Power distribution network management and control system and method
Through the setting calculation module, data collaboration module and safety protection module in the distribution network management and control system, the time-consuming and error problems caused by manual operation are solved, fast and accurate setting calculation and all-round safety protection are achieved, and the management and control effect and reliability of the distribution network are improved.
Patent Information
- Application Number
- CN202510760146.4
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-06-09
- Publication Date
- 2025-09-05
AI Technical Summary
The existing distribution network control system relies on manual operation, which is time-consuming and labor-intensive and easily affected by human factors. The setting calculation results have large errors and the control effect is poor.
Adopting the setting calculation module, data collaboration module and control module, data cleaning, federated learning algorithm and non-dominated sorting genetic algorithm are used to perform data collaborative processing and setting calculation, combined with the security protection module for permission control and data encryption to build a comprehensive security protection system.
It achieves fast and accurate setting calculation results, improves the effect and reliability of distribution network management and control, and ensures the safety and stability of the system.
Smart Images
Figure CN120601619A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of power distribution networks, and in particular to a power distribution network management and control system and method. Background Art
[0002] In recent years, with the rapid development of the electric power industry, the complexity and scale of distribution networks have increased dramatically, encompassing a diverse range of power equipment and multiple management entities. This trend has placed higher demands on the setting calculations, control, and management of distribution networks. Existing distribution network management and control systems require manual operation to perform equipment setting calculations and adjust equipment parameters based on the setting calculation results. However, relying on manual operation for distribution network management and control is not only time-consuming and labor-intensive, but also susceptible to human factors, resulting in large errors in the setting calculation results and poor control of distribution network equipment. Summary of the Invention
[0003] The present invention provides a distribution network control system and method, which can solve the technical problems in the prior art that distribution network control relies on manual operation, which is not only time-consuming and labor-intensive, but also easily affected by human factors, resulting in large errors in setting calculation results and poor control effect on distribution network equipment.
[0004] The present invention provides a distribution network management and control system, comprising:
[0005] A setting calculation module is used to collect operating data of several devices in the distribution network, send the operating data to the data collaboration module, update the global model data returned by the data collaboration module, update the setting algorithm model stored locally in the device, and perform setting calculations on each device based on the updated setting algorithm model and the pre-processed data returned by the data collaboration module to obtain setting calculation results, and transmit the setting calculation results to the control module;
[0006] a data collaboration module, configured to obtain the operating data transmitted by the setting calculation module, collaboratively process the operating data, obtain global model update data and pre-processed data of a plurality of devices, and transmit the data to the setting calculation module;
[0007] The control module is used to adjust the device parameters of each device according to the setting calculation results transmitted by the setting calculation module.
[0008] Furthermore, the data collaboration module is specifically used to:
[0009] performing data cleaning, data conversion, and data compression processing on the operating data in sequence to obtain preprocessed data;
[0010] Use federated learning algorithms to collaboratively process preprocessed data and generate global model update data;
[0011] The global model update data and the pre-processed data are transmitted to the tuning calculation module.
[0012] Furthermore, the setting calculation is performed on each device according to the updated setting algorithm model and the pre-processed data returned by the data collaboration module to obtain a setting calculation result, including:
[0013] Acquire multiple optimization objectives for each device to be tuned, define corresponding indicators for each optimization objective based on the preprocessed data, and construct a multi-objective optimization model based on the multiple optimization objectives;
[0014] The multi-objective optimization model is solved using a non-dominated sorting genetic algorithm, with parameter combinations as individuals. During the solution process, the crowding distance of each individual in the population is calculated, and individuals corresponding to crowding distances greater than a preset threshold are selected for genetic operations. When a preset iteration condition is met, a candidate parameter combination set is output, and the candidate parameter combination set is the solution result of the multi-objective optimization model.
[0015] A multi-objective tuning calculation is performed based on the updated tuning algorithm model and the solution result to obtain a tuning calculation result, which is the optimal parameter combination in the candidate parameter combination set.
[0016] Furthermore, the expression of the crowding distance is:
[0017]
[0018] Among them, d i is the crowding distance of individual i, f k (i+1) and f k (i-1) are the function values of the two individuals adjacent to individual i on target k; and are the maximum and minimum values of target k in the current population respectively.
[0019] Furthermore, the security protection module is also used to:
[0020] Receive the business data transmitted by the business extension module, adopt a threat situation awareness model based on machine learning, perceive and predict the threat situation based on the business data, and obtain the threat level of the distribution network.
