Microgrid group distributed coordination control method and device based on Gossip algorithm

Abstract

The embodiment of the invention provides a micro-grid group distributed coordination control method and device based on a Gossip algorithm, and the method comprises the steps: carrying out the initial control of each distributed power supply under droop control through the following formula under the condition that a micro-grid is disturbed, so as to maintain the power balance of the micro-grid; obtaining an average marginal cost parameter and frequency information of each micro-grid through in-grid distributed communication in the constructed distributed double-layer control architecture, and performing secondary control by adopting a preset Gossip consistency algorithm so as to realize active power economic distribution and frequency stability of the micro-grid; through distributed communication, average marginal cost information of neighbor microgrids is obtained, and secondary control is carried out by adopting a preset Gossip consistency algorithm, so that active economic distribution among the microgrids is realized.

Description

Technical Field

[0001] The present invention relates to the field of microgrid power control, and relates to, but is not limited to, a distributed coordinated control method and device for a microgrid group based on the Gossip algorithm. Background Art

[0002] With the continuous advancement of distributed power sources accessing the power system, the demand for the configuration and application of microgrids is increasing. At present, the structures of microgrids are diverse and the layouts are scattered. Compared with distributed control methods, the traditional centralized control mode is difficult to meet the requirements of autonomous management and coordinated optimization, and cannot meet the diverse needs of flexible loads. The microgrid cluster based on intelligent soft-switch interconnection, with its inter-network bidirectional power flow control ability and the ability of dynamic flexible reconstruction of the microgrid under faults, can be used as a new solution to improve the power supply reliability of the microgrid. However, compared with the microgrid cluster interconnected by traditional tie switches, the operating frequency of the microgrid cluster based on intelligent soft-switch interconnection changes from a global variable to a local variable, and the frequencies of different microgrids may be different, making it difficult to achieve frequency synchronization among the microgrids, resulting in a decline in the overall stability of the microgrid group and a weakening of the system's anti-disturbance ability.

[0003] At present, distributed control based on the consensus algorithm is widely used in microgrids due to its high real-time communication interaction advantage. However, the existing microgrid group control strategies based on the traditional average consensus algorithm have problems such as slow convergence and strong communication dependence. At the same time, the secondary power control of the microgrid group is mainly based on proportional distribution according to capacity, and less consideration is given to the cost economy problem of coordinated operation among sub-microgrids. Summary of the Invention

[0004] The present invention provides a distributed coordinated control method and device for a microgrid group based on the Gossip algorithm to solve the problems of inter-network frequency decoupling, high operating cost, and fuzzy inter-network transmission power control existing in the microgrid group under traditional control.

[0005] The technical method of the embodiment of the present invention is implemented as follows:

[0006] In a first aspect, the embodiment of the present invention provides a distributed coordinated control method for a microgrid group based on the Gossip algorithm, and the method includes:

[0007] In the case of a disturbance in the microgrid, each distributed power source of the droop control performs primary control through the following formula to maintain the power balance of the microgrid; the formula is: where f i and U i respectively represent the frequency amplitude and voltage amplitude of the i-th distributed power source; f 0 and U 0respectively represent the rated frequency amplitude and the rated voltage amplitude of the distributed power source; P and Q respectively represent the active power and the reactive power of the distributed power source; P 0 and Q 0 respectively represent the active power reference value and the reactive power reference value of the distributed power source; K P and K Q respectively represent the droop coefficient of frequency and the droop coefficient of voltage;

[0008] Through the in-network distributed communication in the constructed distributed two-layer control architecture, the average marginal cost parameter and the frequency information of each microgrid are obtained, and the preset Gossip consensus algorithm is used for secondary control to achieve the economic distribution of the active power and the frequency stability of the microgrid;

[0009] Through the distributed communication combining between-network and in-network, the average marginal cost information of neighbor microgrids is obtained, and the preset Gossip consensus algorithm is used for secondary control to achieve the active power economic distribution among microgrids.

[0010] In a second aspect, the present invention provides a distributed coordinated control device for a microgrid group based on the Gossip algorithm, and the device includes:

[0011] A primary control module, configured to, in the case of a disturbance in the microgrid, each distributed power source performing droop control performs primary control through the following formula to maintain the power balance of the microgrid; the formula is: wherein, f i and U i respectively represent the frequency amplitude and the voltage amplitude of the i-th distributed power source; f 0 and U 0 respectively represent the rated frequency amplitude and the rated voltage amplitude of the distributed power source; P and Q respectively represent the active power and the reactive power of the distributed power source; P 0 and Q 0 respectively represent the active power reference value and the reactive power reference value of the distributed power source; K P and K Q respectively represent the droop coefficient of frequency and the droop coefficient of voltage;

[0012] A secondary control module, configured to, through the in-network distributed communication in the constructed distributed two-layer control architecture, obtain the average marginal cost parameter and the frequency information of each microgrid, and use the preset Gossip consensus algorithm for secondary control to achieve the economic distribution of the active power and the frequency stability of the microgrid;

[0013] The secondary control module is further configured to obtain the average marginal cost information of neighbor microgrids through inter-network and intra-network combined distributed communication, and perform secondary control using the preset Gossip consensus algorithm to achieve active power economic distribution among microgrids.

