Intelligent power grid safety communication method and system based on wireless energy transmission

Abstract

The invention discloses an intelligent power grid safety communication method and system based on wireless energy transmission, and the method comprises the steps: firstly constructing a wireless energy transmission enabling sensing communication network architecture facing an intelligent power grid, and then determining the effective safety throughput of the safety communication of the intelligent power grid based on the network architecture, according to the method, an optimization problem model P1 with the goal of maximizing the effective security throughput of smart power grid security communication is constructed, and finally, the optimization problem model P1 is solved to obtain an optimal code length combination of an energy collection stage and a wireless information transmission stage, so that the security communication of smart power grid wireless energy transmission is realized. According to the method, the code length combination of the energy collection stage and the wireless information transmission stage is adjusted, the effective safe throughput of safe communication of the intelligent power grid is maximized, safe, reliable and efficient data communication is achieved in a dynamic and complex power grid environment, and meanwhile the stability and adaptability of a power grid system in actual operation are guaranteed.

Description

Technical Field

[0001] The present invention belongs to the field of Internet of Things communications, and in particular relates to a smart grid security communication method and system based on wireless energy transmission. Background Art

[0002] With the rapid development of smart grids, IoT devices in power systems are also taking on more and more important responsibilities, such as collecting grid data, accurately monitoring operating status, and remotely controlling operating equipment. In order to ensure the stable operation of smart grids, efficient and secure data communication must be carried out between IoT devices in power systems. However, due to the complex operating environment and numerous devices in smart grids, how to ensure the long-term stable operation of each IoT device and achieve secure communication between devices has become a challenge. Summary of the invention

[0003] The purpose of the present invention is to provide a smart grid security communication method and system based on wireless energy transmission, which is suitable for a smart grid environment, in view of the above-mentioned problems existing in the prior art.

[0004] To achieve the above objectives, the technical solution of the present invention is as follows:

[0005] In a first aspect, the present invention proposes a smart grid secure communication method based on wireless energy transmission, comprising:

[0006] S1. Construct a wireless energy transmission-enabled sensor communication network architecture for smart grids, wherein the network architecture includes legal sensors, a control center, and illegal eavesdroppers, wherein the legal sensors obtain power from the control center during the energy collection phase and transmit grid data to the control center during the wireless information transmission phase;

[0007] S2,determine the effective security throughput of smart grid security communication based on wireless energy transfer enabled sensor communication network architecture;

[0008] S3, based on the effective security throughput of smart grid security communication, construct an optimization problem model P1 with the goal of maximizing the effective security throughput of smart grid security communication;

[0009] S4. Solve the optimization problem model P1 to obtain the optimal code length combination for the energy collection stage and the wireless information transmission stage, and realize the secure communication of wireless energy transmission in the smart grid.

[0010] The S1 includes:

[0011] S11, energy collection stage, the control center sends a radio frequency signal to the legal sensor, and the legal sensor converts the radio frequency signal into a direct current signal through the energy collection device to charge the legal sensor;

[0012] The charging power of the legal sensor is:

[0013] P ch =F nl (Q a );

[0014] Q a =P·h a，b ;

[0015] In the above formula, P ch is the charging power of the legal sensor, F n1 (·) is the nonlinear relationship between charging power and received RF signal power, Q a is the radio frequency signal power received by the legal sensor from the control center, P is the transmission power of the control center, and h a，b is the path loss between the legitimate sensor and the control center;

[0016] S12, using the energy obtained in the energy collection phase, the legitimate sensor sends the power grid operation data to the control center during the wireless information transmission phase, and the illegal eavesdropper will try to intercept the power grid operation data during the transmission process;

[0017] The data transmission transmission power of the legal sensor is:

[0018]

[0019] In the above formula, P a is the transmission power of legal sensor data transmission, n c 、n r They are the code lengths of the energy collection phase and the wireless information transmission phase respectively.

[0020] In S2, the effective security throughput of the smart grid security communication is calculated using the following formula:

[0021]

[0022] ε LF =1-(1-ε b )ε e ;

[0023]

[0024] Q jam =P·h b，e ;

[0025] In the above formula, τ is the effective security throughput of smart grid security communication, k is the packet size, and n is c 、n rare the code lengths of the energy collection phase and the wireless information transmission phase, respectively, LF is the “leakage-failure” probability of smart grid security communication, ε b is the transmission error probability when the control center receives a data packet from a legitimate sensor, ε e is the eavesdropping failure probability of an illegal eavesdropper, is the Gaussian Q function, ω b is the intermediate parameter of the control center transmission error probability, γ b is the signal-to-noise ratio when the control center receives a data packet from a legitimate sensor, P ch is the charging power of the legal sensor, h a，b is the path loss between the legitimate sensor and the control center, σ 2 is the signal noise power, ω e is the intermediate parameter of the probability of eavesdropping failure of the illegal eavesdropper, γ e is the signal-to-noise ratio of the illegal eavesdropper, h a，e is the path loss between the legitimate sensor and the illegal eavesdropper, Q jam is the interference signal power from the control center received by the illegal eavesdropper, P is the transmission power of the control center, and h b，e is the path loss between the control center and the illegal eavesdropper.

[0026] In S3, the optimization problem model P1 with the goal of maximizing the effective security throughput of smart grid security communication is:

[0027]

[0028] In the above formula, τ is the effective security throughput of smart grid security communication, n c 、n r are the code lengths of the energy collection phase and the wireless information transmission phase, respectively; k is the packet size, and ε LF is the “leakage-failure” probability of smart grid security communication, n total is the upper limit of the total code length in the energy collection phase and the wireless information transmission phase, γ b is the signal-to-noise ratio when the control center receives a data packet from a legitimate sensor, P ch is the charging power of the legal sensor, h a，e is the path loss between the legitimate sensor and the illegal eavesdropper, Q jam is the interference signal power from the control center received by the illegal eavesdropper, σ 2 is the signal-to-noise power.

