An entropy value-based new energy transformer area communication resource management method and device

Abstract

The application relates to the technical field of power communication, in particular to a new energy transformer area communication resource management method and device based on an entropy value, which virtualizes physical communication resources of a new energy transformer area to obtain virtual resources, and abstracts the virtual resources into services of various businesses; network data of the new energy transformer area is monitored in real time, and an entropy value is calculated; when the entropy value exceeds a set threshold value, quality of service optimization is carried out for various businesses to adjust communication resources and reduce the entropy value; wherein the entropy value is calculated based on a quality of service metric, and the quality of service metric includes response time, success rate, reliability and load rate in the network data. Thus, the entropy value concept is introduced into communication resource management, which is used for measuring uncertainty and chaos degree of the system, and through monitoring and controlling the entropy value, the order and efficiency of the communication network can be effectively improved, the reasonable allocation and utilization of network resources are ensured, and the efficient and reliable transmission of data of the new energy transformer area is effectively supported.

Description

Technical Field

[0001] The present application relates to the field of electric power communication technology, and in particular to a method and device for managing communication resources in a new energy station area based on entropy. Background Art

[0002] A new energy substation refers to an electricity supply unit that integrates a variety of new energy power generation equipment (such as solar photovoltaic panels, wind turbines, etc.), energy storage systems (such as battery energy storage) and related power loads (such as residential electricity, industrial and commercial electricity, etc.) within a certain area, and is equipped with advanced communication, control and management technologies to achieve efficient consumption of new energy, balance of electricity supply and demand, and intelligent operation.

[0003] Currently, local communication networks in power substations primarily rely on HPLC (High-Speed ​​Power Line Carrier) and wireless private networks. With the digital development of new energy substations, the frequency of data collection for services such as minute-by-minute electricity consumption information, distributed photovoltaic control, containerized energy storage monitoring, and low-voltage distribution monitoring has increased, leading to explosive growth in the scale of these services. However, in practice, existing local communication networks lack communication resource management. This high frequency of data collection leads to severe conflicts between wired and wireless channels, making it impossible to provide a reliable and stable communication network to support the development of "observable, measurable, adjustable, and controllable" new energy substations. Summary of the Invention

[0004] In order to overcome the shortcomings of the existing technology, the present application provides a new energy station area communication resource management method and device based on entropy value, which can effectively improve the orderliness and efficiency of the communication network through entropy value monitoring and management, and ensure the rational allocation and utilization of network resources.

[0005] In a first aspect, the present application provides a method for managing communication resources in a new energy station area based on entropy, the method comprising the following steps:

[0006] Virtualizing the physical communication resources of the new energy station area to obtain virtual resources, and abstracting the virtual resources into services of various types of business; the various types of business include at least one of control business, collection business, and maintenance business;

[0007] The network data of the new energy substation is monitored in real time and the entropy value is calculated. When the entropy value exceeds the set threshold, the service quality is optimized for each type of business to adjust the communication resources to reduce the entropy value. The entropy value is calculated based on the service quality metric, and the service quality metric includes the response time, success rate, reliability and load rate in the network data.

[0008] In a possible implementation, the physical communication resources of the new energy station area are virtualized to obtain virtual resources using software-defined networking (SDN) and network function virtualization (NFV).

[0009] In one possible implementation, the entropy value H′ is calculated using the following formula: i (p):

[0010] H′ i (p)=-lnH i (p)

[0011]

[0012] Among them, H i (p) represents the QoS scale of communication resources; Q ij It indicates the quality of service of the i-th available channel selected for the j-th service communication, and Q ij =(Q ijk ,1≤k≤4), k represents the number of the quality of service metric, max(Q ijk ) represents Q ij The maximum value of the kth quality of service metric, w represents the weight of the quality of service metric, w = (w k ,1≤k≤4,Σw k =1).

[0013] In a possible implementation, for control services / collection services, a local search algorithm is used to optimize the quality of service, including the following steps:

[0014] Determine the number of control service / collection service requests, and for each control service / collection service request, determine the number of communication resources that meet the conditions;

[0015] Randomly select one communication resource from each control service / collection service request to form an initial resource allocation scheme as the initial solution, and set the objective function that minimizes the entropy value and meets the upper limit requirement of the service response time;

[0016] A random perturbation strategy is used to obtain the initial point, and the domain structure is defined based on the response time critical path node sequence to determine the communication resource adjustment direction;

[0017] Starting from the initial solution, search within the defined neighborhood structure, adjust the current resource allocation scheme, and obtain the neighborhood solution;

[0018] Calculate the entropy value and service response time corresponding to each neighborhood solution to determine whether it meets the objective function requirements; if so, update the current optimal solution to the neighborhood solution; if not, continue searching within the defined neighborhood structure until the set stopping condition is met, and output the current optimal solution as the optimized resource allocation plan.