[0014] In some embodiments, the secondary control module is further configured to obtain the cost parameters of each distributed power source in each microgrid through the intra-network distributed communication, and establish a distributed power generation cost function based on the cost parameters; calculate the marginal cost parameters of each distributed power source based on the distributed power 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 amplitudes of the secondary controller applied to the droop control based on the preset Gossip consensus algorithm; and achieve active power economic distribution and frequency stability of the microgrid through applying secondary control.

[0015] In some embodiments, the secondary control module is further configured to reduce the output of the microgrid with a high operating marginal cost and increase the output of the microgrid with a low operating marginal cost through primary control between microgrids, so that the operating marginal costs of adjacent microgrids are consistent; calculate the average operating marginal cost of each distributed power source between adjacent microgrids; the calculation formula is: In the formula, G is the number of FASs, μ(n) is the difference in the average operating marginal cost between adjacent microgrids at time n, μ 1 (n) is the FAS at time n 1 Difference in the average operating marginal cost between adjacent microgrids, μ 2 (n) is the FAS at time n 2 Difference in the average operating marginal cost between adjacent microgrids, μ G (n) is the FAS at time n G Difference in the average operating marginal cost between adjacent microgrids, L MG,α (P) and L MG,β (P) are the average marginal costs of microgrids α and β respectively; transmit the average operating marginal cost from the distributed power source to the FAS, and the local VSC primary control term of the FAS is: In the formula, is the local VSC primary control parameter of the FAS, μ is the deviation of the average marginal cost between adjacent microgrids, is the proportional parameter of the FAS primary control PI controller, is the integral parameter of the FAS primary control PI controller, s is the Laplace operator; iterate based on the preset Gossip consensus algorithm to calculate the total marginal cost of the microgrid group; achieve the control of the microgrid group 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, is the secondary control parameter of the FAS local VSC, is the proportional parameter of the secondary control PI controller, is the integral parameter of the secondary control PI controller, s is the Laplace operator, and μ(n) is the difference in the average operating marginal cost between adjacent microgrids at the nth moment. is the total operating marginal cost error value; on the basis of the two-way VSC in the FAS controlling the power transmission of the local microgrid, by constructing the FAS secondary control term and interacting with the adjacent FAS for status information, the control task among the overall microgrid group is achieved to realize the goal of active power distribution according to the marginal cost.

[0016] In a third aspect, an embodiment of the present invention provides an electronic device, including: a memory for storing executable instructions; a processor for implementing the above-mentioned distributed coordinated control method for a microgrid group based on the Gossip algorithm when executing the executable instructions stored in the memory.

[0017] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium storing executable instructions for causing a processor to implement the above-mentioned distributed coordinated control method for a microgrid group based on the Gossip algorithm when executing the executable instructions.

[0018] The distributed coordinated control method for a microgrid group based on the Gossip algorithm provided by the embodiment of the present invention first performs primary control to maintain the power balance of the microgrid and the microgrid group; secondly, a distributed two-layer control architecture is constructed, and each DG obtains neighbor marginal cost and frequency information through in-network distributed communication, and uses an improved consensus control based on the Gossip algorithm to achieve active power economic distribution and frequency deviation elimination; finally, each microgrid agent flexible switch obtains neighbor microgrid average marginal cost information through distributed communication, and uses an improved consensus control based on the Gossip algorithm to achieve active power economic distribution among microgrids. In this way, the present invention establishes a two-layer coordinated control architecture for the microgrid group. The upper layer realizes inter-network power exchange and cost information sharing through the agent flexible switch, and the lower layer coordinates the flexible economic distribution of the output of each distributed power source according to the marginal cost information; and the Gossip consensus algorithm is introduced, and based on the concurrent propagation characteristic of the algorithm information, the global information sharing process is accelerated; at the same time, through the control of the power flow direction by the inter-network agent flexible switch and the characteristic of distributing power according to the marginal cost of each distributed power source in the network, the stable and reliable operation of the microgrid group is realized. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 is a schematic flow chart of a distributed coordinated control method for a microgrid group based on the Gossip algorithm provided by an embodiment of the present invention;

[0020] Figure 2 It is the structure diagram of the microgrid system provided by the embodiment of the present invention;

[0021] Figure 3 It is the topological structure diagram of the simulation microgrid group system model provided by the embodiment of the present invention;

[0022] Figure 4 It is the operating frequency diagram of each MG within the MMG provided by the embodiment of the present invention;

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

[0024] Figure 6 It is the exchanged power diagram of each FAS between networks within the MMG provided by the embodiment of the present invention;

[0025] Figure 7 It is the operating marginal cost diagram of each DG within the MMG provided by the embodiment of the present invention;

[0026] Figure 8 It is the schematic diagram of the composition structure of the distributed coordinated control device for the microgrid group based on the Gossip algorithm provided by the embodiment of the present invention. Specific embodiments

[0027] In order 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 of the present invention. All other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the scope of protection of the present invention.