[0021] Furthermore, the distribution network management and control system also includes a business extension module, which is used to build a standardized interface set and an extensible module framework, wherein the standardized interface set includes a data interface, a service interface, and a plug-in interface; the data interface is used to convert different data types and formats; the service interface is used to adopt modern network communication protocols to achieve remote calls and distributed deployment; the plug-in interface is used to provide a third-party developer interface;
[0022] The expandable module framework is used to modularize a plurality of devices according to their functions.
[0023] Furthermore, the distribution network management and control system also includes a security protection module, which is used to control the authority of data access to the business extension module and perform data encryption and privacy protection processing on the business data transmitted by the business extension module.
[0024] Furthermore, the security protection module is also used to:
[0025] Utilizing a role-based access control model, dynamically adjusting data access permissions of the business extension module based on environmental context data, wherein the environmental context data includes user request, time, location, and device status;
[0026] The business data transmitted by the business extension module is homomorphically encrypted and differentially privately processed.
[0027] Furthermore, the security protection module is also used to:
[0028] By recording and analyzing key information during the operation of the distribution network system, determining whether there is a security incident by analyzing the key information, and triggering the emergency response process when a security risk is detected, the key information includes system operation logs and security incidents.
[0029] Furthermore, the use of a role-based access control model to dynamically adjust the data access permissions of the business extension module according to environmental context data includes:
[0030] In the role-based access control model, basic permissions are pre-assigned according to the user's role. When the user accesses data in the business extension module, the corresponding security policy and business rules are matched according to the environmental context and the preset security policy and business rules.
[0031] The basic permissions are adjusted based on the security policy and the business rules.
[0032] The present invention provides a distribution network management and control method, which is applicable to the distribution network management and control system as described above, comprising:
[0033] Collecting operating data of several devices in the distribution network, sending the operating data to the data collaboration module, updating the global model data returned by the data collaboration module, updating the setting algorithm model stored locally on the device, and performing setting calculations on each device based on the updated setting algorithm model and the pre-processed data returned by the data collaboration module to obtain setting calculation results, and transmitting the setting calculation results to the control module;
[0034] Acquiring the operating data transmitted by the setting calculation module, collaboratively processing the operating data to obtain global model update data and preprocessing data of a plurality of devices, and transmitting the global model update data and preprocessing data to the setting calculation module;
[0035] According to the setting calculation results transmitted by the setting calculation module, the device parameters of each device are adjusted accordingly.
[0036] The present invention performs global model updates and setting calculations on the data returned by the data collaboration module based on the setting calculation module, without relying on manual setting calculations, effectively reducing human calculation errors, and thus being able to accurately and quickly obtain the setting calculation results of the equipment, and then being able to adjust the equipment parameters based on the setting calculation results, so that the operation of the distribution network system meets the needs of various scenarios and effectively improves the effect of distribution network management and control; and the embodiment of the present invention performs collaborative processing of operation data through the data collaboration module, which can effectively promote data sharing and collaboration, provide comprehensive data support for subsequent setting calculations and distribution network management and control, and effectively improve the reliability of distribution network management and control.
[0037] Furthermore, the present invention can effectively build a comprehensive security protection system by controlling data access permissions and encrypting and protecting business data through the security protection module. By adopting multiple security measures to ensure the stable operation of the distribution network system, it can effectively resist external threats, thereby effectively improving the security and reliability of distribution network management and control. BRIEF DESCRIPTION OF THE DRAWINGS
[0038] In order to more clearly illustrate the technical solution of the present application, the following is a brief introduction to the drawings required for use in the implementation. Obviously, the drawings described below are only some implementation methods of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.
[0039] Figure 1 This is a schematic structural diagram of a distribution network management and control system provided by an embodiment of the present invention;
[0040] Figure 2 It is a flow chart of a distribution network control method provided by an embodiment of the present invention. DETAILED DESCRIPTION
[0041] To make the objectives, technical solutions, and advantages of this application more clear, the technical solutions in this application will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of this application. Obviously, the described embodiments are only part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making any creative efforts are within the scope of protection of this application.
[0042] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this application belongs; the terms used herein are only for the purpose of describing specific embodiments and are not intended to limit this application; the terms "including" and "having" and any variations thereof in the specification and claims of this application and the above-mentioned figure descriptions are intended to cover non-exclusive inclusions.
