A micro-grid distributed consistent economic dispatching method and system

Abstract

The application discloses a micro-grid distributed consistency economic dispatching method and system, comprising the following steps: constructing a communication topology model of a micro-grid system; establishing an economic dispatching model of the micro-grid; deducing a calculation form of optimal solutions of generator output power and optimal solutions of incremental cost of the micro-grid; initializing related parameters required by a consistency economic dispatching algorithm; iteratively updating the incremental cost of each generator so that the incremental cost gradually tends to be consistent, and updating the output power of all generators and the deviation between the output power and the demand, so that the deviation gradually tends to be zero; and outputting optimal incremental cost and optimal generator output power. The method solves the problem of how to effectively perform consistency economic dispatching when the communication link connectivity in the actual micro-grid exists random fluctuation, and reduces the dependence on network connection strength and low delay.

Description

Technical Field

[0001] This invention belongs to the field of microgrid energy optimization scheduling technology, specifically relating to a distributed consensus economic scheduling method and system for microgrids. Background Technology

[0002] With the transformation of the global energy structure and the development of smart grid technology, microgrids, as a flexible, efficient, and renewable form of power system, are playing an increasingly important role in power dispatch and energy management. Microgrids not only enable autonomous dispatch of distributed energy resources but also ensure the reliability and economy of energy supply, whether connected to the main grid or operating in isolation. Therefore, optimizing microgrid dispatch, especially dispatch methods in distributed environments, has become a research hotspot.

[0003] Traditional economic dispatching methods typically employ centralized algorithms, such as genetic algorithms, particle swarm optimization, evolutionary programming, differential evolution, and simulated annealing. These algorithms rely on a central controller to collect global information and process large amounts of data, requiring high storage capacity and fast processing speeds. However, centralized methods are costly, prone to single points of failure, and lack robustness. When generators or loads need to be added or removed in a smart grid, the entire system needs to be reconfigured, resulting in insufficient flexibility.

[0004] To address the aforementioned issues, existing technologies typically employ distributed economic scheduling methods as an effective solution. These methods fully utilize the local information of each distributed node, achieving global goals through local decision-making and coordination mechanisms. However, traditional distributed economic scheduling methods often rely on centralized communication network architectures, where communication between nodes requires strong connectivity and low latency, and places high demands on the network topology. In practical applications, communication links may be interrupted due to network failures, signal attenuation, packet loss, etc., causing some nodes to fail to transmit information in real time, thus affecting data exchange and collaborative optimization during the scheduling process. Summary of the Invention

[0005] The technical problem to be solved by this invention is how to effectively perform consistent economic scheduling when the connectivity of communication links in a real microgrid is subject to random fluctuations.

[0006] The present invention solves the above-mentioned technical problems through the following technical means:

[0007] This invention provides a distributed consensus economic dispatch method for microgrids, characterized by comprising:

[0008] S1. Construct a communication topology model for a microgrid system and use a dynamic graph to characterize its stochastic communication process.

[0009] S2. In a random communication environment, establish an economic dispatch model for the microgrid, including: generator generation cost, objective function of microgrid economic dispatch, generator output power limit constraint and supply-demand balance constraint;

[0010] S3. Based on the established economic dispatch model, derive the calculation forms for the optimal solution of generator output power and the optimal solution of incremental cost in the microgrid;

[0011] S4. Initialize the relevant parameters required for the consensus-based economic scheduling algorithm;

[0012] S5. Iteratively update the incremental cost of each generator to make it gradually consistent, and at the same time update the output power of all generators and its deviation from the demand, so that the deviation gradually approaches zero.

[0013] S6. Determine if the deviation between the output power and the demand is 0; if so, output the optimal incremental cost and the optimal generator output power; otherwise, return to step S5.