[0028] In the following description, reference is made to "some embodiments", which describe a subset of all possible embodiments. However, it can be understood that "some embodiments" can be the same subset or different subsets of all possible embodiments, and can be combined with each other without conflict. Unless otherwise defined, all technical and scientific terms used in the embodiments of the present invention have the same meaning as commonly understood by those skilled in the technical field to which the embodiments of the present invention belong. The terms used in the embodiments of the present invention are only for the purpose of describing the embodiments of the present invention and are not intended to limit the present invention.

[0029] The following describes the exemplary application of the distributed coordinated control device for a microgrid group based on the Gossip algorithm according to the embodiments of the present invention. The landslide and rockfall detection device provided by the embodiments of the present invention can be implemented as a terminal or a server. In one implementation, the distributed coordinated control device for a microgrid group based on the Gossip algorithm provided by the embodiments of the present invention can be implemented as various types of terminals such as laptops, tablets, desktop computers, and mobile devices; in another implementation, the distributed coordinated control device for a microgrid group based on the Gossip algorithm provided by the embodiments of the present invention can also be implemented as a server. Among them, the server can be an independent physical server, a server cluster or a 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 communications, middleware services, domain name services, security services, content delivery networks (CDNs, Content Delivery Networks), and big data and artificial intelligence platforms. The terminal and the server can be directly or indirectly connected through wired or wireless communication methods, which are not limited in the embodiments of the present invention. Next, the exemplary application when the distributed coordinated control device for a microgrid group based on the Gossip algorithm is implemented as a server will be described.

[0030] The embodiments of the present invention provide a distributed coordinated control method for a microgrid group based on the Gossip algorithm. Refer to Figure 1 , Figure 1 which is a schematic flowchart of the distributed coordinated control method for a microgrid group based on the Gossip algorithm provided by the embodiments of the present invention, and will be described in conjunction with the steps shown in Figure 1 .

[0031] Step S110, in the case of a microgrid disturbance, each distributed power source under droop control performs primary control through the following formula to maintain the power balance of the microgrid.

[0032] Here, the formula is: In the formula, f i and U i respectively represent the frequency amplitude and voltage amplitude of the i-th distributed power source; f 0 and U 0 respectively represent the rated frequency amplitude and rated voltage amplitude of the distributed power source; P and Q respectively represent the active power and reactive power of the distributed power source; P 0 and Q 0 respectively represent the active power reference value and reactive power reference value of the distributed power source; K P and K Q respectively represent the droop coefficient of frequency and the droop coefficient of voltage.

[0033] In the embodiments of the present invention, during the operation of the microgrid, disturbances are inevitable, such as sudden changes in load, connection or disconnection of distributed power sources, etc. Droop control is a control strategy used to automatically allocate power among distributed power sources and maintain the power balance of the microgrid. When a disturbance occurs in the microgrid, through the primary control of droop control, each distributed power source can respond quickly and initially stabilize the operating state of the microgrid.

[0034] Step S120: Obtain the average marginal cost parameter and frequency information of each microgrid through in-network distributed communication in the constructed distributed two-layer control architecture, and perform secondary control using the preset Gossip consensus algorithm to achieve economic distribution of active power and frequency stability of the microgrid.

[0035] In the embodiments of the present invention, to achieve more optimized control of the microgrid, a distributed two-layer control architecture is constructed. Among them, in-network distributed communication refers to the way of information interaction among distributed power sources and between 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 is used to reflect the cost increase for each additional unit of power generation in the microgrid, which is crucial for achieving economic distribution of active power. The frequency information is one of the key indicators for the stable operation of the microgrid.

[0037] In the present invention, the average marginal cost parameter and frequency information are propagated among the internal nodes of the microgrid through the Gossip algorithm, enabling each distributed power source to gradually reach a consistent understanding of this information. Based on this consistency, each distributed power source can adjust its own power generation, thereby achieving economic distribution of active power in the microgrid, that is, minimizing the power generation cost under the premise of meeting the power demand of the microgrid. At the same time, by adjusting and controlling the frequency, the frequency stability of the microgrid is maintained, ensuring that the microgrid can operate stably and reliably.

[0038] Step S130: Obtain the average marginal cost information of neighboring microgrids through distributed communication combining between-network and in-network, and perform secondary control using the preset Gossip consensus algorithm to achieve economic distribution of active power among microgrids.

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

[0040] After that, the preset Gossip consensus algorithm is adopted again for secondary control. By this algorithm, the average marginal cost information is propagated among the microgrids, enabling each microgrid to adjust its active power output based on the cost information with common cognition, so as to achieve the active economic distribution among the microgrids. This means that in the entire microgrid group, the active power can be more reasonably distributed, avoiding excessive power generation costs of some microgrids, and at the same time making full use of the power generation resources of each microgrid to improve the operation economy and reliability of the entire microgrid group.

