A micro-grid group distributed coordination control method and device based on a gossip algorithm

Abstract

The embodiment of the application provides a micro-grid group distributed coordination control method and device based on a Gossip algorithm, and the method comprises the following steps: in the case that a micro-grid is disturbed, each distributed power supply of droop control is controlled by the following formula to maintain power balance of the micro-grid; average marginal cost parameters and frequency information of each micro-grid are obtained through in-network distributed communication in a constructed distributed double-layer control architecture, and secondary control is performed by using a preset Gossip consistency algorithm to realize economic distribution of active power and frequency stability of the micro-grid; neighbor micro-grid average marginal cost information is obtained through distributed communication, and secondary control is performed by using the preset Gossip consistency algorithm to realize economic distribution of active power among micro-grids.

Description

Technical Field

[0001] This invention relates to the field of microgrid power control, and to, but is not limited to, a distributed coordinated control method and apparatus for microgrid groups based on the Gossip algorithm. Background Technology

[0002] With the continuous advancement of distributed power generation integration into the power system, the demand for microgrid configuration and application is increasing. Currently, microgrids exhibit diverse structures and dispersed layouts. Compared to distributed control methods, traditional centralized control modes struggle to meet the requirements of autonomous management and coordinated optimization, and cannot satisfy the diverse needs of flexible loads. Microgrid clusters based on intelligent soft-switching interconnection, with their bidirectional power flow control capabilities between grids and dynamic flexible reconfiguration capabilities under fault conditions, can serve as a new solution to improve the reliability of microgrid power supply. However, compared to traditional interconnected microgrid clusters using tie switches, the operating frequency of microgrid clusters based on intelligent soft-switching interconnection changes from a global variable to a local variable. Differences in frequency between different microgrids may exist, making frequency synchronization between microgrids difficult, resulting in a decrease in the overall stability of the microgrid cluster and a weakening of the system's disturbance rejection capability.

[0003] Currently, distributed control based on consensus algorithms is widely used in microgrids due to its high real-time communication and interaction capabilities. However, existing microgrid group control strategies based on traditional average consensus algorithms suffer from slow convergence and strong communication dependencies. Furthermore, secondary power control in microgrid groups primarily allocates power according to capacity ratios, with less consideration given to the cost-effectiveness of coordinated operation between sub-microgrids. Summary of the Invention

[0004] This invention provides a distributed coordinated control method and device for microgrid groups based on the Gossip algorithm, which solves the problems of inter-grid frequency decoupling, high operating costs, and fuzzy control of inter-grid transmission power in microgrid groups under traditional control.

[0005] The technical method of this invention is implemented as follows:

[0006] In a first aspect, embodiments of the present invention provide a distributed coordinated control method for microgrid groups based on the Gossip algorithm, the method comprising:

[0007] In the event of a disturbance in the microgrid, each distributed power source under droop control performs initial control using the following formula to maintain the power balance of the microgrid: In the formula, f i and U iLet fi and U0 represent the frequency amplitude and voltage amplitude of the i-th distributed power source, respectively; f0 and U0 represent the rated frequency amplitude and rated voltage amplitude of the distributed power source, respectively; P and Q represent the active power and reactive power of the distributed power source, respectively; P0 and Q0 represent the reference values ​​of the active power and reactive power of the distributed power source, respectively; K P and K Q These represent the droop factor for frequency and the droop factor for voltage, respectively.

[0008] By using distributed communication within the network in the constructed distributed two-layer control architecture, the average marginal cost parameters and frequency information of each microgrid are obtained, and a preset Gossip consensus algorithm is used for secondary control to achieve economic allocation of active power and frequency stability of the microgrid.

[0009] By using distributed communication combining inter-network and intra-network communication, the average marginal cost information of neighboring micronets is obtained, and the preset Gossip consensus algorithm is used for secondary control to achieve active power economic allocation among micronets.

[0010] Secondly, the present invention provides a distributed coordination control device for microgrid groups based on the Gossip algorithm, the device comprising:

[0011] The initial control module is used to maintain the power balance of the microgrid by initially controlling each distributed power source under droop control according to the following formula in the event of a disturbance in the microgrid: In the formula, f i and U i Let fi and U0 represent the frequency amplitude and voltage amplitude of the i-th distributed power source, respectively; f0 and U0 represent the rated frequency amplitude and rated voltage amplitude of the distributed power source, respectively; P and Q represent the active power and reactive power of the distributed power source, respectively; P0 and Q0 represent the reference values ​​of the active power and reactive power of the distributed power source, respectively; K P and K Q These represent the droop factor for frequency and the droop factor for voltage, respectively.

[0012] The secondary control module is used to obtain the average marginal cost parameters and frequency information of each microgrid through distributed communication within the network in the constructed distributed two-layer control architecture, and to perform secondary control using a preset Gossip consensus algorithm to achieve economic allocation of active power and frequency stability of the microgrid.

[0013] The secondary control module is also used to obtain the average marginal cost information of neighboring micronets through distributed communication combining inter-network and intra-network communication, and to perform secondary control using the preset Gossip consensus algorithm to achieve active power economic allocation between micronets.

[0014] In some embodiments, the secondary control module is further configured to: acquire the cost parameters of each distributed power source within each microgrid through the intra-network distributed communication; establish a distributed power source generation cost function based on the cost parameters; calculate the marginal cost parameters of each distributed power source based on the distributed power source generation cost function; estimate the average marginal cost parameters of each microgrid based on a preset distributed algorithm and the marginal cost parameters; determine the input parameters and frequency amplitude of the secondary controller applied to the droop control based on the preset Gossip consensus algorithm; and apply secondary control to achieve economic allocation of active power and frequency stability of the microgrid.

