CN116345430B - Synchronous oscillation finite time function projection control method for micro-grid - Google Patents
Synchronous oscillation finite time function projection control method for micro-grid Download PDFInfo
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
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- H—ELECTRICITY
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- H—ELECTRICITY
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- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/381—Dispersed generators
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- H—ELECTRICITY
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- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
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Abstract
The invention discloses a synchronous oscillation finite time function projection control method of a micro-grid, which comprises the following steps: establishing a distributed hierarchical control micro-grid structure; establishing a hierarchical control nonlinear dynamic model of the micro-grid according to the hierarchical control micro-grid structure; combining the small-world network model with the micro-grid hierarchical control nonlinear dynamic model to obtain a micro-grid small-world network model; analyzing and obtaining system oscillation factors caused by asynchronous nodes in the micro-grid small-world network according to the micro-grid small-world network model; analyzing and obtaining a system oscillation mechanism according to oscillation factors; according to the system oscillation mechanism, the micro-grid chaotic synchronization is realized by adopting a finite time function projection control method. By the method, synchronization of the micro-grid small-world network nodes can be realized rapidly, and therefore oscillation of the system is avoided.
Description
Technical Field
The invention belongs to the field of stable operation of new power sources, and particularly relates to a synchronous oscillation limited time function projection control method of a micro-grid.
Background
Along with the protrusion of new energy, the requirements on the electric energy quality of the electric power source are very high. The micro-grid can effectively solve the requirements of renewable energy power generation utilization rate, improving power supply reliability, meeting the flexibility and diversity of users and the like on the medium-low voltage level. However, the coupling degree between micro sources in the micro power grid is high, and the conditions of multiple types, multiple loads, interaction on multiple time scales and the like exist, so that the system is easy to generate oscillation phenomenon, and serious harm is caused to the safety and stability of the micro power grid.
At present, researches at home and abroad mainly focus on the aspect of a state space method aiming at the synchronization problem of a micro-grid system. The state space method is to divide a micro-grid according to the topological structure of a new energy power system, determine the constitution form of a single distributed power generation unit in the micro-grid, establish the connection parameters and variables of the distributed power generation unit and the micro-grid at a public coupling port, then determine the state variables and input variables of the system based on the distributed power generation unit and the micro-grid system structure, respectively obtain state space equations corresponding to basic loops and different paths in the micro-grid, and analyze the system stability based on the determined state space equations. The state space method has better research on the linear system, and in practical engineering application, a plurality of inverter nodes are connected into a network form according to a certain topology, so that more complex dynamic behaviors exist, and the stability and reliability requirements on the micro-grid are higher. Some new research results show that shortcuts in the small world network allow network synchronization performance to be enhanced, as the small world network can well describe the real world complex network. Micro-grid is used as a topological network structure of electric power energy, and has small world network characteristics in a complex network. Therefore, the realization of synchronization of nodes in a micro-grid complex small-world network is an important problem for avoiding system breakdown.
The control response time is relatively complex or not considered in the control design of the micro-grid system at present. The research on node synchronization and chaotic behavior of the micro-grid is particularly important, and corresponding control strategies are provided in a targeted manner. The control of the system using the finite time stabilization principle is more studied, but is less applied in the control of micro-grids.
In summary, how to describe the chaotic synchronization behavior of the current micro-grid complex network, and provide a corresponding synchronization control strategy in a targeted manner, which is a technical problem to be solved in the aspect of ensuring the safe and stable operation of the power grid.
Disclosure of Invention
In view of the above problems, the present invention provides a method for controlling projection of a synchronous oscillation finite time function of a micro-grid, which at least solves some of the above technical problems, and by using the method, synchronization of network nodes of a micro-grid small world can be rapidly achieved, so as to avoid oscillation of a system. .