[0041] The distributed coordinated control method for a microgrid group based on the Gossip algorithm provided by the embodiment of the present invention first performs primary control to maintain the power balance of the microgrid and the microgrid group; secondly, a distributed two-layer control architecture is constructed, and each DG obtains the neighbor marginal cost and frequency information through in-network distributed communication, and uses the improved consensus control based on the Gossip algorithm to achieve active economic distribution and frequency deviation elimination; finally, each microgrid agent flexible switch obtains the average marginal cost information of the neighbor microgrids through distributed communication, and uses the improved consensus control based on the Gossip algorithm to achieve active economic distribution among the microgrids. In this way, the present invention establishes a two-layer coordinated control architecture for the microgrid group. The upper layer realizes the inter-network power exchange and cost information sharing through the agent flexible switch, and the lower layer coordinates the flexible and economic distribution of the output of each distributed power source according to the marginal cost information; and the Gossip consensus algorithm is introduced, and based on the information concurrent propagation characteristic of this algorithm, the global information sharing process is accelerated; at the same time, through the characteristics of controlling the power flow by the inter-network agent flexible switch and distributing the power of each distributed power source in the network according to the marginal cost, the stable and reliable operation of the microgrid group is realized.

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

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

[0044] Step S122, based on the distributed power source power generation cost function, calculate the marginal cost parameters of each distributed power source.

[0045] Step S123, based on a 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, based on the application of secondary control, to achieve the economic distribution of active power and frequency stability of the microgrid.

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

[0049] Step S131, through the primary control between microgrids, reduce the output of the microgrid with a high operating marginal cost and increase the output of the microgrid with a low operating marginal cost, so that the operating marginal costs of adjacent microgrids are consistent.

[0050] Step S132, calculate the average operating marginal cost of each distributed power source between adjacent microgrids.

[0051] Here, the calculation formula is: In the formula, G is the number of FASs, μ(n) is the difference in the average operating marginal cost between adjacent microgrids at time n, μ 1 (n) is the average operating marginal cost difference of FASs between adjacent microgrids at time n 1 The average operating marginal cost difference between adjacent microgrids, μ 2 (n) is the average operating marginal cost difference of FASs between adjacent microgrids at time n 2 The average operating marginal cost difference between adjacent microgrids, μ G (n) is the average operating marginal cost difference of FASs between adjacent microgrids at time n G The average operating marginal cost difference between adjacent microgrids, L MG,α (P) and L MG,β (P) are the average marginal costs of microgrids α and β respectively.

[0052] Step S133, transfer the average operating marginal cost from the distributed power source to the FAS, and the primary control term of the FAS local VSC is: In the formula, is the primary control parameter of the FAS local VSC, μ is the average marginal cost deviation between adjacent microgrids, is the proportional parameter of the primary control PI controller of the FAS, is the integral parameter of the primary control PI controller of the FAS, and s is the Laplace operator.

[0053] Step S134, based on the iteration of the preset Gossip consensus algorithm, calculate the total marginal cost.

[0054] Step S135, achieve the microgrid group control by adding a secondary control term to the local VSC, based on the local secondary control term of the FAS; the local secondary control term is expressed as: In the formula, is the secondary control parameter of the FAS local VSC, is the proportional parameter of the secondary control PI controller, is the integral parameter of the secondary control PI controller, s is the Laplace operator, and μ(n) is the difference in the average operating marginal cost between adjacent microgrids at time n. is the total operating marginal cost error value.

[0055] Step S136: On the basis of the power transfer control of the local microgrid by the bidirectional VSC in the FAS, by constructing the secondary control term of the FAS and interacting with the adjacent FAS for status information, the control task among the overall microgrid group is achieved to realize the goal of active power distribution according to the marginal cost.

[0056] The present invention considers a distributed coordinated control method for a flexible interconnected autonomous microgrid group based on the Gossip algorithm under a hierarchical control mode, establishes a two-layer coordinated control architecture for the microgrid group. The upper layer realizes the inter-network power exchange and cost information sharing through the intelligent agent flexible switch, and the lower layer coordinates the flexible and economic distribution of the output of each distributed power source according to the marginal cost information; introduces the Gossip consensus algorithm, and accelerates the global information sharing process based on the concurrent propagation characteristics of the algorithm information; proposes a distributed coordinated control method for the microgrid group, and realizes the stable and reliable operation of the microgrid group through the characteristics of controlling the power flow by the inter-network intelligent agent flexible switch and distributing the power of each distributed power source in the network according to the marginal cost.

[0057] Next, the exemplary application of the embodiment of the present invention in an actual application scenario will be described.

[0058] The present invention provides a distributed coordinated control method for a flexible interconnected autonomous microgrid group based on the Gossip algorithm, including the following steps:

[0059] Step 1: Each distributed power source in the microgrid adopts droop control, and the microgrids are connected through flexible switches. The rectifier side adopts constant DC voltage control, 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 power source (Distributed Generator, DG) obtains the neighbor marginal cost and frequency information through the in-network distributed communication, and adopts an improved consensus control based on the Gossip algorithm to achieve active power economic distribution and frequency deviation elimination.