[0015] In some embodiments, the secondary control module is further configured to reduce the output of microgrids with high operating marginal costs and increase the output of microgrids with low operating marginal costs through primary control between microgrids, so as to make the operating marginal costs of adjacent microgrids consistent; and to calculate the average operating marginal cost of each distributed power source among adjacent microgrids; the calculation formula is: In the formula, G is the number of FAS, μ(n) is the difference in average operating marginal cost between adjacent microgrids at time n, μ1(n) is the difference in average operating marginal cost between adjacent microgrids of FAS1 at time n, μ2(n) is the difference in average operating marginal cost between adjacent microgrids of FAS2 at time n, and μ G (n) represents FAS at time n. G The difference in average operating marginal cost between adjacent microgrids, L MG,α (P) and L MG,β (P) represents the average marginal cost of microgrids α and β, respectively; the average operating marginal cost is transferred from the distributed power source to the FAS, and the primary control term of the local VSC in the FAS is: In the formula, Here, μ represents the primary control parameter of the local VSC in FAS, and μ is the average marginal cost deviation between adjacent microgrids. For the proportional parameters of the PI controller in the primary control of FAS, The integral parameters of the PI controller for the primary control of the FAS are given, and s is the Laplace operator. Based on the preset Gossip consensus algorithm iteration, the total marginal cost of the microgrid group is calculated. The microgrid group control is achieved by adding a secondary control term to the local VSC, based on the local secondary control term of the FAS. The local VSC secondary control term is expressed as: In the formula, For FAS local VSC secondary control parameters, The proportional parameters are for the secondary control PI controller. Here, s represents the integral parameter of the PI controller for secondary control, s is the Laplace operator, and μ(n) is the difference in average operating marginal cost between adjacent microgrids at time n. The total operating marginal cost error value; based on the bidirectional VSC in FAS to control the power transmission of the local microgrid, by constructing a secondary control term in FAS and exchanging status information with adjacent FAS, the control task among the entire microgrid group is achieved, so as to realize the goal of allocating active power according to marginal cost.

[0016] Thirdly, embodiments of the present invention provide an electronic device, including: a memory for storing executable instructions; and a processor for implementing the above-mentioned distributed coordinated control method for microgrid groups based on the Gossip algorithm when executing the executable instructions stored in the memory.

[0017] Fourthly, embodiments of the present invention provide a computer-readable storage medium storing executable instructions, which, when executed by a processor, implement the aforementioned distributed coordinated control method for microgrid groups based on the Gossip algorithm.

[0018] The distributed coordinated control method for microgrid groups based on the Gossip algorithm provided in this invention first performs primary control to maintain the power balance of the microgrid and microgrid group. Second, a distributed two-layer control architecture is constructed. Each distributed generation (DG) obtains neighbor marginal cost and frequency information through distributed communication within the network, and uses improved consensus control based on the Gossip algorithm to achieve economical active power allocation and frequency deviation elimination. Finally, each microgrid's intelligent agent flexible switch obtains the average marginal cost information of neighboring microgrids through distributed communication, and uses improved consensus control based on the Gossip algorithm to achieve economical active power allocation between microgrids. Thus, this invention establishes a two-layer coordinated control architecture for the microgrid group. The upper layer uses intelligent agent flexible switches to achieve inter-grid power exchange and cost information sharing, while the lower layer coordinates the flexible and economical allocation of output from each distributed power source based on marginal cost information. Furthermore, the Gossip consensus algorithm is introduced, and its concurrent information propagation characteristics accelerate the global information sharing process. Simultaneously, by controlling power flow through inter-grid intelligent agent flexible switches and leveraging the characteristic of distributing power according to marginal cost among distributed power sources within the network, stable and reliable operation of the microgrid group is achieved. Attached Figure Description

[0019] Figure 1 This is a flowchart illustrating a distributed coordinated control method for microgrid groups based on the Gossip algorithm provided in an embodiment of the present invention.

[0020] Figure 2 This is a microgrid system structure diagram provided in an embodiment of the present invention;

[0021] Figure 3 This is a topology diagram of a simulated microgrid group system model provided in an embodiment of the present invention;

[0022] Figure 4This is a diagram showing the operating frequencies of each MG within the MMG provided in this embodiment of the invention;

[0023] Figure 5 This is an active power diagram of each DG within the MMG provided in an embodiment of the present invention;

[0024] Figure 6 This is a diagram showing the switching power of each FAS within the MMG intranet provided in this embodiment of the invention;

[0025] Figure 7 This is a marginal cost diagram of each DG within the MMG provided in this embodiment of the invention;

[0026] Figure 8 This is a schematic diagram of the composition structure of a microgrid group distributed coordination control device based on the Gossip algorithm provided in an embodiment of the present invention. Detailed Implementation

[0027] To make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings. The described embodiments should not be regarded as limitations on 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.

[0028] In the following description, references to "some embodiments" refer to a subset of all possible embodiments; however, it is understood that "some embodiments" may be the same or different subsets of all possible embodiments and may be combined with each other without conflict. Unless otherwise defined, all technical and scientific terms used in the embodiments of the invention have the same meaning as commonly understood by one of ordinary skill in the art to which the embodiments of the invention pertain. The terminology used in the embodiments of the invention is for the purpose of describing the embodiments of the invention only and is not intended to limit the invention.