[0029] The S4 includes:

[0030] S41, reconstruct the optimization problem model P1 into a convex optimization problem model P2:

[0031] P2: min(-τ new ) = ρ1 + ρ2 - ρ3;

[0032]

[0033] In the above formula, τ new is the effective security throughput of the new smart grid security communication after model reconstruction, ρ1 is the first intermediate parameter variable, ρ2 is the second intermediate parameter variable, ρ3 is the third intermediate parameter variable, and n c 、n r are the code lengths of the energy collection phase and the wireless information transmission phase, n total is the upper limit of the total code length in the energy collection phase and the wireless information transmission phase, γ b is the signal-to-noise ratio when the control center receives data packets from legitimate sensors, P ch is the charging power of the legal sensor, h a，e is the path loss between the legitimate sensor and the illegal eavesdropper, Q jam is the interference signal power from the control center received by the illegal eavesdropper, σ 2 is the signal noise power, D (α) 、E (α) are the convex approximation parameters in the αth iteration;

[0034] in,

[0035]

[0036] In the above formula, k is the packet size, ψ (α) is the ratio of the transmission error probability when the control center receives the data packet from the legitimate sensor in the αth iteration to the eavesdropping failure probability of the illegal eavesdropper, ε b is the transmission error probability when the control center receives a data packet from a legitimate sensor, is the intermediate parameter of the probability of eavesdropping failure of the illegal eavesdropper ω e A, B, and C are all intermediate parameters of the probability of failure of eavesdropping by illegal eavesdroppers ω e Approximate parameters of the Gaussian Q function;

[0037] S42. Solve the reconstructed convex optimization problem model P2 to obtain the optimal code length combination for the energy collection stage and the wireless information transmission stage, thereby maximizing the effective security throughput of smart grid security communications.

[0038] In a second aspect, the present invention proposes a smart grid security communication system based on wireless energy transmission, including a network architecture building module, an effective security throughput determination module, an optimization problem model building module, and an optimization problem model solving module;

[0039] The network architecture building module is used to build a wireless energy transmission-enabled sensor communication network architecture for smart grids, wherein the network architecture includes legal sensors, a control center, and illegal eavesdroppers, wherein the legal sensors obtain power from the control center during the energy collection phase and transmit power grid data to the control center during the wireless information transmission phase;

[0040] The effective safety throughput determination module is used to determine the effective safety throughput of smart grid safety communication based on the wireless energy transmission enabled sensor communication network architecture;

[0041] The optimization problem model building module is used to build an optimization problem model P1 with the goal of maximizing the effective security throughput of smart grid security communication based on the effective security throughput of smart grid security communication;

[0042] The optimization problem model solving module is used to solve the optimization problem model P1, obtain the optimal code length combination in the energy collection stage and the wireless information transmission stage, and realize the secure communication of wireless energy transmission in the smart grid.

[0043] The network architecture building module includes an energy collection unit and a wireless information transmission unit;

[0044] The energy collection unit is used for, during the energy collection phase, the control center sends a radio frequency signal to the legal sensor, and the legal sensor converts the radio frequency signal into a direct current signal through the energy collection device to charge the legal sensor;

[0045] The charging power of the legal sensor is:

[0046] P ch =F nl (Q a );

[0047] Q a =P·h a，b ;

[0048] In the above formula, P ch is the charging power of the legal sensor, F n1 (·) is the nonlinear relationship between charging power and received RF signal power, Q a is the radio frequency signal power received by the legal sensor from the control center, P is the transmission power of the control center, and h a，b is the path loss between the legitimate sensor and the control center;

[0049] The wireless information transmission unit is used to utilize the energy obtained in the energy collection phase. The legitimate sensor sends the power grid operation data to the control center during the wireless information transmission phase. The illegal eavesdropper will try to intercept the power grid operation data during the transmission process.

[0050] The data transmission transmission power of the legal sensor is:

[0051]

[0052] In the above formula, P a is the transmission power of legal sensor data transmission, n c 、n r They are the code lengths of the energy collection phase and the wireless information transmission phase respectively.

[0053] In the effective safety throughput determination module, the effective safety throughput of the smart grid safety communication is calculated using the following formula:

[0054]

[0055] ε LF =1-(1-ε b )ε e ;

[0056]

[0057] In the above formula, τ is the effective security throughput of smart grid security communication, k is the packet size, and n is c 、n r are the code lengths of the energy collection phase and the wireless information transmission phase, respectively, LF is the “leakage-failure” probability of smart grid security communication, ε b is the transmission error probability when the control center receives a data packet from a legitimate sensor, ε e is the eavesdropping failure probability of an illegal eavesdropper, is the Gaussian Q function, ω b is the intermediate parameter of the control center transmission error probability, γ b is the signal-to-noise ratio when the control center receives a data packet from a legitimate sensor, P ch is the charging power of the legal sensor, h a，b is the path loss between the legitimate sensor and the control center, σ 2 is the signal noise power, ω e is the intermediate parameter of the probability of eavesdropping failure of the illegal eavesdropper, γ e is the signal-to-noise ratio of the illegal eavesdropper, h a，e is the path loss between the legitimate sensor and the illegal eavesdropper, Q jamis the interference signal power from the control center received by the illegal eavesdropper, P is the transmission power of the control center, and h b，e is the path loss between the control center and the illegal eavesdropper.

[0058] In the optimization problem model building module, the optimization problem model P1 with the goal of maximizing the effective security throughput of smart grid security communication is:

[0059]

[0060] In the above formula, τ is the effective security throughput of smart grid security communication, n c 、n r are the code lengths of the energy collection phase and the wireless information transmission phase, respectively; k is the packet size, and ε LF is the “leakage-failure” probability of smart grid security communication, n total is the upper limit of the total code length in the energy collection phase and the wireless information transmission phase, γ b is the signal-to-noise ratio when the control center receives a data packet from a legitimate sensor, P ch is the charging power of the legal sensor, h a，e is the path loss between the legitimate sensor and the illegal eavesdropper, Q jam is the interference signal power from the control center received by the illegal eavesdropper, σ 2 is the signal-to-noise power.