The embodiment of the invention provides a synchronous oscillation finite time function projection control method of a micro-grid, which comprises the following steps:
s1, establishing a distributed hierarchical control micro-grid structure;
s2, establishing a hierarchical control nonlinear dynamic model of the micro-grid according to the hierarchical control micro-grid structure;
s3, combining the small-world network model with the micro-grid hierarchical control nonlinear dynamic model to obtain a micro-grid small-world network model;
s4, analyzing and obtaining system oscillation factors caused by asynchronization of all nodes in the micro-grid small-world network according to the micro-grid small-world network model;
s5, analyzing and obtaining a system oscillation mechanism according to the oscillation factors;
and S6, according to the system oscillation mechanism, adopting a finite time function projection control method to realize the chaotic synchronization of the micro-grid.
Further, the step S1 specifically includes: dividing the micro-grid into a primary control layer, a secondary control layer and a tertiary control layer by adopting a distributed layered control structure;
the primary control layer is used for locally controlling the distributed units;
the secondary control layer is used for correcting power, voltage and frequency offset when the time scale exceeds a preset value after the primary control layer is stabilized;
the third control layer is used for global optimization of the micro-grid, management of the micro-grid and work output of the micro-grid.
Further, each distributed power generation unit comprises an independent primary control layer and secondary control layer.
Further, the micro-grid hierarchical control nonlinear dynamic model is expressed as:
wherein i is 0 Representing a direct current input current; i.e 1 Representing inductance L 1 A terminal outputs a current; i.e 2 Representing inductance L 2 A terminal outputs a current; u (U) C1 Representing capacitance C 1 The two ends output voltage; u (U) C2 Representing capacitance C 2 The two ends output voltage; s represents the switch of the DC/AC converter; r is R 1 And R is 2 All represent filter resistance, R L Representing the load equivalent resistance.
Further, the micro-grid small world network model is expressed as:
wherein x is j A state variable representing node j; when a is ij =1 means that node i is coupled to node j; c represents coupling strength; n represents the number of nodes in the network; h is an in-coupling matrix in the micro-grid small-world network model; h=diag (r) 1 ,r 2 ,r 3 ,r 4 ) Diag () represents a diagonal matrix, r n =1 indicates that there is a coupling between the nth state variables of the two nodes.
Further, the step S4 specifically includes:
aiming at the influence degree of parameters on the synchronization time, a variance is introduced to describe the synchronization condition of a micro-grid small-world network model, which is specifically expressed as:
wherein x is im A state variable representing an mth node in the network;representing the state variable average value of the mth node of the network; n represents the number of nodes in the network; sigma (sigma) m The smaller the value, the higher the network synchronization degree is indicated; sigma (sigma) m =0, then this indicates that the network is fully synchronized;
aiming at different network structures, according to different probability values, under the condition that the number of nodes in the network is the same, analyzing the influence of the different network structures on the oscillation of the micro-grid system;
based on the micro-grid small-world network model, the influence of different parameters on the oscillation of the micro-grid system is analyzed.
Further, the step S5 specifically includes: and based on the micro-grid small world network model, external noise interference is applied to the system, and the self synchronous control and regulation capacity of the system is judged.
Compared with the prior art, the synchronous oscillation limited time function projection control method of the micro-grid has the following beneficial effects:
the invention establishes a nonlinear dynamic model of hierarchical control of the micro-grid, and analyzes the system oscillation phenomenon caused by the asynchronism of each node in the micro-grid small-world network based on the micro-grid small-world network model. Then, aiming at asynchronous oscillation caused by interference of external noise and the like of the system, a finite time function projection control method is provided for realizing chaotic synchronization of the micro-grid, and synchronization of network nodes of the micro-grid small world can be realized rapidly, so that oscillation of the system is avoided, and a theoretical basis is provided for realizing synchronous control of the micro-grid.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims thereof as well as the appended drawings.
The invention will be further described in detail with reference to the drawings and detailed description, in order to make the objects, features and advantages of the invention more apparent.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
fig. 1 is a schematic flow chart of a synchronous oscillation finite time function projection control method of a micro-grid according to an embodiment of the present invention.
Fig. 2 is a schematic diagram of a micro grid system connection according to an embodiment of the present invention.
