Distributed communication resource allocation and voltage coordinated regulation and control method and device

Abstract

The invention discloses a distributed communication resource allocation and voltage coordinated regulation and control method and device, and belongs to the technical field of power system operation optimization. The method comprises the following steps: constructing a wireless network control system based on a 5G local area network for a novel power system; determining a wireless transmission model of the wireless network control system and a dynamical model of voltage control; determining a cross-domain dependency coupling relationship between wireless communication of the wireless network control system and the performance of the control system based on the wireless transmission model and the dynamical model of voltage control; determining a cross-domain optimization problem based on the cross-domain dependency coupling relationship; and solving the cross-domain optimization problem by using a primal dual graph neural network algorithm to obtain an optimal voltage control and communication power distribution strategy.

Description

Technical Field

[0001] The present application belongs to the technical field of power system operation optimization, and in particular, relates to a distributed communication resource allocation and voltage coordinated control method and device. Background Art

[0002] With the increase in the penetration rate of renewable energy in the distribution network of the new power system, the active and reactive power injected by the distributed generator (DG) into the main grid often changes. The traditional centralized structure voltage control obtains the global information of DG through the central computing and communication unit. Under the characteristics of the distribution network terminal points, the control information interaction failure caused by communication packet loss can easily lead to undesirable control decisions. 5G network can play its advantages of ultra-high bandwidth and low latency. However, it is difficult to achieve better overall performance of multi-loop wireless network control system only through power management. There is still a problem of insufficient business collaboration, which cannot effectively meet the above distribution network control business needs. Summary of the invention

[0003] The present application aims to solve at least one of the technical problems existing in the related art. To this end, the present application proposes a distributed communication resource allocation and voltage coordinated control method and device, which realizes distributed communication resource allocation and voltage coordinated control.

[0004] In a first aspect, the present application provides a distributed communication resource allocation and voltage coordinated control method, the method comprising: For new power systems, build a wireless network control system based on 5G local area network; Determining a wireless transmission model and a dynamic model of voltage control of the wireless network control system; Based on the wireless transmission model and the dynamic model of voltage control, determining the cross-domain dependent coupling relationship between wireless communication and control system performance of the wireless network control system; Based on the cross-domain dependency coupling relationship, determining a cross-domain optimization problem; The cross-domain optimization problem is solved using the primal-dual graph neural network algorithm to obtain the optimal voltage control and communication power allocation strategy.

[0005] In the above technical scheme, for the new power system, a wireless network control system based on 5G local area network is constructed, the wireless transmission model of the wireless network control system and the dynamic model of voltage control are determined, and then based on the wireless transmission model and the dynamic model of voltage control, the dependency coupling relationship between the control domain and the communication domain is determined. Based on the cross-domain dependency coupling relationship, the cross-domain optimization problem is determined, and the original dual graph neural network algorithm is used to solve the cross-domain optimization problem to obtain the optimal voltage control and communication power allocation strategy, realizing distributed communication resource allocation and coordinated control of voltage, which can ensure that the voltage control system of the variable new energy distribution network has ideal dynamic and steady-state response characteristics and meets the business communication network requirements.

[0006] According to one embodiment of the present application, for the new power system, a wireless network control system based on a 5G local area network is constructed, including: The distributed controller is connected to multiple distribution network nodes of the new power system through the 5G local area network to realize distributed communication and control, and dynamically adjust the voltage control and communication power allocation strategy in each control cycle to cope with voltage fluctuations and load changes in the distribution network.

[0007] In the above technical solution, the distributed controller is connected to multiple distribution network nodes of the new power system through the 5G local area network, realizing distributed communication and control. The voltage control strategy and communication power allocation strategy can be dynamically adjusted in each control cycle, which can effectively cope with voltage fluctuations and load changes in the distribution network, and improve the control performance and communication performance of the new power system.

[0008] According to one embodiment of the present application, the connecting of the distributed controller to multiple distribution network nodes of the novel power system through a 5G local area network includes: Determining a plurality of control areas according to a distribution network topology structure corresponding to the novel power system; Wireless bearer is realized between different control areas through network nodes; In each control area, the network node covers at least one distributed energy node, and the distributed energy node includes: a new energy generation node or a common distributed generation node. The common distributed generation node serves as the distribution network node and is sensed by the associated new energy generation node. The common distributed generation node and the associated new energy generation node communicate through an end-to-end link in the control area to which they belong; The state information of the common distributed power generation node is transmitted to the new energy power generation node through the end-to-end link to form an uplink state perception of the control loop. The new energy power generation node acts as the distributed controller to aggregate the uplink state information through the end-to-end link, determine the reactive power injection ratio value, and execute the downlink voltage control command; The network node performs power allocation for end-to-end links within a control area covered by the network node, and transmits a power allocation instruction to the new energy power generation node.

[0009] In the above technical scheme, the status information of the ordinary distributed power generation node is transmitted to the new energy power generation node through the end-to-end link to form the uplink status perception of the control loop. The new energy power generation node, as a distributed controller, aggregates the uplink status information through the end-to-end link, determines the reactive power injection ratio, and executes the downlink voltage control command to realize voltage control. The network node allocates power for the end-to-end link within the covered control area, and transmits the power allocation instruction to the new energy power generation node, so that the new energy power generation node can communicate with the ordinary distributed power generation node associated with it according to the allocated communication power, thereby realizing the conversion of the power system to the wireless network control system.

[0010] According to one embodiment of the present application, the mth new energy generation node associated with the adjacent ordinary distributed generation node is set as the mth distributed controller of the wireless network control system to form an mth control subsystem, and a plurality of the control subsystems form a closed feedback loop through the 5G local area network; The state of the m-th new energy generation node at a certain moment depends on its own measurement value and the measurement value obtained from its neighbors.

[0011] In the above technical solution, the mth new energy power generation node associated with the adjacent ordinary distributed power generation node is set as the mth distributed controller of the wireless network control system to form the mth control subsystem. A closed feedback loop is formed between the multiple control subsystems through the 5G local area network, and the sensor information and control command information are transmitted through the wireless medium, thereby realizing a wireless network voltage control system based on the 5G local area network, and further realizing the coordinated optimization between the control system and the communication system.

[0012] According to an embodiment of the present application, determining the cross-domain dependent coupling relationship between wireless communication and control system performance of the wireless network control system based on the wireless transmission model and the dynamic model of voltage control includes: Based on Lyapunov stability theory and the wireless transmission model, the stability and rapidity of the voltage-controlled dynamic model are analyzed to determine the exponential stability constraint and convergence rate constraint under the condition of an imperfect wireless link.

[0013] In the above technical scheme, based on Lyapunov stability theory and the wireless transmission model, the stability and rapidity of the dynamic model of the voltage control are analyzed, and the exponential stability constraints and convergence rate constraints under imperfect wireless link conditions are determined. The cross-domain dependency coupling relationship between wireless communication and control system performance is reflected by the exponential stability constraints and convergence rate constraints under imperfect wireless link conditions. Subsequently, the cross-domain optimization problem is determined based on the cross-domain dependency coupling relationship, which can ensure that the wireless network voltage control closed-loop system has ideal dynamic and steady-state response characteristics while meeting communication requirements.