[0061] Step 3: The upper layer is the microgrid group level. Each microgrid (Microgrid, MG) intelligent agent flexible switch (Flexible Agent interconnection Switch, FAS) obtains the average marginal cost information of the neighbor microgrids through the distributed communication, and adopts an improved consensus control based on the Gossip algorithm to achieve active power economic distribution among the microgrids.

[0062] In the embodiment of the present invention, Step 1 further includes the following steps:

[0063] When a disturbance occurs in the microgrid, the distributed power sources with droop control automatically perform the control as shown in the following formula to maintain the power balance of the microgrid;

[0064] In the formula, f i and U i respectively represent the frequency amplitude and voltage amplitude of the i-th distributed power source; f 0 and U 0 respectively represent the rated frequency amplitude and rated voltage amplitude of the distributed power source; P and Q respectively represent the active power and reactive power of the distributed power source; P 0 and Q 0 respectively represent the active power reference value and reactive power reference value of the distributed power source; K P and K Q respectively represent the droop coefficient of frequency and the droop coefficient of voltage.

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

[0066] Step 2.1: Obtain the DG cost parameters in each MG subnet, establish the distributed power generation cost function, and calculate the marginal cost of each DG on this basis.

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

[0068] In the formula, C i is the power generation cost of the i-th distributed power source, a i is the non-linear variable cost coefficient such as equipment wear of the distributed power source, b i is the linear power generation cost coefficient such as fuel and operation and maintenance of the distributed power source, c i is the fixed cost part such as the upfront investment and installation of the power source; P i is the active power of the i-th distributed power source.

[0069] At this time, the DG cost margin 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. From 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 input the marginal cost parameter η iand the corresponding weight factor w i .

[0072] At the nth control moment of each subsequent 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) is the scaling factor information sent by control node j to i at the nth iteration, is the scaling factor information after the (n + 1)th iteration, j is the adjacent node of node i, is the average marginal cost of the output microgrid, x is the average state value after being adjusted by the scaling factor, is the average marginal cost after being adjusted by the scaling factor after the (n + 1)th iteration, w i is the weight factor of each node's information.

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

[0076]

[0077] In the formula: f i is the frequency value at node i, f ref is the frequency reference value at node i, u P is the input parameter of the secondary controller applied to the droop control, m i,p is the product of the droop coefficient and the active power, is the secondary control term considering the marginal cost of DG operation, is the secondary control term considering the frequency of DG.

[0078] According to the application of the secondary control, active power economic distribution and frequency stability in the MG are achieved, where:

[0079]

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

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

[0082] Step 3.1: The primary control between microgrids reduces the output of the MG with a high operating marginal cost and increases the output of the MG with a low cost, so that the operating marginal costs of adjacent MGs are consistent. Then there is:

[0083]

[0084] In the formula, G is the number of FASs, μ(n) is the difference in the average operating marginal cost between adjacent microgrids at time n, μ 1 (n) is the difference in the average operating marginal cost of FAS 1 between adjacent microgrids at time n, μ 2 (n) is the difference in the average operating marginal cost of FAS 2 between adjacent microgrids at time n, μ G (n) is the difference in the average operating marginal cost of FAS G between adjacent microgrids at time n, L MG,α (P) and L MG,β (P) are the average marginal costs of the α and β microgrids respectively. After calculating the average operating marginal cost of each DG in the MG, it is transmitted from the DG to the FAS through the communication network. After design, the primary control term of the FAS local VSC is:

[0085]

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

[0087] Here, VSC refers to the converter, that is, the voltage source converter.

[0088] Step 3.2: The FAS agents between microgrids interact and iteratively calculate 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, as an independent control node, the FAS adjusts the marginal cost of each DG by exchanging the average marginal cost information of the DGs in each MG (that is, the average marginal cost of the microgrid in step 2.2 ) to achieve active economic distribution; at the physical layer, the power compensation between MGs 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 terms to the local VSC. The secondary control terms based on FAS are as follows:

[0091]

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

[0093] By constructing the FAS secondary control terms, on the basis of the local microgrid power transmission control of the bidirectional VSC in the FAS, interact with the status information of the adjacent FAS to achieve the overall microgrid group control task and realize the goal of active power distribution according to the marginal cost.

[0094] By constructing the FAS secondary control terms, on the basis of the local microgrid power transmission control of the bidirectional VSC in the FAS, interact with the status information of the adjacent FAS to achieve the overall microgrid group control task and realize the goal of active power distribution according to the marginal cost. The expression and control block diagram of the overall control strategy between microgrid groups based on FAS are as follows:

[0095]

[0096] Embodiment 1

[0097] The present invention also provides a distributed coordinated control method for a flexible interconnected autonomous microgrid group considering the Gossip algorithm, including the following steps:

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

[0099] Step 2. Construct a distributed two-layer control architecture. The lower layer is the microgrid level. Each DG obtains the neighbor marginal cost and frequency information through in-network distributed communication, and adopts an improved consensus control based on the Gossip algorithm to achieve active power economic distribution and frequency deviation elimination.

[0100] Step 3. The upper layer is the microgrid group level. The flexible switches of each microgrid agent obtain the neighbor microgrid average marginal cost information through distributed communication, and adopt an improved consensus control based on the Gossip algorithm to achieve active power economic distribution between microgrids.