[0019] In one possible implementation, the random perturbation strategy is formulated as follows:

[0020] During the search within the defined neighborhood structure, the number of consecutive steps without finding a better solution is recorded, as well as the degree of convergence for the set number of consecutive steps.

[0021] If the number of consecutive steps without finding a better solution reaches the set first threshold, or the convergence degree of the set number of consecutive steps is less than the set second threshold, the current neighborhood solution is randomly perturbed.

[0022] In one possible implementation, the domain structure is defined by the following formula:

[0023]

[0024] Among them, x i ∈X k , X k =(x1,x2...x n ) is the critical path node sequence of X response time.

[0025] In a possible implementation, when optimizing the quality of service for maintenance services, the following steps are included:

[0026] When it is detected that the data packet loss rate exceeds a third threshold, reducing the transmission rate and the channel time slot;

[0027] When it is detected that the traffic transmission volume increases and the load rate does not exceed the fourth threshold, the transmission rate is increased and the channel time slot is added; when it is detected that the traffic transmission volume increases and the load rate exceeds the fourth threshold, a new channel is enabled according to the priority;

[0028] When it is detected that the channel utilization rate is lower than the fifth threshold, channel recovery is performed; when it is detected that the channel utilization rate is higher than the sixth threshold, a new channel is enabled according to the priority.

[0029] In a second aspect, the present application provides an entropy-based new energy area communication resource management device, the device comprising:

[0030] A conversion module is used to virtualize the physical communication resources of the new energy station area to obtain virtual resources, and abstract the virtual resources into services of various types of business; the various types of business include at least one of control business, collection business, and maintenance business;

[0031] The management module is used to monitor the network data of the new energy substation in real time and calculate the entropy value. When the entropy value exceeds the set threshold, the service quality is optimized for various services to adjust communication resources to reduce the entropy value. The entropy value is calculated based on the service quality metric, which includes the response time, success rate, reliability and load rate in the network data.

[0032] In the third aspect, the present application provides an electronic device comprising: a processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor. When the electronic device is running, the processor and the memory communicate through the bus, and when the machine-readable instructions are executed by the processor, the steps of the new energy station area communication resource management method based on entropy value as described in any one of the first aspects are performed.

[0033] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the steps of the new energy station area communication resource management method based on entropy value as described in any one of the first aspects are executed.

[0034] This embodiment provides a method and device for managing communication resources in new energy substations based on entropy values. The method virtualizes the physical communication resources in new energy substations to obtain virtual resources, and abstracts the virtual resources into services for various types of businesses. The method monitors the network data of new energy substations in real time and calculates the entropy value. When the entropy value exceeds a set threshold, the method optimizes the service quality for various types of businesses to adjust the communication resources and reduce the entropy value. The entropy value is calculated based on the service quality metric, and the service quality metric includes the response time, success rate, reliability, and load rate in the network data. Thus, the concept of entropy value is introduced into communication resource management to measure the uncertainty and chaos of the system. By monitoring and controlling the entropy value, the orderliness and efficiency of the communication network can be effectively improved, the rational allocation and utilization of network resources can be ensured, and the efficient and reliable transmission of data in new energy substations can be effectively supported. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments. It should be understood that the following drawings only illustrate certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without paying any creative work.

[0036] Figure 1 A flowchart of a method for managing new energy area communication resources based on entropy value according to an embodiment of the present application is shown;

[0037] Figure 2 A flowchart illustrating service quality optimization for control services / collection services according to an embodiment of the present application is shown;

[0038] Figure 3 A schematic diagram of the structure of a new energy area communication resource management device based on entropy value according to an embodiment of the present application is shown;

[0039] Figure 4A structural block diagram of the electronic device according to an embodiment of the present application is shown. DETAILED DESCRIPTION

[0040] To make the objectives, technical solutions, and advantages of the embodiments of the present application clearer, the following will be combined with the accompanying drawings for the embodiments of the present application to make a clear and complete description of the technical solutions in the embodiments of the present application. It should be understood that the accompanying drawings in the present application are only for the purpose of illustration and description, and are not used to limit the scope of protection of the present application. In addition, it should be understood that the schematic drawings are not drawn according to the actual proportions. The flowcharts used in the present application show the operations implemented according to some embodiments of the present application. It should be understood that the operations of the flowcharts can not be implemented in sequence, and the steps without logical context relationship can be reversed in sequence or implemented simultaneously. In addition, one or more other operations can be added to the flowcharts or one or more operations can be removed from the flowcharts under the guidance of the content of the present application.

