CN113741190B - Microgrid distributed power supply enclosure control method and device based on directed topology network - Google Patents
Microgrid distributed power supply enclosure control method and device based on directed topology network Download PDFInfo
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Abstract
The method introduces a directed network topology idea into information interaction of distributed power supplies in a microgrid, constructs a second-order dynamical system model of the distributed power supplies to model the power supply state, further establishes a state error system equation of the microgrid system, and simultaneously introduces power supply noise
And analyzing the state error system equation and the performance index function by utilizing the Lyapunov stability theory to obtain a stability condition and a disturbance suppression condition, so that a control gain coefficient capable of realizing the stability of the microgrid system can be obtained by solving the stability condition and the disturbance suppression condition.
Description
Technical Field
The application relates to the technical field of micro-grids, in particular to a micro-grid distributed power supply enclosure control method and device based on a directed topology network.
Background
With the continuous development of smart power grids and power electronic technologies, micro-grid systems gradually become a new direction for the development of related fields of power grids. The microgrid system is a power grid system formed by a plurality of distributed power sources and related loads according to a certain topological structure, wherein various power generation technologies such as wind power generation, photovoltaic power generation and the like can be integrated, and the microgrid system can be specifically formed by the distributed power sources, the loads, an energy storage device, an energy conversion device, a control device and the like.
In the operation process of the distributed power supplies, noise interference in the operation environment can be caused, so that unstable fluctuation of state parameters such as frequency and voltage in each distributed power supply is caused, and the group consistency of the micro-grid is damaged.
In some tasks, part of power supplies in the microgrid system need to maintain state parameters such as different voltages and frequencies, and the like, and then a part of power supply signals have consistency A, and the other part of power supply signals are distributed and form consistency B around A. Correspondingly, different group consistencies in the micro-grid system can be regarded as the enclosure of one part of power supply signals to the other part of power supply signals, the mode is favorable for group control of the micro-grid, and a special expected task target is realized.
Therefore, how to perform appropriate distributed enclosure control on the whole microgrid system to meet the enclosure control of group consistency of the microgrid system enables each distributed power supply in the microgrid system to reach an expected state, that is, a power supply group can generate an expected signal in the enclosed state, and the actual requirements of construction and operation of the microgrid are better met, so that the problem that group consistency in the microgrid system needs to be considered in the field is urgently needed.
Disclosure of Invention
In order to realize the enclosure control of group consistency in a microgrid system, the embodiment of the application provides a microgrid distributed power supply enclosure control method and device based on a directed topology network. The technical scheme is as follows:
in a first aspect, an embodiment of the present application provides a microgrid distributed power supply enclosure control method based on a directed topology network, where the method includes:
dividing all distributed power supplies in the micro-grid system into n leader power supplies and m follower power supplies, and generating an information interaction relation between the distributed power supplies by utilizing a directed topology network;
according to a preset power supply expected model, the internal state X of each distributed power supplyiAnd constructing each point in the information interaction relationControl input equation u for each of the distributed power sourcesiSaid control input equation uiIncluding the control gain factor to be solved;
establishing a second-order dynamic system model of each distributed power supply and a state error system equation of the micro-grid system relative to the power supply expected model;
an output voltage Y for each of the distributed power suppliesi(t) and bounded noise disturbance wi(t) introduction of l2-l∞Performance index function of
Analyzing the state error system equation and the performance index function respectively through a Lyapunov stability theory to generate a stability control condition and a disturbance suppression condition of the micro-grid system;
solving a control input equation of each distributed power supply by using the stability condition and the disturbance suppression condition of the microgrid system to obtain a control gain coefficient corresponding to the distributed power supply;
loading the control gain factor into a controller of each of the distributed power sources to cause the controller to control each of the distributed power sources according to the control gain factor.
Based on the technical scheme, the distributed power supply state of the micro-grid system is modeled, the cooperative control gain coefficient among the distributed power supplies is obtained through mathematical analysis, and the distributed power supplies can be accurately controlled in real time by using the power controller, so that the group consistency of the micro-grid system can be effectively realized.
Optionally, the generating, by using a directed topology network, an information interaction relationship between the distributed power supplies includes:
setting all the distributed power supplies as nodes in a directed topology network by using the knowledge of graph theory;
generating an adjacency matrix A ═ α of the directed topology networkij]Wherein i and j are adjacent distributed power sourcesI, j ═ 1, 2., n + m, element αij1 indicates that information interaction exists between the ith distributed power supply and the jth distributed power supply, and the element alphaij0 means that there is no information interaction between the ith distributed power source and the jth distributed power source.