[0029] The following describes an exemplary application of the distributed coordination and control device for microgrid clusters based on the Gossip algorithm according to embodiments of the present invention. The landslide and rockfall detection device provided in this embodiment can be implemented as a terminal or as a server. In one implementation, the distributed coordination and control device for microgrid clusters based on the Gossip algorithm provided in this embodiment can be implemented as various types of terminals such as laptops, tablets, desktop computers, and mobile devices. In another implementation, the distributed coordination and control device for microgrid clusters based on the Gossip algorithm provided in this embodiment can also be implemented as a server. The server can be an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDNs), and big data and artificial intelligence platforms. The terminal and the server can be directly or indirectly connected via wired or wireless communication, which is not limited in this embodiment. The following will describe an exemplary application of the distributed coordination and control device for microgrid clusters based on the Gossip algorithm when implemented as a server.

[0030] This invention provides a distributed coordinated control method for microgrid groups based on the Gossip algorithm. (See also...) Figure 1 , Figure 1 This is a flowchart illustrating the distributed coordinated control method for microgrid groups based on the Gossip algorithm provided in this embodiment of the invention. Figure 1 The steps shown are explained.

[0031] In step S110, when a disturbance occurs in the microgrid, each distributed power source under droop control is initially controlled using the following formula to maintain the power balance of the microgrid.

[0032] Here, the formula is: In the formula, f i and U i Let fi and U0 represent the frequency amplitude and voltage amplitude of the i-th distributed power source, respectively; f0 and U0 represent the rated frequency amplitude and rated voltage amplitude of the distributed power source, respectively; P and Q represent the active power and reactive power of the distributed power source, respectively; P0 and Q0 represent the reference values ​​of the active power and reactive power of the distributed power source, respectively; K P and K Q These represent the droop factor for frequency and the droop factor for voltage, respectively.

[0033] In this embodiment of the invention, disturbances are unavoidable during the operation of a microgrid, such as sudden load changes, the connection or disconnection of distributed power sources, etc. Droop control is a control strategy used to automatically distribute power among distributed power sources and maintain the power balance of the microgrid. When a disturbance occurs in the microgrid, the initial control through droop control enables each distributed power source to respond quickly, initially stabilizing the operating state of the microgrid.

[0034] Step S120: Through distributed communication within the network in the constructed distributed two-layer control architecture, the average marginal cost parameters and frequency information of each microgrid are obtained, and a preset Gossip consensus algorithm is used for secondary control to achieve economic allocation of active power and frequency stability of the microgrid.

[0035] In this embodiment of the invention, a distributed two-layer control architecture is constructed to achieve more optimized control of the microgrid. Intra-grid distributed communication refers to the method of information exchange between distributed power sources and with other relevant control units within each microgrid. Through this communication method, each distributed power source can obtain the average marginal cost parameter and frequency information of the entire microgrid.

[0036] In some embodiments, the average marginal cost parameter reflects the increased cost of generating one additional unit of electricity in a microgrid, and is crucial for achieving economical allocation of active power. Frequency information is one of the key indicators for stable operation of a microgrid.

[0037] In this invention, the Gossip algorithm is used to propagate average marginal cost parameters and frequency information among nodes within the microgrid, enabling distributed power sources to gradually achieve a consistent understanding of this information. Based on this consistency, each distributed power source can adjust its own power generation, thereby achieving economical allocation of active power within the microgrid, i.e., minimizing power generation costs while meeting the microgrid's power demands. Simultaneously, frequency adjustment and control maintain the microgrid's frequency stability, ensuring stable and reliable operation.

[0038] Step S130: Obtain the average marginal cost information of neighboring micronets through distributed communication combining inter-network and intra-network communication, and use the preset Gossip consensus algorithm for secondary control to realize the active power economic allocation between micronets.

[0039] In this invention, the average marginal cost information of neighboring microgrids can be obtained through distributed communication. In the operation scenario of a microgrid cluster, the microgrids are interconnected. By obtaining the average marginal cost information of neighboring microgrids, each microgrid can understand the power generation cost of surrounding microgrids, providing a data foundation for achieving optimized and coordinated control among microgrids.

[0040] Subsequently, a second round of control is performed using the pre-defined Gossip consensus algorithm. This algorithm propagates average marginal cost information among the microgrids, enabling each microgrid to adjust its active power output based on shared cost information, thus achieving economical allocation of active power among the microgrids. This means that active power can be allocated more rationally throughout the entire microgrid network, preventing excessively high generation costs for some microgrids while fully utilizing the generation resources of each microgrid, thereby improving the overall operational economy and reliability of the microgrid network.

[0041] The distributed coordinated control method for microgrid groups based on the Gossip algorithm provided in this invention first performs primary control to maintain the power balance of the microgrid and microgrid group. Second, a distributed two-layer control architecture is constructed. Each distributed generation (DG) obtains neighbor marginal cost and frequency information through distributed communication within the network, and uses improved consensus control based on the Gossip algorithm to achieve economical active power allocation and frequency deviation elimination. Finally, each microgrid's intelligent agent flexible switch obtains the average marginal cost information of neighboring microgrids through distributed communication, and uses improved consensus control based on the Gossip algorithm to achieve economical active power allocation between microgrids. Thus, this invention establishes a two-layer coordinated control architecture for the microgrid group. The upper layer uses intelligent agent flexible switches to achieve inter-grid power exchange and cost information sharing, while the lower layer coordinates the flexible and economical allocation of output from each distributed power source based on marginal cost information. Furthermore, the Gossip consensus algorithm is introduced, and its concurrent information propagation characteristics accelerate the global information sharing process. Simultaneously, by controlling power flow through inter-grid intelligent agent flexible switches and leveraging the characteristic of distributing power according to marginal cost among distributed power sources within the network, stable and reliable operation of the microgrid group is achieved.