Fig. 3 is a schematic diagram of a micro-grid small world network topology structure according to an embodiment of the present invention.
FIG. 4 (a) shows a variable x in a rule network according to an embodiment of the present invention i4 Variance diagram.
FIG. 4 (b) shows a variable x in a rule network according to an embodiment of the present invention i4 And synchronizing the graphs.
FIG. 5 (a) is a diagram of a variable x in a small world network according to an embodiment of the present invention i4 Variance diagram.
FIG. 5 (b) is a diagram of a variable x in a small world network according to an embodiment of the present invention i4 And synchronizing the graphs.
Fig. 6 is a graph showing a probability change of synchronization time according to an embodiment of the present invention.
FIG. 7 (a) shows the variable x before and after disturbance in the small world network according to the embodiment of the present invention i4 Variance diagram.
FIG. 7 (b) shows the variable x before and after disturbance in the small world network according to the embodiment of the present invention i4 And synchronizing the graphs.
FIG. 8 (a) shows a variable x before and after the synchronous controller control according to an embodiment of the present invention i4 Variance diagram.
FIG. 8 (b) shows a synchronous controller for controlling the front-to-back variation according to an embodiment of the present inventionQuantity x i4 Synchronous diagram
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
Referring to fig. 1, the embodiment of the invention provides a synchronous oscillation finite time function projection control method of a micro-grid, which specifically comprises the following steps:
s1, establishing a distributed hierarchical control micro-grid structure;
s2, establishing a hierarchical control nonlinear dynamic model of the micro-grid according to the hierarchical control micro-grid structure;
s3, combining the small-world network model with the micro-grid hierarchical control nonlinear dynamic model to obtain a micro-grid small-world network model;
s4, analyzing and obtaining system oscillation factors caused by asynchronization of all nodes in the micro-grid small-world network according to the micro-grid small-world network model;
s5, analyzing and obtaining a system oscillation mechanism according to the oscillation factors;
and S6, according to the system oscillation mechanism, adopting a finite time function projection control method to realize the chaotic synchronization of the micro-grid.
The above steps are described in detail below.
In the step S1, according to the structural features and control principles of the micro-grid shown in fig. 2, the micro-grid is divided into a first-layer control, a second-layer control and a third-layer control by adopting a distributed layered control structure; wherein each layer of control has respective implementation functions: the primary control layer is mainly limited to the local control of the distributed units, so that the system variable can track the set value of the system variable at the fastest response speed; the secondary control layer corrects the power, voltage and frequency offset under a longer time scale by adjusting the set value of the distributed generation unit after the primary control is stable; the third control layer is mainly responsible for global optimization of the micro-grid, management of the micro-grid and work output of the micro-grid;
in distributed hierarchical control, each distributed power generation unit is provided with a primary control layer and a secondary control layer which are independent, and the primary control layer and the secondary control layer are combined together and embedded in each distributed power generation unit; the secondary control layer collects data required by the primary control layer, corrects power, voltage and frequency deviation by adjusting a set value of DG, generates a proper reference control signal and transmits the proper reference control signal to the primary control layer, so that information delay and congestion caused by overlarge data and the like caused by centralized control are avoided, the communication bandwidth is reduced, and the control is more economical and simple, the reliability is high, and the information sharing is easy; finally, the secondary control layers of each distributed power generation unit are linked through network communication, so that control networking is realized, and meanwhile, the connection between field control and upper management is enhanced. Therefore, the micro-grid is very beneficial to the operation of accessing the micro-grid into the power distribution network under the combined action of three layers of control; based on the above, the embodiment of the invention eliminates the deviation of system parameters and the problems of load and communication distribution among nodes through distributed hierarchical control.