[0061] The optimization problem model solving module includes an optimization problem model reconstruction unit and an optimization problem model solving unit;

[0062] The optimization problem model reconstruction unit is used to reconstruct the optimization problem model P1 into a convex optimization problem model P2:

[0063] P2: min(-τ new ) = ρ1 + ρ2 - ρ3;

[0064]

[0065] In the above formula, τ new is the effective security throughput of the new smart grid security communication after model reconstruction, ρ1 is the first intermediate parameter variable, ρ2 is the second intermediate parameter variable, ρ3 is the third intermediate parameter variable, and n c 、n r are the code lengths of the energy collection phase and the wireless information transmission phase, n total is the upper limit of the total code length in the energy collection phase and the wireless information transmission phase, γ b is the signal-to-noise ratio when the control center receives data packets from legitimate sensors, P ch is the charging power of the legal sensor, ha，e is the path loss between the legitimate sensor and the illegal eavesdropper, Q jam is the interference signal power from the control center received by the illegal eavesdropper, σ 2 is the signal noise power, D (α) 、E (α) are the convex approximation parameters in the αth iteration;

[0066] in,

[0067]

[0068]

[0069] In the above formula, k is the packet size, ψ (α) is the ratio of the transmission error probability when the control center receives the data packet from the legitimate sensor in the αth iteration to the eavesdropping failure probability of the illegal eavesdropper, ε b is the transmission error probability when the control center receives a data packet from a legitimate sensor, is the intermediate parameter of the probability of eavesdropping failure of the illegal eavesdropper ω e A, B, and C are all intermediate parameters of the probability of failure of eavesdropping by illegal eavesdroppers ω e Approximate parameters of the Gaussian Q function;

[0070] The optimization problem model solving unit is used to solve the reconstructed convex optimization problem model P2, obtain the optimal code length combination in the energy collection stage and the wireless information transmission stage, and maximize the effective security throughput of the smart grid security communication.

[0071] Compared with the prior art, the present invention has the following beneficial effects:

[0072] The present invention proposes a smart grid security communication method and system based on wireless energy transmission. The method first constructs a wireless energy transmission-enabled sensor communication network architecture for the smart grid, wherein the network architecture includes legal sensors, a control center, and illegal eavesdroppers; then, based on the wireless energy transmission-enabled sensor communication network architecture, the effective security throughput of the smart grid security communication is determined; and based on the effective security throughput of the smart grid security communication, an optimization problem model P1 is constructed with the goal of maximizing the effective security throughput of the smart grid security communication; finally, the optimization problem model P1 is solved to obtain the optimal code length combination of the energy collection stage and the wireless information transmission stage, thereby realizing the secure communication of the smart grid wireless energy transmission. On the one hand, this method divides the wireless energy transmission-enabled sensor communication network architecture into an energy collection stage and a wireless information transmission stage, providing sustainable energy for sensor nodes widely deployed in smart grids and ensuring the long-term operation of sensor nodes; on the other hand, this method aims to maximize the effective security throughput of smart grid security communications, and constructs an optimization problem model for smart grid security communications, which is particularly suitable for energy supply and data transmission of remote devices. In a dynamic and complex power grid environment, by solving the optimization problem model P1, the optimal code length combination of the energy collection stage and the wireless information transmission stage is obtained, maximizing the effective security throughput of smart grid security communications. While ensuring the security of smart grid communications, it reduces the operating energy consumption of sensor equipment, improves the reliability of data transmission, and ensures the stability and adaptability of the power grid system in actual operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0073] Figure 1 The figure is an overall flow chart of the method of the present invention.

[0074] Figure 2 This is a structural diagram of the sensor communication network architecture described in Example 1.

[0075] Figure 3 The structure diagram of the system of the present invention is shown in FIG. DETAILED DESCRIPTION

[0076] The present invention is further described in detail below in conjunction with specific implementations and drawings.

[0077] The present invention proposes a smart grid security communication method and system based on wireless energy transmission, which are applied to Internet of Things devices in the smart grid, such as distribution terminals, substation sensors, distributed energy management nodes, etc., to address the problem of insufficient balance between security and reliability of existing smart grid communications, and to meet the security communication needs of smart grids based on wireless energy transmission. With the goal of maximizing the effective security throughput of smart grid security communications and the constraint of meeting the security and reliability requirements of smart grid data transmission, an optimization problem model for smart grid security communications is constructed. While improving the security data transmission efficiency and overall network performance of devices in the smart grid, low energy consumption operation of sensor devices and high reliability of data transmission are ensured.

[0078] Embodiment 1:

[0079] like Figure 1 As shown, a smart grid secure communication method based on wireless energy transmission is performed in the following steps:

[0080] 1. Build a wireless energy transmission-enabled sensor communication network architecture for smart grids:

[0081] Wireless energy transfer enables sensor communication network architecture such as Figure 2 As shown, it includes legal sensors, a control center, and illegal eavesdroppers, wherein legal sensors are used to monitor the operating status of the smart grid, such as sensors in substations and power distribution terminals. Legal sensors are powered by wireless energy transmission and transmit the collected grid operation data to the control center when the energy is sufficient; the control center is used to provide energy and receive data for legal sensors, that is, to power legal sensors through wireless energy transmission and receive grid operation data transmitted by legal sensors; it is assumed that there are potential illegal eavesdroppers, which are used to intercept the communication between legal sensors and the control center and steal key operation data in the grid;