[0043] In the description of the embodiments of this application, the technical terms "first" and "second" are used only to distinguish different objects and should not be understood to indicate or imply relative importance or implicitly specify the quantity, specific order, or primary and secondary relationship of the indicated technical features. In the description of the embodiments of this application, the meaning of "plurality" is more than two, unless otherwise clearly and specifically defined.
[0044] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute an independent or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.
[0045] In the description of the embodiments of this application, the term "and / or" is simply a description of the association relationship between associated objects, indicating that three relationships can exist. For example, A and / or B can represent the following three situations: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " in this document generally indicates that the associated objects are in an "or" relationship.
[0046] In the description of the embodiments of the present application, the term "multiple" refers to more than two (including two). Similarly, "multiple groups" refers to more than two groups (including two groups), and "multiple pieces" refers to more than two pieces (including two pieces).
[0047] In the description of the embodiments of the present application, unless otherwise expressly specified or limited, technical terms such as "installed," "connected," "connected," and "fixed" should be understood in a broad sense. For example, they can refer to fixed connections, detachable connections, or integration; mechanical connections or electrical connections; direct connections or indirect connections through an intermediate medium; internal connections between two components or interactions between two components. Those skilled in the art can understand the specific meanings of the above terms in the embodiments of the present application based on specific circumstances.
[0048] See also Figure 1 In order to solve the technical problem that the existing technology relies on manual operation to achieve distribution network control, which is not only time-consuming and labor-intensive, but also easily affected by human factors, resulting in large errors in setting calculation results and poor control effect on distribution network equipment, the present invention provides a distribution network control system according to one embodiment of the present invention, including:
[0049] The setting calculation module 10 is used to collect operating data of several devices in the distribution network, send the operating data to the data collaboration module 20, update the global model data returned by the data collaboration module 20, update the setting algorithm model stored locally on the device, and perform setting calculations on each device based on the updated setting algorithm model and the pre-processed data returned by the data collaboration module 20 to obtain setting calculation results, and transmit the setting calculation results to the control module;
[0050] In an embodiment of the present invention, the equipment in the distribution network includes at least one of a line, a transformer, a capacitor, and a circuit breaker.
[0051] a data collaboration module 20 for acquiring the operating data transmitted by the setting calculation module 10, collaboratively processing the operating data, obtaining global model update data and pre-processed data of a plurality of devices, and transmitting the data to the setting calculation module 10;
[0052] In the embodiment of the present invention, the data collaboration module 20 can also break down data silos and achieve seamless connection and efficient circulation of data by constructing a unified data model and interface standard.
[0053] The control module 30 is used to adjust the device parameters of each device according to the setting calculation results transmitted by the setting calculation module 10.
[0054] The embodiment of the present invention performs global model update and setting calculation on the data returned by the data collaboration module 20 according to the setting calculation module 10, without relying on manual setting calculation, so that the setting calculation results of the equipment can be obtained accurately and quickly, and then the equipment parameters can be adjusted based on the setting calculation results, so that the operation of the distribution network system meets the needs of various scenarios and effectively improves the effect of distribution network management and control; and the embodiment of the present invention performs collaborative processing of operation data through the data collaboration module 20, which can effectively promote data sharing and collaboration, provide comprehensive data support for subsequent setting calculations and distribution network management and control, and effectively improve the reliability of distribution network management and control.
[0055] In one embodiment, the data collaboration module 20 is specifically configured to:
[0056] performing data cleaning, data conversion, and data compression processing on the operating data in sequence to obtain preprocessed data;
[0057] In an embodiment of the present invention, the data may be cleaned and normalized, converted into semantic information that can be processed by an algorithm, and then processed by data compression to improve the quality and availability of the data.
[0058] Use federated learning algorithms to collaboratively process preprocessed data and generate global model update data;
[0059] The global model update data and preprocessed data are transferred to the tuning calculation module.
[0060] In an embodiment of the present invention, by integrating a federated learning algorithm into the data processing and collaboration process, it is possible to achieve joint training and optimization of the model without exposing the original data, thereby effectively solving the privacy protection problem in data collaboration.