[0041] In addition, the described embodiments are only some of the embodiments of the present application, not all the embodiments. The components of the embodiments of the present application described and shown in the accompanying drawings can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the accompanying drawings is not intended to limit the scope of the claimed present application, but only represents selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0042] It should be noted that the term "comprising" will be used in the embodiments of the present application to indicate the presence of the features declared thereafter, but does not exclude the addition of other features.

[0043] In view of the technical problems proposed in the background art, the present application provides a new energy station area communication resource management method and device based on entropy value, which can effectively improve the orderliness and efficiency of the communication network through entropy value monitoring and management, and ensure the reasonable allocation and utilization of network resources.

[0044] In an embodiment, referring to the description accompanying Figure 1 The present application provides a new energy station area communication resource management method based on entropy value, which comprises the following steps:

[0045] S1, virtualizing the physical communication resources of the new energy station area to obtain virtual resources, and abstracting the virtual resources into services of various types of businesses; the various types of businesses include at least one of control type business, collection type business, and maintenance type business;

[0046] S2. Monitor the network data of the new energy substation in real time and calculate the entropy value. When the entropy value exceeds the set threshold, optimize the service quality for each type of business to adjust the communication resources to reduce the entropy value. The entropy value is calculated based on the service quality metric, and the service quality metric includes the response time, success rate, reliability and load rate in the network data.

[0047] In step S1, the physical communication resources of the new energy station area can be virtualized to obtain virtual resources using software-defined networking (SDN) and network function virtualization (NFV), and the virtual resources can be abstracted into services for various businesses for flexible adjustment and efficient utilization.

[0048] For example, by deploying an SDN controller and connecting it to physical network devices (such as switches and routers) within a new energy substation, and configuring the communication protocol between the controller and the devices, the controller can centrally manage and control the network devices. The SDN controller collects resource information about physical network devices, including port numbers, port rates, link bandwidth, and device load. Based on this information, it abstracts physical network resources into virtual resources. The SDN controller can then dynamically combine and configure the resources of physical network devices based on upper-layer service requirements, forming a virtual network topology and providing customized network services for different services.

[0049] Alternatively, an NFV management platform can be built. Virtualization software can be installed on general-purpose servers to create virtual machines or container environments, and network functions (such as firewalls, load balancing, and intrusion detection) can be deployed as software within these virtual machines or containers. Based on business needs, the NFV management platform partitions the server's physical resources (CPU, memory, storage, etc.) into multiple virtual resource pools, each allocated to a specific virtual network function. Furthermore, the NFV management platform decouples network functions from dedicated hardware devices and runs them as software on general-purpose servers. These software-based network functions can be flexibly deployed and configured as needed, becoming part of the service.

[0050] In addition, it is necessary to conduct a detailed analysis of the communication needs within the new energy area to clarify which businesses require high-frequency collection, which businesses require real-time monitoring, and the specific requirements of these businesses for communication resources. In this application, the business types in the new energy area are divided into control, collection and maintenance, and multiple dedicated channels are allocated for each type of business. Among them, control services have the highest priority in the new energy area. These services have extremely high real-time requirements and must ensure that control instructions can reach the execution equipment in a timely and accurate manner; collection services are mainly responsible for collecting data from various equipment and environments in the new energy area. The dedicated channels for these services need to have a high bandwidth and a certain degree of reliability to ensure that a large amount of real-time data can be quickly and accurately transmitted to the data center for analysis and processing; maintenance services are mainly used to handle faults and problems in the communication system. Its dedicated channels need to have rapid response capabilities and a certain priority so that fault information and maintenance instructions can be transmitted in a timely manner when a fault occurs.

[0051] In step S2, the entropy value is calculated to determine the uncertainty and chaos in the new energy substation communication network. This is used to improve the multi-mode mutual communication technology capabilities of the active distribution network, continuously optimize communication resource management, and thus improve the orderliness and efficiency of the communication network. When the entropy value is monitored to increase, it indicates that the uncertainty and chaos in the system are increasing. In order to timely adjust and optimize the allocation of communication resources and ensure the efficiency and reliability of control services, the entropy value needs to be reduced in a timely manner.