[0082] The working process in the wireless energy transmission enabled sensor communication network architecture is divided into the energy collection stage and the wireless information transmission stage. In the energy collection stage, the control center sends radio frequency signals to the legitimate sensors, and the legitimate sensors convert the radio frequency signals into direct current signals through the energy collection device to charge the legitimate sensors for use in the collection of grid operation data and data transmission by the sensor equipment; in the wireless information transmission stage, the legitimate sensors use the energy obtained in the energy collection stage to send grid operation data to the control center, and illegal eavesdroppers will try to intercept these data during the transmission process;

[0083] During the energy harvesting phase, the charging power of the legal sensor is:

[0084] P ch =F nl (Q a );

[0085] Q a =P·h a，b ;

[0086] In the above formula, P ch is the charging power of the legal sensor, F n1 (·) is the nonlinear relationship between charging power and received RF signal power, i.e., nonlinear energy harvesting model function, Q a is the radio frequency signal power received by the legal sensor from the control center, P is the transmission power of the control center, and h a，b is the path loss between the legitimate sensor and the control center;

[0087] In the wireless information transmission stage, the data transmission transmission power of the legal sensor is:

[0088]

[0089] In the above formula, P a is the transmission power of legal sensor data transmission, n c 、n r They are the code lengths of the energy collection phase and the wireless information transmission phase, i.e., the number of symbols, indicating the time length of each symbol.

[0090] 2. Determine the effective security throughput of smart grid security communications based on a wireless energy transfer enabled sensor communication network architecture;

[0091] Before determining the effective security throughput of smart grid security communication, the "leakage-failure" probability of smart grid security communication is first characterized. The "leakage-failure" probability of smart grid security communication is defined as the probability that the data of a legitimate sensor is eavesdropped and successfully decoded by an illegal eavesdropper, or the probability that the grid operation data sent by a legitimate sensor cannot be correctly decoded by the control center. In order to characterize the "leakage-failure" probability of smart grid security communication, it is necessary to characterize the signal-to-noise ratio when the control center receives the data packet from the legitimate sensor, as well as the signal-to-noise ratio of the illegal eavesdropper;

[0092] Among them, the signal-to-noise ratio when the control center receives a legitimate sensor data packet is:

[0093]

[0094] In the above formula, γ b is the signal-to-noise ratio when the control center receives a data packet from a legitimate sensor, P ch is the charging power of the legal sensor, n c 、n r are the code lengths of the energy collection phase and the wireless information transmission phase, respectively. a，bis the path loss between the legitimate sensor and the control center, σ 2 is the signal-to-noise power;

[0095] The signal-to-noise ratio of an illegal eavesdropper is:

[0096]

[0097] In the above formula, γ e is the signal-to-noise ratio of the illegal eavesdropper, h a，e is the path loss between the legitimate sensor and the illegal eavesdropper, Q jam is the interference signal power from the control center received by the illegal eavesdropper, P is the transmission power of the control center, and h b，e is the path loss between the control center and the illegal eavesdropper;

[0098] Based on the signal-to-noise ratio when the control center receives data packets from legitimate sensors and the signal-to-noise ratio of illegal eavesdroppers, and according to the transmission communication performance of finite code length, the transmission error probability when the control center receives data packets from legitimate sensors and the eavesdropping failure probability of illegal eavesdroppers are calculated;

[0099] Among them, the transmission error probability when the control center receives a data packet from a legitimate sensor is calculated using the following formula:

[0100]

[0101] In the above formula, ε b is the transmission error probability when the control center receives a data packet from a legitimate sensor, is the Gaussian Q function, defined as ω b is the intermediate parameter of the control center transmission error probability, k is the data packet size;

[0102] The failure probability of an illegal eavesdropper's eavesdropping is calculated using the following formula:

[0103]

[0104] In the above formula, ε e is the eavesdropping failure probability of the illegal eavesdropper, ω e is the intermediate parameter of the probability of eavesdropping failure of an illegal eavesdropper;

[0105] In summary, the "leakage-failure" probability of smart grid security communication can be expressed as:

[0106] ε LF =1-(1-ε b )ε e ;

[0107] In the above formula, εLF The “leakage-failure” probability of secure communication for smart grids;

[0108] Finally, the effective security throughput of smart grid security communication is determined and calculated using the following formula:

[0109]

[0110] In the above formula, τ is the effective security throughput of smart grid security communication.

[0111] 3. Based on the effective security throughput of smart grid security communication, an optimization problem model P1 is constructed to maximize the effective security throughput of smart grid security communication;

[0112] The purpose of the optimization problem model P1 is to find the best code length configuration that can simultaneously meet the security and reliability of smart grid communication by adjusting the code length in the energy collection phase and the wireless information transmission phase, so as to minimize the probability of leakage failure and maximize the effective security throughput of smart grid security communication;

[0113] The optimization problem model P1, which aims to maximize the effective security throughput of smart grid security communication, is constructed as follows:

[0114]

[0115] In the above formula, τ is the effective security throughput of smart grid security communication, n c 、n r are the code lengths of the energy collection phase and the wireless information transmission phase, respectively; k is the packet size, and ε LF is the “leakage-failure” probability of smart grid security communication, n total is the upper limit of the total code length in the energy collection phase and the wireless information transmission phase, γ b is the signal-to-noise ratio when the control center receives a data packet from a legitimate sensor, P ch is the charging power of the legal sensor, h a，e is the path loss between the legitimate sensor and the illegal eavesdropper, Q jam is the interference signal power from the control center received by the illegal eavesdropper, σ 2 is the signal-to-noise power.