[0061] In a specific implementation, assume that there are N management entities in the distribution network, and each entity i holds a local data set D i and the corresponding local model M i The goal of federated learning is to make the local models of all entities gradually approach a global model update data ΔM through iterative updates. global In each iteration, each subject i first runs the data D based on the local collection. i Tuning algorithm model M stored locally i Perform training to get the model update ΔM i These model updates are then sent to a central server for aggregation to generate global model update data ΔM global Finally, the global model update data is distributed back to each agent to update its local model.
[0062]
[0063] Among them, ΔM global represents the global model update data, N represents the number of management entities with several devices, i represents the i-th management entity, D i Indicates the locally collected operating data, |D i | represents the size of the running data set of management subject i, M i Represents the locally stored tuning algorithm model, ΔM i Indicates a model update.
[0064] In an embodiment of the present invention, each management entity can jointly participate in model training without sharing original data, thereby achieving the dual goals of data collaboration and privacy protection.
[0065] Furthermore, each device is tuned based on the updated tuning algorithm model and pre-processed data returned by the data collaboration module to obtain tuning results, including:
[0066] Obtain multiple optimization objectives for each device to be tuned, define corresponding indicators for each optimization objective based on the preprocessed data, and construct a multi-objective optimization model based on the multiple optimization objectives, wherein the expression of the multi-objective optimization model is as follows:
[0067] minF(x)=[f1(x),f2(x),..,f n (x)]
[0068] stg i (x)≤0,i=1,2,..,m
[0069] h j (x)=0,j=1,2,...,p
[0070] Among them, F(x) is a vector function, f n (x) is the nth target to be optimized; x is the decision variable vector, which is the equipment parameter to be adjusted and calculated; g i (x) and h j (x) are inequality constraints and equality constraints for several different equipment constraints;
[0071] In an embodiment of the present invention, the constraints of the inequality constraint include equipment voltage limitation, transformer capacity limitation, line current limitation and inverter power output limitation; the equipment constraint of the equality constraint includes node power limitation, protection device action time limitation and system response time limitation.
[0072] The multi-objective optimization model is solved using a non-dominated sorting genetic algorithm, with parameter combinations as individuals. During the solution process, the crowding distance of each individual in the population is calculated, and individuals corresponding to crowding distances greater than a preset threshold are selected for genetic operations. When a preset iteration condition is met, a candidate parameter combination set is output, and the candidate parameter combination set is the solution result of the multi-objective optimization model.
[0073] In an embodiment of the present invention, a non-dominated sorting genetic algorithm based on the Pareto front can be used to solve multi-objective optimization problems. The non-dominated sorting genetic algorithm based on the Pareto front maintains a heavy punch and sorts and selects individuals according to the Pareto dominance relationship in each generation to guide the search process closer to the Pareto front. In the non-dominated sorting genetic algorithm based on the Pareto front, by calculating the crowding distance of the individual, the density of the solutions around each individual in the target space can be effectively reflected. The expression of the crowding distance is:
[0074]
[0075] Among them, d i is the crowding distance of individual i, which is used to maintain the diversity of the population, avoid premature convergence and fall into the local optimal solution, f k (i+1) and f k (i-1) are the function values of the two individuals adjacent to individual i on target k; and are the maximum and minimum values of target k in the current population respectively.
[0076] The embodiment of the present invention introduces the crowding distance, so that the non-dominated sorting genetic algorithm based on the Pareto front can maintain the diversity of the population during the selection process, thereby avoiding premature convergence and falling into a local optimal solution.
[0077] A multi-objective tuning calculation is performed based on the updated tuning algorithm model and the solution result to obtain a tuning calculation result, which is the optimal parameter combination in the candidate parameter combination set.
[0078] In one embodiment, the security protection module is further configured to:
[0079] Receive the business data transmitted by the business extension module, adopt a threat situation awareness model based on machine learning, perceive and predict the threat situation based on the business data, and obtain the threat level of the distribution network.
[0080] In an embodiment of the present invention, a threat situation awareness model based on learning and application of threat perception and prediction algorithms is used for perception and prediction. The threat perception and prediction algorithms collect and analyze multi-source information such as historical security event data, network traffic characteristics, and user behavior patterns to construct a threat situation awareness model. The key steps are:
[0081] (1) Data preprocessing: Data cleaning and normalization are used to convert raw data into semantic information that can be processed by the algorithm.
[0082] (2) Feature extraction: Use principal component analysis (PCA) and autoencoder to extract key features from high-dimensional data.
[0083] (3) Model training: The long short-term memory network (LSTM) time series analysis model is used in combination with the classification algorithm to identify and predict threat types.