[0042] In some embodiments, step S120 can be implemented by the following steps S121 to S125:

[0043] Step S121: Obtain the cost parameters of each distributed power source in each microgrid through the distributed communication within the network, and establish a distributed power source generation cost function based on the cost parameters.

[0044] Step S122: Calculate the marginal cost parameter of each distributed power source based on the distributed power generation cost function.

[0045] Step S123: Based on the preset distributed algorithm and the marginal cost parameters, estimate the average marginal cost parameters of each microgrid.

[0046] Step S124: Based on the preset Gossip consensus algorithm, determine the input parameters and frequency amplitude of the secondary controller applied to the droop control.

[0047] Step S125: Apply secondary control to achieve economical distribution of active power and frequency stability of the microgrid.

[0048] In some embodiments, step S130 above can be implemented by the following steps S131 to S136:

[0049] Step S131: Through primary control between microgrids, the output of microgrids with high operating marginal costs is reduced, and the output of microgrids with low operating marginal costs is increased, so as to make the operating marginal costs of adjacent microgrids consistent.

[0050] Step S132: Calculate the average operating marginal cost of each of the distributed power sources among adjacent microgrids.

[0051] Here, the calculation formula is: In the formula, G is the number of FAS, μ(n) is the difference in average operating marginal cost between adjacent microgrids at time n, μ1(n) is the difference in average operating marginal cost between adjacent microgrids of FAS1 at time n, μ2(n) is the difference in average operating marginal cost between adjacent microgrids of FAS2 at time n, and μ G (n) represents FAS at time n. G The difference in average operating marginal cost between adjacent microgrids, L MG,α (P) and L MG,β (P) represents the average marginal cost of the α and β microgrids, respectively.

[0052] Step S133: The average operating marginal cost is transferred from the distributed power source to the FAS. The primary control item of the local VSC in the FAS is: In the formula, Here, μ represents the local VS C primary control parameters for FAS, and μ is the average marginal cost deviation between adjacent microgrids. For the proportional parameters of the PI controller in the primary control of FAS, Here, s represents the integral parameter of the PI controller for primary control of FAS, and s is the Laplace operator.

[0053] Step S134: Calculate the total marginal cost based on the preset Gossip consensus algorithm iteration.

[0054] Step S135: Microgrid group control is achieved by adding secondary control terms to the local VSC, based on the local secondary control terms of FAS; the local secondary control terms are expressed as: In the formula, For FAS local VSC secondary control parameters, The proportional parameters are for the secondary control PI controller. Here, s represents the integral parameter of the PI controller for secondary control, s is the Laplace operator, and μ(n) is the difference in average operating marginal cost between adjacent microgrids at time n. This represents the total operating marginal cost error value.

[0055] Step S136: Based on the bidirectional VSC in FAS for power transmission control of the local microgrid, a secondary control item is constructed in FAS and status information is exchanged with adjacent FAS to achieve the control task among the entire microgrid group, so as to realize the goal of allocating active power according to marginal cost.

[0056] This invention considers a distributed coordination control method for flexible interconnected autonomous microgrids based on the Gossip algorithm under a hierarchical control mode. A two-layer coordination control architecture for the microgrid is established. The upper layer uses intelligent agent flexible switches to achieve power exchange and cost information sharing between grids, while the lower layer coordinates the flexible and economical allocation of power output from each distributed power source based on marginal cost information. The Gossip consensus algorithm is introduced, and its concurrent information propagation characteristics accelerate the global information sharing process. A distributed coordination control method for the microgrid is proposed, which utilizes the characteristics of inter-grid intelligent agent flexible switches controlling power flow and the allocation of power to each distributed power source within the grid according to marginal cost to achieve stable and reliable operation of the microgrid.

[0057] The following will describe an exemplary application of the embodiments of the present invention in a practical application scenario.

[0058] This invention provides a distributed coordination and control method for flexible interconnected autonomous microgrid groups based on the Gossip algorithm, comprising the following steps:

[0059] Step 1: Each distributed power source within the microgrid adopts droop control, and the microgrids are connected through flexible switches. The rectifier side adopts constant DC voltage, and the inverter side adopts constant power control.

[0060] Step 2: Construct a distributed two-layer control architecture. The lower layer is the microgrid level. Each distributed generator (DG) obtains the marginal cost and frequency information of its neighbors through distributed communication within the network. An improved consistency control based on the Gossip algorithm is used to achieve active power economic allocation and frequency deviation elimination.

[0061] Step 3: The upper layer is the microgrid group level. Each microgrid (MG) intelligent agent flexible agent interconnection switch (FAS) obtains the average marginal cost information of neighboring microgrids through distributed communication, and adopts improved consistency control based on the Gossip algorithm to realize the economic allocation of active power among microgrids.

[0062] In this embodiment of the invention, step 1 further includes the following steps:

[0063] When a disturbance occurs in the microgrid, the droop-controlled distributed power source automatically performs the control shown in the following formula to maintain the power balance of the microgrid.

[0064] In the formula, f i and U i Let fi and U0 represent the frequency amplitude and voltage amplitude of the i-th distributed power source, respectively; f0 and U0 represent the rated frequency amplitude and rated voltage amplitude of the distributed power source, respectively; P and Q represent the active power and reactive power of the distributed power source, respectively; P0 and Q0 represent the reference values ​​of the active power and reactive power of the distributed power source, respectively; K P and K Q These represent the droop factor for frequency and the droop factor for voltage, respectively.