[0116] 4. Since the optimization problem model P1 constructed to maximize the effective security throughput of smart grid security communication is a non-convex problem and cannot be solved, the optimization problem model P1 is reconstructed into a convex optimization problem model P2 through an approximate algorithm;

[0117] Through the approximate algorithm, the steps of reconstructing the optimization problem model P1 include:

[0118] First, the “leakage-failure” probability ε of smart grid security communication in the objective function of the optimization problem model P1 is LF To constrain:

[0119]

[0120] In the above formula, ε LF is the “leakage-failure” probability of smart grid security communication, ε b is the transmission error probability when the control center receives a data packet from a legitimate sensor, ε e is the eavesdropping failure probability of the illegal eavesdropper, ψ (α) is the ratio of the transmission error probability when the control center receives the data packet from the legitimate sensor in the αth iteration to the eavesdropping failure probability of the illegal eavesdropper, that is, And (α) ≥0; the formula is Place to take, etc. are the values ​​of the code length in the energy collection phase and the code length in the wireless information transmission phase in the αth iteration respectively;

[0121] Due to ε LF =1-(1-ε b )ε e , In order to facilitate the solution, for Q(ω e ) to approximate the upper and lower bounds and convert it into a convex function:

[0122] For a given illegal eavesdropper, the intermediate parameter of the eavesdropping failure probability ω e Local point Q(ω e ) has the following upper and lower bounds:

[0123]

[0124] In the above formula, Q(ω e ) is the Gaussian Q function of the intermediate parameter of the probability of failure of eavesdropping by the illegal eavesdropper. When equal, A, B, and C are Approximate parameters of ;

[0125] Comprehensive smart grid security communication "leakage-failure" probability constraints and Q(ω e ) is approximated by the upper and lower bounds, and the objective function of the optimization problem model P1 is transformed into:

[0126] min(-τ new ) = ρ1 + ρ2 - ρ3;

[0127]

[0128] In the above formula, τ new is the effective security throughput of the new smart grid security communication after model reconstruction, ρ1 is the first intermediate parameter variable, ρ2 is the second intermediate parameter variable, and ρ3 is the third intermediate parameter variable; k is the packet size, n c 、n r are the code lengths of the energy collection phase and the wireless information transmission phase respectively;

[0129] Then, the non-convex constraints in the optimization problem model P1 are Perform a preliminary exponential transformation and a continuous convex approximation:

[0130] Among them, the preliminary index is converted into:

[0131]

[0132] In the above formula, P ch is the charging power of the legal sensor, h a，e is the path loss between the legitimate sensor and the illegal eavesdropper, Q jam is the interference signal power from the control center received by the illegal eavesdropper, σ 2 is the signal-to-noise power;

[0133] The continuous convex approximation is:

[0134]

[0135] In the above formula, D (α) 、E (α) are the convex approximation parameters in the αth iteration;

[0136] Finally, based on the above objective function transformation and constraint processing of the optimization problem model P1, the optimization problem model P1 is reconstructed into a convex optimization problem model as shown in P2:

[0137] P2:min(-τ new ) = ρ1 + ρ2 - ρ3;

[0138]

[0139] In the above formula, n total is the upper limit of the total code length in the energy collection phase and the wireless information transmission phase, γ b It is the signal-to-noise ratio when the control center receives data packets from legitimate sensors; the optimization problem model P2 has a convex relationship with the code length in the energy collection phase and the code length in the wireless information transmission phase.

[0140] 5. Solve the reconstructed optimization problem model P2 through the alternating optimization algorithm to obtain the optimal code length combination in the energy collection stage and the wireless information transmission stage, thereby maximizing the effective security throughput of smart grid security communication and realizing the security communication of smart grid wireless energy transmission;

[0141] The reconstructed convex optimization problem model P2 is decomposed into two sub-problems:

[0142] Sub-problem 1: By fixing the code length n during the wireless information transmission phase r , optimize the code length n in the energy harvesting phase c ;

[0143] Sub-problem 2: By fixing the code length n during the energy harvesting phase c , optimize the code length n in the wireless information transmission stage r ;

[0144] Alternately optimize n of subproblems 1 and 2 c 、n r The steps include:

[0145] Step 1: Initialize and define the maximum effective security throughput as τ new 0 , the code length in the wireless information transmission phase is n r [0] , the code length of the optimal wireless information transmission stage is n r * , and let n r * =n r [0] , initialize the number of alternating iterations ξ=1;

[0146] Step 2: In a given optimal wireless information transmission phase, the code length n r * Next, solve subproblem 1 to obtain the optimal code length n in the energy harvesting phase. c * ;

[0147] Step 3: Substitute the optimal code length n obtained in step 2 for the energy collection phase c * Substitute the known value into subproblem 2 to solve and obtain the optimal code length n for the wireless information transmission stage. r * ;

[0148] Step 4: Based on the n obtained in Step 2 and Step 3 c * 、n r * , calculate the maximum effective security throughput τ obtained in the ξth alternating iterationnew ξ ;

[0149] Step 5: Determine τ new ξ -τ new ξ-1 <τ th Whether it satisfies, where τ th To determine the threshold of the convergence of the alternating optimization, if it is satisfied, then exit the alternating optimization and obtain the optimal code length combination of the energy collection phase and the wireless information transmission phase. If it is not satisfied, set ξ=ξ+1 and return to step 2 to continue the alternating optimization;

[0150] Finally, through the above steps, the optimal solution of the reconstructed convex optimization problem model P2 is gradually approached, and the optimal code length combination of the energy collection stage and the wireless information transmission stage is obtained to maximize the effective security throughput of smart grid security communication.

[0151] Embodiment 2:

[0152] like Figure 3 As shown, a smart grid security communication system based on wireless energy transmission includes a network architecture building module, an effective security throughput determination module, an optimization problem model building module, and an optimization problem model solving module;

[0153] The network architecture building module is used to build a wireless energy transmission-enabled sensor communication network architecture for smart grids, wherein the network architecture includes legal sensors, a control center, and illegal eavesdroppers, wherein the legal sensors obtain power from the control center during the energy collection phase and transmit power grid data to the control center during the wireless information transmission phase;

[0154] The effective safety throughput determination module is used to determine the effective safety throughput of smart grid safety communication based on the wireless energy transmission enabled sensor communication network architecture;

[0155] The optimization problem model building module is used to build an optimization problem model P1 with the goal of maximizing the effective security throughput of smart grid security communication based on the effective security throughput of smart grid security communication;

[0156] The optimization problem model solving module is used to solve the optimization problem model P1, obtain the optimal code length combination in the energy collection stage and the wireless information transmission stage, and realize the secure communication of wireless energy transmission in the smart grid.

