A data security transmission method and system in an interconnected transformer area under uncertain interference

Abstract

The application discloses a kind of data security transmission method and system under the uncertain interference of interconnected transformer area, belong to the data transmission technical field in interconnected transformer area, method includes: obtaining power generation unit data, through Lagrange multiplier method analysis incremental cost and output power calculation paradigm;If not initial time, receive neighbor encrypted data, update weight matrix after attack detection filtering, update incremental cost and power using distributed algorithm;After meeting convergence, output power is quantized and encrypted transmission is decrypted to transformer area intelligent agent node, calculate total demand;Based on total demand, establish transformer area model and convert into dual problem;Receive inter-transformer area encrypted information, update weight matrix after attack detection filtering, update incremental cost and transmission power using distributed algorithm, until meeting convergence output optimal configuration.The application realizes data security circulation and light weight transportation by attack detection filtering, privacy protection and communication quantization mechanism.

Description

Technical Field

[0001] This invention relates to a method and system for secure data transmission under uncertain interference in interconnected network areas, belonging to the field of data transmission technology in interconnected network areas. Background Technology

[0002] In recent years, with the large-scale integration of distributed energy sources (such as photovoltaic, wind power, and energy storage systems), the operation mode of the power system has gradually evolved from centralized dispatch to distributed intelligent dispatch. As an autonomous operating unit at the end of the distribution network, a distribution transformer (DTR) possesses diverse characteristics of energy production and bidirectional interaction. Through distributed economic dispatch, it achieves optimized allocation of power generation resources, helping to improve energy utilization efficiency, reduce operating costs, and enhance system flexibility and power supply reliability. In the distributed economic dispatch of a DTR area, frequent data exchange is required between distributed generation units, including real-time incremental costs and auxiliary variables. This type of information often needs to be transmitted across nodes during the optimization calculation process, thus providing a global decision-making basis for the dispatch algorithm.

[0003] However, with the opening of communication networks and the distribution of scheduling modes, data transmission faces various security threats: the data transmitted by nodes contains sensitive information. Unauthorized access or interception of this data during transmission could lead to privacy breaches. Furthermore, in distributed collaborative scheduling scenarios, some nodes may send false data or perform destructive computations due to malicious intrusion or internal failures; these actions are collectively known as Byzantine attacks. Byzantine nodes can manipulate the consensus process by creating false data, causing scheduling schemes to deviate from optimality and resource allocation to become unbalanced, potentially leading to system instability or economic losses. Therefore, in interconnected distribution areas, uncertain disturbances in the communication network have become a significant concern in the economic scheduling of these areas. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of the prior art and provide a method and system for secure data transmission under uncertain interference in interconnected networks. It aims to solve the problems of privacy theft and Byzantine attacks in communication networks by designing attack detection and filtering mechanisms, privacy protection algorithms, and communication quantization mechanisms to achieve secure data flow and lightweight transportation in communication networks.

[0005] To achieve the above objectives, the present invention is implemented using the following technical solution:

[0006] In a first aspect, the present invention provides a method for secure data transmission under uncertain interference in interconnected network areas, comprising:

[0007] Based on the cost parameters, power constraints and load demand data of each power generation unit in the interconnected distribution area, an economic optimization mathematical model for the distribution area is established, and the calculation paradigm of the optimal incremental cost and output power of each power generation unit is obtained analytically.

[0008] If it is the initial moment, then the incremental cost and output power of each power generation unit are initialized according to the calculation paradigm.

[0009] If it is not the initial moment, the neighbor transmission data received by each power generation unit is obtained, and the dynamic weight matrix is ​​updated after attack detection and anomaly filtering, and the incremental cost and output power of each power generation unit are updated.

[0010] Calculate the power balance residual based on the updated output power, and determine whether the global optimal convergence threshold is met. If it is met, store the output power information; if it is not met and the output power has not reached the upper limit, return to the step of obtaining neighbor transmission data; otherwise, store the output power information.

[0011] The stored output power information is quantized, compressed, and homomorphically encrypted before being transmitted to the intelligent agent node in the distribution area.

[0012] Based on the decryption and restoration of the output power of the intelligent agent node in the transformer area, calculate the backup capacity of each transformer area and the total demand of interconnected transformer areas.

[0013] Based on the total demand scale, an economic scheduling model for interconnected power distribution areas is established and transformed into a global optimal dual problem;

[0014] Within the inter-station area, data from neighboring stations received by each station is acquired. After attack detection and anomaly filtering, the inter-station weight matrix is ​​updated based on blockchain technology.

[0015] By combining the global optimal dual problem, the filtered neighboring station data, and the weight matrix, the incremental cost and transmission power of each station are updated.

[0016] Calculate the cross-domain transmission power balance residual based on the updated transmission power, and determine whether it meets the preset cross-domain convergence threshold. If it does, output the optimal transmission power configuration result between stations; otherwise, return to the step of obtaining neighbor transmission data.

[0017] Furthermore, the method for obtaining cost parameters, power constraints, and load demand data of each power generation unit in the interconnected distribution area includes:

[0018] Obtain the life-cycle cost model parameters for each power generation unit, wherein the life-cycle cost model is expressed as:

[0019] ;

[0020] in, , Characterizes the total number and scale of multi-functional power generation units in the distribution area. , This represents the overall number of interconnected TV stations. Indicates the area Inner The output power of the generator unit Indicates the area Internal power generation unit The life-cycle cost model, in which, It is the first The core cost parameters of the power generation unit meet the requirements. ;

[0021] Obtain the lower and upper limits of the output power of each power generation unit:

[0022] ;

[0023] in, These represent the lower and upper limits of the generator's output power, respectively.

[0024] To obtain the total power demand and renewable energy output of the distribution area, and to determine the set of honest power generation units, the formula is as follows:

[0025] ;

[0026] in, Indicates the area Total power demand Taiwan District Internal renewable energy output power, This represents a set of honest power generation units.