[0014] According to an embodiment of the present application, determining the cross-domain optimization problem based on the cross-domain dependency coupling relationship includes: Determining an objective function, the objective function comprising: a first objective function for causing the corresponding voltage to converge to a desired range within a preset time period, and a second objective function for introducing penalties for voltage deviation and reactive power injection; Determining target constraints according to dynamic model rules, transient response requirements, exponential stability constraints and convergence rate constraints under the imperfect wireless link conditions, transmission power constraints, and packet loss rate constraints; The cross-domain optimization problem is determined according to the objective function and the objective constraint condition.

[0015] In the above technical problems, the optimization problem is overcome to make the corresponding voltage converge to the expected range within a preset time, and the penalty for voltage deviation and reactive power injection is introduced as the goal. The dynamic model rules, transient response requirements, exponential stability and convergence rate under imperfect wireless link conditions, transmission power, packet loss rate and other constraints are considered, and distributed communication resource allocation and coordinated control of voltage are realized, which can ensure that the voltage control system of the variable new energy distribution network has ideal dynamic and steady-state response characteristics and meets the needs of the business communication network.

[0016] According to an embodiment of the present application, the cross-domain optimization problem is solved by using the primal-dual graph neural network algorithm to obtain the optimal voltage control and communication power allocation strategy, including: Parameterizing the constraints in the cross-domain optimization problem to establish the constraints in the design of the graph neural network model to form a parameterized joint optimization problem; The parameterized joint optimization problem is expressed by a Lagrangian dual function that considers both the optimization objective and the constraints; Modeling the wireless network control system as a directed communication graph, and determining node characteristics and edge characteristics of the directed communication graph; The node features and edge features are input into the graph neural network model, and the Lagrangian dual function is used as the loss function. The graph neural network model is trained in combination with the original dual learning. After the training, the output of the graph neural network model is obtained to obtain the optimal voltage control and communication power allocation strategy.

[0017] In the above technical scheme, the constraints in the cross-domain optimization problem are parameterized so that the constraints are established in the design of the graph neural network model to form a parameterized joint optimization problem; the parameterized joint optimization problem is expressed by the Lagrangian dual function that simultaneously considers the optimization objectives and constraints, the wireless network control system is modeled as a directed communication graph, the node characteristics and edge characteristics of the directed communication graph are determined, and the graph neural network model is trained by inputting the node characteristics and edge characteristics into the graph neural network model, using the Lagrangian dual function as the loss function, and combining the original dual learning. After the training, the output of the graph neural network model is obtained to obtain the optimal voltage control and communication power allocation strategy, which can be used to design an information interaction transmission scheme for remote control under a high proportion of new energy access in the distribution network. The control system requirements and the limitations of spectrum and energy resources are taken into consideration to obtain the optimal voltage control strategy and communication resource allocation strategy, and the distributed communication resource allocation and voltage coordinated control are realized, which can improve the information exchange capability and control performance of the new power system.

[0018] In a second aspect, the present application provides a distributed communication resource allocation and voltage coordinated control device, the device comprising: System construction unit, used to build a wireless network control system based on 5G local area network for new power systems; A model determination unit, used to determine a wireless transmission model and a dynamic model of voltage control of the wireless network control system; A cross-domain dependency relationship determination unit, used to determine the cross-domain dependency coupling relationship between the wireless communication of the wireless network control system and the control system performance based on the wireless transmission model and the dynamic model of voltage control; An optimization problem determination unit, configured to determine a cross-domain optimization problem based on the cross-domain dependency coupling relationship; A solving unit is used to solve the cross-domain optimization problem using a primal-dual graph neural network algorithm to obtain an optimal voltage control and communication power allocation strategy.

[0019] In the above technical scheme, for the new power system, a wireless network control system based on 5G local area network is constructed, the wireless transmission model of the wireless network control system and the dynamic model of voltage control are determined, and then based on the wireless transmission model and the dynamic model of voltage control, the dependency coupling relationship between the control domain and the communication domain is determined. Based on the cross-domain dependency coupling relationship, the cross-domain optimization problem is determined, and the original dual graph neural network algorithm is used to solve the cross-domain optimization problem to obtain the optimal voltage control and communication power allocation strategy, realizing distributed communication resource allocation and coordinated control of voltage, which can ensure that the voltage control system of the variable new energy distribution network has ideal dynamic and steady-state response characteristics and meets the business communication network requirements.

[0020] In a third aspect, the present application provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the distributed communication resource allocation and voltage coordinated regulation method as described in the first aspect above is implemented.

[0021] In a fourth aspect, the present application provides a non-transitory computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the distributed communication resource allocation and voltage coordinated regulation method as described in the first aspect above is implemented.

[0022] In a fifth aspect, the present application provides a chip, comprising a processor and a communication interface, wherein the communication interface is coupled to the processor, and the processor is used to run programs or instructions to implement the distributed communication resource allocation and voltage coordinated control method as described in the first aspect.

[0023] In a sixth aspect, the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the distributed communication resource allocation and voltage coordinated regulation method as described in the first aspect above.

[0024] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the description of the embodiments in conjunction with the following drawings, in which: Figure 1 One of the flow charts of the distributed communication resource allocation and voltage coordinated control method provided in the embodiment of the present application; Figure 2 A schematic diagram of the architecture of a wireless network control system based on a 5G local area network provided in an embodiment of the present application; Figure 3 A schematic diagram of a process for solving the cross-domain optimization problem using a primal-dual graph neural network algorithm to obtain an optimal voltage control and communication power allocation strategy provided in an embodiment of the present application; Figure 4 A schematic diagram of the structure of a distributed communication resource allocation and voltage coordinated control device provided in an embodiment of the present application; Figure 5 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0026] The following will be combined with the drawings in the embodiments of the present application to clearly describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments in the present application belong to the scope of protection of this application.

[0027] The terms "first", "second", etc. in the specification and claims of the present application are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable under appropriate circumstances, so that the embodiments of the present application can be implemented in an order other than those illustrated or described here, and the objects distinguished by "first", "second", etc. are generally of one type, and the number of objects is not limited. For example, the first object can be one or more. In addition, "and / or" in the specification and claims represents at least one of the connected objects, and the character " / " generally indicates that the objects associated with each other are in an "or" relationship.

[0028] The distributed communication resource allocation and voltage coordinated control method and device provided in the embodiments of the present application are described in detail below in conjunction with the accompanying drawings through specific embodiments and their application scenarios.

[0029] The executor of the distributed communication resource allocation and voltage coordinated regulation method provided in the embodiment of the present application may be an electronic device or a functional module or functional entity in the electronic device that can implement the distributed communication resource allocation and voltage coordinated regulation method. The electronic devices mentioned in the embodiment of the present application include but are not limited to processors, controllers, computing platforms, cloud platforms, servers, terminals, etc. The distributed communication resource allocation and voltage coordinated regulation method provided in the embodiment of the present application is described below using the electronic device as an example of the executor.

[0030] like Figure 1 As shown, the distributed communication resource allocation and voltage coordinated control method includes: step 110, step 120, step 130, step 140 and step 150.