[0101] Embodiment 2

[0102] The present invention also provides another flexible interconnected autonomous microgrid group distributed coordination control method considering the Gossip algorithm, including the following steps:

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

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

[0105] Step 3: The upper layer is the microgrid group level. Each microgrid microgrid agent flexible switch obtains the neighbor microgrid average marginal cost information through distributed communication, and uses an improved consensus control based on the Gossip algorithm to achieve active power economic distribution among microgrids.

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

[0107] On the basis of inheriting the characteristics of the traditional consensus algorithm, the actual dynamic state quantity z of the system is also considered i and the information weight w of each node i . Whenever the control period arrives, node i will send the relevant scaling factor information s i→j and the state average value x adjusted by the scaling factor i→j to its neighbor node j. The specific interaction iteration process is as follows:

[0108] First, perform parameter initialization. Node i assigns these two pieces of information of node j as s i→j (0) = ω i and x i→j (0) = z i .

[0109] Then, the surrounding neighboring nodes will continuously share their own information with the local node to achieve local information update. Therefore, the following information is obtained for the state quantity in the nth iteration of control node i:

[0110]

[0111] In the subsequent n + 1th time, control node i sequentially performs the following calculations and transmits the results to neighbor distributed power source j to achieve interaction with node j:

[0112]

[0113] Finally, to prevent the cyclic propagation of information, that is, to avoid sending back the information obtained from a certain neighbor node, the node will exclude this information in the subsequent control cycle to ensure that the transmitted content is limited to newly acquired data. Define Vi(d) as the set of nodes that can reach the control node i through at most d steps in the communication network. At the same time, define Gi(Gj) as the sub-network connected to node i (or j) in the communication network after the link between distributed power sources i and j is disconnected, and the average value of the obtained state quantity is:

[0114]

[0115] In the formula, w m is the initial assignment of the proportional factor parameter between nodes i and j, and z m is the initial assignment of the average marginal cost parameter between nodes i and j.

[0116] It should be noted that each node in the inter-network and intra-network communications here is each distributed power source.

[0117] Embodiment 3

[0118] The simulation example of the present invention uses a microgrid under hierarchical control for case analysis. The structure of the microgrid group is as Figure 2 shown. Build a topological model of the microgrid group system as Figure 3 shown on the MATLAB / Simulink simulation platform. Among them, each secondary control module in the system communication network is modeled based on the S-Function module in Simulink. In the physical layer of the system, each DG is set in a single-bus parallel mode, and the MG is connected in parallel to the inter-network common bus through each microgrid FAS. Among them, MG1 contains three DGs (DG 1 -DG 3 ), MG 2 contains three DGs (DG 4 -DG 6 ), MG 3 contains four DGs (DG 7 -DG 10 ), and all DGs are ideal inverter types. The information layer includes secondary power / frequency controllers, etc. Each distributed power source is configured with an agent to interact information with neighbor agents and eliminate frequency errors and perform economic distribution of active power through secondary control.

[0119] To verify the effectiveness of the proposed economic distributed coordination control strategy based on marginal cost, by setting different droop coefficients and cost coefficients for each DG, the diversity of DG types and the flexibility of scenarios in the microgrid group are fully reflected. The system components and control parameters in the multi-microgrids (MMG) and the cost coefficients of each DG are shown in Tables 1 and 2. The total running time of the simulation example is 5 s, where the system physical simulation step size T p = 50 μs, and the communication cycle T s = 3 ms.

[0120] Table 1

[0121]

[0122]

[0123] Table 2

[0124]

[0125] The simulation analysis of improving the economic operation of the system by considering the operating marginal cost through secondary control in this experiment is as follows: From 0 to 1 s at the beginning of the simulation, only droop control is used as the primary control for each DG in the MMG system, and the active power output of each DG is allocated according to different droop coefficients; at 1 s, the secondary control is put into the network. Each DG in each MG reaches the marginal cost consistency by exchanging its operating cost information using the Gossip algorithm, realizing the optimal economic operation of each DG within the MG; at 2 s, the inter-group control is put into the system again. The flexible interconnection device FAS between each MG is independently used as an Agent to transmit the average marginal cost information in the network for consistency iteration. Among them, FAS is only used as an inter-network information interaction Agent and has no own cost parameters. The output of each DG within the MG and the power transmission of each FAS between groups are adjusted through the new marginal cost information to realize the inter-group secondary control; at 3 s, a sudden load of 30 kW + 15 kVar is added to the MMG system, and the load exits at 4 s; the simulation ends at 5 s.

