraints.

[0089] Based on the above technical solution, the node power constraint condition is expressed as: Where ψ(i) represents the set of end nodes of the node branch starting with node i; δ(i) represents the set of beginning nodes of the node branch ending with node i; R ki , X ki Respectively represent the resistance and reactance of feeder ki; I ki,t represents the current value flowing through feeder ki at time t; P i,t , Q i,t They represent the active power and reactive power injected into node i at time t respectively.

[0090] The device for coordinated energy control of multiple distribution areas in a distribution network based on soft switches provided in an embodiment of the present invention can execute the method for coordinated energy control of multiple distribution areas in a distribution network based on soft switches provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects for executing the method for coordinated energy control of multiple distribution areas in a distribution network based on soft switches.

[0091] It is worth noting that in the above-mentioned embodiment of coordinated energy control of multiple distribution areas in the distribution network based on soft switches, the various units and modules included are only divided according to functional logic, but are not limited to the above-mentioned division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of the present invention.

[0092] Embodiment 3

[0093] Figure 5 A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0094] like Figure 5As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0095] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0096] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The processor 11 executes the various methods and processes described above, such as a method for coordinated energy control of multiple distribution areas in a distribution network based on soft switching.

[0097] In some embodiments, the method for coordinated energy regulation of multiple distribution areas in a distribution network based on soft switches can be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the method for coordinated energy regulation of multiple distribution areas in a distribution network based on soft switches described above can be executed. Alternatively, in other embodiments, the processor 11 can be configured to execute the method for coordinated energy regulation of multiple distribution areas in a distribution network based on soft switches in any other appropriate manner (for example, by means of firmware).

[0098] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0099] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0100] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0101] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0102] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0103] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0104] An embodiment of the present invention also provides a computer program product, including a computer program, which, when executed by a processor, implements the method for coordinated energy control of multiple distribution areas in a distribution network based on soft switches as provided in any embodiment of the present application.

[0105] In the process of implementation, the computer program product can be written in one or more programming languages ​​or a combination thereof to perform the computer program code of the present invention, and the programming language includes an object-oriented programming language, such as Java, Smalltalk, C++, and also includes a conventional procedural programming language, such as "C" language or similar programming language. The program code can be executed completely on the user's computer, partially on the user's computer, as an independent software package, partially on the user's computer and partially on the remote computer, or completely on the remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (for example, using an Internet service provider to connect through the Internet). The program product and the method for coordinated energy control of multiple distribution network areas based on soft switches disclosed in each embodiment of the present application belong to the same inventive concept, so it will not be repeated here.

[0106] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0107] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for coordinated energy control of multiple distribution areas in a distribution network based on soft switching, characterized in that: include: Obtain the distribution network information and historical regulation data corresponding to the distribution network to be regulated; Determine a distribution network collaborative control model corresponding to the distribution network to be controlled based on the distribution network information; Determine reference control data corresponding to the distribution network to be controlled based on the historical control data and the pre-trained prediction network model; Based on the reference control data and the distribution network collaborative control model, a target control strategy corresponding to the distribution network to be regulated is determined.

2. The method according to claim 1, characterized in that: The distribution network coordinated control model includes: a maximum operation cost control sub-model and a distribution system dynamic power supply recovery sub-model; The maximum operating cost control sub-model is used to control the maximum operating cost of each substation in the distribution network; The distribution system dynamic power supply restoration sub-model is used to generate a sequential action strategy for switching lines using soft switches.

3. The method according to claim 2, characterized in that The maximum operating cost control sub-model takes the maximum total operating cost of the distribution network as the objective function; The objective function is expressed as the maximum value of the sum of power loss cost and switching action cost.

4. The method according to claim 3, characterized in that The power loss cost is expressed as: Where T represents the total time period; b represents the total number of all lines; N represents the total number of distribution network nodes; R ij is the resistance value of branch ij; P ij,t and Q ij,t They represent the active power and reactive power flowing through branch ij in period t respectively; U i , t is the voltage amplitude of node i in period t; C L and C sop They represent network loss costs and soft switch operating costs respectively.

5. The method according to claim 3, characterized in that: The switching action cost is expressed as: Among them, B is the total number of switches, C S The cost of one switch operation; ij,t Indicates the on / off state of the switch on line ij during period t.

6. The method according to claim 3, characterized in that: The constraint conditions of the objective function include: node power constraint conditions, operation safety constraint conditions and switching number constraint conditions.

7. The method according to claim 6, characterized in that The node power constraint condition is expressed as: Where ψ(i) represents the set of end nodes of the node branch starting with node i; δ(i) represents the set of beginning nodes of the node branch ending with node i; R ki , X ki Respectively represent the resistance and reactance of feeder ki; I ki,t represents the current value flowing through feeder ki at time t; P i,t , Q i,t They represent the active power and reactive power injected into node i at time t respectively.

8. A distribution network multi-zone energy coordinated control device based on soft switching, characterized in that: The device comprises: An information acquisition module is used to obtain distribution network information and historical control data corresponding to the distribution network to be regulated; A model determination module, used to determine a distribution network collaborative control model corresponding to the distribution network to be controlled based on the distribution network information; A reference control data determination module, used to determine reference control data corresponding to the distribution network to be regulated based on the historical control data and a pre-trained prediction network model; The target control strategy determination module is used to determine the target control strategy corresponding to the distribution network to be regulated based on the reference control data and the distribution network collaborative control model.

9. An electronic device, characterized in that: The electronic device comprises: one or more processors; A memory for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the method for coordinated energy control of multiple distribution areas in a distribution network based on soft switches as described in any one of claims 1-7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method for coordinated energy control of multiple distribution areas in a distribution network based on soft switches as described in any one of claims 1 to 7 is implemented.

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