[0031] Step 110: Build a wireless network control system based on 5G local area network for the new power system; Step 120: determining a wireless transmission model and a dynamic model of voltage control of the wireless network control system; Step 130: Determine the cross-domain dependent coupling relationship between wireless communication and control system performance of the wireless network control system based on the wireless transmission model and the dynamic model of voltage control; Step 140: Determine a cross-domain optimization problem based on the cross-domain dependency coupling relationship; Step 150: Use the primal-dual graph neural network algorithm to solve the cross-domain optimization problem to obtain the optimal voltage control and communication power allocation strategy.

[0032] New power systems are gradually evolving into large-scale time-varying topologies with a large number of distributed generation, rooftop photovoltaic (PV) penetration, and explosive information exchange. Distributed energy resources, especially numerous geographically dispersed distributed PV systems, introduce significant uncertainty in key production control operations, such as PV regulation and new load control. Wireless communication in control loops is often susceptible to transmission packet loss probability and uncertain network-induced delays. Dynamic wireless links severely limit control performance, and it is particularly important to improve reliable transmission capabilities during the sharing of available wireless media.

[0033] For wireless applications in the power industry, the bandwidth of the dedicated 230MHz frequency band is only 1MHz, which cannot meet the needs of typical key control scenarios including intelligent distributed automation and distributed energy regulation. The current wireless communication network used in power systems lacks an effective and reliable communication mechanism to facilitate reliable and economical access to numerous distributed control terminals. This limitation hinders the realization of comprehensive network coverage, hinders the ability to meet the needs of distributed terminals, and cannot meet the requirements of high-frequency and real-time data communication on site. Compared with the 230MHz dedicated network and the 5G public network, the 5G Local Area Network (LAN) wireless communication technology emphasizes ultra-reliable low-latency communications (URLLC), which is closely aligned with the needs of the power system and can meet the communication needs of universal, flexible and mobile access without relying on physical cables. Therefore, using 5G LAN wireless communication technology, power control system terminal sensors and actuators can be widely deployed to monitor and control physical processes, and many small-scale integrated control subsystems that share 5G communication resources form a wireless network control system to transmit sensor information and control command information through wireless media.

[0034] Related technologies only focus on optimizing control design to adapt to the physical system state and assume that the packet loss rate on unreliable wireless channels has been fully described. The clear relationship between control performance and transmission reliability and delay is still unclear, which makes the analysis and optimization of control performance challenging.

[0035] This application aims at the goal of reliable transmission and deterministic guarantee of wireless bearer of power distributed control services, and proposes a distributed communication resource allocation and voltage coordinated regulation method.

[0036] This application first targets the new power system and constructs a wireless network control system based on 5G local area network, that is, based on the physical topology structure of the new power system, a wireless network control system based on 5G local area network is constructed. The physical topology structure of the new power system can be divided into multiple control areas, and the control areas can be divided based on the main branch nodes of the physical topology structure.

[0037] Then, the reliability and packet loss rate of wireless communication are considered to determine the wireless transmission model of the wireless network control system, and the influence of the unreliability of wireless communication on voltage control is considered to determine the dynamic model of voltage control of the wireless network control system.

[0038] Furthermore, considering the stability and speed of the wireless network control system, based on the wireless transmission model and the dynamic model of voltage control, the cross-domain dependency coupling relationship between the wireless communication and the control system performance of the wireless network control system is determined, wherein the cross-domain dependency coupling relationship refers to the dependency coupling relationship between the control domain and the communication domain.

[0039] Furthermore, considering the variable topological structure characteristics of new energy and the cross-domain dependency coupling relationship, the cross-domain optimization problem is determined while meeting the control system requirements and spectrum resource constraints, and then the voltage control and communication power allocation are jointly optimized.

[0040] Finally, the primal-dual graph neural network algorithm is used to obtain the optimal voltage control strategy and communication power allocation strategy to ensure that the voltage control system of the variable renewable energy distribution network has ideal dynamic and steady-state response characteristics and meets the business communication network requirements.

[0041] The distributed communication resource allocation and voltage coordinated regulation method provided in the embodiment of the present application is aimed at the new power system, constructs a wireless network control system based on the 5G local area network, determines the wireless transmission model of the wireless network control system and the dynamic model of voltage control, and then determines the dependency coupling relationship between the control domain and the communication domain based on the wireless transmission model and the dynamic model of voltage control. Based on the cross-domain dependency coupling relationship, the cross-domain optimization problem is determined, and the original dual graph neural network algorithm is used to solve the cross-domain optimization problem to obtain the optimal voltage control and communication power allocation strategy, thereby realizing distributed communication resource allocation and voltage coordinated control, which can ensure that the voltage control system of the variable new energy distribution network has ideal dynamic and steady-state response characteristics and meets the business communication network requirements.

[0042] In some embodiments, step 110 constructs a wireless network control system based on a 5G local area network for a new power system, including: The distributed controller is connected to multiple distribution network nodes of the new power system through the 5G local area network to realize distributed communication and control, and dynamically adjust the voltage control and communication power allocation strategy in each control cycle to cope with voltage fluctuations and load changes in the distribution network.

[0043] Distribution network nodes generally include power generation nodes, power transmission and transformation nodes, energy storage nodes, load nodes, etc. In the embodiment of the present application, the distribution network nodes are power generation nodes.

[0044] The embodiment of the present application takes into account the variable topology characteristics of new energy sources, and connects a distributed controller to multiple distribution network nodes of a new power system through a 5G local area network, wherein the distributed controller is deployed on or near a new energy power generation node (such as a photovoltaic (PV) node). The new energy power generation node can be used as a distributed controller, and the ordinary distributed power generation node can be used as a distribution network node. One new energy power generation node can be associated with multiple ordinary distributed power generation nodes, and the new energy power generation node and the ordinary distributed power generation node communicate through a D2D link, thereby realizing distributed communication and control, and dynamically adjusting the voltage control strategy and the communication power allocation strategy in each control cycle to cope with voltage fluctuations and load changes in the distribution network.

[0045] The distributed communication resource allocation and voltage coordinated regulation method provided in the embodiment of the present application connects the distributed controller to multiple distribution network nodes of the new power system through the 5G local area network, realizes distributed communication and control, and can dynamically adjust the voltage control strategy and communication power allocation strategy in each control cycle, which can effectively cope with voltage fluctuations and load changes in the distribution network, and improve the control performance and communication performance of the new power system.

[0046] In some embodiments, the connecting of the distributed controller to multiple distribution network nodes of the novel power system through a 5G local area network includes: Determining a plurality of control areas according to a distribution network topology structure corresponding to the novel power system; Wireless bearer is realized between different control areas through network nodes; In each control area, the network node covers at least one distributed energy node, and the distributed energy node includes: a new energy generation node or a common distributed generation node. The common distributed generation node serves as the distribution network node and is sensed by the associated new energy generation node. The common distributed generation node and the associated new energy generation node communicate through an end-to-end link in the control area to which they belong; The state information of the common distributed power generation node is transmitted to the new energy power generation node through the end-to-end link to form an uplink state perception of the control loop. The new energy power generation node acts as the distributed controller to aggregate the uplink state information through the end-to-end link, determine the reactive power injection ratio value, and execute the downlink voltage control command; The network node performs power allocation for end-to-end links within a control area covered by the network node, and transmits a power allocation instruction to the new energy power generation node.

