A Distributed Economic Dispatch Method for Energy Internet Based on Self-Triggering Mechanism

Abstract

This invention belongs to the field of energy internet economic dispatch and discloses a distributed economic dispatch method for the energy internet based on a self-triggering mechanism. This method consists of energy routers, multiple distributed interconnected microgrids, and a main power grid. Each microgrid comprises distributed generators, intelligent control units, and local loads. Each generator and load is directly controlled by its assigned local intelligent control unit. The intelligent control unit performs information exchange and algorithm calculations. The intelligent control unit calculates and propagates individual electricity prices, while the energy router calculates and propagates the power exchanged with the main power grid. To effectively reduce network communication pressure, a self-triggering mechanism is employed in this process. This invention enables on-demand transmission of electricity prices between intelligent control units, optimizes the total generation cost, significantly reduces network communication pressure, decreases the computational resources of the entire system, and ensures the safe and stable operation of the entire energy internet system.

Description

Technical Field

[0001] This invention belongs to the field of energy internet economic dispatch, specifically relating to a distributed economic dispatch method for the energy internet based on a self-triggering mechanism. Background Technology

[0002] In recent years, renewable energy technologies such as wind power, hydropower, and solar power have been widely applied. Compared with traditional non-renewable energy sources, renewable energy is cleaner and more renewable. Microgrids, composed of distributed renewable energy generators, are flexible and efficient, representing the future trend of renewable energy development. However, the intermittency and uncertainty of renewable energy pose significant challenges to the control and optimization of power systems. The Energy Internet is a network-physical energy system that combines the Internet, renewable energy generators, and smart grid technologies. In the Energy Internet, the main grid is the "backbone," and microgrids are local area networks. In a microgrid, loads and each distributed generator are directly controlled by their respective local smart control units, and adjacent smart control units can exchange information. Energy routers, acting as intermediary units connecting the microgrid and the main grid, ensure the supply and demand balance of the microgrid through power exchange.

[0003] With the development of the new energy industry, the economic dispatch problem of the energy internet has become a fundamental issue in energy internet research and application. Through rational allocation, generators can optimize the total power generation cost and improve system reliability under conditions of supply-demand balance and power generation limitations. Currently, traditional economic dispatch optimization methods are based on centralized control. However, centralized control is heavily reliant on a control center; information from each generator must be transmitted to the control center for processing. This not only increases the computational burden on the control center but also significantly increases system operating costs. If one generator fails, the safety and reliability of the entire system will be affected. Therefore, distributed control methods offer a new approach to solving the economic dispatch problem.

[0004] In the distributed framework of the energy internet, distributed generators calculate their average exchange power with the main grid based on a given main grid electricity price, their own load, and line consumption, and then estimate the total exchange power of the microgrid. First, all intelligent control units exchange their individual electricity prices with their neighbors and reach a consensus price through a consensus algorithm. Second, they calculate the exchange power with the main grid using the electricity price and reach an average exchange power through a consensus algorithm. Compared to traditional centralized scheduling methods, the distributed control framework distributes the computational tasks of economic scheduling to each individual in the system, eliminating the need for a complex and expensive central control center. Furthermore, the decentralized execution of computational tasks makes the system more robust, flexible, and economical.

[0005] As mentioned earlier, to execute the energy internet economic dispatch strategy under the distributed control framework, all entities within the system need to exchange information via a communication network. In the future context of renewable energy development, the number of distributed renewable energy sources will increase significantly. The real-time, continuous information exchange between numerous intelligent control units poses a severe challenge to the limited bandwidth resources of the communication network, potentially leading to the failure of the entire energy internet and seriously affecting the stability and security of the energy internet system. Summary of the Invention

[0006] To address the problems of severe waste of communication resources and excessively high proportion of unnecessary communication in the information exchange during the economic dispatch process of the energy internet in existing technologies, this invention provides a distributed economic dispatch method for the energy internet based on a self-triggering mechanism. This method optimizes the total power generation cost while achieving supply and demand balance and power generation limitations. At the same time, while ensuring the effective completion of the above tasks, it reduces the information transmission pressure between various intelligent control units and ensures the safe and stable operation of the dispatch system.