[0014] Further, S1 includes the following steps:

[0015] S11. Treat the microgrid as a two-way graph. ;in, This represents the set of nodes in a microgrid. The total number of nodes. Let be the set of edges, where Represents a node To the node A communication link exists; if the node Can send to nodes Sending a message is called... for The neighbor If node Can receive nodes The sent information is called for The neighbor ;definition Represents a node Number of inbound neighbors; definition Represents a node The number of neighbors;

[0016] S12, The randomness of inter-node communication link connections is mediated by events. Indicates communication link Exists, and with probability The probability of a link existing is described, and its size satisfies equation (1):

[0017] (1)

[0018] in, The specific values ​​are determined based on the communication characteristics of different communication scenarios; therefore, random communication topology uses a series of dynamic graphs. express, for A collection of communication links between time nodes.

[0019] Further, S2 includes the following steps:

[0020] S21, using formula (2) to represent the first The power generation cost of one generator:

[0021] (2)

[0022] in, Indicates the first The cost of generating electricity from a generator; Indicates the first The output power of the generator; , and Indicates the first Cost coefficient of a generator;

[0023] S22. Equation (3) is used to represent the objective function of economic dispatch of the microgrid, the output power limit constraint of the generator, and the supply and demand balance constraint:

[0024] (3)

[0025] in, and They represent the first The maximum and minimum output power of the generator; This indicates the total demand for electricity generation.

[0026] Further, S3 includes the following steps:

[0027] S31, using formula (4) to represent the first Incremental cost of generator :

[0028] (4)

[0029] S32. Construct the Lagrangian function of equation (3) using equation (5):

[0030] (5)

[0031] in, Represent the Lagrange function; This represents the Lagrange multiplier related to the supply and demand balance constraint; according to the first-order optimality condition, the optimal solution is obtained when equation (6) is satisfied:

[0032] (6)

[0033] According to equation (6), the output power is optimal when the incremental cost of each generator is equal.

[0034] S33. Based on equations (3) and (4), the optimal solution for incremental cost is obtained. It can be expressed by equation (7):

[0035] (7)

[0036] in, This is the optimal solution for incremental cost; This represents the set of generators whose output power ranges between the maximum and minimum values.

[0037] Furthermore, the relevant parameters mentioned in S4 are specifically as follows (8):

[0038] (8)

[0039] in, Indicates the first The initial value of the output power of the generator; Indicates the first Initial value of the incremental cost of one generator; For the first The initial value of the deviation of the generator.

[0040] Further, S5 includes the following steps:

[0041] S51, Calculate using formula (9) Time of the first The neighbor coefficient of the generator:

[0042] (9)

[0043] in, express Time of the first The neighbor coefficient of a generator; express Time of the first The number of incoming neighbors of each generator;

[0044] S52, Calculate using formula (10) Time of the first The outgoing neighbor coefficient of the generator:

[0045] (10)

[0046] in, express Time of the first The neighbor coefficient of the generator; express Time of the first The number of neighboring generators;

[0047] S53, Calculate using formula (11) Time of the first Incremental cost per generator:

[0048] (11)

[0049] in, express Time of the first The incremental cost of one generator; express Time of the first The incremental cost of one generator; express Time of the first j The incremental cost of one generator; express The switching coefficient at time, when the subsequent terms hour, Conversely, when hour, ; express Time of the first The discrepancy between the power generation of the generator and the demand; Indicates the first generator about Feedback gain;

[0050] S54, Calculate using formula (12) Time of the first Output power of generator :

[0051] (12)

[0052] S55, Calculate using formula (13) Time of the first The deviation between the power generation and demand of the generator :

[0053] (13).

[0054] This invention also provides a microgrid distributed consensus economic dispatch system, characterized in that the system operates using the above-described method and includes the following modules:

[0055] The communication topology construction module is used to build a communication topology model of a microgrid system and to represent its random communication process using a dynamic graph.