[0065] In this embodiment of the invention, step 2 includes the following steps:

[0066] Step 2.1: Obtain the DG cost parameters within each MG subnetwork, establish the distributed generation cost function, and calculate the marginal cost of each DG based on this function.

[0067] Specifically, the cost function of distributed generation is expressed as:

[0068] In the formula, C i Let a be the generation cost of the i-th distributed power source. i b represents the nonlinear variable cost coefficients such as wear and tear of distributed power equipment. i c represents the linear generation cost coefficient for distributed power sources, including fuel, operation, and maintenance. i This includes the fixed costs such as initial investment and installation of the power supply; P i Let be the active power of the i-th distributed power source.

[0069] At this point, DG's marginal cost is:

[0070] In the formula, L i [Pi] represents the marginal cost of the i-th distributed power source at time n.

[0071] Step 2.2: Estimate the average marginal cost parameter of each microgrid unit based on the Gossip algorithm, and then use the marginal cost parameter η. i =L i (P i ), its average value is Where N is the number of DGs in the microgrid, and η is the marginal cost parameter of each DG. i and the corresponding weighting factor w i .

[0072] At each subsequent nth control time of the distributed power source, the average marginal cost of the microgrid can be calculated and output using the Gossip algorithm based on all currently known information. The calculation formula is as follows:

[0073]

[0074] In the formula, sη j→i (n) represents the scaling factor information sent by control node j to i during the nth iteration. This represents the scaling factor information after n+1 iterations, where j is the neighboring node of node i. To output the average marginal cost of the microgrid, x is the average state value after iterative adjustment by a scaling factor. w is the average marginal cost after n+1 iterations, adjusted by the scaling factor. i Weighting factors for information at each node.

[0075] Step 2.3: Within the MG, a secondary control term is applied in the primary droop control based on the Gossip consensus algorithm to adjust the marginal cost of each DG during system operation, enhance operational economy, and compensate for static frequency offset, as follows:

[0076]

[0077] In the formula: f i f is the frequency value at node i. ref Let u be the frequency reference value at node i. P m is the input parameter for the secondary controller applied to droop control. i,p It is the product of the droop coefficient and the active power. To account for secondary control items that take into account the marginal cost of DG operation, This is a secondary control term that takes into account the DG frequency.

[0078] By applying secondary control, economical distribution of active power and frequency stability within the MG are achieved, wherein:

[0079]

[0080] In the formula, k pc k is the proportional parameter of the active power PI controller. ic k is the integral parameter of the active power PI controller. pf k is the proportional parameter of the frequency PI controller. if f is the integral parameter of the frequency PI controller. ref (n) represents the reference value of the frequency at time n based on Gossip consistency, f i (n) represents DG at time n. i The frequency value.

[0081] In this embodiment of the invention, step 3 includes the following steps:

[0082] Step 3.1: The primary control between microgrids reduces the output of MGs with high operating marginal costs and increases the output of MGs with low costs, so that the operating marginal costs of adjacent MGs are made the same. Then:

[0083]

[0084] In the formula, G is the number of FAS, μ(n) is the difference in average operating marginal cost between adjacent microgrids at time n, μ1(n) is the difference in average operating marginal cost between adjacent microgrids of FAS1 at time n, μ2(n) is the difference in average operating marginal cost between adjacent microgrids of FAS2 at time n, and μ G (n) represents FAS at time n. G The difference in average operating marginal cost between adjacent microgrids, L MG,α (P) and L MG,β (P) represents the average marginal cost of microgrids α and β, respectively. After calculating the average operating marginal cost of each DG within the MG, the cost is transmitted from the DG to the FAS via the communication network. The primary control term of the FAS local VSC is designed as follows:

[0085]

[0086] In the formula, μ represents the average marginal cost deviation between microgrids. For the proportional parameters of the PI controller in the primary control of FAS, Here, s represents the integral parameter of the PI controller for primary control of FAS, and s is the Laplace operator.

[0087] Here, VSC refers to the converter, i.e., the voltage source converter.

[0088] Step 3.2: Interaction between FAS agents in the microgrids, iteratively calculating the total marginal cost based on the Gossip algorithm. The specific process is the same as step 2.2 above.

[0089] At the information layer, FAS acts as an independent control node, exchanging information on the average marginal cost of DG within each MG (i.e., the average marginal cost of the microgrid in step 2.2). The marginal cost of each DG is adjusted to achieve economic allocation of active power; at the physical layer, power compensation between each MG is achieved by controlling the switching power of the intelligent flexible switch FAS.

[0090] Step 3.3: Implement microgrid group control by adding secondary control items to the local VSC. The secondary control items based on FAS are:

[0091]

[0092] In the formula, For FAS local VSC secondary control parameters, The proportional parameters are for the secondary control PI controller. Here, s represents the integral parameter of the PI controller for secondary control, s is the Laplace operator, and μ(n) is the difference in average operating marginal cost between adjacent microgrids at time n. This represents the total operating marginal cost error value.

[0093] By constructing secondary control items in the FAS, and based on the local microgrid power transmission control using bidirectional VSCs in the FAS, the system interacts with the status information of adjacent FASs to achieve the overall microgrid group control task and realize the goal of allocating active power according to marginal cost.

[0094] By constructing a secondary control term in the FAS, and based on local microgrid power transmission control via bidirectional VSCs within the FAS, interaction with adjacent FAS status information is achieved to accomplish the overall inter-microgrid control task, realizing the goal of active power allocation according to marginal cost. The overall inter-microgrid control strategy expression and control block diagram based on FAS are as follows:

[0095]

[0096] Example 1

[0097] This invention also provides a distributed coordination and control method for a flexible interconnected autonomous micronet group based on the Gossip algorithm, comprising the following steps:

[0098] Step 1: Each distributed power source within the microgrid adopts droop control, and the microgrids are connected through flexible switches. The rectifier side adopts constant DC voltage, and the inverter side adopts constant power control.