[0157] The network architecture building module includes an energy collection unit and a wireless information transmission unit;

[0158] The energy collection unit is used for, during the energy collection phase, the control center sends a radio frequency signal to the legal sensor, and the legal sensor converts the radio frequency signal into a direct current signal through the energy collection device to charge the legal sensor;

[0159] The charging power of the legal sensor is:

[0160] P ch =F nl (Q a );

[0161] Q a =P·h a，b ;

[0162] In the above formula, P ch is the charging power of the legal sensor, F n1 (·) is the nonlinear relationship between charging power and received RF signal power, Q a is the radio frequency signal power received by the legal sensor from the control center, P is the transmission power of the control center, and h a，b is the path loss between the legitimate sensor and the control center;

[0163] The wireless information transmission unit is used to utilize the energy obtained in the energy collection phase. The legitimate sensor sends the power grid operation data to the control center during the wireless information transmission phase. The illegal eavesdropper will try to intercept the power grid operation data during the transmission process.

[0164] The data transmission transmission power of the legal sensor is:

[0165]

[0166] In the above formula, P a is the transmission power of legal sensor data transmission, n c 、n r They are the code lengths of the energy collection phase and the wireless information transmission phase respectively.

[0167] In the effective safety throughput determination module, the effective safety throughput of the smart grid safety communication is calculated using the following formula:

[0168]

[0169] ε LF =1-(1-ε b )ε e ;

[0170]

[0171]

[0172] In the above formula, τ is the effective security throughput of smart grid security communication, k is the packet size, and n is c 、n r are the code lengths of the energy collection phase and the wireless information transmission phase, respectively, LF is the “leakage-failure” probability of smart grid security communication, ε b is the transmission error probability when the control center receives a data packet from a legitimate sensor, ε e is the eavesdropping failure probability of an illegal eavesdropper, is the Gaussian Q function, ω b is the intermediate parameter of the control center transmission error probability, γ b is the signal-to-noise ratio when the control center receives a data packet from a legitimate sensor, P ch is the charging power of the legal sensor, h a，b is the path loss between the legitimate sensor and the control center, σ 2 is the signal noise power, ω e is the intermediate parameter of the probability of eavesdropping failure of the illegal eavesdropper, γ e is the signal-to-noise ratio of the illegal eavesdropper, h a，e is the path loss between the legitimate sensor and the illegal eavesdropper, Q jam is the interference signal power from the control center received by the illegal eavesdropper, P is the transmission power of the control center, and h b，e is the path loss between the control center and the illegal eavesdropper.

[0173] In the optimization problem model building module, the optimization problem model P1 with the goal of maximizing the effective security throughput of smart grid security communication is:

[0174]

[0175] In the above formula, τ is the effective security throughput of smart grid security communication, n c 、n r are the code lengths of the energy collection phase and the wireless information transmission phase, respectively; k is the packet size, and ε LF is the “leakage-failure” probability of smart grid security communication, n total is the upper limit of the total code length in the energy collection phase and the wireless information transmission phase, γ b is the signal-to-noise ratio when the control center receives a data packet from a legitimate sensor, P ch is the charging power of the legal sensor, h a，e is the path loss between the legitimate sensor and the illegal eavesdropper, Q jam is the interference signal power from the control center received by the illegal eavesdropper, σ 2 is the signal-to-noise power.

[0176] The optimization problem model solving module includes an optimization problem model reconstruction unit and an optimization problem model solving unit;

[0177] The optimization problem model reconstruction unit is used to reconstruct the optimization problem model P1 into a convex optimization problem model P2:

[0178] P2: min(-τ new ) = ρ1 + ρ2 - ρ3;

[0179]

[0180] In the above formula, τ new is the effective security throughput of the new smart grid security communication after model reconstruction, ρ1 is the first intermediate parameter variable, ρ2 is the second intermediate parameter variable, ρ3 is the third intermediate parameter variable, and n c 、n r are the code lengths of the energy collection phase and the wireless information transmission phase, n total is the upper limit of the total code length in the energy collection phase and the wireless information transmission phase, γ b is the signal-to-noise ratio when the control center receives data packets from legitimate sensors, P ch is the charging power of the legal sensor, h a，e is the path loss between the legitimate sensor and the illegal eavesdropper, Q jam is the interference signal power from the control center received by the illegal eavesdropper, σ 2 is the signal noise power, D (α) 、E (α) are the convex approximation parameters in the αth iteration;

[0181] in,

[0182]

[0183] In the above formula, k is the packet size, ψ (α) is the ratio of the transmission error probability when the control center receives the data packet from the legitimate sensor in the αth iteration to the eavesdropping failure probability of the illegal eavesdropper, ε b is the transmission error probability when the control center receives a data packet from a legitimate sensor, is the intermediate parameter of the probability of eavesdropping failure of the illegal eavesdropper ω e A, B, and C are all intermediate parameters of the probability of failure of eavesdropping by illegal eavesdroppers ω e Approximate parameters of the Gaussian Q function;

[0184] The optimization problem model solving unit is used to solve the reconstructed convex optimization problem model P2, obtain the optimal code length combination in the energy collection stage and the wireless information transmission stage, and maximize the effective security throughput of the smart grid security communication.