[0056] The economic dispatch model construction module is used to establish an economic dispatch model for a microgrid in a stochastic communication environment, including: generator generation cost, objective function of microgrid economic dispatch, generator output power limit constraints, and supply and demand balance constraints;

[0057] The output power and incremental cost calculation module is used to derive the calculation forms of the optimal solution for the output power and the optimal solution for the incremental cost of the microgrid generator based on the established economic dispatch model.

[0058] The initialization module is used to initialize the relevant parameters required by the consensus economic scheduling algorithm.

[0059] The iterative algorithm module is used to iteratively update the incremental cost of each generator to make it gradually converge, while updating the output power of all generators and its deviation from the demand, so that the deviation gradually approaches zero.

[0060] The output module is used to determine whether the deviation between the output power and the demand is 0; if it is, the optimal incremental cost and the optimal generator output power are output; otherwise, the algorithm returns to the iterative algorithm module.

[0061] The advantages of this invention are:

[0062] (1) This invention fully considers the impact of random communication networks during the scheduling process, and can maintain the stability of the system even in the event of network failure or communication delay. Compared with traditional methods, this invention reduces the dependence on network connection strength and low latency, enabling the scheduling system to continue to operate when faced with communication uncertainties in practical applications, and avoiding system crashes or performance degradation caused by unstable communication links.

[0063] (2) Due to the randomness of communication networks, power balance constraints are often difficult to achieve. Introducing the deviation between the generator's output and demand during the iteration process can ensure that the system can meet this constraint throughout the process. At the same time, the feedback gain can be adjusted according to different situations to achieve the fastest convergence speed and improve the system's operating efficiency.

[0064] (3) This invention is a fully distributed algorithm that can dynamically update the local information of each generator node without the need for global information and with each node communicating only with its neighboring nodes, thereby gradually converging to the global optimization objective, significantly reducing the communication burden and reducing the network load, so that the system can still operate efficiently in large-scale microgrids, and is particularly suitable for distributed energy systems. Attached Figure Description

[0065] Figure 1 This is a flowchart illustrating a microgrid distributed consensus economic dispatch method according to an embodiment of the present invention.

[0066] Figure 2 This is a schematic diagram illustrating the iterative results of the deviation between power generation and demand over time in an embodiment of the present invention.

[0067] Figure 3 This is a schematic diagram showing the iterative results of the generator output power over time in an embodiment of the present invention. Detailed Implementation

[0068] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below in conjunction with the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0069] Example 1

[0070] This embodiment provides a distributed consensus economic dispatch method for microgrids, such as... Figure 1 As shown, the specific implementation steps include:

[0071] S1. Construct a communication topology model for the microgrid system and represent its stochastic communication process using a dynamic graph. The specific implementation steps are as follows:

[0072] S11. Treat the microgrid as a two-way graph. ;in, This represents the set of nodes in a microgrid. The total number of nodes. Let be the set of edges, where Represents a node To the node A communication link exists; if the node Can send to nodes Sending a message is called... for The neighbor If node Can receive nodes The sent information is called for The neighbor ;definition Represents a node Number of inbound neighbors; definition Represents a node The number of neighbors;

[0073] S12, The randomness of inter-node communication link connections is mediated by events. Indicates communication link Exists, and with probability The probability of a link existing is described, and its size satisfies equation (1):

[0074] (2)

[0075] in, The specific values ​​are determined based on the communication characteristics of different communication scenarios; therefore, random communication topology uses a series of dynamic graphs. express, for A collection of communication links between time nodes.

[0076] S2. Under a random communication environment, establish an economic dispatch model for the microgrid, including: generator generation cost, objective function for microgrid economic dispatch, generator output power limitation constraints, and supply-demand balance constraints. The specific implementation steps are as follows:

[0077] S21, using formula (2) to represent the first The power generation cost of one generator:

[0078] (2)

[0079] in, Indicates the first The cost of generating electricity from a generator; Indicates the first The output power of the generator; , and Indicates the first Cost coefficient of a generator;

[0080] S22. Equation (3) is used to represent the objective function of economic dispatch of the microgrid, the output power limit constraint of the generator, and the supply and demand balance constraint:

[0081] (3)

[0082] in, and They represent the first The maximum and minimum output power of the generator; This indicates the total demand for electricity generation.