Based on the technical scheme, the graph theory knowledge is utilized, the directed network topology idea is introduced into the information interaction of the distributed power supplies in the micro-grid system, the fact that any new power supply can be started in real time after being merged into the micro-grid is guaranteed, plug and play of the micro-grid system in the grid connection process is achieved, and the actual requirements of micro-grid system construction are met better.
Optionally, the internal state X of each distributed power supply according to a preset power supply expectation modeliConstructing a control input equation u of each distributed power supply according to the information interaction relationiThe method comprises the following steps:
loading a preset power supply expected model, wherein the power supply expected model comprises an expected state change equation
And desired output voltage equation Y0(t)＝CX0(t) wherein X0To a desired power state, r0For desired control input, Y0For the desired output voltage, A, B, C are the adaptive system matrix,
e is the power supply capacitance value, S is the voltage load regulation effect coefficient, R is the maximum active power, and C is 10]；
Based on the adjacency matrix A ═ alphaij]Internal state X of each of the leader power suppliesiAnd said X0Constructing a neighbor error equation for each of the leader power sources
Constructing a control input equation u for each leader power supply based on the neighbor error equation for each leader power supplyi＝K1εi+ Γ r, where i ═ 1,2, ·, n, K1F is the control gain to be solved;
based on the adjacency matrix A ═ alphaij]Internal state X of each follower power supplyiAnd said X0Constructing a neighbor error equation for each of the follower power sources
Constructing a control input equation of each follower power supply based on a neighbor error equation of each follower power supply
Wherein i is n +1, n +2,.., n + m; k2Γ is the control gain to be solved;
inverse matrix L being Laplace matrix L-1Ith row in the matrix
Column elements, the Laplace matrix L ═ degree matrix D-the adjacency matrix A, the degree matrix
Based on the technical scheme, the control input equations of the leader power supply and the follower power supply are established by utilizing the information interaction relation between the distributed power supply and other distributed power supplies, the power supply state of each distributed power supply and the preset power supply expectation model, so that the control input equations can be matched with the real requirements of the follower power supply.
Optionally, the establishing a second-order dynamical system model of each distributed power supply includes:
on a per basisInternal state X of the distributed power supplyiAmount of change in state
Bounded noise disturbance wiAnd the control input equation uiAnd establishing a second-order dynamic system model of each distributed power supply.
Based on the technical scheme, the complex state inside the distributed power supply can be modeled by establishing a second-order dynamic system model, so that the subsequent state change of the distributed power supply can be quickly and effectively analyzed.
Optionally, the internal state X based on each distributed power supplyiAmount of change in state
Bounded noise disturbance wiAnd the control input equation uiEstablishing a second-order dynamical system model of each distributed power supply, wherein the second-order dynamical system model comprises the following steps:
based on internal state X of each distributed power supplyiAmount of change in state
Constructing an internal state augmentation vector X for a distributed power supplyi(t)；
Internal state augmentation vector X based on distributed power supplyi(t) bounded noise interference vector wi(t) and the control input equation ui(t) establishing a state change equation of the distributed power supply
Wherein,
the superscript T denotes transpose, an
E is the power supply capacitance, S is the voltage load regulation effect coefficient, RIn order to be the maximum active power,
establishing a voltage output equation Y of the distributed power supply based on a state change equation of the distributed power supplyi(t)＝CXi(t), wherein C ═ 10]。
Based on the technical scheme, the state quantity and the state variation of the distributed power supply are fully considered, the state influence of input and noise interference on the distributed power supply is controlled, and the fact that a second-order dynamic system model is constructed to be more consistent with the actual state of the distributed power supply in the micro-grid system can be guaranteed.
Optionally, establishing a state error system equation of the microgrid system relative to the power source expectation model includes:
constructing a state error system equation of all leader power supplies in the micro-grid system relative to the power supply expectation model based on the neighbor error equation of each leader power supply
Constructing a state error system equation of all follower power supplies in the micro-grid system relative to the power supply expectation model based on the neighbor error equation of each follower power supply
Wherein ∈ col { ε1,ε2,...,εn}，ζ＝col{ζn+1,ζn+2,...,ζn+m}，wL＝col{w1,w2,...,wn}，wF＝col{wn+1,wn+2,...,wn+m}，IN，IMAre respectively an N-dimensional identity matrix and an M-dimensional identity matrix,
represents the kronecker product, L11,L21,L22Are respectively provided withAre sub-matrices in the laplacian matrix L,
based on the technical scheme, the state error system equation of the relative power supply expected model is constructed respectively for the leader power supply and the follower power supply, so that the state error system equation can fully reflect the stability requirement of the micro-grid system.