[0052] Specifically, in this application, response time, success rate, reliability and load rate are used as service quality QoS metrics, and are quantitatively defined respectively.

[0053] The response time consists of three parts: local processing time T deal (R ij ), system intermediate overhead T mid (R ij ) and network transmission time T net (R ij ), the total response time is Q ij.time =T deal (R ij )+T mid (R ij )+T net (R ij ).

[0054] The success rate is the ratio of the number of successful business transmissions to the total number of transmissions: where N r (R ij ) indicates that the service is in channel R ij Number of successful transmissions, Nf (R ij ) indicates that the service is in channel R ij The number of transmission failures.

[0055] The reliability is the probability that the channel is available Where T r (R ij ) represents the channel resource R ij The average available time, T f (R ij ) indicates resource R ij The average unavailable time.

[0056] The load rate is the service in channel R ij Load rate Where T u (R ij ) indicates occupied resources, T n (R ij ) indicates unoccupied resources.

[0057] Then let R ij It means that the i-th available channel is selected after searching for the j-th service, and the resource R ij The quality of service is denoted as Q ij , represented by the following vector: Q ij =(Q ij.time ,Q ij.suc_rate ,Q ij.reliability ,Q ij.load ). At the same time, define entropy in:

[0058]

[0059]

[0060] Where w=(w k ,1≤k≤4,Σw k =1) represents the weight of the service quality metric; in this application, Q ij.time It is a negative metric, the higher its value, the lower the quality; positive metrics include Q ij.suc_rate , Q ij.reliability , Q ij.load The higher the value, the higher the quality. The entropy function H constructed i (p) can characterize the QoS scale of communication resources. According to this definition, the more stable the QoS of communication resources is, the greater the cost-effectiveness of the resources is. i (p) is larger, then let H′ i (p)=-lnH i(p), that is, by taking the negative logarithm, we can obtain the QoS stability scale-entropy scale that characterizes the communication resources.

[0061] See the instructions attached Figure 2 When optimizing the quality of service for control services / collection services, a local search algorithm is used, which includes the following steps:

[0062] S201. Determine the number of control service / collection service requests, and for each control service / collection service request, determine the number of communication resources that meet the requirements.

[0063] S202: Randomly select one communication resource from each control service / collection service request to form an initial resource allocation scheme as an initial solution, and set an objective function that minimizes the entropy value and meets the upper limit requirement of the service response time;

[0064] S203, using a random perturbation strategy to obtain an initial point, and defining a domain structure based on a response time critical path node sequence to determine a communication resource adjustment direction;

[0065] S204, starting from the initial solution, searching within the defined neighborhood structure, adjusting the current resource allocation scheme, and obtaining a neighborhood solution;

[0066] S205. Calculate the entropy value and service response time corresponding to each neighborhood solution to determine whether the objective function requirements are met; if so, update the current optimal solution to the neighborhood solution; if not, continue searching within the defined neighborhood structure until the set stopping condition is met, and output the current optimal solution as the optimized resource allocation plan.

[0067] In step S201, the number of control-type service / collection-type service requests in the system is determined, and for each control-type service / collection-type service request, the number of communication resources that meet the conditions is determined. These communication resources cover different attributes such as channels, bandwidths, and transmission rates, forming a resource set for selection. For example, if there are M1 control-type service requests in the system, each service request has N1 communication resources that can meet the conditions. Find a solution from the solutions to optimize in order to reduce the entropy value; for example, there are M2 collection-type business requests in the system, and each business request has N2 communication resources that can meet the conditions. Find a solution to optimize among the solutions to reduce the entropy value.

[0068] In step S202, a random selection of communication resources from each control / collection service request is used to form an initial resource allocation scheme, serving as the initial solution. For example, for the control service of distributed power generation device A, wireless communication channel 1 is randomly selected; for device B, wired Ethernet link 2 is selected, and so on. Simultaneously, an objective function is set to minimize entropy while meeting the upper limit on service response time. This objective function is related to response time, success rate, reliability, and load factor, and is calculated using the aforementioned formula.

[0069] In step S203, in order to prevent the initial solution from falling into a local optimum, a random perturbation strategy is used to obtain an initial point; and the algorithm domain structure is defined based on the response time critical path node sequence to clarify the resource adjustment direction. In one embodiment, the domain structure is defined by the following formula:

[0070]

[0071] Among them, x i ∈X k , X k =(x1,x2...x n ) is a sequence of nodes on the critical path of the X response time. The critical path node sequence includes the nodes that have the greatest impact on the response time throughout the entire process from the issuance of the service instruction to its final execution, such as the control instruction issuance node, network transmission node, and device reception node.