[0007] To achieve the above objectives, the present invention is implemented through the following technical solution:

[0008] This invention is a study on distributed economic dispatching of the energy internet based on a self-triggering mechanism, comprising the following steps:

[0009] Step 1: Set system parameters, including the number of distributed generators N and the discrete time k, s, where A small positive constant is used to determine whether the electricity price and exchange power in the algorithm have become consistent; ε is the algorithm step size; α is a small positive constant. i ,β i B i P for generator i i Determine the parameters, where γ, η, Φ, Γ are the parameters of the triggering condition, and P Di For generator i, the local load, P Li For generator i, the line load.

[0010] Step 2: Set the communication connection coefficient 'a' based on whether the intelligent control units have information exchange capabilities. ij ,j=1,2,3,4......N,i≠j,d i ,d j These are the Laplacian matrix values ​​for communication connectivity coefficients, and the communication connectivity coefficient 'a' with the energy router. i0 .

[0011] Step 3: At the initial moment k0 = 0, the energy router transmits the main grid electricity price λ0 of the energy internet to the intelligent control units of each generator, and the initial electricity price λ of generator i. i(k0) propagates to neighboring generators, assuming the initial trigger time of generator i.

[0012] Step 4: When each intelligent control unit detects that the time equals its own trigger time, that is... Need to predict the next trigger time Proceed to step five; when each intelligent control unit detects that it is not within its own trigger time, i.e., k ≠ k * Then proceed to step seven.

[0013] Step 5: The intelligent control unit stores the current electricity price information and transmits it to the neighbors.

[0014] Step Six: Predict the next trigger time using the self-triggering mechanism Store and send to the adjacent generator.

[0015] Step 7: Each intelligent control unit uses the stored neighbor electricity prices. Its own propagation electricity price The leader follower algorithm is used to determine the main grid electricity price λ0.

[0016] Step 8: Each intelligent control unit determines the electricity price λ at time k. i (k) and the electricity price λ at time k-1 i Is the difference of (k-1) less than If so, the leader in step seven follows the algorithm to the end and obtains the electricity price; otherwise, it returns to step four, and the time is updated to k = k + 1.

[0017] Step Nine: The electricity price algorithm ends. The exchange power of each generator is calculated using the current electricity price and propagated to each generator. The initial time of the exchange power algorithm is s0 = k, and the trigger time of the exchange power algorithm is set to s. i * =s0.

[0018] Step 10: When each intelligent control unit detects that the time equals its own trigger time, that is... We need to predict the next trigger time (s+1). i * Proceed to step eleven; when each intelligent control unit detects that it is not within its own trigger time... Proceed to step thirteen.

[0019] Step 11: The intelligent control unit stores the switching power information and transmits it to the neighbors.

[0020] Step 12: Predict the next trigger time using the self-triggering mechanism Store and send to the adjacent generator.

[0021] Step 13: The intelligent control unit utilizes the stored neighbor exchange power. Its own propagation exchange power Perform a leaderless follower algorithm.

[0022] Step Fourteen: Each intelligent control unit determines the switching power P at time s. MGi P at time (s) and s-1 MGi Is the difference between (s-1) and (s-1) less than 1? If so, the leaderless follower algorithm in step thirteen ends and the exchange power is obtained; otherwise, return to step ten and update the time to s = s + 1.

[0023] Step 15: The power exchange algorithm ends. Each intelligent control unit calculates the average power exchanged between each generator and the main grid, and the energy router can then calculate the total power P exchanged between the main grid and the microgrid. MG0 =NP MGi (s).