[0126] Through the calculation and analysis of the system operating cost under the control strategy of the present invention, Table 3 can be obtained:

[0127] Table 3

[0128]

[0129] As Figure 4 shown, from 0 to 1 s during the simulation operation, only droop control is used for each DG in the MMG system, and the operating frequencies of each MG are different and not operating at the rated frequency of 50 Hz. After 1 s, due to the addition of the secondary control in the network, the operating frequency of the MG returns to the rated value and as Figure 5 and 7As shown, the operating margins in each MG are iterated until they are consistent, and each DG in the network is adjusted to output active power according to the marginal cost. At this time, the inter-group secondary control is not involved. The system implements the inter-group secondary control at 2 - 3 s. Through the FAS, information interaction is realized to make the marginal costs of all DGs in the system consistent, and the active power output and the power flow between MGs are adjusted according to the marginal cost information. As Figure 5 shown, since the MG 2 has a relatively large marginal cost, and the MG 1 / MG 3 has a relatively small marginal cost, according to the inter-network control strategy, each DG in the MG 1 / MG 3 increases the power generation, and each DG in the MG 2 reduces the power output to meet the optimal economic operation of the MMG system; as Figure 6 shown, the increased power is positive and the decreased power is negative. At the inter-network FAS, the power flow direction is from FAS 3 →FAS 2 , FAS 1 →FAS 2 ; The MG 3 with the lowest marginal cost increases the most power, and the MG 1 follows. At 3 s, the system suddenly increases the load, and each DG adjusts its output power to continue to meet the optimal economic operation. At 4 s, the load exits the system and returns to normal until the end of the simulation. During the simulation, when the load changes, the system can still distribute the power output of each DG according to its consistent marginal cost and coordinate the power transmission changes between MGs through the FAS, effectively verifying the feasibility of the control strategy and the economy of the system regulation operation.

[0130] It should be noted that in the embodiments of the present invention, if the above-mentioned distributed coordinated control method for a microgrid group based on the Gossip algorithm is implemented in the form of software function modules and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the embodiments of the present invention, in essence, or the part that makes contributions to the 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 enable a terminal to execute all or part of the methods described in the embodiments of the present invention. The aforementioned storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROM, Read Only Memory), magnetic disks, or optical discs that can store program codes. In this way, the embodiments of the present invention are not limited to any specific combination of hardware and software.

[0131] Correspondingly, the embodiments of the present invention provide a distributed coordinated control device for a microgrid group based on the Gossip algorithm, Figure 8 which is a schematic diagram of the composition structure of the distributed coordinated control device for a microgrid group based on the Gossip algorithm provided by the embodiments of the present invention. AsFigure 8 As shown, the distributed coordinated control device 800 for a microgrid group based on the Gossip algorithm at least includes: a processor 801 and a computer-readable storage medium 802 configured to store executable instructions, where the processor 801 generally controls the overall operation of the distributed coordinated control device for the microgrid group based on the Gossip algorithm. 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 already processed by the processor 801 and each module in the distributed coordinated control device 800 for the microgrid group, and can be implemented by flash memory (FLASH) or random access memory (RAM, Random Access Memory).

[0132] An embodiment of the present invention provides a storage medium storing executable instructions, where the executable instructions, when executed by a processor, will cause the processor to execute the method provided by the embodiment of the present invention. For example, as Figure 1 shown in the method.

[0133] In some embodiments, the storage medium may be a computer-readable storage medium. For example, ferromagnetic random access memory (FRAM), read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), flash memory, magnetic surface memory, optical disc, or compact disk-read only memory (CD-ROM), etc.; it may also be various devices including one or any combination of the above memories.

[0134] In some embodiments, the executable instructions may be in 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 can be deployed in any form, including being deployed as an independent program or being deployed as a module, component, subroutine, or other unit suitable for use in a computing environment.

[0135] As an example, the executable instructions may or may not correspond to files in a file system, and may be stored as part of a file that holds other programs or data. For example, they may be stored in one or more scripts in a Hyper Text Markup Language (HTML) document, in a single file dedicated to the program under discussion, or in multiple cooperating files (such as files that store one or more modules, subroutines, or code portions). As an example, the executable instructions may be deployed to execute on one electronic device, or on multiple electronic devices located at one site, or on multiple electronic devices distributed across multiple sites and interconnected by a communication network.

[0136] As described above, the above are only embodiments of the present invention and are not intended to limit the protection scope of the present invention. Any modifications, equivalent replacements, and improvements made within the spirit and scope of the present invention are all included in the protection scope of the present invention.

[0137] It should be understood that the phrase "one embodiment" or "an embodiment" mentioned throughout the specification means that a specific feature, structure, or characteristic related to the embodiment is included in at least one embodiment of the present invention. Therefore, the phrases "in one embodiment" or "in an embodiment" that appear throughout the specification do not necessarily refer to the same embodiment. In addition, these specific features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. It should be understood that in various embodiments of the present invention, the sequence numbers of the above processes do not imply the order of execution. The order of execution of each process should be determined by its function and internal logic and should not constitute any limitation to the implementation process of the embodiments of the present invention. The sequence numbers of the embodiments of the present invention described above are only for description and do not represent the superiority or inferiority of the embodiments.

[0138] It should be noted that in this document, the term "comprising", "including" or any other variation thereof is intended to cover a non-exclusive inclusion, such that a process, method, or apparatus that includes a series of elements includes not only those elements but also other elements not expressly listed, or elements that are inherent to such process, method, or apparatus. Without further limitation, an element defined by the phrase "comprising a..." does not exclude the presence of additional identical elements in the process, method, article, or apparatus that includes the element. In several embodiments provided by the present 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 the units is only a logical functional division, and there may be other division methods in actual implementation. For example, multiple units or components can be combined, or integrated into another system, or some features can be ignored, or not executed.