[0072] In step S204-step S205, during the search process within the defined neighborhood structure starting from the initial solution, the number of consecutive steps in which no better solution is found is recorded, as well as the degree of convergence of the consecutive set number of steps. If the number of consecutive steps in which no better solution is found reaches a set first threshold, or the degree of convergence of the consecutive set number of steps is less than a set second threshold, the current neighborhood solution is randomly perturbed.

[0073] Specifically, during the search within the defined neighborhood structure, after a certain number of neighborhood searches, it is determined whether the solution has fallen into a local minimum state. The judgment is based on whether a better solution to the objective function, i.e., a solution with a smaller entropy value and a better response time, has not been found in consecutive steps. For example, in the process of optimizing control-type service resources, if after adjusting the resource allocation plan for 10 consecutive steps, the resource QoS entropy has not decreased or the service response time has not been further improved, then it is very likely that the current solution has already reached a local minimum, and continuing to search in this direction may not lead to a global optimal solution. In this case, a random perturbation strategy is implemented to jump out of the local minimum area and continue searching.

[0074] Alternatively, during the search within a defined neighborhood structure, a low degree of convergence over a certain number of consecutive steps means that the solution changes very little, indicating that the algorithm has reached a stable state. However, this state may only be a local optimum, not a global optimum. For example, when optimizing resources for a collection service, if adjusting resource allocation over 100 consecutive steps only results in a small change in resource QoS entropy, a random perturbation strategy may be implemented to re-direct the search to escape the local minimum.

[0075] When the stopping condition is met (for example, no better solution is found within consecutive steps), the search stops and the current optimal solution is output. This optimal solution is the resource allocation plan optimized for control services / collection services. It can minimize resource entropy while meeting the upper limit requirements of service response time, thereby ensuring the efficiency and reliability of control services / collection services.

[0076] Furthermore, for maintenance services, a high packet loss rate increases the system's stability entropy. Excessively high load rates can lead to uneven resource allocation and increased data transmission delays, which in turn increases system uncertainty and the entropy value. For maintenance services, excessively high or low channel utilization is detrimental to system stability, further impacting the entropy value. Therefore, when optimizing quality of service: when the packet loss rate exceeds the third threshold, the transmission rate is reduced and channel time slots are shortened; when an increase in service traffic is detected and the load rate does not exceed the fourth threshold, the transmission rate is increased and channel time slots are added; when an increase in service traffic is detected and the load rate exceeds the fourth threshold, new channels are activated based on priority; when channel utilization is detected below the fifth threshold, channels are reclaimed; and when channel utilization is detected above the sixth threshold, new channels are activated based on priority.

[0077] Specifically, when a high packet loss rate is detected, the system first implements measures such as reducing the transmission rate and channel time slots. This step aims to initially alleviate packet loss by reducing data transmission volume and channel occupancy. This may be due to the channel's inability to handle the current transmission rate or improper time slot configuration. Furthermore, if the problem persists, the system immediately reports it to the platform and notifies personnel for repair. Service transmission on the channel is interrupted, and service requests are prioritized and stored in a waiting area. For control services, personnel are additionally notified to add a new channel for transmission to ensure continuity of control commands and prevent channel failures from impacting system control functions. If a channel is determined to be experiencing interference but the interference is not persistent, service transmission on the channel is interrupted and resumed after the interference ends, minimizing the impact of unstable interference on service data. If the interference persists, the system also reports it to the platform and notifies personnel for repair. Service transmission on the channel is interrupted, and service requests are stored in a waiting area. For control services, personnel are notified to add a new channel to ensure normal service operation during the channel repair period.

[0078] When the service transmission volume is detected to increase, firstly, it is judged whether the load rate of the occupied channel exceeds 80%, which is set based on the load bearing capacity and performance optimization of the channel, and exceeding the load rate can cause problems such as transmission delay and packet loss. Among them, if the load rate does not exceed 80%, the transmission rate is accelerated and the channel time slot is increased, so as to fully utilize the existing channel resources to meet the increasing service transmission demand. If the demand still cannot be met, it is further judged whether there is a free channel, so as to expand the resources if necessary. If the load rate exceeds 80% and there is a free channel, a new channel is enabled to share the service transmission pressure. If the existing resources are insufficient, the staff is immediately notified to add a new channel for the control type service to ensure the normal operation of its high priority service; for the acquisition type service, the low priority request is interrupted, and the request with higher priority is allocated to the free channel, so as to reasonably allocate the limited resources and give priority to the data transmission of important services.