[0024] Furthermore, the conditions for the self-triggering mechanism in step six are:

[0025] only

[0026]

[0027] When time k equals trigger time Only then will the self-triggered mechanism operation be performed, making If the algorithm inequality is not true, K is incremented by 1. When the algorithm inequality is true, K is obtained.

[0028] Where: K is used to calculate the next trigger time. The parameters. If the neighbor does not transmit the next trigger time. Using its own trigger time Instead of performing algorithmic calculations.

[0029] Trigger time The value is first updated to the next trigger time. The value is Next trigger time Then update it to the value of K, which is (k+1). i * =K. Because the next trigger time is at k0. If the value does not exist, the above assignment equation cannot be true. Therefore, we preset the next trigger time to be at time k0. Value 1.

[0030] m is a parameter in the self-triggering mechanism algorithm. It is the minimum of the time and the next trigger time of the neighbor. It is the maximum of the time and the next trigger time of the neighbor, where m is the summation parameter in the algorithm, taking values ​​from the next trigger time of the neighbor to...

[0031]

[0032] For the neighbor's electricity price, The electricity price for its own propagation and λ0 for the main grid electricity price.

[0033] Furthermore, the leader-follower algorithm for the electricity price of the i-th generator in step seven is as follows:

[0034]

[0035] Furthermore, in step nine, the P of generator i... i ,P MGi for:

[0036] (If the value exceeds the limit, the upper or lower limit shall be taken) )

[0037] P MGi (s0)=P Di +P Li +P i ,P Li =B i (P i ) 2 .

[0038] Furthermore, the conditions for the self-triggering mechanism in step twelve are as follows:

[0039]

[0040] Only when time s equals the trigger time Only then will the self-triggered mechanism operation be performed, making If the algorithm inequality is not true, K is incremented by 1. When the algorithm inequality is true, K is obtained.

[0041] Where: K is used to calculate the next trigger time. The parameters. If the neighbor does not transmit the next trigger time. Using its own trigger time Instead of performing algorithmic calculations.

[0042] Trigger time The value is first updated to the next trigger time. The value is Next trigger time Then update it to the value of K. Because at time s0, the next trigger time If the value does not exist, the above assignment equation cannot be true. Therefore, we preset the next trigger time to be at time s0. The value is equal to s0+1.

[0043]

[0044]

[0045] Exchange power with neighbors It exchanges power for its own propagation.

[0046] Furthermore, the leaderless follower algorithm for the power exchange of the i-th generator in step thirteen is as follows:

[0047] The beneficial effects of this invention are:

[0048] 1. This invention optimizes the power generation cost of the entire energy internet system by balancing the benefits generated by the energy internet with the costs incurred.

[0049] 2. Based on ensuring the effective completion of the energy internet economic dispatch task, this invention allows the individual electricity price (exchange power) of each generator in the system to be sent to other generators adjacent to it in the microgrid in a discrete non-uniform periodic form according to the set self-triggering mechanism. This can effectively reduce the pressure on the communication network and ensure the safe and stable operation of the energy internet system.

[0050] 3. The self-triggering mechanism and the individual electricity price (exchange power) consistency update algorithm based on this mechanism of the present invention only require obtaining the electricity price (exchange power) of the neighbors to update the current individual electricity price (exchange power). The overall design method is based on a distributed control architecture, which has the characteristics of low cost, strong scalability, and high robustness. At the same time, compared with traditional distributed control methods, it significantly reduces computer monitoring resources and reduces computer resource consumption. Therefore, it is particularly suitable for the energy internet environment of future large-scale and widely distributed microgrids.

[0051] 4. This invention can solve the problem of large-scale distributed economic scheduling of the energy internet under the condition of limited communication network bandwidth resources. Attached Figure Description

[0052] Figure 1 This is a flowchart of the scheduling method of the present invention.

[0053] Figure 2 This is a communication network topology diagram between the generators in an embodiment of the present invention.

[0054] Figure 3This is a graph showing the electricity price trend of each generator in an embodiment of the present invention.