[0099] Step 2: Construct a distributed two-layer control architecture. The lower layer is a microgrid level. Each DG obtains neighbor marginal cost and frequency information through distributed communication within the network. An improved consistency control based on the Gossip algorithm is used to achieve active power economic allocation and frequency deviation elimination.

[0100] Step 3: The upper layer is the microgrid group level. Each microgrid intelligent agent flexible switch obtains the average marginal cost information of neighboring microgrids through distributed communication, and adopts improved consistency control based on the Gossip algorithm to realize the economic allocation of active power among microgrids.

[0101] Example 2

[0102] This invention also provides another distributed coordination and control method for flexible interconnected autonomous micronet groups based on the Gossip algorithm, comprising the following steps:

[0103] Step 1: Each distributed power source within the microgrid adopts droop control, and the microgrids are connected through flexible switches. The rectifier side adopts constant DC voltage, and the inverter side adopts constant power control.

[0104] Step 2: Construct a distributed two-layer control architecture. The lower layer is a microgrid level. Each distributed power source obtains neighbor marginal cost and frequency information through distributed communication within the network. An improved consistency control based on the Gossip algorithm is used to achieve active power economic allocation and frequency deviation elimination.

[0105] Step 3: The upper layer is the microgrid group level. Each microgrid's intelligent agent flexible switch obtains the average marginal cost information of neighboring microgrids through distributed communication, and adopts improved consistency control based on the Gossip algorithm to realize the economic allocation of active power among microgrids.

[0106] It should be noted that the improved consensus algorithm based on Gossip in steps 2 and 3 above specifically includes:

[0107] Building upon the characteristics of traditional consensus algorithms, this also considers the actual dynamic state variable z of the system. i and the information weight w of each node i Whenever a control cycle arrives, node i will send the relevant scaling factor information s to its neighbor node j. i→j and the state average value x after scaling factor adjustment i→j The specific interactive iteration process is as follows:

[0108] First, parameter initialization is performed, with node i assigning values ​​s to these two pieces of information from node j. i→j (0)=ω i and x i→j (0)=z i .

[0109] Next, neighboring nodes continuously share their information with the local node, updating the local information. Therefore, the state variable obtains the following information in the nth iteration of the control node i:

[0110]

[0111] In the (n+1)th subsequent iteration, control node i performs the following calculations sequentially and transmits the results to its neighboring distributed power source j, thus enabling interaction with node j:

[0112]

[0113] Finally, to prevent information looping—that is, to avoid sending back information obtained from a neighboring node—the node will exclude such information in subsequent control cycles, ensuring that the transmitted content is limited to newly acquired data. Vi(d) is introduced as the set of nodes in the communication network that can reach control node i in at most d steps. Meanwhile, Gi(Gj) is defined as the average state variable of the subnetwork connected to node i (or j) in the communication network after the link between distributed power sources i and j is broken.

[0114]

[0115] In the formula, w m Initialize the scaling factor parameter between nodes i and j, z m Initialize and assign values ​​to the average marginal cost parameter between nodes i and j.

[0116] It should be noted that the nodes in the inter-network and intra-network communication here refer to each distributed power source.

[0117] Example 3

[0118] The simulation examples of this invention use microgrids under hierarchical control for case analysis. The microgrid group structure is as follows: Figure 2 As shown, a simulation platform is built using MATLAB / Simulink. Figure 3 The microgrid cluster system topology model is shown. In this model, each secondary control module in the system's communication network is modeled based on the S-Function module in Simulink. The physical layer of the system sets each DG (Distributed Generation Group) to a single-bus parallel configuration. MGs (Multi-Governing Grids) are connected in parallel to the common inter-grid bus via the FAS (Functional Automation System) of each microgrid. MG1 contains three DGs (DG1-DG3), MG2 contains three DGs (DG4-DG6), and MG3 contains four DGs (DG7-DG8). 10 All distributed generation (DG) systems are ideal inverter types. The information layer includes secondary power / frequency controllers, etc. Each DG is configured with an agent that interacts with neighboring agents and uses secondary control to eliminate frequency errors and economically allocate active power.

[0119] To verify the effectiveness of the proposed economic distributed coordinated control strategy based on marginal cost, the droop coefficient and cost coefficient of each DG were set differently to fully reflect the diversity of DG types and the flexibility of scenarios in the microgrid cluster. The system components and control parameters in the multi-microgrid (MMG) cluster, along with the cost coefficients of each DG, are shown in Tables 1 and 2. The total simulation runtime is 5 seconds, with the system physical simulation step size T. p =50μs, communication period T s =3ms.

[0120] Table 1

[0121]

[0122]

[0123] Table 2

[0124]

[0125] This experiment considers marginal operating costs through secondary control to improve the system's operational economy. The simulation analysis is as follows: From 0 to 1 second at the start of the simulation, each DG in the MMG system uses only droop control as primary control, allocating active power output to each DG according to different droop coefficients. At 1 second, intra-network secondary control is activated. Each DG in each MG exchanges its operating cost information and uses the Gossip algorithm to achieve marginal cost consistency, realizing optimal economic operation of each DG in the MG. At 2 seconds, the system again activates inter-group control, using the flexible interconnection device FAS between each MG as an independent agent to transmit the intra-network average marginal cost information for consistency iteration. The FAS only acts as an inter-network information exchange agent and has no cost parameters of its own. It adjusts the output of each DG in the MG and the power transmission between each FAS in the inter-group through the new marginal cost information, realizing inter-group secondary control. At 3 seconds, the MMG system experiences a sudden load increase of 30kW + 15kVar, and the load is removed at 4 seconds. The simulation ends at 5 seconds.