[0027] Furthermore, the establishment of the mathematical model for optimizing the economic distribution area, and the analytical calculation paradigm for the optimal incremental cost and output power of each power generation unit, includes:

[0028] Based on the acquired cost parameters, power constraints, and load demand data, a mathematical model for economic dispatching of transformer substations is constructed, as shown in the following formula:

[0029] ;

[0030] in, The total operating cost of transformer substation l;

[0031] The mathematical model of economic dispatching of the transformer substation is transformed into a Lagrange function using the Lagrange multiplier method, as shown in the following formula:

[0032] ;

[0033] in, , Represents a set cardinality, These are Lagrange multipliers, representing incremental costs;

[0034] Taking the partial derivative of the Lagrange function, we obtain the calculation paradigm for the optimal incremental cost and output power:

[0035] ;

[0036] ;

[0037] in , Representing the respective districts Optimal incremental cost and transformer area Internal power generation unit The optimal output power.

[0038] Furthermore, the initialization of the incremental cost and output power of each power generation unit includes:

[0039] Initialize the set of power generation units within the transformer area Byzantine power generation unit assembly and Communication topology diagram between power generation units and edge set ,make Indicates power generation unit The neighbor set, initializing the power generation cost coefficient ;

[0040] Based on the aforementioned calculation paradigm, the incremental cost and output power of each power generation unit at the initial moment are set to complete the globally optimal initial configuration.

[0041] Furthermore, the step of acquiring the neighbor transmission data received by each power generation unit, and updating the dynamic weight matrix after attack detection and anomaly filtering includes:

[0042] Acquire power generation unit exist Real-time reception of neighbor transmission data from neighboring units and The neighbor transmission data contains conditional noise. and Auxiliary variables and ;

[0043] For the received data or Sort by value from smallest to largest, and remove values ​​greater than 100%. or of Data and less than or of If the number of data points exceeds the limit, the quantity of the excess data is insufficient. Then all excess data are removed, resulting in the filtered neighbor set. ;

[0044] Update the in-weight matrix and out-weight matrix according to the following rules: ; ;

[0045] in, These represent the in weight matrix and the out weight matrix, respectively.

[0046] Furthermore, updating the incremental cost and output power of each power generation unit includes:

[0047] The accelerated push-pull distributed adaptive economic dispatch algorithm is adopted, and the generation units are updated according to the following rules. incremental cost and related auxiliary variables:

[0048] ;

[0049] ;

[0050] ;

[0051] ;

[0052] in, To maintain a fixed step size, and To accelerate parameters, For the number of honest power generation units, This represents the transmission power of the distribution area, which is 0 when no inter-distribution scheduling is performed.

[0053] Furthermore, the calculation of the power balance residual and the determination of whether it meets the global optimal convergence threshold include:

[0054] The formula for calculating the power balance residual is as follows:

[0055] ;

[0056] in, express Time residuals;

[0057] Set threshold ,judge If the condition is met, the output power information of each newly acquired power generation unit is stored, and the optimal output power configuration result of each power generation unit in the distribution area is output. Then, the subsequent steps are executed. If the condition is not met, it is further determined whether the output power of all honest power generation units has reached the constraint limit. If the limit has not been reached, the step of obtaining neighbor transmission data is returned. If it has been reached, the output power information of each newly acquired power generation unit is stored, and the subsequent steps are executed.

[0058] Furthermore, the step of quantizing, compressing, and homomorphically encrypting the stored output power information before transmitting it to the intelligent agent node in the distribution area includes:

[0059] According to the formula Output power of each power generation unit within the substation area Quantification is performed, among which The quantization coefficients are used to obtain quantized data. ;

[0060] Randomly generate two distinct large prime numbers Calculate public key parameters and The formula is: , ;

[0061] verify If the condition is not met, select a larger prime number until the condition is met; calculate the private key parameters. and The formula is as follows:

[0062] ,

[0063] ;

[0064] public key The private key is made public to all power generation units within the distribution area. Hand it over to the corresponding smart agent node in the transformer area;

[0065] Generate random numbers satisfy Quantitative data Encrypt: Obtain encrypted data from neighbors ;

[0066] Encrypt neighbor data Transmitted to the intelligent agent node in the distribution area.

[0067] Furthermore, based on the decryption and restoration of output power by the intelligent agent nodes in the distribution area, the backup capacity of each distribution area and the total demand of interconnected distribution areas are calculated, including:

[0068] The intelligent agent node in the transformer area decrypts the received encrypted data from neighbors to restore the output power of each power generation unit, as shown in the following formula:

[0069] ;

[0070] Calculate the difference between the demand of the transformer area and the total output power: ;

[0071] Calculate the standby capacity of the transformer area: ,in Reserve capacity for the transformer area;

[0072] Iterate through all distribution areas. If the standby capacity of a distribution area is negative, it is identified as a demand side, and the total system-level demand of interconnected distribution areas is aggregated and calculated. .

[0073] Furthermore, the establishment of the interconnected regional economic scheduling model, and its transformation into a global optimal dual problem, includes:

[0074] Based on the reserve capacity and total demand of each transformer area, an economic dispatch model for interconnected transformer areas is established:

[0075] ;

[0076] in For the collection of intelligent agent nodes in the honest distribution area, Taiwan District The transmission cost function, This is the transmission cost coefficient;

[0077] The Lagrangian function for constructing the economic dispatch model of interconnected power grid areas: ,in It is a Lagrange multiplier.

[0078] Furthermore, the step of acquiring neighboring station data received by each station area, and updating the inter-station weight matrix based on blockchain technology after attack detection and anomaly filtering includes:

[0079] Get TV area exist Received information from neighboring stations in real time and The received information includes conditional noise superimposed on it. and Auxiliary variables and ;

[0080] Received information or Sort by value from smallest to largest, and remove values ​​greater than 100%. or of Data and less than or of If the number of data points is insufficient, all excess data are removed to obtain the filtered set of neighboring stations. ;

[0081] Based on blockchain technology, update the in-weight matrix and out-weight matrix between platforms according to the following rules:

[0082] ;

[0083] ;

[0084] in, These represent the in-weight matrix and out-weight matrix of the inter-station area, respectively.

[0085] Furthermore, combining the aforementioned global optimal dual problem, the filtered neighboring station data, and the weight matrix, the incremental cost and transmission power of each station are updated, including:

[0086] A distributed optimization algorithm is used to update the transformer area according to the following rules. Incremental cost and transmission power: ;

[0087] ;

[0088] ;

[0089] ;

[0090] in, To maintain a fixed step size, and To accelerate parameters, Taiwan District exist Incremental cost per moment Taiwan District exist Transmission power at any given time The number of honest neighbors in the district.