Claims

1. A smart grid secure communication method based on wireless energy transmission, characterized in that: The method comprises: S1. Construct a wireless energy transmission-enabled sensor communication network architecture for smart grids, wherein the network architecture includes legal sensors, a control center, and illegal eavesdroppers, wherein the legal sensors obtain power from the control center during the energy collection phase and transmit grid data to the control center during the wireless information transmission phase; S2,determine the effective security throughput of smart grid security communication based on wireless energy transfer enabled sensor communication network architecture; S3, based on the effective security throughput of smart grid security communication, construct an optimization problem model P1 with the goal of maximizing the effective security throughput of smart grid security communication; S4. Solve the optimization problem model P1 to obtain the optimal code length combination for the energy collection stage and the wireless information transmission stage, and realize the secure communication of wireless energy transmission in the smart grid.

2. A smart grid secure communication method based on wireless energy transmission according to claim 1, characterized in that: The S1 includes: S11, energy collection stage, the control center sends a radio frequency signal to the legal sensor, and the legal sensor converts the radio frequency signal into a direct current signal through the energy collection device to charge the legal sensor; The charging power of the legal sensor is: P ch =F nl (Q a ); Q a =P·h a，b ; In the above formula, P ch is the charging power of the legal sensor, F n1 (·) is the nonlinear relationship between charging power and received RF signal power, Q a is the radio frequency signal power received by the legal sensor from the control center, P is the transmission power of the control center, and h a，b is the path loss between the legitimate sensor and the control center; S12, using the energy obtained in the energy collection phase, the legitimate sensor sends the power grid operation data to the control center during the wireless information transmission phase, and the illegal eavesdropper will try to intercept the power grid operation data during the transmission process; The data transmission transmission power of the legal sensor is: In the above formula, P a is the transmission power of legal sensor data transmission, n c 、n r They are the code lengths of the energy collection phase and the wireless information transmission phase respectively.

3. A smart grid secure communication method based on wireless energy transmission according to claim 1, characterized in that: In S2, the effective security throughput of the smart grid security communication is calculated using the following formula: e LF =1-(1-e b )e e ; Q jam =P·h b，e ; In the above formula, τ is the effective security throughput of smart grid security communication, k is the packet size, and n is c 、n r are the code lengths of the energy collection phase and the wireless information transmission phase, respectively, LF is the "leakage-failure" probability of smart grid security communication, ε b is the transmission error probability when the control center receives a data packet from a legitimate sensor, ε e is the eavesdropping failure probability of an illegal eavesdropper, is the Gaussian Q function, ω b is the intermediate parameter of the control center transmission error probability, γ b is the signal-to-noise ratio when the control center receives a data packet from a legitimate sensor, P ch is the charging power of the legal sensor, h a，b is the path loss between the legitimate sensor and the control center, σ 2 is the signal noise power, ω e is the intermediate parameter of the probability of eavesdropping failure of the illegal eavesdropper, γ e is the signal-to-noise ratio of the illegal eavesdropper, h a，e is the path loss between the legitimate sensor and the illegal eavesdropper, Q jam is the interference signal power from the control center received by the illegal eavesdropper, P is the transmission power of the control center, and h b，e is the path loss between the control center and the illegal eavesdropper.

4. A smart grid secure communication method based on wireless energy transmission according to claim 1, characterized in that: In S3, the optimization problem model P1 with the goal of maximizing the effective security throughput of smart grid security communication is: In the above formula, τ is the effective security throughput of smart grid security communication, n c 、n r are the code lengths of the energy collection phase and the wireless information transmission phase, respectively; k is the packet size, and ε LF is the "leakage-failure" probability of smart grid security communication, n total is the upper limit of the total code length in the energy collection phase and the wireless information transmission phase, γ b is the signal-to-noise ratio when the control center receives a data packet from a legitimate sensor, P ch is the charging power of the legal sensor, h a，e is the path loss between the legitimate sensor and the illegal eavesdropper, Q jam is the interference signal power from the control center received by the illegal eavesdropper, σ 2 is the signal-to-noise power.

5. A smart grid secure communication method based on wireless energy transmission according to claim 1, characterized in that: The S4 includes: S41, reconstruct the optimization problem model P1 into a convex optimization problem model P2: P2:min(-τ new )=ρ1+ρ2-ρ3; In the above formula, τ new is the effective security throughput of the new smart grid security communication after model reconstruction, ρ1 is the first intermediate parameter variable, ρ2 is the second intermediate parameter variable, ρ3 is the third intermediate parameter variable, and n c 、n r are the code lengths of the energy collection phase and the wireless information transmission phase, n total is the upper limit of the total code length in the energy collection phase and the wireless information transmission phase, γ b is the signal-to-noise ratio when the control center receives data packets from legitimate sensors, p ch is the charging power of the legal sensor, h a，e is the path loss between the legitimate sensor and the illegal eavesdropper, Q jam is the interference signal power from the control center received by the illegal eavesdropper, σ 2 is the signal noise power, D (α) 、E (α) are the convex approximation parameters in the αth iteration; in, In the above formula, k is the packet size, ψ (α) is the ratio of the transmission error probability when the control center receives the data packet from the legitimate sensor in the αth iteration to the eavesdropping failure probability of the illegal eavesdropper, ε b is the transmission error probability when the control center receives a data packet from a legitimate sensor, is the intermediate parameter of the illegal eavesdropper's eavesdropping failure probability ω e A, B, and C are all intermediate parameters of the probability of failure of eavesdropping by illegal eavesdroppers ω e Approximate parameters of the Gaussian Q function; S42. Solve the reconstructed convex optimization problem model P2 to obtain the optimal code length combination for the energy collection stage and the wireless information transmission stage, thereby maximizing the effective security throughput of smart grid security communications.