In the step S2, in order to describe that the micro-grid system has significant randomness, multiple scales, multiple couplings and strong time variability, a nonlinear dynamic characteristic model of the micro-grid is built according to fig. 3:
wherein i is 0 Representing a direct current input current; i.e 1 Representing inductance L 1 A terminal outputs a current; i.e 2 Representing inductance L 2 A terminal outputs a current; u (U) C1 Representing capacitance C 1 The two ends output voltage; u (U) C2 Representing capacitance C 2 The two ends output voltage; s represents the switch of the DC/AC converter; r is R 1 And R is 2 All represent the filter resistance in the line, R L Representing the load equivalent resistance in the line；
Wherein I is ph Indicating photocurrent; i S Representing the saturation current; ns represents the number of units of the internal module; t represents the module temperature; a represents a diode management thinking factor; r is R sh Representing shunt resistance; a, a 0 、a 1 、a 2 And a 3 All represent polynomial fitting coefficients; q represents a basic charge of (1.60217657X 10-19); k represents a Boltzmann constant (1.3806488 ×10-23); n is n p And n s All represent photovoltaic coefficients, in the embodiment of the invention, n is taken p ＝6，n s ＝15。
In the step S3, according to the characteristics of synchronous control of the complex network, the small-world network model and the hierarchical control nonlinear dynamic model of the micro-grid are combined, which specifically includes:
(1) Network model analysis:
in fig. 3, the small world network is a network model between the regular network and the global coupling network, and through the random reconnection process between the nodes, the relationship between the small world network and the regular network and the random network can be clearly shown, and fig. 3 shows 3 network topologies of 20 nodes, namely the regular network, the small world network and the random network, when the random reconnection probability p=0, the network is a ring-shaped regular network topology; when the random reconnection probability p=1, the network is an irregular random network topology; when the random reconnection probability is 0< p <1, the network structure is a small-world network topology.
(2) Combination of small world network model and micro-grid hierarchical control nonlinear dynamic model:
according to the characteristics of the synchronous control of the complex network in fig. 3, for not losing generality and considering the same characteristics of the micro-grid and the small-world network topology model, the micro-grid small-world network model is obtained by combining the complex network-small-world network model and the micro-grid hierarchical control nonlinear dynamic model (i.e. the micro-grid topology model):
wherein x is j A state variable representing node j; its proximity coupling rule network matrix a n ＝(a ij )∈R N×N Constructing a small world network model, and comparing and analyzing the adjacent regular network and the small world network; when a is ij =1 means that node i is coupled to node j; c represents coupling strength; n represents the number of nodes in the network; h is an in-coupling matrix in the micro-grid small-world network model; h=diag (r) 1 ,r 2 ,r 3 ,r 4 ) Diag () represents a diagonal matrix, r n =1 indicates that there is a coupling between the nth state variables of the two nodes.
In the step S4, based on the micro-grid small-world network model, when all nodes in the micro-grid small-world network are not synchronous, analyzing factors causing system oscillation, and adopting system parameter control to achieve synchronous node solving; the method specifically comprises the following steps:
(1) Synchronous quantitative analysis:
aiming at the influence degree of parameters on the synchronization time, variance is introduced to describe the synchronization condition of the micro-grid small-world network model, and the expression is as follows:
wherein x is im A state variable representing an mth node in the network;representing the state variable average value of the mth node of the network; n represents the number of nodes in the network; sigma (sigma) m The smaller the value, the higher the network synchronization degree is indicated; sigma (sigma) m =0, then this indicates that the network is fully synchronized.
2) Analyzing the influence of the network structure:
aiming at different network structures, according to different values of the probability p, under the condition that the number N of nodes in the network is the same, analyzing the influence of the different network structures on the oscillation of the micro-grid system; if the network structures are different, the number of nodes is the same, that is, the network probability p influences the oscillation of the micro-grid system, and the smaller the probability p is, the longer the synchronization time is, and the longer the oscillation time is.
3) Analysis of the influence of parameters
For different parameters (coupling coefficient, control parameter, node number, network model probability and the like), based on the micro-grid small-world network model, the influence of the different parameters on the micro-grid system oscillation is analyzed.