[0084] Assume that the input sequence is X={x1,x2,...,x t}, where X t represents the input feature vector at time t. LSTM updates its internal state using the following formula:
[0085] f t =σ(W f ·[h t-1 , x t ]+b f )
[0086] i t =σ(W i ·[h t-1 , x t ]+b i )
[0087]
[0088] o t =σ(W o ·[ht-1,x t ]+b o )
[0089] h t =o t *tanh(C t );
[0090] Among them, f t 、i t 、o t are the activation values of the forget gate, input gate, and output gate respectively; C t and is the unit state and candidate unit state; h tis the output state at the current moment; σ is the sigmoid activation function; * represents matrix element multiplication; [,] represents vector concatenation; W and b are model parameters, b f 、b i 、b C 、b o is the bias term, b f Represents the bias term corresponding to the forget gate, which determines the memory state (hidden state) h at the previous moment t-1 Should it be retained? i Represents the bias term corresponding to the input gate, which controls the inflow of new information, b C represents the bias term corresponding to the cell state, controlling the storage intensity of new information, b o Represents the bias term corresponding to the output gate, which controls the hidden state h at the current moment t output level.
[0091] In one embodiment, the distribution network management and control system further includes a business extension module, which is used to build a standardized interface set and an extensible module framework, wherein the standardized interface set includes a data interface, a service interface, and a plug-in interface; the data interface is used to convert different data types and formats; the service interface is used to adopt modern network communication protocols to achieve remote calls and distributed deployment; the plug-in interface is used to provide a third-party developer interface;
[0092] In an embodiment of the present invention, the data interface can define clear data exchange formats and protocols to ensure that data can flow smoothly between the business extension module and other modules of the system. The data interface supports conversion of multiple data types and formats to meet data requirements in different business scenarios.
[0093] In an embodiment of the present invention, the service interface can provide a series of standardized service call interfaces, including user management, permission control, and business process processing. Its interface adopts modern network communication protocols such as RESTful or gRPC, and supports remote calls and distributed deployment.
[0094] In an embodiment of the present invention, the plug-in interface can design a flexible plug-in mechanism, allowing third-party developers or users to develop functional modules according to their needs and seamlessly integrate them into the system through the plug-in interface. Among them, the plug-in interface can define the full life cycle management specifications of the plug-in, such as loading, initialization, execution and unloading, thereby improving the management standardization of the plug-in.
[0095] The expandable module framework is used to modularize a plurality of devices according to their functions.
[0096] In the embodiment of the present invention, the business expansion module adopts a modular design and can expand system functions according to actual needs, thereby ensuring that the system can adapt to various scenarios of the distribution network and meet different distribution network management and control requirements.
[0097] In an embodiment of the present invention, an extensible module framework is used to modularize a number of devices according to their functions, and adopt a dynamic management mechanism recorded in the modules to dynamically add, update or delete modules in an uninterrupted system, and configure each divided module according to the received configuration file to adapt to the business needs of different management entities.
[0098] The embodiment of the present invention divides the system into relatively independent modules, each module is responsible for completing independent specific functions, and the modules communicate and collaborate through standardized interfaces, which can effectively reduce the coupling between modules and effectively improve the maintainability and scalability of the system.
[0099] Furthermore, the embodiment of the present invention also supports hot plugging. By realizing the hot plugging function of the module, it is possible to dynamically add, update or delete modules without interrupting the normal operation of the system, thereby improving the flexibility of module operation; and the embodiment of the present invention can also flexibly configure the system's business processes, functional modules, parameter settings, etc. through configuration files or databases, so that the system can be quickly adjusted and optimized according to different business needs.
[0100] In one embodiment, the distribution network management and control system further includes a security protection module, which is used to perform permission control on data access of the business expansion module and perform data encryption and privacy protection processing on the business data transmitted by the business expansion module.
[0101] In an embodiment of the present invention, the security protection module can effectively build a comprehensive security protection system by controlling data access permissions and encrypting and protecting business data. It can also effectively resist external threats by adopting multiple security measures to ensure the stable operation of the distribution network system, thereby effectively improving the security and reliability of distribution network management and control.
[0102] In one embodiment, the security protection module is further configured to:
[0103] Utilizing a role-based access control model, dynamically adjusting data access permissions of the business extension module based on environmental context data, wherein the environmental context data includes user request, time, location, and device status;
[0104] The business data transmitted by the business extension module is homomorphically encrypted and differentially privately processed.