[0079] When the channel utilization rate is detected to be lower than 10%, it is further judged whether the occupied channel has sufficient capacity. If there is no sufficient capacity, the channel is not recovered to avoid insufficient subsequent service transmission resources due to the recovery of the channel; if there is sufficient capacity, the service is migrated to a channel with lower utilization rate, and the services are reordered according to the priority of the service request, the channel with low utilization rate is recovered, and the utilization rate of the overall channel resources is improved. When the channel utilization rate is higher than 80%, firstly, it is judged whether there is a free channel, if there is, a new channel is enabled; if there is not, the staff is immediately notified to add a new channel for the control type service, and for the acquisition type service, the low priority request is interrupted, and the request with higher priority is allocated to the free channel, so as to ensure that the channel resources can meet the service demand and avoid affecting the service performance due to channel overload.

[0080] It can be seen that the new energy transformer area communication resource management method based on entropy value provided by the present application can effectively measure and control the uncertainty and chaos degree in the communication network, thereby improving the orderliness and efficiency of the communication network. Moreover, it can flexibly cope with various communication demands, especially in the high-frequency acquisition and real-time monitoring double-service scenario of the new energy transformer area, thereby ensuring the stability and reliability of the communication network.

[0081] Based on the same inventive concept, the present application also provides a new energy transformer area communication resource management device based on entropy value. Since the principle of solving problems in the device of the present application is similar to the above-mentioned new energy transformer area communication resource management method based on entropy value, the implementation of the device can be referred to the implementation of the method, and the repeated parts will not be described here.

[0082] As shown in the accompanying drawings Figure 3 The device for managing communication resources in a new energy transformer area based on entropy value provided by the present application comprises:

[0083] The conversion module 301 is configured to virtualize the physical communication resources of the new energy station area to obtain virtual resources, and abstract the virtual resources into services of various types of business; the various types of business include at least one of control services, collection services, and maintenance services;

[0084] The management module 302 is used to monitor the network data of the new energy substation in real time and calculate the entropy value. When the entropy value exceeds the set threshold, the service quality is optimized for each type of business to adjust the communication resources to reduce the entropy value; wherein the entropy value is calculated based on the service quality metric, and the service quality metric includes the response time, success rate, reliability and load rate in the network data.

[0085] In one embodiment, the conversion module 301 virtualizes the physical communication resources of the new energy station area to obtain virtual resources using software-defined networking (SDN) and network function virtualization (NFV).

[0086] In one embodiment, the management module 302 calculates the entropy value H′ using the following formula: i (p):

[0087] H′ i (p)=-lnH i (p)

[0088]

[0089] Among them, H i (p) represents the QoS scale of communication resources; Q ij It indicates the quality of service of the i-th available channel selected for the j-th service communication, and Q ij =(Q ijk ,1≤k≤4), k represents the number of the quality of service metric, max(Q ijk ) represents Q ij The maximum value of the kth quality of service metric, w represents the weight of the quality of service metric, w = (w k ,1≤k≤4,Σw k =1).

[0090] In an embodiment, the management module 302 employs a local search algorithm for quality of service optimization for control type traffic / gathering type traffic, including: determining the number of control type traffic / gathering type traffic requests, and for each control type traffic / gathering type traffic request, determining the number of communication resources that meet the conditions thereof; randomly selecting one from each of the communication resources of the control type traffic / gathering type traffic request to form an initial resource allocation scheme as an initial solution, and setting a target function that minimizes the entropy value and meets the upper limit requirement of service response time; employing a random disturbance strategy to obtain an initial point, and defining a domain structure based on a sequence of response time critical path nodes to determine the adjustment direction of the communication resources; starting from the initial solution to search within the defined domain structure to adjust the current resource allocation scheme to obtain a neighborhood solution; calculating the entropy value and service response time corresponding to each neighborhood solution to determine whether the target function requirement is met; if met, updating the current optimal solution as the neighborhood solution; if not met, continuing to search within the defined domain structure; until a set stop condition is met, outputting the current optimal solution as the optimized resource allocation scheme.

[0091] In an embodiment, the management module 302 formulates a random disturbance strategy by: recording the number of steps in which no better solution is found consecutively and recording the convergence degree of the set number of steps during the search within the defined domain structure; if the number of steps in which no better solution is found consecutively reaches a set first threshold value, or the convergence degree of the set number of steps is less than a set second threshold value, randomly disturbing the current neighborhood solution.