[0091] Furthermore, the calculation of the cross-domain transmission power balance residual and the determination of whether a preset cross-domain convergence threshold is met include:

[0092] Calculate the cross-domain transmission power balance residual The formula is as follows:

[0093] ;

[0094] Set threshold ,judge If the condition is met, output the optimal transmission power configuration result for the station interval; otherwise, return to the step of obtaining neighbor transmission data.

[0095] Secondly, the present invention provides a data security transmission system under uncertain interference in interconnected substations, comprising:

[0096] The data acquisition and analysis module is used to establish a mathematical model for the economic optimization of the power generation unit in the interconnected distribution area based on the acquired cost parameters, power constraints and load demand data of each power generation unit, and to analyze and obtain the calculation paradigm of the optimal incremental cost and output power of each power generation unit.

[0097] An initialization module is used to initialize the incremental cost and output power of each power generation unit according to the calculation paradigm when the current time is the initial time.

[0098] The first processing module is used to acquire the neighbor transmission data received by each power generation unit at non-initial time, update the dynamic weight matrix after attack detection and anomaly filtering, and update the incremental cost and output power of each power generation unit.

[0099] The storage module is used to calculate the power balance residual based on the updated output power and determine whether the global optimal convergence threshold is met. If it is met, the output power information is stored; if it is not met and the output power has not reached the upper limit, the step of obtaining neighbor transmission data is returned; otherwise, the output power information is stored.

[0100] The encrypted transmission module is used to quantize, compress, and homomorphically encrypt the stored output power information before transmitting it to the intelligent agent node in the distribution area.

[0101] The decryption module is used to decrypt and restore the output power based on the intelligent agent node of the transformer area, and to calculate the backup capacity of each transformer area and the total demand of interconnected transformer areas.

[0102] The model building and transformation module is used to build an economic scheduling model for interconnected distribution areas based on the total demand scale, and transform it into a global optimal dual problem;

[0103] The second processing module is used to obtain neighboring data received by each station within the station area, and after attack detection and anomaly filtering, update the weight matrix between stations based on blockchain technology.

[0104] The update module is used to update the incremental cost and transmission power of each transformer area by combining the global optimal dual problem, the filtered neighbor transformer area data and the weight matrix.

[0105] The judgment and iteration module is used to calculate the cross-domain transmission power balance residual based on the updated transmission power, determine whether the preset cross-domain convergence threshold is met, and output the optimal transmission power configuration result between stations if it is met; otherwise, it returns to the step of obtaining neighbor transmission data.

[0106] Thirdly, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of any of the methods described above.

[0107] Fourthly, the present invention provides an electronic device, comprising:

[0108] Memory, used to store computer programs / instructions;

[0109] A processor for executing the computer program / instructions to implement the steps of any of the methods described above.

[0110] Fifthly, the present invention provides a computer program product, including a computer program / instructions that, when executed by a processor, implement the steps of any of the methods described above.

[0111] Compared with the prior art, the beneficial effects achieved by the present invention are as follows:

[0112] This invention innovatively constructs an intelligent detection and filtering system for abnormal economic dispatch information in interconnected distribution transformer areas. By performing multi-dimensional sorting and modeling of real-time neighbor node transmission information, it adaptively filters and removes Top-K extreme value interference data (including the maximum / minimum value subset), achieving precise isolation and robust suppression of Byzantine attacks from the information source. This overcomes the technical bottlenecks of traditional methods, which have weak anti-attack capabilities and insufficient robustness, and provides core protection for the safe and stable operation of interconnected distribution transformer areas.

[0113] This invention addresses the challenges of privacy protection and convergence efficiency in economic scheduling of interconnected substations under directed communication topologies. It proposes a privacy enhancement algorithm that integrates dynamic injection of conditional noise and differential cancellation mechanisms. An adaptive noise accumulation cancellation strategy is designed to achieve precise noise ablation during iteration. Simultaneously, an improved Nesterov acceleration framework is introduced, significantly improving the algorithm's consistent convergence rate in directed graph topologies through gradient optimization and adaptive step size adjustment. This method achieves, for the first time, a synergistic optimization of privacy protection and fast convergence in directed topology scenarios, significantly outperforming the overall performance of existing technologies.

[0114] This invention innovatively constructs a global communication collaboration architecture within and between interconnected distribution stations, proposing a two-level secure transmission mechanism of "communication quantization + homomorphic encryption." Addressing the data flow needs under uncertain interference environments in interconnected distribution stations, it achieves a dynamic balance between transmission accuracy and privacy security. This method is the first to deeply integrate the concept of global communication collaboration with lightweight encrypted transmission technology, solving the technical pain points of traditional methods in multi-distribution interconnection scenarios, such as low data transmission efficiency, weak privacy protection, and poor anti-interference capabilities. It provides a novel solution for the secure and efficient flow of data between interconnected distribution stations in complex and uncertain environments. Attached Figure Description

[0115] Figure 1 This is a flowchart of a data security transmission method under uncertain interference in an interconnected network provided by an embodiment of the present invention;

[0116] Figure 2 This is a topology diagram of the communication network between the dispatchable power generation units within the substation area in this embodiment;

[0117] Figure 3 This is a graph showing the incremental cost changes of each dispatchable power generation unit within the substation area in this implementation method.

[0118] Figure 4 This is a diagram showing the output power variation of each dispatchable power generation unit within the substation area in this embodiment;

[0119] Figure 5 This is a graph showing the changes in total output power and power demand within the substation area in this implementation method;

[0120] Figure 6 This is a graph showing the incremental cost changes of each station area within the intermediate station section in this implementation method;

[0121] Figure 7 This is a diagram showing the transmission power variation of each station area in the intermediate station section of this implementation method;

[0122] Figure 8 This diagram illustrates the changes in total transmission power and power demand between the intermediate stations in this implementation scheme. Detailed Implementation

[0123] The present invention will be further described below with reference to the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and should not be used to limit the scope of protection of the present invention.