[0126] Table 3 is obtained through the calculation and analysis of the system operating cost under the control strategy of this invention:

[0127] Table 3

[0128]

[0129] like Figure 4 As shown, during the simulation run from 0 to 1 second, each DG in the MMG system only uses droop control, and the operating frequencies of each MG are different and not operating at the rated frequency of 50Hz. After 1 second, due to the addition of internal secondary control, the MG operating frequency returns to the rated value and... Figure 5 and 7 As shown, each MG operates at the marginal cost until it is consistent, and the active power output of each DG in the network is adjusted according to the marginal cost. At this time, no inter-group secondary control is involved. From 2 to 3 seconds, the system implements inter-group secondary control, using FAS to achieve information exchange and ensure that the marginal cost of all DGs in the system is consistent. Based on the marginal cost information, the active power output and power flow between MGs are adjusted. Figure 5 As shown, since the marginal cost of MG2 is relatively large and the marginal cost of MG1 / MG3 is relatively small, according to the inter-network control strategy, each DG in MG1 / MG3 increases its power output while each DG in MG2 reduces its power output to meet the optimal economic operation of the MMG system; for example... Figure 6As shown, increased power output is positive, and decreased power output is negative. At the inter-network FAS, the power flow is FAS3→FAS2 and FAS1→FAS2. MG3 has the lowest marginal cost and the highest increased power output, followed by MG1. At 3 seconds, the system experiences a sudden load increase. Each DG adjusts its output power to continue meeting optimal economic operation. At 4 seconds, the load exits the system, restoring normal operation until the simulation ends. During the simulation, despite load changes, the system can still consistently allocate power output among the DGs according to their marginal costs and coordinate power transmission changes between MGs through the FAS, effectively verifying the feasibility of the control strategy and the economic efficiency of system regulation and operation.

[0130] It should be noted that, in the embodiments of the present invention, if the above-described distributed coordinated control method for microgrid groups based on the Gossip algorithm is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiments of the present invention, or the part that contributes to related technologies, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a terminal to execute all or part of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), magnetic disks, or optical disks. Thus, the embodiments of the present invention are not limited to any specific hardware and software combination.

[0131] Correspondingly, embodiments of the present invention provide a distributed coordination control device for microgrid groups based on the Gossip algorithm. Figure 8 This is a schematic diagram of the composition structure of a microgrid group distributed coordination control device based on the Gossip algorithm provided in an embodiment of the present invention, as shown below. Figure 8 As shown, the Gossip-based microgrid distributed coordination control device 800 includes at least a processor 801 and a computer-readable storage medium 802 configured to store executable instructions. The processor 801 typically controls the overall operation of the Gossip-based microgrid distributed coordination control device. The computer-readable storage medium 802 is configured to store instructions and applications executable by the processor 801, and can also cache data to be processed or processed by various modules in the processor 801 and the Gossip-based microgrid distributed coordination control device 800. This cache can be implemented using flash memory or random access memory (RAM).

[0132] This invention provides a storage medium storing executable instructions. When these executable instructions are executed by a processor, they cause the processor to perform the method provided in this invention, for example... Figure 1 The method shown.

[0133] In some embodiments, the storage medium may be a computer-readable storage medium, such as a ferromagnetic random access memory (FRAM), a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), flash memory, magnetic surface memory, optical disc, or a compact disk-read-only memory (CD-ROM); or it may be a device that includes one or any combination of the above-mentioned memories.

[0134] In some embodiments, executable instructions may take the form of a program, software, software module, script, or code, written in any form of programming language (including compiled or interpreted languages, or declarative or procedural languages), and may be deployed in any form, including as a standalone program or as a module, component, subroutine, or other unit suitable for use in a computing environment.

[0135] As an example, executable instructions may, but do not necessarily, correspond to files in a file system. They may be stored as part of a file containing other programs or data, for example, in one or more scripts within a Hyper Text Markup Language (HTML) document, in a single file dedicated to the program in question, or in multiple co-located files (e.g., files storing one or more modules, subroutines, or code sections). As an example, executable instructions may be deployed to execute on a single electronic device, or on multiple electronic devices located in one location, or on multiple electronic devices distributed across multiple locations and interconnected via a communication network.

[0136] The above description is merely an embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and scope of the present invention are included within the scope of protection of the present invention.

[0137] It should be understood that the phrase "one embodiment" or "an embodiment" throughout the specification means that a specific feature, structure, or characteristic related to the embodiment is included in at least one embodiment of the invention. Therefore, "in one embodiment" or "in an embodiment" appearing throughout the specification does not necessarily refer to the same embodiment. Furthermore, these specific features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. It should be understood that in the various embodiments of the invention, the sequence numbers of the above-described processes do not imply a sequential order of execution; the execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the invention. The sequence numbers of the above-described embodiments of the invention are merely descriptive and do not represent the superiority or inferiority of the embodiments.

[0138] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element. In the several embodiments provided by this invention, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods, such as: multiple units or components may be combined, or integrated into another system, or some features may be ignored or not performed.