In the step S5, based on the micro-grid small-world network model, external noise and other interference are applied to the system, and the self synchronous control and adjustment capability of the system is determined; the system synchronous control is to judge the influence capability of the coupling coefficient on the synchronous performance through the adjustment of the coupling coefficient; if the coupling coefficient is changed, the system can be synchronized under the condition of external interference, and the system has synchronous control and adjustment capability; if the system receives external interference and the coupling coefficient is adjusted, the system cannot be restored to synchronization, and the system parameters do not have synchronous control and adjustment capability. The synchronous control and adjustment capability of the system is that the system itself adjusts parameters, so as to judge whether the system variables can be synchronized; the oscillation mechanism is a phenomenon, and whether the system oscillates or synchronizes is reflected through the oscillation mechanism. For example, the coupling coefficients are different in value, and the system is stable in value within a certain range; and if the value exceeds the stable range, the system oscillates. For another example, if the probabilities p of the network models of the systems are different, the synchronization time of the systems is different, so that the non-synchronization is that the nodes will oscillate, and the mechanism is that the smaller the network model or the probability p is, the worse the synchronization performance is, and the easier the oscillation is.
The overall dynamic equation of the system disturbance micro-grid small world network can be expressed as:
the formula shows that the micro-grid small world network model applies external interference, whereinRepresenting a micro-grid small world network model; WG (Crystal growth promoting) i Representing external interference; w represents a disturbance matrix, and the disturbance factor may be represented as w=diag (f 1 ,f 2 ,f 3 ,f 4 )；G i Representing the disturbance signal.
In the above step S6, the finite time stabilization theory means that the unstable system is controlled to a stable state in a short time. Finite time stable control is a method that enables effective control of a nonlinear system, allowing controlled system variables to converge to equilibrium points in a finite time. In the embodiment of the invention, in order to solve the problem of system non-synchronization caused by node disturbance and the like, a chaotic synchronization control method in a nonlinear system is provided based on a finite time stabilization theory and a chaotic synchronization thought (namely a Lyapunov stabilization theory); the method aims at the synchronous error to design a controller u, and the state synchronous error of a driving system and a response system is 0 in a limited time; the method specifically comprises the following steps:
i in the above 1 、i 2 、U C1 And U C2 The variable value to be regulated is the response system value; let the values of these four variables at the balance point be i respectively 10 、i 20 、U C10 And U C20 ；
Selecting a balance point with s (t) as an isolated node as a driving system, wherein the balance point is as follows:
the system is selected to be in a chaotic running state as a response system, and the following steps are adopted:
wherein u is 1 、u 2 、u 3 And u 4 All representing the controller to be designed, the finite time function projects a synchronization error such asThe following steps:
wherein x and y both represent state vectors; u represents a controller;representing a driving system, alpha (t) representing a scale function; />Representing the derivative of the scale function; />Representing the response system of the application controller, f (x) and g (y) each represent a nonlinear differentiable function; the synchronization error is expressed as:
the appropriate controller u is designed to make the synchronization error 0, i.eThe driving system and the response system achieve function projection synchronization.
The controller is designed as follows, so that the system can realize the projection synchronous control of the finite time function:
wherein k represents the control coupling strength; beta represents a controller parameter; e, e β Indicating the elimination of high-order anti-interference performance.
If there is a time t * The errors of the chaotic system and the stabilizing system are satisfied as follows:
the chaotic system and the stabilizing system achieve synchronization within a limited time.
In order to verify the feasibility of the method, the micro-grid network and the micro-grid are combined together according to the nonlinear dynamics characteristic of the micro-grid with the layered control structure, and the micro-grid network synchronous oscillation characteristics under the external noise interference and the synchronous controller are respectively analyzed, so that the accuracy of theoretical analysis is verified. The main parameters and the control parameters are selected as shown in tables 1 and 2.
TABLE 1 Main parameters
TABLE 2 control parameters
Firstly, synchronously analyzing a micro-grid small world network:
in the micro-grid small world network model, taking network nodes N=200, c=500, H=diag (0, 1), the degree m=4, the integral step h=0.0000001 and the small world network p=0.7, and calculating the maximum eigenvalue λmax= -1.8x10-13 of the coupling matrix An by adopting a numerical method<0[30]Indicating that the network is synchronizable, taking the variable x in the node i4 The analysis was performed as follows.