[0124] Example 1: This example describes a method for secure data transmission under uncertain interference in interconnected network areas, including:

[0125] Based on the cost parameters, power constraints and load demand data of each power generation unit in the interconnected distribution area, an economic optimization mathematical model for the distribution area is established, and the calculation paradigm of the optimal incremental cost and output power of each power generation unit is obtained analytically.

[0126] If it is the initial moment, then the incremental cost and output power of each power generation unit are initialized according to the calculation paradigm.

[0127] If it is not the initial moment, the neighbor transmission data received by each power generation unit is obtained, and the dynamic weight matrix is ​​updated after attack detection and anomaly filtering, and the incremental cost and output power of each power generation unit are updated.

[0128] Calculate the power balance residual based on the updated output power, and determine whether the global optimal convergence threshold is met. If it is met, store the output power information; if it is not met and the output power has not reached the upper limit, return to the step of obtaining neighbor transmission data; otherwise, store the output power information.

[0129] The stored output power information is quantized, compressed, and homomorphically encrypted before being transmitted to the intelligent agent node in the distribution area.

[0130] Based on the decryption and restoration of the output power of the intelligent agent node in the transformer area, calculate the backup capacity of each transformer area and the total demand of interconnected transformer areas.

[0131] Based on the total demand scale, an economic scheduling model for interconnected power distribution areas is established and transformed into a global optimal dual problem;

[0132] Within the inter-station area, data from neighboring stations received by each station is acquired. After attack detection and anomaly filtering, the inter-station weight matrix is ​​updated based on blockchain technology.

[0133] By combining the global optimal dual problem, the filtered neighboring station data, and the weight matrix, the incremental cost and transmission power of each station are updated.

[0134] Calculate the cross-domain transmission power balance residual based on the updated transmission power, and determine whether it meets the preset cross-domain convergence threshold. If it does, output the optimal transmission power configuration result between stations; otherwise, return to the step of obtaining neighbor transmission data.

[0135] like Figure 1 As shown in the figure, the data security transmission method under uncertain interference in interconnected stations provided in this embodiment involves the following steps in its application process:

[0136] Step 1: For the complex scenario of multi-entity collaborative dispatching in interconnected power distribution areas, establish a comprehensive economic optimization mathematical modeling system, deeply integrating the full life-cycle cost model of each distributed generation unit, multi-dimensional power boundary constraints, and cross-temporal and spatial supply and demand dynamic balance constraint mechanism, as detailed below:

[0137] Economic dispatch model within the distribution area:

[0138] ;

[0139] in, , This indicates the number of power generation units in the transformer substation. , Indicates the number of transformer substations. Indicates the area Inner The output power of the generator unit Indicates the area Internal power generation unit The power generation cost function, where, It is the first The cost parameters of the power generation unit meet the requirements. ..also, Indicates the area Total power demand Taiwan District Internal renewable energy output power, This represents a set of honest power generation units. These represent the lower and upper limits of the generator's output power, respectively.

[0140] In this embodiment, the number of dispatchable power generation units within a given distribution area is n=60, and the number of distribution areas is... A collection of honest power generation A collection of Byzantine power generation units The total output power requirement of the dispatchable power generation unit is Fitting parameters , , The communication topology is a directed topology.

[0141] In this implementation plan, the directed communication topology graph is as follows: Figure 2 As shown.

[0142] Step 2: Based on advanced Lagrange multiplier dual optimization theory, the high-dimensional complex mathematical model constructed in Step 1 is transformed into a Lagrange objective function. Through in-depth derivation, the adaptive calculation paradigm of the output power of each power generation unit and the incremental cost equilibrium condition that satisfies global Pareto optimality are derived analytically. The specific steps are as follows:

[0143] For the economic dispatch mathematical model within the distribution area, the Lagrange multiplier method is used to transform it into a Lagrange function:

[0144] ;

[0145] in, , Represents a set Cardinal number. For Lagrange multipliers, in economic scheduling problems, it represents incremental cost.

[0146] Lagrange function To each Find the partial derivative:

[0147] ;

[0148] ;

[0149] in , Representing the respective districts Optimal incremental cost and transformer area Internal power generation unit The optimal output power.

[0150] Step 3: Construct an intelligent initial state determination mechanism in the spatiotemporal dimension to determine whether the current time t is the initial time. If so, initialize the power limit of the power generation unit, i.e., the distribution area. Inner The lower and upper limits of the output power of each honest power generation unit are respectively , Incremental cost of each power generation unit at the initial moment and output power Otherwise proceed to step 4;

[0151] Step 4: An innovative "conditional constraint-differential privacy" two-layer adaptive noise injection encryption architecture is proposed to achieve high-security encrypted transmission of core information from neighboring nodes. Simultaneously, an intelligent attack detection and anomaly filtering engine is developed to accurately identify and eliminate malicious interference data. Based on this, a dynamic weight matrix real-time update mechanism is constructed. The specific steps are as follows:

[0152] Power generation unit exist Receive information from neighbors at all times and , ,in Both and are auxiliary variables. and These represent the conditional noise added to the transmitted information, for the received information. and Sort them in ascending order, removing those greater than... of 1 neighbor information, remove those less than 1. of The neighbor information, if greater than or less than The number is less than Then remove all ratios Numbers greater than or less than. Similarly, neighbor information. That's how it's handled. Let Let represent the filtered neighbor set. Let ... Let these represent the in-weight matrix and the out-weight matrix, respectively. The weight matrices follow the following distribution:

[0153] ;

[0154] ;

[0155] Step 5: Each honest power generation unit, relying on a distributed collaborative computing architecture, inputs the encrypted information of neighboring nodes (after anomaly filtering) into a self-developed accelerated push-pull distributed adaptive economic scheduling algorithm to achieve... Incremental cost of each power generation unit at any given time With output power The global collaborative optimization and update process involves the following steps:

[0156] Taiwan Internal power generation units incremental cost The update rules are as follows:

[0157] ;

[0158] ;

[0159] ;

[0160] ;

[0161] in To maintain a fixed step size, and For acceleration parameters, This represents the number of honest generator sets. Taiwan District Transmission power is negative for demanders and positive for suppliers, assuming no inter-station scheduling. All .

[0162] A fixed step size is set in the specific implementation plan. acceleration parameters and .