[0139] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A distributed coordinated control method for microgrid groups based on the Gossip algorithm, characterized in that, The method includes: In the event of a disturbance in the microgrid, each distributed power source under droop control performs initial control using the following formula to maintain the power balance of the microgrid: In the formula, f i and U i Let fi and U0 represent the frequency amplitude and voltage amplitude of the i-th distributed power source, respectively; f0 and U0 represent the rated frequency amplitude and rated voltage amplitude of the distributed power source, respectively; P and Q represent the active power and reactive power of the distributed power source, respectively; P0 and Q0 represent the reference values ​​of the active power and reactive power of the distributed power source, respectively; K P and K Q These represent the droop factor for frequency and the droop factor for voltage, respectively. By using distributed communication within the network in the constructed distributed two-layer control architecture, the average marginal cost parameters and frequency information of each microgrid are obtained, and a preset Gossip consensus algorithm is used for secondary control to achieve economic allocation of active power and frequency stability of the microgrid. Through distributed communication combining inter-network and intra-network communication, the average marginal cost information of neighboring micronets is obtained, and secondary control is performed using the preset Gossip consensus algorithm to achieve active power economic allocation among micronets, including: Through a single control operation between microgrids, the marginal operating costs of adjacent microgrids are made consistent; based on the preset Gossip consensus algorithm iteration, the total marginal cost of the microgrid group is calculated. The microgrid group control is achieved by adding a secondary control term to the local VSC. Based on the power transmission control of the local microgrid by the bidirectional VSC in FAS, the goal of allocating active power according to marginal cost is achieved by constructing a secondary control term in FAS.

2. The method according to claim 1, characterized in that, The aforementioned distributed communication within the network, constructed through a distributed two-layer control architecture, obtains neighbor marginal cost information and frequency information, and employs a preset Gossip consensus algorithm for secondary control to achieve active power economic allocation and frequency deviation elimination, including: Through the distributed communication within the network, the cost parameters of each distributed power source in each microgrid are obtained, and a distributed power generation cost function is established based on the cost parameters. Based on the distributed power generation cost function, calculate the marginal cost parameter of each distributed power source. Based on the preset distributed algorithm and the marginal cost parameters, the average marginal cost parameters of each microgrid are estimated; Based on the preset Gossip consensus algorithm, the input parameters and frequency amplitude of the secondary controller applied to the droop control are determined; By applying secondary control, the active power distribution and frequency stability of the microgrid can be achieved.

3. The method according to claim 1, characterized in that, The distributed communication via a combination of inter-network and intra-network communication also includes: Calculate the average operating marginal cost of each distributed power source among adjacent microgrids; the calculation formula is: In the formula, G is the number of FAS, and μ(n) is the difference in average operating marginal cost between adjacent microgrids at time n. Let n be the difference in average operating marginal cost between adjacent microgrids of FAS1. Let n be the difference in average operating marginal cost between adjacent microgrids of FAS2. FAS at time n G The difference in average operating marginal cost between adjacent microgrids and These are the average marginal costs of α and β microgrids, respectively; The average operating marginal cost is transferred from the distributed power source to the FAS. The primary control item of the FAS local VSC is: In the formula, Here, μ represents the primary control parameter of the local VSC in FAS, and μ is the average marginal cost deviation between adjacent microgrids. For the proportional parameters of the PI controller in the primary control of FAS, For the FAS primary control PI controller integral parameters, s is the Laplace operator; The local VSC secondary control item is represented as follows: In the formula, For FAS local VSC secondary control parameters, The proportional parameters are for the secondary control PI controller. Here, s represents the integral parameter of the PI controller for secondary control, s is the Laplace operator, and μ(n) is the difference in average operating marginal cost between adjacent microgrids at time n. This represents the total operating marginal cost error value.

4. A distributed coordination control device for microgrid groups based on the Gossip algorithm, characterized in that, The device includes: The initial control module is used to maintain the power balance of the microgrid by initially controlling each distributed power source under droop control according to the following formula in the event of a disturbance in the microgrid: In the formula, f i and U i Let fi and U0 represent the frequency amplitude and voltage amplitude of the i-th distributed power source, respectively; f0 and U0 represent the rated frequency amplitude and rated voltage amplitude of the distributed power source, respectively; P and Q represent the active power and reactive power of the distributed power source, respectively; P0 and Q0 represent the reference values ​​of the active power and reactive power of the distributed power source, respectively; K P and K Q These represent the droop factor for frequency and the droop factor for voltage, respectively. The secondary control module is used to obtain the average marginal cost parameters and frequency information of each microgrid through distributed communication within the network in the constructed distributed two-layer control architecture, and to perform secondary control using a preset Gossip consensus algorithm to achieve economic allocation of active power and frequency stability of the microgrid. The secondary control module is also used to obtain the average marginal cost information of neighboring micronets through distributed communication combining inter-network and intra-network communication, and to perform secondary control using the preset Gossip consensus algorithm to achieve active power economic allocation between micronets. Through a single control operation between microgrids, the marginal operating costs of adjacent microgrids are made consistent; based on the preset Gossip consensus algorithm iteration, the total marginal cost of the microgrid group is calculated. The microgrid group control is achieved by adding a secondary control term to the local VSC. Based on the power transmission control of the local microgrid by the bidirectional VSC in FAS, the goal of allocating active power according to marginal cost is achieved by constructing a secondary control term in FAS.

5. A distributed coordination control device for microgrid groups based on the Gossip algorithm, characterized in that, include: Memory, used to store executable instructions; The processor, when executing executable instructions stored in the memory, implements the distributed coordinated control method for microgrid groups based on the Gossip algorithm as described in any one of claims 1 to 3.

6. A computer-readable storage medium storing executable instructions for causing a processor to execute the executable instructions to implement the distributed coordinated control method for microgrid groups based on the Gossip algorithm as described in any one of claims 1 to 3.

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