[0092] In an embodiment, the management module 302 defines the domain structure by the following formula:

[0093]

[0094] wherein x i ∈X k , X k =(x1,x2...x n ) is the sequence of response time critical path nodes of X.

[0095] In an embodiment, when the management module 302 performs quality of service optimization for maintenance type traffic, including: when detecting that the data packet loss rate exceeds a third threshold value, reducing the transmission rate and reducing the channel time slot; when detecting that the traffic transmission volume increases and the load rate does not exceed a fourth threshold value, increasing the transmission rate and increasing the channel time slot; when detecting that the traffic transmission volume increases and the load rate exceeds the fourth threshold value, enabling a new channel according to the priority; when detecting that the channel utilization rate is lower than a fifth threshold value, performing channel recycling; when detecting that the channel utilization rate is higher than a sixth threshold value, enabling a new channel according to the priority.

[0096] The present application provides a new energy station area communication resource management device based on entropy value, which virtualizes the physical communication resources of the new energy station area to obtain virtual resources through a conversion module, and abstracts the virtual resources into services for various types of businesses; monitors the network data of the new energy station area in real time and calculates the entropy value through a management module, and when the entropy value exceeds the set threshold, optimizes the service quality for various types of businesses to adjust the communication resources to reduce the entropy value; wherein the entropy value is calculated based on the service quality metric, and the service quality metric includes the response time, success rate, reliability and load rate in the network data. Thus, the concept of entropy value is introduced into communication resource management to measure the uncertainty and chaos of the system, and by monitoring and controlling the entropy value, the orderliness and efficiency of the communication network can be effectively improved, the rational allocation and utilization of network resources can be ensured, and the efficient and reliable transmission of data in the new energy station area can be strongly supported.

[0097] Based on the same concept of the present invention, the specification Figure 4 As shown, an embodiment of the present application provides a structure of an electronic device 400, which includes: at least one processor 401, at least one network interface 404 or other user interface 403, a memory 405, and at least one communication bus 402. The communication bus 402 is used to achieve connection and communication between these components. The electronic device 400 optionally includes a user interface 403, including a display (for example, a touch screen, LCD, CRT, holographic imaging (Holographic) or projection (Projector), etc.), a keyboard or a pointing device (for example, a mouse, trackball (trackball), touchpad or touch screen, etc.).

[0098] The memory 405 may include a read-only memory and a random access memory, and provides instructions and data to the processor 401. A portion of the memory 405 may also include a non-volatile random access memory (NVRAM).

[0099] In some embodiments, the memory 405 stores the following elements, executable modules, or data structures, or a subset or extended set thereof:

[0100] Operating system 4051, including various system programs for implementing various basic services and processing hardware-based tasks;

[0101] The application module 4052 includes various application programs, such as a launcher, a media player, a browser, etc., which are used to implement various application services.

[0102] In an embodiment of the present application, by calling the program or instructions stored in the memory 405, the processor 401 is used to execute steps in a new energy station area communication resource management method based on entropy value, which can effectively improve the orderliness and efficiency of the communication network through entropy value monitoring and management, and ensure the rational allocation and utilization of network resources.

[0103] The present application also provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the steps in the method for managing communication resources of new energy stations based on entropy values ​​are executed.

[0104] Specifically, the storage medium can be a general storage medium, such as a mobile disk, a hard disk, etc. When the computer program on the storage medium is run, it can execute the above-mentioned entropy-based new energy station area communication resource management method.

[0105] In the embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interface, the indirect coupling or communication connection of the device or unit can be electrical, mechanical or other forms.

[0106] Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0107] In addition, each functional unit in the embodiments provided in the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0108] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the various embodiments of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0109] Finally, it should be noted that the above embodiments are only specific implementation methods of the present application, which are used to illustrate the technical solutions of the present application, rather than to limit them. The scope of protection of the present application is not limited thereto. Although the present application has been described in detail with reference to the above embodiments, those skilled in the art should understand that any person skilled in the art can modify or easily conceive of changes to the technical solutions described in the above embodiments within the technical scope disclosed in the present application, or replace some of the technical features therein with equivalents. However, these modifications, changes, or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application. They should all be included in the scope of protection of the present application. Therefore, the scope of protection of the present application should be based on the scope of protection of the claims.