[0163] Step 6: Construct a comprehensive power balance residual intelligent verification system. Calculate the dynamic residual index in real time based on the total output power to determine if the preset global optimal convergence threshold is met. If the convergence condition is met, proceed to the cross-domain collaborative scheduling stage. If not, activate the power constraint limit judgment mechanism to verify whether the output power of each power generation unit has reached the global optimal constraint upper limit. If met, proceed to Step 7; otherwise, return to Step 4 for iterative optimization. The specific steps are as follows:

[0164] The residual is calculated using the following formula:

[0165] ;

[0166] in express The residual at time step, with a threshold set. ,judge Check if it's true. If true, proceed to the next step. If false, check if... If the condition is true for any honest power generation unit within the transformer area, then proceed to step 4.

[0167] In the specific implementation of this method, a threshold is set. .

[0168] Step 7: Addressing the core risk of privacy leakage in cross-domain communication network interactions, an innovative two-level collaborative security protection mechanism of "communication quantization-homomorphic encryption" is developed to construct a "secure isolation zone" for cross-domain information transmission. Specifically, the output power information of each power generation unit within the distribution area is adaptively quantized and compressed, and then transmitted to the intelligent agent node of the distribution area through homomorphic encryption technology to achieve full-process privacy protection of "encrypted transmission-decryption operation." The intelligent agent of the distribution area completes information restoration through a high-performance decryption engine, accurately calculates the redundancy of the backup power generation capacity of the distribution area based on multi-dimensional distribution area data, intelligently determines the demand-side distribution area (with negative backup capacity), and aggregates and calculates the total system-level demand scale of interconnected distribution areas. The specific steps are as follows:

[0169] Each power generation unit within the distribution area will quantify its calculated power information using the following formula:

[0170] ;

[0171] in This is the quantization factor, typically a multiple of 10, selected based on the required data transmission accuracy. Taiwan District Internal generator set The output power, which is the object being quantized here. The information is quantized; the quantized data is then encrypted using homomorphic encryption, with the specific steps as follows:

[0172] Randomly generate two distinct large prime numbers Calculate public key parameters and :

[0173] ;

[0174] ;

[0175] verify If the condition is not met, randomly select a large prime number again until the condition is met. Used to find and The greatest common divisor;

[0176] Calculate private key parameters and :

[0177] ;

[0178] ;

[0179] in Used to obtain and The least common multiple of, ), It is a modulo function.

[0180] public key The private key is made public to all power generation units within the distribution area. Give the intelligent agent to this area.

[0181] Plain text processing:

[0182] Generate random numbers Requirements must be met Transmitting data to neighbors encryption:

[0183] ;

[0184] in This is encrypted information. It's worth noting that this applies to data transmission between different neighbors. Each has a different random number. .

[0185] After the data encryption is completed, the power generation unit sends the encrypted data to the intelligent agent in the distribution area. The intelligent agent in the distribution area decrypts the received data. The decryption process is as follows:

[0186] ;

[0187] Computing area Difference between demand and total output power:

[0188] ;

[0189] Computing area Reserve capacity:

[0190] ;

[0191] in Taiwan District The reserve capacity, in Total demand for time zone:

[0192] cycle If the above judgment is true, , ,in This indicates the total power demand between stations.

[0193] In the specific implementation of this method, to retain three decimal places in the transmitted information, the following settings are configured: . large prime numbers , Generated randomly by computer and satisfying .

[0194] Step 8: Based on the demand aggregation results in Step 7, establish a cross-domain collaborative economic scheduling optimization model between distribution stations. This model deeply integrates the full-link cost function of power transmission between distribution stations, the output power inequality constraint system under multiple constraints, and the global supply-demand balance equality constraint mechanism across distribution stations. Using the Lagrange multiplier dual transformation technique, the complex constraint problem is transformed into a globally optimal dual problem without inequality constraints. The specific steps are as follows:

[0195] Establish an economic dispatch model for interconnected power grids:

[0196] ;

[0197] in It is a collection of honest platform agents. Taiwan District Transmission cost function The Lagrangian function of the transmission cost coefficient is:

[0198] ;

[0199] in .

[0200] In the specific implementation of this method, the set of honest platforms is set as , , , Reserve capacity of each transformer substation and inter-platform demand The above formula can be used to obtain the result.

[0201] Step 9: Construct a distributed trust and collaboration mechanism between stations. Each honest station receives core information from neighboring stations that has been encrypted with conditional constraints and noise. Anomaly information is accurately filtered through a cross-domain collaborative attack detection engine. Trusted dynamic updates of the weight matrix between stations are achieved using blockchain technology. The specific steps are as follows:

[0202] Taiwan exist Receive information from neighbors at all times and , ,in and All are auxiliary variables. and These represent the conditional noise in the information transmitted between stations. Indicates the area The set of neighbors. Regarding the received information. and Sort them in ascending order, removing those greater than... of 1 neighbor information, remove those less than 1. of The neighbor information, if greater than or less than The number is less than Then remove all ratios Numbers greater than or less than. Similarly, neighbor information. That's how it's handled. Let Let represent the filtered neighbor set. Let ... These represent the in-line weight matrix and the out-line weight matrix between stations, respectively. The weight matrices follow the following distribution:

[0203] ;

[0204] ;

[0205] In the specific implementation of this method, conditional noise and Generated randomly by computer, and the noise level should be such that the mean of the generated noise is [value missing]. The variance has an upper bound.

[0206] Step 10: Based on the cross-domain trusted neighbor information dataset, the distributed optimization algorithm developed in Step 5 is used to complete the global collaborative calculation of the incremental cost of each transformer area at the current moment. Combined with the cross-domain power transmission efficiency model, the optimal transmission power configuration scheme between transformer areas is accurately solved. The specific steps are as follows:

[0207] Taiwan The agent uses the following algorithm to update incremental cost and transmission power.

[0208] ;

[0209] ;

[0210] ;

[0211] ;

[0212] in To maintain a fixed step size, and For acceleration parameters, Taiwan District exist Incremental cost at any moment Taiwan District exist Transmission power at any given time This indicates the number of its honest neighbors.

[0213] In the specific implementation of this method, a fixed step size is set. acceleration parameters and .