[0055] Figure 4 This is a diagram showing the electricity price triggering times for each generator in an embodiment of the present invention.

[0056] Figure 5 This is a power exchange trend diagram of each generator in an embodiment of the present invention.

[0057] Figure 6 This is a diagram showing the triggering times for the power exchange of each generator in an embodiment of the present invention.

[0058] Figure 7 This is a power exchange trend diagram between the microgrid and the main power grid according to an embodiment of the present invention. Detailed Implementation

[0059] The embodiments of the present invention will be disclosed below with reference to the drawings. For clarity, many practical details will be described in the following description. However, it should be understood that these practical details are not intended to limit the invention. That is, in some embodiments of the invention, these practical details are not essential.

[0060] like Figure 1 As shown, this invention is a distributed economic dispatch method for the energy internet based on a self-triggering mechanism. This method considers the economic dispatch of an energy internet composed of energy routers, multiple distributed interconnected microgrids, and the main power grid. Each microgrid consists of distributed generators, intelligent control units, and local loads. Each generator and load is directly controlled by its assigned local intelligent control unit, which performs information exchange and algorithm calculations. The intelligent control unit calculates and propagates individual electricity prices, while the energy router calculates and propagates the power exchanged with the main power grid. To effectively reduce network communication pressure, a self-triggering mechanism is employed. Specifically, the economic dispatch method of this invention includes the following steps:

[0061] Includes the following steps:

[0062] Step 1: Set system parameters, specifying the number of distributed generators N=5, and parameters.

[0063] α i =[-783.011;-4658.777;-533.761;-604.720;-546.896],β i =[93.81;56.24;64.52;73.75;67.48],B i = [0.00021; 0.00017; 0.00016; 0.00020; 0.00019], ε = 0.1, η = 15, γ = 0.9999, P Di=[2;3.5;2.7;5;3.8],Φ=22.5

[0064] Step 2: Set the communication connection coefficient 'a' based on whether the intelligent control units have information exchange capabilities. ij j = 1, 2, 3, 4, ..., N, i ≠ j. If generator i has the ability to exchange information with generator j, then a ij =1, otherwise a ij =0,d i ,d j These are the Laplacian matrix values ​​for communication connectivity coefficients, and the communication connectivity coefficient 'a' with the energy router. i0 .

[0065] 1 0 1 0 1 0 2 1 0 1 0 0 3 0 1 0 1 1 4 1 0 1 0 0 5 0 0 1 0 0

[0066] Step 3: At the initial moment k0 = 0, the energy router transmits the main grid electricity price λ0 of the energy internet to the intelligent control units of each generator, and the initial electricity price λ of generator i. i (k0) propagates to neighboring generators, assuming the initial trigger time of generator i.

[0067] Step 4: When each intelligent control unit detects that the time equals its own trigger time, that is... Need to predict the next trigger time Proceed to step 5; when each intelligent control unit detects that it is not within its own trigger time, i.e., k ≠ k * Then proceed to step 7.

[0068] Step 5: The intelligent control unit stores the current electricity price information and transmits it to the neighbors.

[0069] Step 6: Predict the next trigger time using the self-triggering mechanism. The self-triggering mechanism stores and sends data to adjacent generators under the following conditions:

[0070] only

[0071]

[0072] When time k equals trigger time Only then will the self-triggered mechanism operation be performed, making If the algorithm inequality is not true, K is incremented by 1. When the algorithm inequality is true, K is obtained.

[0073] Where: K is used to calculate the next trigger time. The parameters. If the neighbor does not transmit the next trigger time. Using its own trigger time Instead of performing algorithmic calculations.

[0074] Trigger time The value is first updated to the next trigger time. The value is Next trigger time Then update it to the value of K, which is (k+1). i * =K. Because the next trigger time is at k0. If the value does not exist, the above assignment equation cannot be true. Therefore, we preset the next trigger time to be at time k0. Value 1.