[0139] As described above, it is only the specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention can easily think of changes or substitutions, which should all be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claimed rights.

Claims

1. A distributed coordinated control method for a microgrid group based on a Gossip algorithm, characterized in that: The method comprises: In the event of a disturbance in the microgrid, each distributed power source in droop control is initially controlled by the following formula to maintain the power balance of the microgrid; the formula is: In the formula, f i and U i They 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 active power reference value and reactive power reference value of the distributed power source respectively; K P and K Q They represent the frequency droop coefficient and voltage droop coefficient respectively; The average marginal cost parameter and frequency information of each microgrid are obtained through the distributed communication within the constructed distributed two-layer control architecture, and the preset Gossip consensus algorithm is used for secondary control to achieve economic distribution of active power and frequency stability of the microgrid; The average marginal cost information of neighboring microgrids is obtained through inter-grid and intra-grid distributed communication, and the preset Gossip consensus algorithm is used for secondary control to achieve active economic distribution among microgrids.

2. The method according to claim 1, characterized in that: The distributed communication in the network in the constructed distributed two-layer control architecture obtains the neighbor marginal cost information and frequency information, and adopts the preset Gossip consensus algorithm for secondary control to achieve active economic allocation and frequency deviation elimination, including: Obtaining cost parameters of each distributed power source in each microgrid through distributed communication within the network, and establishing a distributed power source power generation cost function based on the cost parameters; Based on the distributed power generation cost function, calculating the marginal cost parameter of each distributed power source; Based on a preset distributed algorithm and the marginal cost parameter, estimating an average marginal cost parameter of each of the microgrids; Based on the preset Gossip consensus algorithm, determining input parameters and frequency amplitude of a secondary controller applied to droop control; Based on applying secondary control, economical active power distribution and frequency stability of the microgrid are achieved.

3. The method according to claim 1, characterized in that The method of obtaining the average marginal cost information of neighboring microgrids through distributed communication and using the preset Gossip consensus algorithm for secondary control to achieve active economic distribution among microgrids includes: Through primary control between microgrids, the output of microgrids with high marginal operating costs is reduced, and the output of microgrids with low marginal operating costs is increased, so that the marginal operating costs of adjacent microgrids are consistent; Calculate the average marginal operating cost of each distributed power source between adjacent microgrids; the calculation formula is: Where G is the number of FAS, μ(n) is the average marginal cost difference between adjacent microgrids at time n, μ1(n) is the average marginal cost difference between adjacent microgrids of FAS1 at time n, μ2(n) is the average marginal cost difference between adjacent microgrids of FAS2 at time n, and μ G (n) is the FAS at time n G The average marginal cost difference of adjacent microgrids, L MG,α (P) and L MG,β (P) are the average marginal costs of microgrids α and β respectively; The average marginal operating cost is transmitted from the distributed power source to the FAS, and the primary control term of the FAS local VSC is: In the formula, is the primary control parameter of the FAS local VSC, μ is the average marginal cost deviation between adjacent microgrids, is the proportional parameter of the FAS primary control PI controller, is the integral parameter of the FAS primary control PI controller, and s is the Laplace operator; Based on the preset Gossip consensus algorithm iteration, calculate the total marginal cost of the microgrid group; The microgrid group control is realized by adding a secondary control item to the local VSC, based on the local secondary control item of FAS; the local VSC secondary control item is expressed as: In the formula, is the FAS local VSC secondary control parameter, is the proportional parameter of the secondary control PI controller, is the integral parameter of the quadratic control PI controller, s is the Laplace operator, μ(n) is the average marginal cost difference between adjacent microgrids at time n, is the total operating marginal cost error value; Based on the power transmission control of the local microgrid by the bidirectional VSC in the FAS, the control tasks among the overall microgrid group are achieved by constructing FAS secondary control items and exchanging status information with adjacent FASs, so as to achieve the goal of allocating active power according to marginal cost.

4. A distributed coordination control device for a microgrid group based on a Gossip algorithm, characterized in that: The device comprises: The primary control module is used to perform primary control on each distributed power source of the droop control by the following formula to maintain the power balance of the microgrid when a disturbance occurs in the microgrid; the formula is: In the formula, f i and U i They 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 active power reference value and reactive power reference value of the distributed power source respectively; K P and K Q They represent the frequency droop coefficient and voltage droop coefficient respectively; A secondary control module is used to obtain the average marginal cost parameter and frequency information of each microgrid through the distributed communication within the constructed distributed two-layer control architecture, and to perform secondary control using a preset Gossip consensus algorithm to achieve economic distribution 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 microgrids through distributed communication combined between networks and within networks, and use the preset Gossip consensus algorithm to perform secondary control to achieve active economic distribution between microgrids.

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

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 a microgrid group based on a Gossip algorithm as described in any one of claims 1 to 3.

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