[0214] Step 11: Establish a final verification mechanism for cross-domain transmission power balance residuals. Calculate the global residual index in real time based on the total transmission power to determine if the preset cross-domain convergence threshold is met. If not, return to Step 4 for full-link iterative optimization. If the global convergence condition is met, output the optimal transmission power configuration result between stations. The specific steps are as follows:

[0215] The residual is calculated using the following formula:

[0216] ;

[0217] in Indicates the interval between stations The residual at time step, with a threshold set. ,judge If the condition is not met, proceed to step 4; if it is met, output the optimal power generation and transmission power.

[0218] To verify the effectiveness of the present invention, experimental simulations were conducted according to the above steps.

[0219] Figure 2 The communication connections between the various power generation units within the distribution area are shown, with units 1-54 being the Honest Power Generation Units and units 55-60 being the Byzantine Power Generation Units. Figure 3 The incremental costs of power generation units 1-54 within the distribution area are displayed. Figure 4 The output power of generator units 1-54 in the transformer area is displayed. Since generators 55-56 are Byzantine generators, their output is uncontrollable, so their incremental cost and output power are not displayed. Figure 5 The data shows the total output power and total demand within the distribution area. It can be seen that as the iteration progresses, the total output and total demand tend to be consistent. Figure 6 The incremental costs of each transformer area are shown in the figure. As can be seen from the figure, transformer areas 1-3 are reliable transformer areas, while transformer area 4 is a Byzantine transformer area, whose incremental costs are uncontrollable. Figure 7 The output power between the substations is shown, with substation 3 having an output power of 0, meaning it is the demand side, while substations 1 and 2 are the supply side. Figure 8 The demonstration showed the supply and demand balance of interconnected transformer substations. Initially, the supply and demand of interconnected transformer substations were both 0. As the iteration progressed, some transformer substations reached their power limits but still could not achieve supply and demand balance, so scheduling was carried out between the transformer substations.

[0220] This embodiment innovatively constructs an intelligent detection and filtering system for abnormal economic dispatch information in interconnected distribution areas. By performing multi-dimensional sorting and modeling of real-time neighbor node transmission information, it adaptively filters and removes Top-K extreme value interference data (including the maximum / minimum value subset), achieving precise isolation and robust suppression of Byzantine attacks from the information source. This overcomes the technical bottlenecks of traditional methods, which have weak anti-attack capabilities and insufficient robustness, and provides core protection for the safe and stable operation of interconnected distribution areas.

[0221] This embodiment addresses the challenges of privacy protection and convergence efficiency in economic scheduling of interconnected substations under directed communication topologies. It proposes a privacy enhancement algorithm that integrates dynamic conditional noise injection and differential cancellation mechanisms. An adaptive noise accumulation cancellation strategy is designed to achieve precise noise ablation during iteration. Simultaneously, an improved Nesterov acceleration framework is introduced, significantly improving the algorithm's consistent convergence rate in directed graph topologies through gradient optimization and adaptive step size adjustment. This method achieves, for the first time, a synergistic optimization of privacy protection and fast convergence in directed topology scenarios, significantly outperforming the overall performance of existing technologies.

[0222] This embodiment innovatively constructs a global communication collaboration architecture within and between distribution stations, proposing a two-level secure transmission mechanism of "communication quantization + homomorphic encryption." Addressing the data flow needs under uncertain interference environments in interconnected distribution stations, it achieves a dynamic balance between transmission accuracy and privacy security. This method is the first to deeply integrate the concept of global communication collaboration with lightweight encrypted transmission technology, solving the technical pain points of traditional methods in multi-distribution interconnection scenarios, such as low data transmission efficiency, weak privacy protection, and poor anti-interference capabilities. It provides a novel solution for the secure and efficient flow of data between interconnected distribution stations in complex and uncertain environments.

[0223] Example 2: This example provides a data security transmission system under uncertain interference in an interconnected network area, comprising:

[0224] The data acquisition and analysis module is used to establish a mathematical model for the economic optimization of the power generation unit in the interconnected distribution area based on the acquired cost parameters, power constraints and load demand data of each power generation unit, and to analyze and obtain the calculation paradigm of the optimal incremental cost and output power of each power generation unit.

[0225] An initialization module is used to initialize the incremental cost and output power of each power generation unit according to the calculation paradigm when the current time is the initial time.

[0226] The first processing module is used to acquire the neighbor transmission data received by each power generation unit at non-initial time, update the dynamic weight matrix after attack detection and anomaly filtering, and update the incremental cost and output power of each power generation unit.

[0227] The storage module is used to calculate the power balance residual based on the updated output power and determine whether the global optimal convergence threshold is met. If it is met, the output power information is stored; if it is not met and the output power has not reached the upper limit, the step of obtaining neighbor transmission data is returned; otherwise, the output power information is stored.

[0228] The encrypted transmission module is used to quantize, compress, and homomorphically encrypt the stored output power information before transmitting it to the intelligent agent node in the distribution area.

[0229] The decryption module is used to decrypt and restore the output power based on the intelligent agent node of the transformer area, and to calculate the backup capacity of each transformer area and the total demand of interconnected transformer areas.

[0230] The model building and transformation module is used to build an economic scheduling model for interconnected distribution areas based on the total demand scale, and transform it into a global optimal dual problem;

[0231] The second processing module is used to obtain neighboring data received by each station within the station area, and after attack detection and anomaly filtering, update the weight matrix between stations based on blockchain technology.

[0232] The update module is used to update the incremental cost and transmission power of each transformer area by combining the global optimal dual problem, the filtered neighbor transformer area data and the weight matrix.

[0233] The judgment and iteration module is used to calculate the cross-domain transmission power balance residual based on the updated transmission power, determine whether the preset cross-domain convergence threshold is met, and output the optimal transmission power configuration result between stations if it is met; otherwise, it returns to the step of obtaining neighbor transmission data.

[0234] The specific functions of each module described above are explained in the relevant content of the method in Embodiment 1, and will not be repeated here.

[0235] Example 3: This example provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of any of the methods described in Example 1.

[0236] Example 4: This example provides an electronic device, including:

[0237] Memory, used to store computer programs / instructions;

[0238] A processor for executing the computer program / instructions to implement the steps of any of the methods described in Embodiment 1.

[0239] Example 5: This example provides a computer program product, including a computer program / instructions, which, when executed by a processor, implement the steps of the method described in any one of Examples 1.