[0047] Figure 2 This is a schematic diagram of the architecture of a wireless network control system based on a 5G local area network provided in an embodiment of the present application. Figure 2 The wireless network control system in the embodiment of the present application is a wireless network voltage control system (or a wireless network voltage control closed-loop system) that considers high-proportion photovoltaic injection. The control area can be divided according to the distribution network topology corresponding to the new power system, specifically, according to the main branch nodes in the distribution network topology, and multiple control areas can be determined.

[0048] In each control area, the network node covers at least one distributed energy node. It should be noted that the network node refers to a node that provides network services, such as a base station. Optionally, each control area includes a new energy power generation node (such as a photovoltaic (PV) node) and at least one ordinary distributed generation (DG) node, and the network node covers a new energy power generation node in the corresponding control area and at least one ordinary distributed generation node associated with the new energy power generation node. Among them, the ordinary distributed generation node, as the distribution network node, is perceived by the new energy power generation node associated with the ordinary distributed generation node, and the ordinary distributed generation node and the associated new energy power generation node communicate through an end-to-end link in the control area to which they belong.

[0049] The state information of the common distributed power generation node is transmitted to the new energy power generation node through the end-to-end link to form an uplink state perception of the control loop. The new energy power generation node, as the distributed controller, aggregates the uplink state information through the end-to-end link, determines the reactive power injection ratio value, and executes the downlink voltage control command to adjust the reactive power according to the reactive power injection ratio value, thereby realizing voltage control; The network node allocates power for the end-to-end links within the covered control area, and transmits the power allocation instruction to the new energy power generation node, so that the new energy power generation node can communicate with the ordinary distributed power generation node associated with it according to the allocated communication power.

[0050] refer to Figure 2 The wireless network control system in the embodiment of the present application includes a cellular base station in each control area covering at least one distributed energy source (DER) node, and these DER nodes are classified into DG nodes and PV nodes.

[0051] The wireless communication network under consideration is In the region, Base stations in the same frequency bandwidth cover PV nodes and The set of DGs and PVs is divided into Group, The set of DG indexes in the group is , these DGs can be sensed by all associated PVs. The PV set of the region is , indicating that these PV nodes are in the total set Consider a wireless network carried by a 5G LAN-type service, where PV-DG transceiver pairs communicate via a device-to-device (D2D, also called end-to-end) mode within the area. The communication link set of PV nodes is , and the set of all D2D links is expressed as The PV node directly aggregates the uplink status information through the D2D link, determines the reactive power injection ratio, and executes the downlink voltage control command. The base station, as a network node, allocates power for the D2D link within the coverage area of ​​the base station. The PV node receives the power allocation instruction and communicates with the DG node associated with it according to the allocated communication power.

[0052] The distributed communication resource allocation and voltage coordinated regulation method provided in the embodiment of the present application, the status information of the ordinary distributed power generation node is transmitted to the new energy power generation node through the end-to-end link, forming the uplink status perception of the control loop, the new energy power generation node acts as a distributed controller by aggregating the uplink status information through the end-to-end link, determines the reactive power injection ratio value, and executes the downlink voltage control command, thereby realizing voltage control, the network node performs power allocation for the end-to-end link within the covered control area, and transmits the power allocation instruction to the new energy power generation node, so that the new energy power generation node can communicate with the ordinary distributed power generation node associated with it according to the allocated communication power, thereby realizing the conversion of the power system to the wireless network control system.

[0053] In some embodiments, the mth new energy generation node associated with the adjacent common distributed generation node is set as the mth distributed controller of the wireless network control system to form an mth control subsystem, and a plurality of the control subsystems form a closed feedback loop through the 5G local area network; The state of the m-th new energy generation node at a certain moment depends on its own measurement value and the measurement value obtained from its neighbors.

[0054] It can be understood that the wireless network control system is composed of multiple control subsystems, and a closed feedback loop is formed between the multiple control subsystems through the 5G local area network.

[0055] The distributed communication resource allocation and voltage coordinated control method provided in the embodiment of the present application sets the mth new energy power generation node associated with the adjacent ordinary distributed power generation node as the mth distributed controller of the wireless network control system to form the mth control subsystem. A closed feedback loop is formed between the multiple control subsystems through the 5G local area network, and the sensor information and control command information are transmitted through the wireless medium, thereby realizing a wireless network voltage control system based on the 5G local area network, and further realizing coordinated optimization between the control system and the communication system.

[0056] In some embodiments, the step 120 of determining the wireless transmission model and the dynamic model of voltage control of the wireless network control system includes: 1) Determine the wireless transmission model a) Channel Model Consider that in each frame, DG sends information bits to its associated PV. In the frame, use Indicates a direct communication link The channel coefficient is Indicates link and The channel coefficient of the interfering link between ), is the number of DGs in the kth control area. These coefficients are affected by both small-scale fading and large-scale attenuation. The channel coefficient matrix of PV Defined as

[0057] in, represents the path loss factor, represents the square root of the large-scale channel gain, and its elements are recorded as and , represents the small-scale channel gain, Represents element-by-element product.

[0058] remember The instantaneous power matrix of PV is ,in Indicates that the link The instantaneous power used in Indicates that the link and The instantaneous power used in the interference link between The signal-to-noise-plus-interference ratio (SINR) is expressed as

[0059] in, Represents the noise power.

[0060] b) Short packet model The state information of DG is transmitted to PV through D2D link, forming the uplink state perception of the control loop, while the distributed PV executes the downlink control command locally. Therefore, when the delay exceeds the maximum delay threshold, the packet loss rate in the uplink D2D transmission is determined. Assuming the total bandwidth of the system is , assigned to the link The bandwidth is . D2D Link The transmission rate of the communication channel can be expressed as

[0061] The state information transmitted in the control system is mainly short data packets. Assume that the transmission data size is b bits and the sampling interval is , each time slot generates bits of data. The state arrival process can be regarded as a queue. Then, the concept of effective capacity is used to derive the constraints that guarantee the queuing delay requirements and packet loss probability. PV nodes The arrival rate of the upstream queue is , is the number of PV nodes in the kth control area. The effective capacity is ,in represents the decay rate of the queue overflow probability, which is a constant in a control environment. The effective capacity can be approximated by

[0062] Given As transmission delay The delay threshold, , the packet loss rate is expressed as

[0063] 2) Determine the voltage control dynamics model For PV distributed control of distribution network, the controller is close to the PV node and far away from the widely distributed DG nodes. Assume that at each moment Time The state of a PV node depends only on its own measurements and the measurements obtained from its neighbors. The voltage of each PV node is

[0064] in For the The voltage of adjacent DGs, is the square of the current, and represent active power and reactive power respectively, and Represents line resistance and reactance respectively. By setting The quadratic term can be ignored, and the approximate model can be obtained and rewritten in vector form

[0065] in, and The length is The vector of It is the bus collected from the main grid through the smart distribution network. voltage. represents the uncontrollable voltage component determined by the active power injection from the load and PV, and The length is Vector.