[0105] In an embodiment of the present invention, the data access rights of the business extension module are dynamically adjusted based on the environmental context data, which can effectively prevent unauthorized access and improve the security of the distribution network system. The introduction of a role-based access control model can combine the flexibility of attributes and access control to further achieve fine-grained permission management. The embodiment of the present invention performs homomorphic encryption on business data, allowing calculations on encrypted data without decryption, which can support data analysis needs while protecting data privacy. By introducing differential privacy technology, it can ensure that the data security of each subject is not leaked during the data collaboration process, effectively improving data security.
[0106] In one embodiment, the security protection module is further configured to:
[0107] By recording and analyzing key information during the operation of the distribution network system, determining whether there is a security incident by analyzing the key information, and triggering the emergency response process when a security risk is detected, the key information includes system operation logs and security incidents.
[0108] In an embodiment of the present invention, the security protection module is also used to timely discover potential security risks by recording and analyzing key information such as system operation logs and security events. When a security risk is detected, the emergency response process is immediately triggered. The emergency response process includes isolating the affected system, starting backup recovery, and notifying relevant personnel, etc., thereby minimizing the impact of security incidents on the business and improving the stability of distribution network operation.
[0109] In one embodiment, the security protection module is further configured to:
[0110] In the role-based access control model, basic permissions are pre-assigned according to the user's role. When the user accesses data to the business extension module, the corresponding security policy and business rules are matched according to the environmental context and the preset security policy and business rules.
[0111] The basic permissions are adjusted based on the security policy and the business rules.
[0112] In an embodiment of the present invention, by comprehensively considering environmental context data such as user requests, time, location and device status, it is possible to more accurately determine whether the user's access behavior meets security requirements, thereby effectively improving the reliability of access permission control.
[0113] The implementation of the present invention has the following beneficial effects:
[0114] The embodiment of the present invention performs global model update and setting calculation on the data returned by the data collaboration module 20 according to the setting calculation module 10, without relying on manual setting calculation, so that the setting calculation results of the equipment can be obtained accurately and quickly, and then the equipment parameters can be adjusted based on the setting calculation results, so that the operation of the distribution network system meets the needs of various scenarios and effectively improves the effect of distribution network management and control; and the embodiment of the present invention performs collaborative processing of operation data through the data collaboration module 20, which can effectively promote data sharing and collaboration, provide comprehensive data support for subsequent setting calculations and distribution network management and control, and effectively improve the reliability of distribution network management and control.
[0115] Furthermore, the embodiment of the present invention can effectively build a comprehensive security protection system by controlling data access permissions and encrypting and protecting business data through a security protection module. By adopting multiple security measures to ensure the stable operation of the distribution network system, it can effectively resist external threats, thereby effectively improving the security and reliability of distribution network management and control.
[0116] See also Figure 2 , is a flow chart of a distribution network control method provided by an embodiment of the present invention, the distribution network control method is applicable to the distribution network control system in the above embodiment, wherein;
[0117] Step S1: Collect operating data of several devices in the distribution network, send the operating data to the data collaboration module, update the data according to the global model returned by the data collaboration module, update the setting algorithm model stored locally on the device, and perform setting calculations on each device based on the updated setting algorithm model and the pre-processed data returned by the data collaboration module to obtain the setting calculation results;
[0118] Step S2: Acquire the operating data transmitted by the setting calculation module, perform collaborative processing on the operating data, obtain global model update data and preprocessing data of multiple devices, and transmit them to the setting calculation module;
[0119] Step S3: Adjust the device parameters of each device accordingly according to the setting calculation results transmitted by the setting calculation module.
[0120] The above is a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications are also considered to be within the scope of protection of the present invention.
Claims
1. A distribution network management and control system, characterized in that: include: A setting calculation module is used to collect operating data of several devices in the distribution network, send the operating data to the data collaboration module, update the global model data returned by the data collaboration module, update the setting algorithm model stored locally in the device, and perform setting calculations on each device based on the updated setting algorithm model and the pre-processed data returned by the data collaboration module to obtain setting calculation results, and transmit the setting calculation results to the control module; a data collaboration module, configured to obtain the operating data transmitted by the setting calculation module, collaboratively process the operating data, obtain global model update data and pre-processed data of a plurality of devices, and transmit the data to the setting calculation module; The control module is used to adjust the device parameters of each device according to the setting calculation results transmitted by the setting calculation module.