[0240] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the technical principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

[0241] Those skilled in the art will understand that embodiments of this disclosure can be provided as methods, systems, or computer program products. Therefore, this disclosure can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this disclosure can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0242] This disclosure is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a machine for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0243] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0244] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0245] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this disclosure and not to limit its protection scope. Although this disclosure has been described in detail with reference to the above embodiments, those skilled in the art should understand that after reading this disclosure, they can still make various changes, modifications or equivalent substitutions to the specific implementation of the invention, but these changes, modifications or equivalent substitutions are all within the protection scope of the pending claims.

Claims

1. A method for secure data transmission under uncertain interference in interconnected network areas, characterized in that, include: Based on the cost parameters, power constraints and load demand data of each power generation unit in the interconnected distribution area, an economic optimization mathematical model for the distribution area is established, and the calculation paradigm of the optimal incremental cost and output power of each power generation unit is obtained analytically. If it is the initial moment, then the incremental cost and output power of each power generation unit are initialized according to the calculation paradigm. If it is not the initial moment, the neighbor transmission data received by each power generation unit is obtained, and the dynamic weight matrix is ​​updated after attack detection and anomaly filtering, and the incremental cost and output power of each power generation unit are updated. Calculate the power balance residual based on the updated output power, determine whether it meets the global optimal convergence threshold, and if it does, store the output power information. If the conditions are not met and the output power has not reached the upper limit, return to the step of obtaining neighbor transmission data; otherwise, store the output power information. The stored output power information is quantized, compressed, and homomorphically encrypted before being transmitted to the intelligent agent node in the distribution area. Based on the decryption and restoration of the output power of the intelligent agent node in the transformer area, calculate the backup capacity of each transformer area and the total demand of interconnected transformer areas. Based on the total demand scale, an economic scheduling model for interconnected power distribution areas is established and transformed into a global optimal dual problem; Within the inter-station area, data from neighboring stations received by each station is acquired. After attack detection and anomaly filtering, the inter-station weight matrix is ​​updated based on blockchain technology. By combining the global optimal dual problem, the filtered neighboring station data, and the weight matrix, the incremental cost and transmission power of each station are updated. Calculate the cross-domain transmission power balance residual based on the updated transmission power, and determine whether it meets the preset cross-domain convergence threshold. If it does, output the optimal transmission power configuration result between stations; otherwise, return to the step of obtaining neighbor transmission data.

2. The data security transmission method under uncertain interference in interconnected areas according to claim 1, characterized in that, The method for obtaining cost parameters, power constraints, and load demand data of each power generation unit in the interconnected distribution area includes: Obtain the life-cycle cost model parameters for each power generation unit, wherein the life-cycle cost model is expressed as: ； in, , Characterizes the total number and scale of multi-functional power generation units in the distribution area. , This represents the overall number of interconnected TV stations. Indicates the area Inner The output power of the generator unit Indicates the area Internal power generation unit The life-cycle cost model, in which, It is the first The core cost parameters of the power generation unit meet the requirements. ; Obtain the lower and upper limits of the output power of each power generation unit: ； in, These represent the lower and upper limits of the generator's output power, respectively. To obtain the total power demand and renewable energy output of the distribution area, and to determine the set of honest power generation units, the formula is as follows: ； in, Indicates the area Total power demand Taiwan District Internal renewable energy output power, This represents a set of honest power generation units.

3. The data security transmission method under uncertain interference in interconnected areas according to claim 1, characterized in that, The establishment of the mathematical model for optimizing the economic distribution area, and the analytical calculation paradigm for the optimal incremental cost and output power of each power generation unit, includes: Based on the acquired cost parameters, power constraints, and load demand data, a mathematical model for economic dispatching of transformer substations is constructed, as shown in the following formula: ； in, The total operating cost of transformer substation l; The mathematical model of economic dispatching of the transformer substation is transformed into a Lagrange function using the Lagrange multiplier method, as shown in the following formula: ； in, , Represents a set cardinality, These are Lagrange multipliers, representing incremental costs; Taking the partial derivative of the Lagrange function, we obtain the calculation paradigm for the optimal incremental cost and output power: ； ； in , Representing the respective districts Optimal incremental cost and transformer area Internal power generation unit The optimal output power.

4. The data security transmission method under uncertain interference in interconnected areas according to claim 1, characterized in that, The initialization of the incremental cost and output power of each power generation unit includes: Initialize the set of power generation units within the transformer area Byzantine power generation unit assembly and Communication topology diagram between power generation units and edge set ,make Indicates power generation unit The neighbor set, initializing the power generation cost coefficient ; Based on the aforementioned calculation paradigm, the incremental cost and output power of each power generation unit at the initial moment are set to complete the globally optimal initial configuration.

5. The data security transmission method under uncertain interference in interconnected areas according to claim 1, characterized in that, The process of acquiring neighbor transmission data received by each power generation unit, updating the dynamic weight matrix after attack detection and anomaly filtering, includes: Acquire power generation unit exist Real-time reception of neighbor transmission data from neighboring units and The neighbor transmission data contains conditional noise. and Auxiliary variables and ; For the received data or Sort by value from smallest to largest, and remove values ​​greater than 100%. or of Data and less than or of If the number of data points exceeds the limit, the quantity of the excess data is insufficient. Then all excess data are removed, resulting in the filtered neighbor set. ; Update the in-weight matrix and out-weight matrix according to the following rules: ; ; in, These represent the in weight matrix and the out weight matrix, respectively.

6. The data security transmission method under uncertain interference in interconnected areas according to claim 1, characterized in that, The updating of the incremental cost and output power of each power generation unit includes: The accelerated push-pull distributed adaptive economic dispatch algorithm is adopted, and the generation units are updated according to the following rules. incremental cost and related auxiliary variables: ； ； ； ； in, To maintain a fixed step size, and To accelerate parameters, For the number of honest power generation units, This represents the transmission power of the distribution area, which is 0 when no inter-distribution scheduling is performed.