[0075] m is a parameter in the self-triggering mechanism algorithm. It is the minimum of the time and the next trigger time of the neighbor. It is the maximum of the time and the next trigger time of the neighbor, where m is the summation parameter in the algorithm, taking values ​​from the next trigger time of the neighbor to...

[0076]

[0077] For the neighbor's electricity price, The electricity price for its own propagation and λ0 for the main grid electricity price.

[0078] Step 7: Each intelligent control unit uses the stored neighbor electricity prices. Its own propagation electricity price The leader-follower algorithm is applied to the main grid electricity price λ0. The leader-follower algorithm for the electricity price of the i-th generator is as follows:

[0079] Step 8: Each intelligent control unit determines the electricity price λ at time k. i (k) and the electricity price λ at time k-1 i Is the difference of (k-1) less than If so, the leader in step 7 follows the algorithm to the end and obtains the electricity price; otherwise, it returns to step 4, and the time is updated to k = k + 1.

[0080] Step 9: The electricity price algorithm ends. The exchange power of each generator is calculated using the current electricity price and propagated to each generator. The initial time of the exchange power algorithm is s0 = k, and the trigger time of the exchange power algorithm is set to s. i * =s0, P of generator i i ,P MGi for:

[0081] If the value exceeds the limit, the upper or lower limit will be used.

[0082] P MGi (s0)=P Di +P Li +P i ,P Li =B i (P i ) 2 .

[0083] Step 10: When each intelligent control unit detects that the time equals its own trigger time, that is... We need to predict the next trigger time (s+1). i * Proceed to step 11; when each intelligent control unit detects that it is not within its own trigger time... Then proceed to step 13.

[0084] Step 11: The intelligent control unit stores the switching power information and transmits it to the neighbor.

[0085] Step 12: Predict the next trigger time using the self-triggering mechanism. The self-triggering mechanism stores and sends data to adjacent generators under the following conditions:

[0086]

[0087] Only when time s equals the trigger time Only then will the self-triggered mechanism operation be performed, making If the algorithm inequality is not true, K is incremented by 1. When the algorithm inequality is true, K is obtained.

[0088] Where: K is used to calculate the next trigger time. The parameters. If the neighbor does not transmit the next trigger time. Using its own trigger time Instead of performing algorithmic calculations.

[0089] Trigger time The value is first updated to the next trigger time. The value is Next trigger time Then update it to the value of K, which is (s+1). i * = K, because the next trigger time is at time s0. If the value does not exist, the above assignment equation cannot be true. Therefore, we preset the next trigger time to be at time s0. The value is equal to s0+1.

[0090]

[0091]

[0092] Exchange power with neighbors It exchanges power for its own propagation.

[0093] Step 13: The intelligent control unit utilizes the stored neighbor exchange power. Its own propagation exchange power The leaderless follower algorithm for exchanging power among the i-th generators is as follows:

[0094]

[0095] Step 14: Each intelligent control unit determines the switching power P at time s. MGi P at time (s) and s-1 MGi Is the difference between (s-1) and (s-1) less than 1? If so, the leaderless follower algorithm in step 13 ends and the exchange power is obtained; otherwise, return to step 10 and update the time to s = s + 1.

[0096] Step 15: The power exchange algorithm ends. Each intelligent control unit calculates the average power exchanged between each generator and the main grid, and the energy router can then calculate the total power P exchanged between the main grid and the microgrid. MG0 =NP MGi (s).

[0097] To verify the effectiveness of the present invention, simulation experiments were conducted.

[0098] Figure 3 The graph showing the electricity price trends of the five generators shows that the electricity prices of all generators converge to the electricity price of the main grid.

[0099] Figure 4 This means that after utilizing the distributed self-triggering mechanism proposed in this invention, the triggering information of each generator regarding electricity price is transmitted in a non-integer cycle on-demand manner.