2. The distribution network management and control system according to claim 1, wherein: The data collaboration module is specifically used for: performing data cleaning, data conversion, and data compression processing on the operating data in sequence to obtain preprocessed data; Use federated learning algorithms to collaboratively process preprocessed data and generate global model update data; The global model update data and the pre-processed data are transmitted to the tuning calculation module.
3. The distribution network management and control system according to claim 1, wherein: The setting calculation is performed on each device based on the updated setting algorithm model and the pre-processed data returned by the data collaboration module to obtain the setting calculation result, including: Acquire multiple optimization objectives for each device to be tuned, define corresponding indicators for each optimization objective based on the preprocessed data, and construct a multi-objective optimization model based on the multiple optimization objectives; The multi-objective optimization model is solved using a non-dominated sorting genetic algorithm, with parameter combinations as individuals. During the solution process, the crowding distance of each individual in the population is calculated, and individuals corresponding to crowding distances greater than a preset threshold are selected for genetic operations. When a preset iteration condition is met, a candidate parameter combination set is output, and the candidate parameter combination set is the solution result of the multi-objective optimization model. A multi-objective tuning calculation is performed based on the updated tuning algorithm model and the solution result to obtain a tuning calculation result, which is the optimal parameter combination in the candidate parameter combination set.
4. The distribution network management and control system according to claim 3, characterized in that: The expression of the crowding distance is: Among them, d i is the crowding distance of individual i, f k (i+1) and f k (i-1) are the function values of the two individuals adjacent to individual i on target k; and are the maximum and minimum values of target k in the current population respectively.
5. The distribution network management and control system according to claim 1, wherein: It also includes a business extension module, which is used to build a standardized interface set and an extensible module framework, wherein the standardized interface set includes a data interface, a service interface, and a plug-in interface; the data interface is used to convert different data types and formats; the service interface is used to adopt modern network communication protocols to achieve remote calls and distributed deployment; the plug-in interface is used to provide a third-party developer interface; The expandable module framework is used to modularize a plurality of devices according to their functions.
6. The distribution network management and control system according to claim 5, characterized in that: It also includes a security protection module, which is used to control the authority of data access of the business expansion module and perform data encryption and privacy protection processing on the business data transmitted by the business expansion module.
7. The distribution network management and control system according to claim 6, characterized in that: The safety protection module is further used for: Receive the business data transmitted by the business extension module, adopt a threat situation awareness model based on machine learning, perceive and predict the threat situation based on the business data, and obtain the threat level of the distribution network.
8. The distribution network management and control system according to claim 7, characterized in that: The safety protection module is also used for: Utilizing a role-based access control model, dynamically adjusting data access permissions of the business extension module based on environmental context data, wherein the environmental context data includes user request, time, location, and device status; The business data transmitted by the business extension module is homomorphically encrypted and differentially privately processed.
9. The distribution network management and control system according to claim 7, characterized in that: The safety protection module is also used for: By recording and analyzing key information during the operation of the distribution network system, determining whether there is a security incident by analyzing the key information, and triggering the emergency response process when a security risk is detected, the key information includes system operation logs and security incidents.
10. The distribution network management and control system according to claim 8, characterized in that: The use of a role-based access control model to dynamically adjust the data access permissions of the business extension module according to environmental context data includes: In the role-based access control model, basic permissions are pre-assigned according to the user's role. When the user accesses data in the business extension module, the corresponding security policy and business rules are matched according to the environmental context and the preset security policy and business rules. The basic permissions are adjusted based on the security policy and the business rules.
11. A distribution network management and control method, characterized in that: A distribution network control system according to any one of claims 1 to 10, comprising: Collecting operating data of several devices in the distribution network, sending the operating data to the data collaboration module, updating the global model data returned by the data collaboration module, updating the setting algorithm model stored locally on the device, and performing setting calculations on each device based on the updated setting algorithm model and the pre-processed data returned by the data collaboration module to obtain setting calculation results, and transmitting the setting calculation results to the control module; Acquiring the operating data transmitted by the setting calculation module, collaboratively processing the operating data to obtain global model update data and preprocessing data of a plurality of devices, and transmitting the global model update data and preprocessing data to the setting calculation module; According to the setting calculation results transmitted by the setting calculation module, the device parameters of each device are adjusted accordingly.