[0083] S3. Based on the established economic dispatch model, derive the calculation forms for the optimal solution for generator output power and the optimal solution for incremental cost in the microgrid. The specific implementation steps are as follows:

[0084] S31, using formula (4) to represent the first Incremental cost of generator :

[0085] (4)

[0086] S32. Construct the Lagrangian function of equation (3) using equation (5):

[0087] (5)

[0088] in, Represent the Lagrange function; This represents the Lagrange multiplier related to the supply and demand balance constraint; according to the first-order optimality condition, the optimal solution is obtained when equation (6) is satisfied:

[0089] (6)

[0090] According to equation (6), the output power is optimal when the incremental cost of each generator is equal.

[0091] S33. Based on equations (3) and (4), the optimal solution for incremental cost is obtained. It can be expressed by equation (7):

[0092] (7)

[0093] in, This is the optimal solution for incremental cost; This represents the set of generators whose output power ranges between the maximum and minimum values.

[0094] S4. Initialize the relevant parameters required for the consensus-based economic scheduling algorithm. The specific parameters for initialization are as follows (8):

[0095] (8)

[0096] in, Indicates the first The initial value of the output power of the generator; Indicates the first Initial value of the incremental cost of one generator; For the first The initial value of the deviation of the generator.

[0097] S5. Iteratively update the incremental cost of each generator to gradually bring it into consistency, while simultaneously updating the output power of all generators and its deviation from demand, gradually bringing the deviation towards zero. The specific implementation steps are as follows:

[0098] S51, Calculate using formula (9) Time of the first The neighbor coefficient of the generator:

[0099] (9)

[0100] in, express Time of the first The neighbor coefficient of a generator; express Time of the first The number of incoming neighbors of each generator;

[0101] S52, Calculate using formula (10) Time of the first The outgoing neighbor coefficient of the generator:

[0102] (10)

[0103] in, express Time of the first The neighbor coefficient of the generator; express Time of the first The number of neighboring generators;

[0104] S53, Calculate using formula (11) Time of the first Incremental cost per generator:

[0105] (11)

[0106] in, express Time of the first The incremental cost of one generator; express Time of the first The incremental cost of one generator; express Time of the first j The incremental cost of one generator; express The switching coefficient at time, when the subsequent terms hour, Conversely, when hour, ; express Time of the first The discrepancy between the power generation of the generator and the demand; Indicates the first generator about Feedback gain;

[0107] S54, Calculate using formula (12) Time of the first Output power of generator :

[0108] (12)

[0109] S55, Calculate using formula (13) Time of the first The deviation between the power generation and demand of the generator :

[0110] (13).

[0111] S6. Determine if the deviation between the output power and the demand is 0; if so, output the optimal incremental cost and the optimal generator output power; otherwise, return to step S5.

[0112] This embodiment also uses MATLAB to simulate the operation of the above algorithm in a microgrid containing four generators. For example... Figure 2 and Figure 3 As shown in the simulation results, the deviation between power generation and demand decreases continuously with iteration, eventually approaching zero, while the generator output power also reaches the optimal solution. Furthermore, at the 6th second, a change in power generation demand was simulated, demonstrating the algorithm's flexibility and rapid adjustment capability in dealing with demand fluctuations. The system can still respond quickly and converge to the optimal value again.