[0100] Figure 5 This shows the changes in the exchange power of each of the five generators, and it can be seen that the exchange power of each generator can reach a consistent average exchange power.

[0101] Figure 6 This means that after utilizing the distributed self-triggering mechanism proposed in this invention, the triggering information of each generator regarding the exchange power is transmitted in a non-integer cycle on-demand manner.

[0102] Figure 7 This indicates that the sum of the power of the microgrid and the total power exchanged between the microgrid and the main grid, along with the load, achieves a power supply-demand balance.

[0103] This invention optimizes the total power generation cost while ensuring supply and demand balance and power generation limitations for each generator. It also enables the on-demand transmission of electricity price (exchange power) calculation and propagation between intelligent control units, eliminating the need for each intelligent control unit to continuously monitor the generator status and listen to its neighbors. This significantly reduces network communication pressure, decreases the computational resources of the entire system, and ensures the safe and stable operation of the entire energy internet system.

[0104] The above description is merely an embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principle of the present invention should be included within the scope of the claims of the present invention.

Claims

1. A distributed economic dispatch method for the energy internet based on a self-triggering mechanism, comprising an energy router, multiple distributed interconnected microgrids, and a main grid. Each microgrid consists of distributed generators, intelligent control units, and local loads. Each generator and load is directly controlled by its assigned local intelligent control unit. The intelligent control unit performs information exchange and algorithm calculations. The intelligent control unit calculates and propagates individual electricity prices, and the energy router calculates and propagates the power exchanged with the main grid. The method is characterized by: The energy internet distributed economic dispatch method includes the following steps: Step 1: Set system parameters, including the number of distributed generators N and the discrete time k, s, where α is a positive constant used to determine whether the electricity price and exchange power in the leader-follower and leaderless-follower algorithms have converged. ε is the step size of the leader-follower and leaderless-follower algorithms, and α is the step size of the leader-follower and leaderless-follower algorithms, respectively. i ,β i B i P for generator i i Determine the parameters, where γ, η, Φ, Γ are the parameters of the triggering condition, and P Di For generator i, the local load, P Li For generator i, the line load; Step 2: Set the communication connection coefficient 'a' based on whether the intelligent control units have information exchange capabilities. ij ,j=1,2,3,4......N,i≠j,d i ,d j These are the Laplacian matrix values ​​for communication connectivity coefficients, and the communication connectivity coefficient 'a' with the energy router. i0 ; Step 3: At the initial moment k0 = 0, the energy router transmits the main grid electricity price λ0 of the energy internet to the intelligent control units of each generator, and the initial electricity price λ of generator i. i (k0) propagates to neighboring generators, assuming the initial trigger time of generator i. Step 4: When each intelligent control unit detects that the time equals its own trigger time, that is... Need to predict the next trigger time Proceed to step 5, when each intelligent control unit detects that it is not within its own trigger time, i.e., k≠k * Then proceed to step 7; Step 5: The intelligent control unit stores the current electricity price information and transmits it to the neighbors. Step 6: Predict the next triggering time of generator i using the self-triggering mechanism. Store and send to adjacent generators; Step 7: Each intelligent control unit uses the stored neighbor electricity prices. Its own propagation electricity price And the leader follower algorithm is applied to the main grid electricity price λ0; Step 8: Each intelligent control unit determines the electricity price λ at time k. i (k) and the electricity price λ at time k-1 i Is the difference of (k-1) less than If so, the leader in step 7 follows the algorithm to the end and obtains the electricity price; otherwise, return to step 4 and update the time to k = k + 1. Step 9: After the electricity price calculation is completed, the exchange power of each generator is calculated using the current electricity price and propagated to each generator. The initial time of the exchange power algorithm is set to s0 = k, and the trigger time of the exchange power algorithm is set to s. i * =s0; Step 10: When each intelligent control unit detects that the time equals its own trigger time, that is... We need to predict the next trigger time (s+1). i * Proceed to step 11; When each intelligent control unit detects that it is outside its own trigger time, that is... Then proceed to step 13; Step 11: The intelligent control unit stores the switching power information and transmits it to the neighbor. Step 12: Predict the next trigger time using the self-triggering mechanism. Store and send to adjacent generators; Step 13: The intelligent control unit utilizes the stored neighbor exchange power. Its own propagation exchange power Perform a leaderless follower algorithm; Step 14: Each intelligent control unit determines the switching power P at time s. MGi P at time (s) and s-1 MGi Is the difference between (s-1) and (s-1) less than 1? If so, the leaderless follower algorithm in step 13 ends and the exchange power is obtained; otherwise, return to step 10 and update the time to s = s + 1. Step 15: Power Exchange Algorithm Ends: Each intelligent control unit obtains the average power exchanged between each generator and the main grid. The energy router then obtains the total power P exchanged between the main grid and the microgrid. MG0 =NP MGi (s).