Referring specifically to fig. 4 and 5, fig. 4 and 5 show the variable x of N nodes i4 The variance and synchronization map of (a) and (b) of fig. 4 are the synchronization cases of a regular network, the variable x to the node in fig. 4 (a) i4 Variance is made, and the variables of 200 nodes reach synchronization at 0.3s when σ=0; FIG. 4 (b) corresponds thereto, and it can be seen that a plurality of node variables x i4 The amplitude and phase are consistent at 0.3s. FIGS. 5 (a) and 5 (b) are synchronous cases of a small world network, and similarly, FIG. 5 (a) is a graph of variable x for nodes i4 Variance is made, the node variables reach synchronization at 0.07sFig. 5 (b) corresponds thereto. As can be seen by comparing fig. 4 (a) with 5 (a), the synchronization performance of the small-world network is better than that of the regular network.
Fig. 6 is a graph of the fit of the synchronization time to the probability change in the network, and in fig. 6, the comparison of fig. 4 and 5 is analyzed, and when the small world network p=0.7, the system synchronization time is about 0.07s; when the network is a regular network, the system is not easy to synchronize, and the synchronization time is about 0.3s. It can be seen that the larger the probability p, the shorter the network synchronization time.
Secondly, synchronously controlling and analyzing the external disturbance of the micro-grid small-world network:
disturbance is applied to the micro-grid small world network model, and the variable x in N nodes is also applied to i4 Analysis was performed taking w=diag (1, 1), perturbation function G i When t=0.3 s, a disturbance was applied to 200sin (wt), and the results before and after the disturbance are shown in the figure.
As can be seen from FIG. 7 (a), before 0.3s, each node of the micro-grid small world network can be enabled to be variable x by adjusting the coupling strength coefficient due to the influence of the coupling relation i4 The variance of (2) is 0, i.e., each node achieves synchronization. After 0.3s, the system variance oscillates within a certain range due to the strong signal disturbance applied, thus it is seen that the variables of the individual nodes have not been synchronized by the control of the coupling strength coefficients. Comparing with FIG. 7 (a), the corresponding node variables x are obtained i4 As shown in FIG. 7 (b), the node variables tended to synchronize from inconsistency before 0.3s, and the nodes were clearly out of sync after 0.3s of the applied disturbance.
In order to solve the defect of the self parameter adjustment of the system, a finite time function projection synchronous control algorithm is adopted, the algorithm effectively compensates the defect of the self parameter adjustment of the system, and synchronous control is well realized, and the result is shown in fig. 8.
Aiming at the phenomenon that the system is unstable due to the fact that physical parameters of all nodes in the micro-grid are out of synchronization to cause oscillation, the embodiment of the invention takes the micro-grid with a layered control structure as a research object, and provides a novel micro-grid synchronous oscillation characteristic and a limited time function projection synchronous control method based on a chaos synchronous thought and a limited time theory. Firstly, a nonlinear dynamic model of hierarchical control of a micro-grid is established, and based on a micro-grid small-world network model, system oscillation phenomenon caused by asynchronism of all nodes in the micro-grid small-world network is analyzed. Then, a new finite time function projection synchronous control method is provided for asynchronous oscillation caused by interference of external noise and the like of the system, synchronization of network nodes of the micro-grid small world can be rapidly achieved, and therefore oscillation of the system is avoided, and theoretical basis is provided for synchronous control of the micro-grid.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (5)
1. The utility model provides a synchronous oscillation finite time function projection control method of a micro-grid, which is characterized by comprising the following steps:
s1, establishing a distributed hierarchical control micro-grid structure;
s2, establishing a hierarchical control nonlinear dynamic model of the micro-grid according to the hierarchical control micro-grid structure;
s3, combining the small-world network model with the micro-grid hierarchical control nonlinear dynamic model to obtain a micro-grid small-world network model;
s4, analyzing and obtaining system oscillation factors caused by asynchronization of all nodes in the micro-grid small-world network according to the micro-grid small-world network model;