[0113] Example 2

[0114] It should be further explained that, based on the same inventive concept, this embodiment also provides a microgrid distributed consensus economic dispatch system. The system operates by applying the method described in Embodiment 1, and includes the following modules:

[0115] The communication topology construction module is used to construct a communication topology model of a microgrid system and to represent its stochastic communication process using a dynamic graph. The specific execution method of the communication topology construction module is as follows:

[0116] (1) Treat the microgrid as a two-way graph ;in, This represents the set of nodes in a microgrid. The total number of nodes. Let be the set of edges, where Represents a node To the node A communication link exists; if the node Can send to nodes Sending a message is called... for The neighbor If node Can receive nodes The sent information is called for The neighbor ;definition Represents a node Number of inbound neighbors; definition Represents a node The number of neighbors;

[0117] (2) The randomness of inter-node communication link connections is achieved through events. Indicates communication link Exists, and with probability The probability of a link existing is described, and its size satisfies equation (1):

[0118] (3)

[0119] in, The specific values ​​are determined based on the communication characteristics of different communication scenarios; therefore, random communication topology uses a series of dynamic graphs. express, for A collection of communication links between time nodes.

[0120] The economic dispatch model construction module is used to establish an economic dispatch model for a microgrid under a stochastic communication environment. This model includes: generator generation cost, objective function for microgrid economic dispatch, generator output power constraints, and supply-demand balance constraints. The economic dispatch model construction module comprises the following units:

[0121] The power generation cost model building unit is used to express the first equation using equation (2). The power generation cost of one generator:

[0122] (2)

[0123] in, Indicates the first The cost of generating electricity from a generator; Indicates the first The output power of the generator; , and Indicates the first Cost coefficient of a generator;

[0124] The objective function and constraint model building unit is used to represent the objective function of economic dispatch of the microgrid, the generator output power limit constraint, and the supply and demand balance constraint using equation (3):

[0125] (3)

[0126] in, and They represent the first The maximum and minimum output power of the generator; This indicates the total demand for electricity generation.

[0127] The output power and incremental cost calculation module is used to derive the calculation forms of the optimal solution for generator output power and the optimal solution for incremental cost in the microgrid based on the established economic dispatch model. The output power and incremental cost calculation module includes the following units:

[0128] Incremental cost calculation unit, used to express the first cost using equation (4). Incremental cost of generator :

[0129] (4)

[0130] The optimal solution unit for output power is used to construct the Lagrangian function of equation (3) using equation (5):

[0131] (5)

[0132] in, Represent the Lagrange function; This represents the Lagrange multiplier related to the supply and demand balance constraint; according to the first-order optimality condition, the optimal solution is obtained when equation (6) is satisfied:

[0133] (6)

[0134] According to equation (6), the output power is optimal when the incremental cost of each generator is equal.

[0135] The incremental cost optimal solution unit is used to derive the optimal solution for incremental cost based on equations (3) and (4). It can be expressed by equation (7):

[0136] (7)

[0137] in, This is the optimal solution for incremental cost; This represents the set of generators whose output power ranges between the maximum and minimum values.

[0138] The initialization module is used to initialize the relevant parameters required by the consensus economic scheduling algorithm.

[0139] The iterative algorithm module is used to iteratively update the incremental cost of each generator to make it gradually converge, while updating the output power of all generators and its deviation from the demand, so that the deviation gradually approaches zero.

[0140] The output module is used to determine whether the deviation between the output power and the demand is 0; if it is, the optimal incremental cost and the optimal generator output power are output; otherwise, the algorithm returns to the iterative algorithm module.