[0066] The first The PV is expressed as A control subsystem, whose status is , the controlled variable is The distributed controller determines the new reactive power injection value, which triggers the voltage update, ensuring that the PV bus voltage is constant under any given operating condition. Stay in a tight range The closed-loop voltage control dynamics is described as follows:

[0067]

[0068] In the case of applying state feedback control, the controller gain matrix is ​​set as ,Right now ,in, is the control signal input, is the rated voltage in steady state, Indicates the rated voltage in steady state In vector form, The voltage vector of the mth control subsystem, is the reactive power vector.

[0069] Multiple controllable subsystems close their feedback loops through a shared 5G wireless network, with a probability that depends on the communication power allocated to the control subsystem and the random channel state of wireless fading. Due to the limited wireless channel and significant electromagnetic interference, the information exchange in the control loop may not successfully reach the PV, so the packet loss rate, which characterizes the reliability of the communication link, is introduced to reflect the impact of the wireless network on the control performance.

[0070] Given packet loss rate and a Bernoulli-distributed binary random variable , when Links to control subsystems The uplink data packets are When the moment is successfully received by PV, and , is the packet loss rate threshold. Otherwise, under the influence of communication conditions, available spectrum resources and transmission power, and . No. The control command actually executed by the control subsystem is , For the The voltage of each PV node, = Therefore, the governing dynamics equation can be rewritten as,

[0071] The distributed communication resource allocation and voltage coordinated control method provided in the embodiment of the present application calculates the communication conditions of the D2D link by determining the channel model and the short packet model, and determines the dynamic model of voltage control by considering the unreliability of communication. Subsequently, cross-domain dependency coupling relationship analysis can be implemented based on the wireless transmission model and the dynamic model of voltage control.

[0072] In some embodiments, step 130 determines the cross-domain dependent coupling relationship between wireless communication and control system performance of the wireless network control system based on the wireless transmission model and the dynamic model of voltage control, including: Based on Lyapunov stability theory and the wireless transmission model, the stability and rapidity of the voltage-controlled dynamic model are analyzed to determine the exponential stability constraint and convergence rate constraint under the condition of an imperfect wireless link.

[0073] It can be understood that, considering the impact of wireless communication on the performance of the control system, based on Lyapunov stability theory and the wireless transmission model, the stability and rapidity analysis of the dynamic model of the voltage control is carried out, and the exponential stability constraints and convergence rate constraints under imperfect wireless link conditions are determined. The exponential stability constraints and convergence rate constraints under imperfect wireless link conditions reflect the cross-domain dependent coupling relationship between wireless communication and control system performance.

[0074] 1) Control system stability In the voltage regulation task, the goal is to find a distributed controller that can drive the system state to eventually reach the equilibrium point (i.e., the desired state). The embodiment of the present application designs a stable distributed controller based on the Lyapunov stability theory. For voltage control, the closed-loop dynamics can be expressed as ,in, represents the control input considering the reliability of the wireless link, represents the mapping function from state to control signal, The voltage control equation is defined as Mathematical notation for . Consider the following Lyapunov function,

[0075] in, is a positive definite matrix, and is positive definite and radially unbounded. Based on the Lasalle invariance theorem, when and Only when holds, indicating that for each initial voltage value, will converge to the maximum invariant set , that is, the voltage trajectory returns to the acceptable upper and lower bounds.

[0076] Assume that for all adjacent DERs, is a continuously differentiable function, and when hour, In addition, each exist and Satisfaction

[0077] and , then the dynamic system is asymptotically stable, where Represents the packet loss rate vector.

[0078] In the case of achieving exponential stability, Lyapunov difference With decay rate , and its stability condition is

[0079] 2) Control system speed In order to consider the unpredictable impact of wireless communication on control convergence performance, this application establishes the definition of average dwell time, given a delay caused by unreliability and switching signal Mapping , where is the sampling interval, express The activation time interval, represents the packet loss time interval. ,make Indicates that in the interval The number of signal switching within. If there is and ,satisfy ,but is the average dwell time of the switching signal, is the jitter boundary. If the closed-loop wireless network control system is exponentially stable, the decay rate is ,in is a given positive constant, and holds for any control dynamics, is a set of integers, and .

[0080] The original convergence rate Compared to The Lyapunov decay rate decreases with Monotonically increasing, Monotonically decreasing, the larger indicates fewer switching times, resulting in a smaller Lyapunov decay rate. The time-varying nature of the delay triggers switching between subsystems, and the average residence time needs to satisfy the lower bound to maintain stability. Therefore, if the rate of change of the delay is small, the state of the closed-loop wireless network control system will converge to the nominal point at a faster speed. In this case, ,Right now .

[0081] Based on the quadratic Lyapunov function , and its expectation inequality can be ,make , we can derive the lower bound of the exponential convergence rate,

[0082] Then the convergence rate of the control system must satisfy , is the time t The transmission success rate of each control subsystem.

[0083] The distributed communication resource allocation and voltage coordinated control method provided in the embodiment of the present application is based on Lyapunov stability theory and the wireless transmission model, and the stability and rapidity analysis of the dynamic model of the voltage control is performed to determine the exponential stability constraint and convergence rate constraint under the condition of an imperfect wireless link. The exponential stability constraint and convergence rate constraint under the condition of an imperfect wireless link are used to reflect the cross-domain dependency coupling relationship between the performance of the wireless communication and the control system. Subsequently, the cross-domain optimization problem is determined based on the cross-domain dependency coupling relationship, which can ensure that the wireless network voltage control closed-loop system has ideal dynamic and steady-state response characteristics while meeting the communication requirements.

[0084] In some embodiments, the step 140 determines the cross-domain optimization problem based on the cross-domain dependency coupling relationship, including: Determining an objective function, the objective function comprising: a first objective function for causing the corresponding voltage to converge to a desired range within a preset time period, and a second objective function for introducing penalties for voltage deviation and reactive power injection; Determining target constraints according to dynamic model rules, transient response requirements, exponential stability constraints and convergence rate constraints under the imperfect wireless link conditions, transmission power constraints, and packet loss rate constraints; The cross-domain optimization problem is determined according to the objective function and the objective constraint condition.

[0085] The present application introduces transient and steady-state optimization problems in the control domain, aiming to achieve two goals: a) The voltage converges quickly to the nominal value surrounding safety margin; b) maintaining relatively economical steady-state costs.

[0086] Here, the steady-state cost is defined as the cost of the control action, which can be expressed in a compact form as

[0087] in, is a diagonal matrix , and , respectively represent the reactive power cost of each DER and its apparent power limit. It should be noted that the last term in the above equation is a constant. The above cost function can also be understood as a penalty for voltage deviation and reactive power injection.

[0088] Next, during the transient period [0, ], the voltage needs to converge to the desired range, that is The transient performance after voltage disturbance is combined with the steady-state cost to ensure the closed-loop control performance. The control optimization problem for a control area is

[0089]

[0090]

[0091]

[0092]

[0093]

[0094] Among them, the constraints and represents the kinetic model rules, Indicates the transient response requirement, and It is the exponential stability constraint and convergence rate constraint under the condition of imperfect wireless link (to achieve the stability and rapidity of the control system).