s5, analyzing and obtaining a system oscillation mechanism according to the oscillation factors;
s6, according to the system oscillation mechanism, adopting a finite time function projection control method to realize the chaotic synchronization of the micro-grid;
the micro-grid hierarchical control nonlinear dynamic model is expressed as:
wherein i is 0 Representing a direct current input current; i.e 1 Representing inductance L 1 A terminal outputs a current; i.e 2 Representing inductance L 2 A terminal outputs a current; u (U) C1 Representing capacitance C 1 The two ends output voltage; u (U) C2 Representing capacitance C 2 The two ends output voltage; s represents the switch of the DC/AC converter; r is R 1 And R is 2 All represent filter resistance, R L Representing the load equivalent resistance;
the micro-grid small world network model is expressed as:
wherein x is j A state variable representing node j; when a is ij =1 means that node i is coupled to node j; c represents coupling strength; n represents the number of nodes in the network; h is an in-coupling matrix in the micro-grid small-world network model; h=diag (r) 1 ,r 2 ,r 3 ,r 4 ) Diag () represents a diagonal matrix, r n =1 represents that there is a coupling between the nth state variables of the two nodes;
the controller is designed as follows, so that the system can realize the projection control of the finite time function:
wherein k represents the control coupling strength; beta represents a controller parameter; e, e β The high-order anti-interference performance is eliminated;
if there is a time t * The errors of the chaotic system and the stabilizing system are satisfied as follows:
the chaotic system and the stabilizing system are synchronized within a limited time;
wherein i is 10 、i 20 、U C10 And U C20 Respectively represent i 1 、i 2 、U C1 And U C2 A value at the equilibrium point;and->Respectively represent i 1 、i 2 、U C1 、U C2 、i 10 、i 20 、U C10 And U C20 Is a derivative of (2); u (u) 1 、u 2 、u 3 And u 4 All represent controllers to be designed; α (t) represents a scale function; />Representing the derivative of the scale function; e, e 1 、e 2 、e 3 And e 4 U respectively 1 、u 2 、u 3 And u 4 Error of (2); y (t) represents a state vector at the time t; n represents the number of nodes in the network.
2. The method for controlling projection of synchronous oscillation finite time function of micro-grid according to claim 1, wherein S1 specifically comprises: dividing the micro-grid into a primary control layer, a secondary control layer and a tertiary control layer by adopting a distributed layered control structure;
the primary control layer is used for locally controlling the distributed units;
the secondary control layer is used for correcting power, voltage and frequency offset under preset conditions after the primary control layer is stable; the preset condition is that the time scale exceeds a preset value;
the third control layer is used for global optimization of the micro-grid, management of the micro-grid and work output of the micro-grid.
3. The method for controlling projection of synchronous oscillation finite time function of micro-grid according to claim 2, wherein: each distributed power generation unit comprises an independent primary control layer and secondary control layer.
4. The method for controlling projection of synchronous oscillation finite time function of micro-grid according to claim 1, wherein S4 specifically comprises:
aiming at the influence degree of parameters on the synchronization time, a variance is introduced to describe the synchronization condition of a micro-grid small-world network model, which is specifically expressed as:
wherein x is im A state variable representing an mth node in the network;representing the state variable average value of the mth node of the network; n represents the number of nodes in the network; sigma (sigma) m The smaller the value, the higher the network synchronization degree is indicated; sigma (sigma) m =0, then this indicates that the network is fully synchronized;
aiming at different network structures, according to different probability values, under the condition that the number of nodes in the network is the same, analyzing the influence of the different network structures on the oscillation of the micro-grid system;
based on the micro-grid small-world network model, the influence of different parameters on the oscillation of the micro-grid system is analyzed.
5. The method for controlling projection of synchronous oscillation finite time function of micro-grid according to claim 1, wherein the step S5 specifically comprises: and based on the micro-grid small world network model, external noise interference is applied to the system, and the self synchronous control and regulation capacity of the system is judged.
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