[0141] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A distributed consensus economic dispatch method for microgrids, characterized in that, include: S1. Construct a communication topology model for the microgrid system and characterize its stochastic communication process using a dynamic graph; including the following steps: S11. Treat the microgrid as a two-way graph. ;in, This represents the set of nodes in a microgrid. The total number of nodes. Let be the set of edges, where Represents a node To the node A communication link exists; if the node Can send to nodes Sending a message is called... for The neighbor If node Can receive nodes The sent information is called for The neighbor ;definition Represents a node Number of inbound neighbors; definition Represents a node The number of neighbors; S12, The randomness of inter-node communication link connections is mediated by events. Indicates communication link Exists, and with probability The probability of a link existing is described, and its size satisfies equation (1): (1) in, The specific values ​​are determined based on the communication characteristics of different communication scenarios; therefore, random communication topology uses a series of dynamic graphs. express, for A collection of communication links between time nodes; S2. In a random communication environment, establish an economic dispatch model for the microgrid, including: generator generation cost, objective function of microgrid economic dispatch, generator output power limit constraint and supply-demand balance constraint; S3. Based on the established economic dispatch model, derive the calculation forms for the optimal solution of generator output power and the optimal solution of incremental cost in the microgrid; S4. Initialize the relevant parameters required for the consensus-based economic scheduling algorithm; S5. Iteratively update the incremental cost of each generator to gradually bring it into consistency, while updating the output power of all generators and its deviation from the demand, so that the deviation gradually approaches zero; including the following steps: S51, Calculate using formula (9) Time of the first The neighbor coefficient of the generator: (9) in, express Time of the first The neighbor coefficient of a generator; express Time of the first The number of incoming neighbors of each generator; S52, Calculate using formula (10) Time of the first The outgoing neighbor coefficient of the generator: (10) in, express Time of the first The neighbor coefficient of the generator; express Time of the first The number of neighboring generators; S53, Calculate using formula (11) Time of the first Incremental cost per generator: (11) in, express Time of the first The incremental cost of one generator; express Time of the first The incremental cost of one generator; express Time of the first j The incremental cost of one generator; express The switching coefficient at time, when the subsequent terms hour, Conversely, when hour, ; express Time of the first The discrepancy between the power generation of the generator and the demand; Indicates the first generator about Feedback gain; S54, Calculate using formula (12) Time of the first Output power of generator : (12) S55, Calculate using formula (13) Time of the first The deviation between the power generation and demand of the generator : (13)； S6. Determine if the deviation between the output power and the demand is 0; if so, output the optimal incremental cost and the optimal generator output power; otherwise, return to step S5.

2. The microgrid distributed consensus economic dispatch method according to claim 1, characterized in that, S2 includes the following steps: S21, using formula (2) to represent the first The power generation cost of one generator: (2) in, Indicates the first The cost of generating electricity from a generator; Indicates the first The output power of the generator; , and Indicates the first Cost coefficient of a generator; S22. Equation (3) is used to represent the objective function of economic dispatch of the microgrid, the output power limit constraint of the generator, and the supply and demand balance constraint: (3) in, and They represent the first The maximum and minimum output power of the generator; This indicates the total demand for electricity generation.

3. The microgrid distributed consensus economic dispatch method according to claim 2, characterized in that, S3 includes the following steps: S31, using formula (4) to represent the first Incremental cost of generator : ；(4) S32. Construct the Lagrangian function of equation (3) using equation (5): ；(5) in, Represent the Lagrange function; This represents the Lagrange multiplier related to the supply and demand balance constraint; according to the first-order optimality condition, the optimal solution is obtained when equation (6) is satisfied: (6) According to equation (6), the output power is optimal when the incremental cost of each generator is equal. S33. Based on equations (3) and (4), the optimal solution for incremental cost is obtained. It can be expressed by equation (7): (7) in, This is the optimal solution for incremental cost; This represents the set of generators whose output power ranges between the maximum and minimum values.

4. The microgrid distributed consensus economic dispatch method according to claim 3, characterized in that, The relevant parameters mentioned in S4 are specifically as follows (8): (8) in, Indicates the first The initial value of the output power of the generator; Indicates the first Initial value of the incremental cost of one generator; For the first The initial value of the deviation of the generator.