[0095] Considering the uplink energy efficiency index of the kth control area based on the effective capacity, it can be expressed as

[0096] in, Indicates DG is the inevitable circuit power consumption due to electronic operation. Indicates link The transmission power in , Indicates Base stations in the control area Therefore, the optimization problem can be expressed as maximizing the total energy efficiency,

[0097]

[0098]

[0099]

[0100]

[0101] Among them, the constraints Make sure that The total transmission power allocated within the control area shall not exceed the maximum Ensure that the transmission power of each communication link is non-negative, the constraint condition Indicates The packet loss rate in the control loop Cannot exceed reliability threshold , and is subject to the coupled inequalities associated with the control performance and constraint.

[0102] The distributed communication resource allocation and voltage coordinated control method provided in the embodiment of the present application transcends the optimization problem to make the corresponding voltage converge to the expected range within a preset time length, and introduces penalties for voltage deviation and reactive power injection as the goal. It takes into account constraints such as dynamic model rules, transient response requirements, exponential stability and convergence rate under imperfect wireless link conditions, transmission power, and packet loss rate, and realizes distributed communication resource allocation and voltage coordinated control, which can ensure that the voltage control system of the variable new energy distribution network has ideal dynamic and steady-state response characteristics and meets the needs of the business communication network.

[0103] In some embodiments, Figure 3 As shown, step 150 uses the primal dual graph neural network algorithm to solve the cross-domain optimization problem to obtain the optimal voltage control and communication power allocation strategy, including: Step 1501: parameterize the constraints in the cross-domain optimization problem to establish the constraints in the design of the graph neural network model to form a parameterized joint optimization problem; The optimal voltage control problem requires explicit knowledge of the system dynamics, while network parameters are usually difficult to estimate, which motivates this application to address the original optimization problem. Specifically, this application parameters each photovoltaic controller as , where the weight of the neural network is , To control the gain, = ,therefore, . Constraints and The control commands of the wireless network control system described in the dynamic state depend on the packet loss rate and the voltage amplitude of the distributed energy, where The controllable reactive power and uncontrollable active power in the photovoltaic are collected. This application restricts the power allocation and control injection strategy to Markov properties, reflecting the dynamic conversion constraints.

[0104] The parameterization of the policy network needs to take into account constraints , which limits the category of stable distributed controllers to strictly monotonically decreasing functions. This application adopts a neural network design that satisfies the stability constraint, and the constructed stacked ReLU (SReLU) activation function is as follows:

[0105]

[0106] Its is monotonically decreasing and in is zero; at the same time, is monotonically decreasing and in When is zero. and is the weight vector, and is the bias vector, combining Hidden layer dimensions, The variable form is .

[0107] Furthermore, the present application achieves this by directly thresholding the slope Bounded, PV controller neural network parameterized controller is constructed as:

[0108] in,

[0109]

[0110] For a finite-dimensional parameter The power allocation strategy maps the channel state information of the D2D link to the normalized transmit power of the uplink transmission, that is, ,in, represents the channel gain matrix of the mth control subsystem. Therefore, let and is the weight parameter, and The parameterized joint optimization problem can be reformulated as:

[0111]

[0112]

[0113] Step 1502: Express the parameterized joint optimization problem by using a Lagrangian dual function that considers both the optimization objective and the constraint conditions; Parameterization in the strategy offers significant computational and practical advantages. However, the problem remains unsolved. Therefore, consider the non-negative dual variables , corresponding to Each constraint in the constraint condition derives the Lagrangian dual problem. The Lagrangian function as an expression of the original problem is defined as follows: -

[0114] Given the coupled Lagrangian function, the corresponding Lagrangian dual function can be defined as . This can be rewritten as a minimax optimization problem as follows:

[0115] Step 1503: Model the wireless network control system as a directed communication graph, and determine node features and edge features of the directed communication graph; Due to the complex cross-domain coupling and transient stability within a limited time, this application adopts the stability-constrained primal-dual GNN algorithm (SPGNN) to effectively solve the constructed multi-objective problem and process large-scale state-action space through stability-constrained policy parameterization.

[0116] In order to characterize the interaction between PV and its neighboring distributed generators DG, the wireless network is modeled as a directed communication graph. ,in express For a collection of end-to-end (D2D) communications, Represents the edge set of the interfering link, the mapping function Pairing nodes Mapping Dimensional Features ,and Map the edges to In the context of wireless network graphs, node features involve the local channel coefficients of D2D links, including The measurement properties of a DG, ,and . The node feature matrix is ​​further defined as ,in, The edge feature is defined as the channel gain of the interfering link, which is composed of the channel coefficient matrix Definition, and the corresponding adjacent feature elements is defined as

[0117] Step 1504: input the node features and edge features into the graph neural network model, use the Lagrangian dual function as the loss function, and combine the original dual learning to train the graph neural network model. After the training, obtain the output of the graph neural network model to obtain the optimal voltage control and communication power allocation strategy.

[0118] The uplink information exchange in the wireless network control system structure considered in the embodiment of the present application is embedded in fading and interference patterns, which can be incorporated into the policy parameterization and aggregated through the message passing stage, and designed as the convolution kernel of the message passing graph neural network. In the message passing stage, each node generates messages based on its local features and passes the generated messages to different neighbors through the edge features of the neighbors. In the aggregation stage, the node aggregates messages from all neighbors to generate aggregate information. Next, in the update stage, the node combines the aggregate information from the neighbors and its local features to update its embedded representation. The embedding obtained by one update step represents the expression of its local features and neighbor features.

[0119] For each node ,make Represents the node corresponding to The initial eigenvector of represents the initial number of features for each node. These feature vectors are obtained through the graph Multi-layer message passing and aggregation are performed on the edges of Indicates the number of layers, for each layer , Representation Node In the The feature vector of the layer, Represents the number of features of each node in each layer. Each such feature vector is based on the previous layer node And its neighbors and self-loop features are aggregated to obtain,

[0120] in, Indicates that the policy parameters parameterized potentially nonlinear aggregation functions, Representation Node The neighbor set of , Represents a collection of nodes. Representation Node The neighboring nodes of represents the edge set, It means node and There is an adjacency relationship between them. After the layer, each node will have a final feature vector , which is called the embedding representation of the node. Therefore, The output of the layer graph neural network can be expressed as:

[0121] in , represents the communication domain power allocation decision, Represents the reactive power ratio decision of the control domain.

[0122] For each transmitter and receiver pair, the transmit power level is:

[0123] in, Represents the Sigmoid function , represents a parameter vector that maps the average node embedding to a scalar, which is then converted to its assigned transmit power.

[0124] For photovoltaic (PV) equipped with continuous action sets, Represents the reactive power ratio generated by it,

[0125] in, represents the designed stacked ReLU function, is a parameter vector used to transform node embeddings into a probability distribution of reactive power fractions.