Claims

1. A method for managing communication resources in new energy areas based on entropy, characterized in that: The method comprises the following steps: Virtualizing the physical communication resources of the new energy station area to obtain virtual resources, and abstracting the virtual resources into services of various types of business; the various types of business include at least one of control business, collection business, and maintenance business; The network data of the new energy substation is monitored in real time and the entropy value is calculated. When the entropy value exceeds the set threshold, the service quality is optimized for each type of business to adjust the communication resources to reduce the entropy value. The entropy value is calculated based on the service quality metric, and the service quality metric includes the response time, success rate, reliability and load rate in the network data.

2. The method for managing new energy area communication resources based on entropy value according to claim 1, characterized in that: in, Software-defined networking (SDN) and network function virtualization (NFV) are used to virtualize the physical communication resources of the new energy substation to obtain virtual resources.

3. The method for managing new energy area communication resources based on entropy value according to claim 1, characterized in that: The entropy value is calculated by the following formula : （k=2，3，4） in, Indicates the QoS scale of communication resources; represents the quality of service of the i-th available channel selected for the j-th service communication, and , A number representing a quality of service metric, express In the The maximum value of the service quality metric, represents the weight of the service quality metric, .

4. The method for managing new energy area communication resources based on entropy value according to claim 3, characterized in that: For control services and collection services, a local search algorithm is used to optimize service quality, including the following steps: Determine the number of control service / collection service requests, and for each control service / collection service request, determine the number of communication resources that meet the conditions; Randomly select one communication resource from each control service / collection service request to form an initial resource allocation scheme as the initial solution, and set the objective function that minimizes the entropy value and meets the upper limit requirement of the service response time; A random perturbation strategy is used to obtain the initial point, and the domain structure is defined based on the response time critical path node sequence to determine the communication resource adjustment direction; Starting from the initial solution, search within the defined neighborhood structure, adjust the current resource allocation scheme, and obtain the neighborhood solution; Calculate the entropy value and service response time corresponding to each neighborhood solution to determine whether it meets the objective function requirements; if so, update the current optimal solution to the neighborhood solution; if not, continue searching within the defined neighborhood structure until the set stopping condition is met, and output the current optimal solution as the optimized resource allocation plan.

5. The method for managing communication resources in new energy areas based on entropy value according to claim 4, characterized in that: in, The random perturbation strategy is formulated as follows: During the search within the defined neighborhood structure, the number of consecutive steps without finding a better solution is recorded, as well as the degree of convergence for the set number of consecutive steps. If the number of consecutive steps without finding a better solution reaches the set first threshold, or the degree of convergence for the set number of consecutive steps is less than the set second threshold, the current neighborhood solution is randomly perturbed.

6. The method for managing communication resources in a new energy area based on entropy value according to claim 4, characterized in that: The domain structure is defined by the following formula: in, represents the node sequence on the critical path of response time, is the i-th node in the sequence, Representation node neighborhood.

7. The method for managing new energy area communication resources based on entropy value according to claim 4, characterized in that: Optimizing service quality for maintenance services involves the following steps: When it is detected that the data packet loss rate exceeds a third threshold, reducing the transmission rate and the channel time slot; When it is detected that the traffic transmission volume increases and the load rate does not exceed the fourth threshold, the transmission rate is increased and the channel time slot is added; when it is detected that the traffic transmission volume increases and the load rate exceeds the fourth threshold, a new channel is enabled according to the priority; When it is detected that the channel utilization rate is lower than the fifth threshold, channel recovery is performed; when it is detected that the channel utilization rate is higher than the sixth threshold, a new channel is enabled according to the priority.

8. A new energy area communication resource management device based on entropy value, characterized in that: The device comprises: A conversion module is used to virtualize the physical communication resources of the new energy station area to obtain virtual resources, and abstract the virtual resources into services of various types of business; the various types of business include at least one of control business, collection business, and maintenance business; The management module is used to monitor the network data of the new energy substation in real time and calculate the entropy value. When the entropy value exceeds the set threshold, the service quality is optimized for various services to adjust communication resources to reduce the entropy value. The entropy value is calculated based on the service quality metric, which includes the response time, success rate, reliability and load rate in the network data.

9. An electronic device, characterized in that: include: A processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor. When the electronic device is running, the processor and the memory communicate through the bus. When the machine-readable instructions are executed by the processor, the steps of the new energy station area communication resource management method based on entropy value are performed as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, which, when executed by a processor, executes the steps of the method for managing new energy station area communication resources based on entropy as described in any one of claims 1 to 7.

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