5. A distributed consensus economic dispatch system for microgrids, characterized in that, Includes the following modules: The communication topology construction module is used to build a communication topology model of a microgrid system and represent its stochastic communication process using a dynamic graph; the specific execution method is as follows: (1) Treat the microgrid as a two-way graph ;in, This represents the set of nodes in a microgrid. The total number of nodes. Let be the set of edges, where Represents a node To the node A communication link exists; if the node Can send to nodes Sending a message is called... for The neighbor If node Can receive nodes The sent information is called for The neighbor ;definition Represents a node Number of inbound neighbors; definition Represents a node The number of neighbors; (2) The randomness of inter-node communication link connections is achieved through events. Indicates communication link Exists, and with probability The probability of a link existing is described, and its size satisfies equation (1): (2) in, The specific values ​​are determined based on the communication characteristics of different communication scenarios; therefore, random communication topology uses a series of dynamic graphs. express, for A collection of communication links between time nodes; The economic dispatch model construction module is used to establish an economic dispatch model for a microgrid in a stochastic communication environment, including: generator generation cost, objective function of microgrid economic dispatch, generator output power limit constraints, and supply and demand balance constraints; The output power and incremental cost calculation module is used to derive the calculation forms of the optimal solution for the output power and the optimal solution for the incremental cost of the microgrid generator based on the established economic dispatch model. The initialization module is used to initialize the relevant parameters required by the consensus economic scheduling algorithm. The iterative algorithm module is used to iteratively update the incremental cost of each generator to gradually bring it into consistency, while simultaneously updating the output power of all generators and its deviation from the demand, so that the deviation gradually approaches zero; the specific execution method is as follows: (1) Calculate using formula (9) Time of the first The neighbor coefficient of the generator: (9) in, express Time of the first The neighbor coefficient of a generator; express Time of the first The number of incoming neighbors of each generator; (2) Calculate using formula (10) Time of the first The outgoing neighbor coefficient of the generator: (10) in, express Time of the first The neighbor coefficient of the generator; express Time of the first The number of neighboring generators; (3) Calculate using formula (11) Time of the first Incremental cost per generator: (11) in, express Time of the first The incremental cost of one generator; express Time of the first The incremental cost of one generator; express Time of the first j The incremental cost of one generator; express The switching coefficient at time, when the subsequent terms hour, Conversely, when hour, ; express Time of the first The discrepancy between the power generation of the generator and the demand; Indicates the first generator about Feedback gain; (4) Calculate using formula (12) Time of the first Output power of generator : (12) (5) Calculate using formula (13) Time of the first The deviation between the power generation and demand of the generator : (13)； The output module is used to determine whether the deviation between the output power and the demand is 0; if it is, the optimal incremental cost and the optimal generator output power are output; otherwise, the algorithm returns to the iterative algorithm module.

6. A microgrid distributed consensus economic dispatch system according to claim 5, characterized in that, The economic scheduling model construction module includes the following units: The power generation cost model building unit is used to express the first equation using equation (2). The power generation cost of one generator: (2) in, Indicates the first The cost of generating electricity from a generator; Indicates the first The output power of the generator; , and Indicates the first Cost coefficient of a generator; The objective function and constraint model building unit is used to represent the objective function of economic dispatch of the microgrid, the generator output power limit constraint, and the supply and demand balance constraint using equation (3): (3) in, and They represent the first The maximum and minimum output power of the generator; This indicates the total demand for electricity generation.

7. A microgrid distributed consensus economic dispatch system according to claim 6, characterized in that, The output power and incremental cost calculation module includes the following units: Incremental cost calculation unit, used to express the first cost using equation (4). Incremental cost of generator : ； (4) The optimal solution unit for output power is used to construct the Lagrangian function of equation (3) using equation (5): ； (5) in, Represent the Lagrange function; This represents the Lagrange multiplier related to the supply and demand balance constraint; according to the first-order optimality condition, the optimal solution is obtained when equation (6) is satisfied: (6) According to equation (6), the output power is optimal when the incremental cost of each generator is equal. The incremental cost optimal solution unit is used to derive the optimal solution for incremental cost based on equations (3) and (4). It can be expressed by equation (7): (7) in, This is the optimal solution for incremental cost; This represents the set of generators whose output power ranges between the maximum and minimum values.

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