[0126] By using a hierarchical optimization decomposition approach, the dual problem can be decomposed into a two-level hierarchy. Evaluating the dual function is transformed into a Markov decision process (MDP) problem where the objective is defined by the Lagrangian function equation. Therefore, the inner maximization can be solved using the SPGNN approach. The outer optimization problem is designed to minimize The dual problem is that the inner layer updates the parameters of the graph neural network, the outer layer updates the parameters of the Lagrange multiplier, and the policy parameters with the constraint set for

[0127] The distributed communication resource allocation and voltage coordinated regulation method provided in the embodiment of the present application parameterizes the constraints in the cross-domain optimization problem so as to establish the constraints in the design of the graph neural network model to form a parameterized joint optimization problem; the parameterized joint optimization problem is expressed by the Lagrangian dual function that simultaneously considers the optimization objective and the constraints, the wireless network control system is modeled as a directed communication graph, the node characteristics and edge characteristics of the directed communication graph are determined, and the graph neural network model is trained by inputting the node characteristics and edge characteristics into the graph neural network model, using the Lagrangian dual function as the loss function, and combining the original dual learning. After the training, the output of the graph neural network model is obtained to obtain the optimal voltage control and communication power allocation strategy, which can be used to design an information interaction transmission scheme for remote control under a high proportion of new energy access in the distribution network, taking into account the needs of the control system and the limitations of spectrum and energy resources, and obtaining the optimal voltage control strategy and communication resource allocation strategy, realizing distributed communication resource allocation and voltage coordinated control, and improving the information exchange capability and control performance of the new power system.

[0128] The distributed communication resource allocation and voltage coordinated regulation method provided in the embodiment of the present application can be executed by a distributed communication resource allocation and voltage coordinated regulation device. In the embodiment of the present application, the distributed communication resource allocation and voltage coordinated regulation method is executed by a distributed communication resource allocation and voltage coordinated regulation device as an example to illustrate the distributed communication resource allocation and voltage coordinated regulation device provided in the embodiment of the present application.

[0129] The present application also provides a distributed communication resource allocation and voltage coordinated control device, such as Figure 4 As shown, the distributed communication resource allocation and voltage coordinated control device 400 includes: a system construction unit 410, a model determination unit 420, a cross-domain dependency determination unit 430, an optimization problem determination unit 440 and a solution unit 450, wherein: A system construction unit 410 is used to construct a wireless network control system based on a 5G local area network for a new power system; A model determination unit 420, configured to determine a wireless transmission model and a dynamic model of voltage control of the wireless network control system; A cross-domain dependency relationship determination unit 430, configured to determine a cross-domain dependency coupling relationship between wireless communication and control system performance of the wireless network control system based on the wireless transmission model and the dynamic model of voltage control; An optimization problem determining unit 440, configured to determine a cross-domain optimization problem based on the cross-domain dependency coupling relationship; The solving unit 450 is used to solve the cross-domain optimization problem by using the primal-dual graph neural network algorithm to obtain the optimal voltage control and communication power allocation strategy.

[0130] In some embodiments, the system construction unit 410 is used to: The distributed controller is connected to multiple distribution network nodes of the new power system through the 5G local area network to realize distributed communication and control, and dynamically adjust the voltage control and communication power allocation strategy in each control cycle to cope with voltage fluctuations and load changes in the distribution network.

[0131] In some embodiments, the connecting of the distributed controller to multiple distribution network nodes of the novel power system through a 5G local area network includes: Determining a plurality of control areas according to a distribution network topology structure corresponding to the novel power system; Wireless bearer is realized between different control areas through network nodes; In each control area, the network node covers at least one distributed energy node, and the distributed energy node includes: a new energy generation node or a common distributed generation node. The common distributed generation node serves as the distribution network node and is sensed by the associated new energy generation node. The common distributed generation node and the associated new energy generation node communicate through an end-to-end link in the control area to which they belong; The state information of the common distributed power generation node is transmitted to the new energy power generation node through the end-to-end link to form an uplink state perception of the control loop. The new energy power generation node acts as the distributed controller to aggregate the uplink state information through the end-to-end link, determine the reactive power injection ratio value, and execute the downlink voltage control command; The network node performs power allocation for end-to-end links within a control area covered by the network node, and transmits a power allocation instruction to the new energy power generation node.

[0132] In some embodiments, the mth new energy generation node associated with the adjacent common distributed generation node is set as the mth distributed controller of the wireless network control system to form an mth control subsystem, and a plurality of the control subsystems form a closed feedback loop through the 5G local area network; The state of the m-th new energy generation node at a certain moment depends on its own measurement value and the measurement value obtained from its neighbors.

[0133] In some embodiments, the cross-domain dependency determination unit 430 is used to: Based on Lyapunov stability theory and the wireless transmission model, the stability and rapidity of the voltage-controlled dynamic model are analyzed to determine the exponential stability constraint and convergence rate constraint under the condition of an imperfect wireless link.

[0134] In some embodiments, the optimization problem determination unit 440 is used to: Determining an objective function, the objective function comprising: a first objective function for causing the corresponding voltage to converge to a desired range within a preset time period, and a second objective function for introducing penalties for voltage deviation and reactive power injection; Determining target constraints according to dynamic model rules, transient response requirements, exponential stability constraints and convergence rate constraints under the imperfect wireless link conditions, transmission power constraints, and packet loss rate constraints; The cross-domain optimization problem is determined according to the objective function and the objective constraint condition.

[0135] In some embodiments, the solving unit 450 is used to: Parameterizing the constraints in the cross-domain optimization problem to establish the constraints in the design of the graph neural network model to form a parameterized joint optimization problem; The parameterized joint optimization problem is expressed by a Lagrangian dual function that considers both the optimization objective and the constraints; Modeling the wireless network control system as a directed communication graph, and determining node characteristics and edge characteristics of the directed communication graph; The node features and edge features are input into the graph neural network model, and the Lagrangian dual function is used as the loss function. The graph neural network model is trained in combination with the original dual learning. After the training, the output of the graph neural network model is obtained to obtain the optimal voltage control and communication power allocation strategy.

[0136] The distributed communication resource allocation and voltage coordinated control device in the embodiment of the present application can be an electronic device, or a component in an electronic device, such as an integrated circuit or a chip. The electronic device can be a processor, a controller, a computing platform, a cloud platform, a server, or a terminal, or other devices, which are not specifically limited in the embodiment of the present application.

[0137] The distributed communication resource allocation and voltage coordinated control device in the embodiment of the present application may be a device having an operating system. The operating system may be a Microsoft (Windows) operating system, an Android (Android) operating system, an IOS operating system, or other possible operating systems, which are not specifically limited in the embodiment of the present application.

[0138] The distributed communication resource allocation and voltage coordinated control device provided in the embodiment of the present application can achieve Figures 1 to 3 The various processes implemented by the method embodiment can achieve the same technical effect, and to avoid repetition, they will not be described here.

[0139] In some embodiments, Figure 5 As shown, an embodiment of the present application also provides an electronic device 500, including a processor 501, a memory 502, and a computer program stored in the memory 502 and executable on the processor 501. When the program is executed by the processor 501, each process of the above-mentioned distributed communication resource allocation and voltage coordinated regulation method embodiment is implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0140] It should be noted that the electronic devices in the embodiments of the present application include the mobile electronic devices and non-mobile electronic devices mentioned above.

[0141] An embodiment of the present application also provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the various processes of the above-mentioned distributed communication resource allocation and voltage coordinated control method embodiment are implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0142] The processor is the processor in the electronic device described in the above embodiment. The readable storage medium includes a computer readable storage medium, such as a computer read-only memory ROM, a random access memory RAM, a magnetic disk or an optical disk.