2. The distributed economic dispatch method for the energy internet based on a self-triggering mechanism according to claim 1, characterized in that: The conditions for the self-triggered mechanism in step 6 are: When time k equals trigger time The self-triggering mechanism is performed at the specified time, causing... If the algorithm inequality is false, K is incremented by 1. When the algorithm inequality is true, K is calculated. K is used to determine the next triggering time of generator i. The parameters, if the neighbor does not transmit the next trigger time Using its own trigger time Instead of performing calculations for the self-triggered mechanism algorithm, Trigger time The value is first updated to the next trigger time of generator i. The value is Next trigger time Then update it to the value of K, which is (k+1). i * =K, because the next trigger time is at k0. The above assignment equation cannot be valid if the value does not exist, therefore the next trigger time is preset to be at time k0. Value equal to 1; m is a parameter in the self-triggering mechanism algorithm. It is the minimum of the time and the next trigger time of the neighbor. It is the maximum of the time and the next trigger time of the neighbor, where m is the summation parameter in the algorithm, taking values ​​from the next trigger time of the neighbor to... in: For the neighbor's electricity price, The electricity price for its own propagation and λ0 for the main grid electricity price.

3. The distributed economic dispatch method for the energy internet based on a self-triggering mechanism according to claim 1, characterized in that: The leader-follower algorithm for the electricity price of the i-th generator in step 7 is as follows: in: For the neighbor's electricity price, For its own propagation electricity price, λ0 is the main grid electricity price.

4. The distributed economic dispatch method for the energy internet based on a self-triggering mechanism according to claim 1, characterized in that: In step 9, the P of generator i in step 9 i ,P MGi for: P MGi (s0)=P Di +P Li +P i ,P Li =B i (P i ) 2 in, 5. The distributed economic dispatch method for the energy internet based on a self-triggering mechanism according to claim 1, characterized in that: The conditions for the self-triggering mechanism in step 12 are: Only when time s equals the trigger time Only then will the self-triggered mechanism operation be performed, making If the algorithm inequality is false, K is incremented by 1. When the algorithm inequality is true, K is calculated. K is used to determine the next trigger time. The parameters, if the neighbor does not transmit the next trigger time Using its own trigger time Instead of performing the self-triggered mechanism algorithm calculation in step 12, Trigger time The value is first updated to the next trigger time. The value is Next trigger time Then update it to the value of K, which is (s+1). i * =K, because the next trigger time is at time s0. Since the value does not exist, the above assignment equation cannot be true. Therefore, the next trigger time is preset to be at time s0. The value is equal to s0+1. Exchange power with neighbors It exchanges power for its own propagation.

6. The distributed economic dispatch method for the energy internet based on a self-triggering mechanism according to claim 1, characterized in that: The leaderless follower algorithm for the power exchange of the i-th generator in step 13 is as follows: in: Exchange power with neighbors Let ε be the propagation exchange power, ε be the algorithm step size, and a be the propagation exchange power. ij This represents the communication connection coefficient.

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