7. The data security transmission method under uncertain interference in interconnected areas according to claim 1, characterized in that, The calculation of the power balance residual, and the determination of whether it meets the global optimal convergence threshold, includes: The formula for calculating the power balance residual is as follows: ； in, express Time residuals; Set threshold ,judge If the condition is met, the output power information of each newly acquired power generation unit is stored, and the optimal output power configuration result of each power generation unit in the distribution area is output. Then, the subsequent steps are executed. If the condition is not met, it is further determined whether the output power of all honest power generation units has reached the constraint limit. If the limit has not been reached, the step of obtaining neighbor transmission data is returned. If it has been reached, the output power information of each newly acquired power generation unit is stored, and the subsequent steps are executed.

8. The data security transmission method under uncertain interference in interconnected areas according to claim 1, characterized in that, The step of quantizing, compressing, and homomorphically encrypting the stored output power information before transmitting it to the intelligent agent node in the distribution area includes: According to the formula Output power of each power generation unit within the substation area Quantification is performed, among which The quantization coefficients are used to obtain quantized data. ; Randomly generate two distinct large prime numbers Calculate public key parameters and The formula is: , ; verify If the condition is not met, select a larger prime number until the condition is met; calculate the private key parameters. and The formula is as follows: ， ； public key The private key is made public to all power generation units within the distribution area. Hand it over to the corresponding smart agent node in the transformer area; Generate random numbers satisfy Quantitative data Encrypt: Obtain encrypted data from neighbors ; Encrypt neighbor data Transmitted to the intelligent agent node in the distribution area.

9. The data security transmission method under uncertain interference in interconnected areas according to claim 1, characterized in that, Based on the decryption and restoration of output power by the intelligent agent node in the distribution area, the backup capacity of each distribution area and the total demand of interconnected distribution areas are calculated, including: The intelligent agent node in the transformer area decrypts the received encrypted data from neighbors to restore the output power of each power generation unit, as shown in the following formula: ； Calculate the difference between the demand of the transformer area and the total output power: ; Calculate the standby capacity of the transformer area: ,in Reserve capacity for the transformer area; Iterate through all distribution areas. If the standby capacity of a distribution area is negative, it is identified as a demand side, and the total system-level demand of interconnected distribution areas is aggregated and calculated. .

10. The data security transmission method under uncertain interference in interconnected areas according to claim 1, characterized in that, The establishment of the interconnected regional economic scheduling model, and its transformation into a global optimal dual problem, includes: Based on the reserve capacity and total demand of each transformer area, an economic dispatch model for interconnected transformer areas is established: ； in For the collection of intelligent agent nodes in the honest distribution area, Taiwan District The transmission cost function, This is the transmission cost coefficient; The Lagrangian function for constructing the economic dispatch model of interconnected power grid areas: ,in It is a Lagrange multiplier.

11. The data security transmission method under uncertain interference in interconnected areas according to claim 1, characterized in that, The process of acquiring neighboring station data received by each station area, performing attack detection and anomaly filtering, and then updating the inter-station weight matrix based on blockchain technology includes: Get TV area exist Received information from neighboring stations in real time and The received information includes conditional noise superimposed on it. and Auxiliary variables and ; Received information or Sort by value from smallest to largest, and remove values ​​greater than 100%. or of Data and less than or of If the number of data points is insufficient, all excess data are removed to obtain the filtered set of neighboring stations. ; Based on blockchain technology, update the in-weight matrix and out-weight matrix between platforms according to the following rules: ； ； in, These represent the in-weight matrix and out-weight matrix of the inter-station area, respectively.

12. The data security transmission method under uncertain interference in interconnected areas according to claim 1, characterized in that, Combining the aforementioned global optimal dual problem, filtered neighboring area data, and weight matrix, the incremental cost and transmission power of each area are updated, including: A distributed optimization algorithm is used to update the transformer area according to the following rules. Incremental cost and transmission power: ; ； ； ； in, To maintain a fixed step size, and To accelerate parameters, Taiwan District exist Incremental cost per moment Taiwan District exist Transmission power at any given time The number of honest neighbors in the district.

13. The data security transmission method under uncertain interference in interconnected areas according to claim 1, characterized in that, The calculation of the cross-domain transmission power balance residual and the determination of whether it meets the preset cross-domain convergence threshold include: Calculate the cross-domain transmission power balance residual The formula is as follows: ； Set threshold ,judge If the condition is met, output the optimal transmission power configuration result for the station interval; otherwise, return to the step of obtaining neighbor transmission data.

14. A data security transmission system under uncertain interference in an interconnected network area, characterized in that, include: The data acquisition and analysis module is used to establish a mathematical model for the economic optimization of the power generation unit in the interconnected distribution area based on the acquired cost parameters, power constraints and load demand data of each power generation unit, and to analyze and obtain the calculation paradigm of the optimal incremental cost and output power of each power generation unit. An initialization module is used to initialize the incremental cost and output power of each power generation unit according to the calculation paradigm when the current time is the initial time. The first processing module is used to acquire the neighbor transmission data received by each power generation unit at non-initial time, update the dynamic weight matrix after attack detection and anomaly filtering, and update the incremental cost and output power of each power generation unit. The storage module is used to calculate the power balance residual based on the updated output power, determine whether the global optimal convergence threshold is met, and if so, store the output power information. If the conditions are not met and the output power has not reached the upper limit, return to the step of obtaining neighbor transmission data; otherwise, store the output power information. The encrypted transmission module is used to quantize, compress, and homomorphically encrypt the stored output power information before transmitting it to the intelligent agent node in the distribution area. The decryption module is used to decrypt and restore the output power based on the intelligent agent node of the transformer area, and to calculate the backup capacity of each transformer area and the total demand of interconnected transformer areas. The model building and transformation module is used to build an economic scheduling model for interconnected distribution areas based on the total demand scale, and transform it into a global optimal dual problem; The second processing module is used to obtain neighboring data received by each station within the station area, and after attack detection and anomaly filtering, update the weight matrix between stations based on blockchain technology. The update module is used to update the incremental cost and transmission power of each transformer area by combining the global optimal dual problem, the filtered neighbor transformer area data and the weight matrix. The judgment and iteration module is used to calculate the cross-domain transmission power balance residual based on the updated transmission power, determine whether the preset cross-domain convergence threshold is met, and output the optimal transmission power configuration result between stations if it is met; otherwise, it returns to the step of obtaining neighbor transmission data.

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