6. A smart grid security communication system based on wireless energy transmission, characterized in that: The system includes a network architecture building module, an effective safety throughput determination module, an optimization problem model building module, and an optimization problem model solving module; The network architecture building module is used to build a wireless energy transmission-enabled sensor communication network architecture for smart grids, wherein the network architecture includes legal sensors, a control center, and illegal eavesdroppers, wherein the legal sensors obtain power from the control center during the energy collection phase and transmit power grid data to the control center during the wireless information transmission phase; The effective safety throughput determination module is used to determine the effective safety throughput of smart grid safety communication based on the wireless energy transmission enabled sensor communication network architecture; The optimization problem model building module is used to build an optimization problem model P1 with the goal of maximizing the effective security throughput of smart grid security communication based on the effective security throughput of smart grid security communication; The optimization problem model solving module is used to solve the optimization problem model P1, obtain the optimal code length combination in the energy collection stage and the wireless information transmission stage, and realize the secure communication of wireless energy transmission in the smart grid.

7. A smart grid security communication system based on wireless energy transmission according to claim 6, characterized in that: The network architecture building module includes an energy collection unit and a wireless information transmission unit; The energy collection unit is used for, during the energy collection stage, the control center sends a radio frequency signal to the legal sensor, and the legal sensor converts the radio frequency signal into a direct current signal through the energy collection device to charge the legal sensor; The charging power of the legal sensor is: P ch =F n1 (Q a ); Q a =P·h a，b ; In the above formula, P ch is the charging power of the legal sensor, F n1 (·) is the nonlinear relationship between charging power and received RF signal power, Q a is the radio frequency signal power received by the legal sensor from the control center, P is the transmission power of the control center, and h a,b is the path loss between the legitimate sensor and the control center; The wireless information transmission unit is used to utilize the energy obtained in the energy collection phase. The legitimate sensor sends the power grid operation data to the control center during the wireless information transmission phase. The illegal eavesdropper will try to intercept the power grid operation data during the transmission process. The data transmission transmission power of the legal sensor is: In the above formula, P a is the transmission power of legal sensor data transmission, n c 、n r They are the code lengths of the energy collection phase and the wireless information transmission phase respectively.

8. A smart grid security communication system based on wireless energy transmission according to claim 6, characterized in that: In the effective safety throughput determination module, the effective safety throughput of the smart grid safety communication is calculated using the following formula: e LF =1-(1-e b )e e ; Q jam =P·h b，e ; In the above formula, τ is the effective security throughput of smart grid security communication, k is the packet size, and n is c 、n r are the code lengths of the energy collection phase and the wireless information transmission phase, respectively, LF is the "leakage-failure" probability of smart grid security communication, ε b is the transmission error probability when the control center receives a data packet from a legitimate sensor, ε e is the eavesdropping failure probability of an illegal eavesdropper, is the Gaussian Q function, ω b is the intermediate parameter of the control center transmission error probability, γ b is the signal-to-noise ratio when the control center receives a data packet from a legitimate sensor, P ch is the charging power of the legal sensor, h a，b is the path loss between the legitimate sensor and the control center, σ 2 is the signal noise power, ω e is the intermediate parameter of the probability of eavesdropping failure of the illegal eavesdropper, γ e is the signal-to-noise ratio of the illegal eavesdropper, h a，e is the path loss between the legitimate sensor and the illegal eavesdropper, Q jam is the interference signal power from the control center received by the illegal eavesdropper, P is the transmission power of the control center, and h b，e is the path loss between the control center and the illegal eavesdropper.

9. A smart grid security communication system based on wireless energy transmission according to claim 6, characterized in that: In the optimization problem model building module, the optimization problem model P1 with the goal of maximizing the effective security throughput of smart grid security communication is: In the above formula, τ is the effective security throughput of smart grid security communication, n c 、n r are the code lengths of the energy collection phase and the wireless information transmission phase, respectively; k is the packet size, and ε LF is the "leakage-failure" probability of smart grid security communication, n total is the upper limit of the total code length in the energy collection phase and the wireless information transmission phase, γ b is the signal-to-noise ratio when the control center receives a data packet from a legitimate sensor, P ch is the charging power of the legal sensor, h a，e is the path loss between the legitimate sensor and the illegal eavesdropper, Q jam is the interference signal power from the control center received by the illegal eavesdropper, σ 2 is the signal-to-noise power.

10. A smart grid security communication system based on wireless energy transmission according to claim 6, characterized in that: The optimization problem model solving module includes an optimization problem model reconstruction unit and an optimization problem model solving unit; The optimization problem model reconstruction unit is used to reconstruct the optimization problem model P1 into a convex optimization problem model P2: P2:min(-τ new )=ρ1+ρ2-ρ3; In the above formula, τ new is the effective security throughput of the new smart grid security communication after model reconstruction, ρ1 is the first intermediate parameter variable, ρ2 is the second intermediate parameter variable, ρ3 is the third intermediate parameter variable, and n c 、n r are the code lengths of the energy collection phase and the wireless information transmission phase, n total is the upper limit of the total code length in the energy collection phase and the wireless information transmission phase, γ b is the signal-to-noise ratio when the control center receives data packets from legitimate sensors, P ch is the charging power of the legal sensor, h a，e is the path loss between the legitimate sensor and the illegal eavesdropper, Q jam is the interference signal power from the control center received by the illegal eavesdropper, σ 2 is the signal noise power, D (α) 、E (α) are the convex approximation parameters in the αth iteration; in, In the above formula, k is the packet size, ψ (α) is the ratio of the transmission error probability when the control center receives the data packet from the legitimate sensor in the αth iteration to the eavesdropping failure probability of the illegal eavesdropper, ε b is the transmission error probability when the control center receives a data packet from a legitimate sensor, is the intermediate parameter of the probability of eavesdropping failure of the illegal eavesdropper ω e A, B, and C are all intermediate parameters of the probability of failure of eavesdropping by illegal eavesdroppers ω e Approximate parameters of the Gaussian Q function; The optimization problem model solving unit is used to solve the reconstructed convex optimization problem model P2, obtain the optimal code length combination in the energy collection stage and the wireless information transmission stage, and maximize the effective security throughput of the smart grid security communication.

Images