[0143] An embodiment of the present application also provides a computer program product, including a computer program, which implements the above-mentioned distributed communication resource allocation and voltage coordinated control method when executed by a processor.

[0144] The processor is the processor in the electronic device described in the above embodiment. The readable storage medium includes a computer readable storage medium, such as a computer read-only memory ROM, a random access memory RAM, a magnetic disk or an optical disk.

[0145] An embodiment of the present application further provides a chip, which includes a processor and a communication interface, wherein the communication interface is coupled to the processor, and the processor is used to run programs or instructions to implement the various processes of the above-mentioned distributed communication resource allocation and voltage coordinated regulation method embodiments, and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0146] It should be understood that the chip mentioned in the embodiments of the present application can also be called a system-level chip, a system chip, a chip system or a system-on-chip chip, etc.

[0147] It should be noted that, in this article, the terms "comprise", "include" or any other variant thereof are intended to cover non-exclusive inclusion, so that the process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise one..." do not exclude the presence of other identical elements in the process, method, article or device including the element. In addition, it should be pointed out that the scope of the methods and devices in the embodiments of the present application is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in reverse order according to the functions involved, for example, the described method may be performed in an order different from that described, and various steps may also be added, omitted, or combined. In addition, the features described with reference to certain examples may be combined in other examples.

[0148] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the relevant technology, can be embodied in the form of a computer software product, which is stored in a storage medium (such as ROM / RAM, disk, CD), and includes a number of instructions for a terminal (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods described in each embodiment of the present application.

[0149] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present application, ordinary technicians in this field can also make many forms without departing from the purpose of the present application and the scope of protection of the claims, all of which are within the protection of the present application.

[0150] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "illustrative embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials, or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0151] Although the embodiments of the present application have been shown and described, those skilled in the art will appreciate that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present application, and that the scope of the present application is defined by the claims and their equivalents.

Claims

1. A distributed communication resource allocation and voltage coordinated control method, characterized in that: include: For new power systems, build a wireless network control system based on 5G local area network; Determining a wireless transmission model and a dynamic model of voltage control of the wireless network control system; Based on the wireless transmission model and the dynamic model of voltage control, determining the cross-domain dependent coupling relationship between wireless communication and control system performance of the wireless network control system; Based on the cross-domain dependency coupling relationship, determining a cross-domain optimization problem; The cross-domain optimization problem is solved using the primal-dual graph neural network algorithm to obtain the optimal voltage control and communication power allocation strategy.

2. The distributed communication resource allocation and voltage coordinated control method according to claim 1, characterized in that: The wireless network control system based on 5G local area network is constructed for the new power system, including: The distributed controller is connected to multiple distribution network nodes of the new power system through the 5G local area network to realize distributed communication and control, and dynamically adjust the voltage control and communication power allocation strategy in each control cycle to cope with voltage fluctuations and load changes in the distribution network.

3. The distributed communication resource allocation and voltage coordinated control method according to claim 2, characterized in that: The method of connecting the distributed controller to multiple distribution network nodes of the novel power system through the 5G local area network includes: Determining a plurality of control areas according to a distribution network topology structure corresponding to the novel power system; Wireless bearer is realized between different control areas through network nodes; In each control area, the network node covers at least one distributed energy node, and the distributed energy node includes: a new energy generation node or a common distributed generation node. The common distributed generation node serves as the distribution network node and is sensed by the associated new energy generation node. The common distributed generation node and the associated new energy generation node communicate through an end-to-end link in the control area to which they belong; The state information of the common distributed power generation node is transmitted to the new energy power generation node through the end-to-end link to form an uplink state perception of the control loop. The new energy power generation node acts as the distributed controller to aggregate the uplink state information through the end-to-end link, determine the reactive power injection ratio value, and execute the downlink voltage control command; The network node performs power allocation for end-to-end links within a control area covered by the network node, and transmits a power allocation instruction to the new energy power generation node.

4. The distributed communication resource allocation and voltage coordinated control method according to claim 3 is characterized in that: The mth new energy generation node associated with the adjacent common distributed generation node is set as the mth distributed controller of the wireless network control system to form an mth control subsystem, and a plurality of the control subsystems form a closed feedback loop through the 5G local area network; The state of the m-th new energy generation node at a certain moment depends on its own measurement value and the measurement value obtained from its neighbors.

5. The distributed communication resource allocation and voltage coordinated control method according to claim 1, characterized in that: The determining of the cross-domain dependent coupling relationship between the wireless communication and the control system performance of the wireless network control system based on the wireless transmission model and the dynamic model of voltage control includes: Based on Lyapunov stability theory and the wireless transmission model, the stability and rapidity of the voltage-controlled dynamic model are analyzed to determine the exponential stability constraint and convergence rate constraint under the condition of an imperfect wireless link.

6. The distributed communication resource allocation and voltage coordinated control method according to claim 5, characterized in that: Determining the cross-domain optimization problem based on the cross-domain dependency coupling relationship includes: Determining an objective function, the objective function comprising: a first objective function for causing the corresponding voltage to converge to a desired range within a preset time period, and a second objective function for introducing penalties for voltage deviation and reactive power injection; Determining target constraints according to dynamic model rules, transient response requirements, exponential stability constraints and convergence rate constraints under the imperfect wireless link conditions, transmission power constraints, and packet loss rate constraints; The cross-domain optimization problem is determined according to the objective function and the objective constraint condition.

7. The distributed communication resource allocation and voltage coordinated control method according to claim 1, characterized in that: The cross-domain optimization problem is solved by using the primal-dual graph neural network algorithm to obtain the optimal voltage control and communication power allocation strategy, including: Parameterizing the constraints in the cross-domain optimization problem to establish the constraints in the design of the graph neural network model to form a parameterized joint optimization problem; The parameterized joint optimization problem is expressed by a Lagrangian dual function that considers both the optimization objective and the constraints; Modeling the wireless network control system as a directed communication graph, and determining node characteristics and edge characteristics of the directed communication graph; The node features and edge features are input into the graph neural network model, and the Lagrangian dual function is used as the loss function. The graph neural network model is trained in combination with the original dual learning. After the training, the output of the graph neural network model is obtained to obtain the optimal voltage control and communication power allocation strategy.

8. A distributed communication resource allocation and voltage coordinated control device, characterized in that: include: System construction unit, used to build a wireless network control system based on 5G local area network for new power systems; A model determination unit, used to determine a wireless transmission model and a dynamic model of voltage control of the wireless network control system; A cross-domain dependency relationship determination unit, used to determine the cross-domain dependency coupling relationship between the wireless communication of the wireless network control system and the control system performance based on the wireless transmission model and the dynamic model of voltage control; An optimization problem determination unit, configured to determine a cross-domain optimization problem based on the cross-domain dependency coupling relationship; A solving unit is used to solve the cross-domain optimization problem using a primal-dual graph neural network algorithm to obtain an optimal voltage control and communication power allocation strategy.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the distributed communication resource allocation and voltage coordinated control method as described in any one of claims 1-7 is implemented.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the distributed communication resource allocation and voltage coordinated control method as described in any one of claims 1 to 7 is implemented.

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