Optionally, the stability control conditions are: if a constant λ exists1>0, dimensional matrix K1And a positive definite matrix Q satisfying
If so, all leader power supplies in the microgrid system are capable of achieving group consistency, wherein,
wherein the element represents an element R symmetrical to the element RT。
Optionally, the stability control conditions are: if a constant λ exists2>0, dimensional matrix K2And a positive definite matrix Q satisfying
If so, all follower power supplies in the microgrid system can achieve population consistency, wherein,
wherein the element represents an element R symmetrical to the element RT。
Optionally, the disturbance suppression condition is: if a constant λ exists1>0, an interference suppression parameter of 0 < gamma < 1 and a positive definite matrix Q, satisfying
And if so, all distributed power supplies in the microgrid system have disturbance suppression performance.
In a second aspect, an embodiment of the present application further provides a microgrid distributed power supply enclosure control apparatus based on a directed topology network, where the apparatus includes:
the topological structure analysis module is used for dividing all distributed power supplies in the micro-grid system into n leader power supplies and m follower power supplies and generating information interaction relations among the distributed power supplies by utilizing a directed topological network;
a control input analysis module for internal state X of each distributed power supply according to a preset power supply expectation modeliConstructing a control input equation u of each distributed power supply according to the information interaction relationiSaid control input equation uiIncluding the control gain coefficient to be solved;
the system equation building module is used for building a second-order dynamic system model of each distributed power supply and a state error system equation of the micro-grid system relative to the power supply expected model;
a noise interference suppression module for suppressing the output voltage Y of each of the distributed power sourcesi(t) and bounded noise disturbance wi(t), introduction of l2-l∞Performance index function of
The stability analysis module is used for analyzing the state error system equation and the performance index function respectively through the Lyapunov stability theory to generate a stability control condition and a disturbance suppression condition of the micro-grid system;
the control gain solving module is used for solving a control input equation of each distributed power supply by using the stability condition and the disturbance suppression condition of the microgrid system to obtain a control gain coefficient corresponding to the distributed power supply;
and the control gain loading module is used for loading the control gain coefficient output by the control gain solving module into the controller of each distributor power supply so as to enable the controller to control the distributor power supply according to the control gain coefficient.
Optionally, the topology analysis module is specifically configured to:
setting all the distributed power supplies as nodes in a directed topology network by using the knowledge of graph theory;
generating an adjacency matrix A ═ α of the directed topology networkij]Wherein i and j are adjacent distributed power sources, i, j is 1,2ij1 indicates that information interaction exists between the ith distributed power supply and the jth distributed power supply, and the element alphaij0 means that there is no information interaction between the ith distributed power source and the jth distributed power source.
Optionally, the control input analysis module is specifically configured to:
loading a preset power supply expected model, wherein the power supply expected model comprises an expected state change equation
And desired output voltage equation Y0(t)＝CX0(t) wherein X0To a desired power state, r0For desired control input, Y0For the desired output voltage, A, B, C are the adaptive system matrix,
e is the power supply capacitance value, S is the voltage load regulation effect coefficient, R is the maximum active power, and C is [10 ]]；
Based on the adjacency matrix A ═ alphaij]Internal state X of each of the leader power suppliesiAnd said X0Constructing a neighbor error equation for each of the leader power sources
Constructing each of the collars based on a neighbor error equation for each of the leader power suppliesControl input equation u of lead power supplyi＝K1εi+ Γ r, where i ═ 1,2, ·, n, K1Γ is the control gain to be solved;
based on the adjacency matrix A ═ alphaij]Internal state X of each follower power supplyiAnd said X0Constructing a neighbor error equation for each of the follower power sources
Constructing a control input equation of each follower power supply based on a neighbor error equation of each follower power supply
Wherein i is n +1, n +2,.., n + m; k2Γ is the control gain to be solved;
inverse matrix L being Laplace matrix L-1Ith row in the matrix
Column elements, the Laplace matrix L ═ degree matrix D-the adjacency matrix A, the degree matrix
Optionally, the system equation building module is specifically configured to:
based on internal state X of each distributed power supplyiAmount of state change
Bounded noise disturbance wiAnd the control input equation uiAnd establishing a second-order dynamic system model of each distributed power supply.
Optionally, the system equation building module is specifically configured to:
on the basis of each of theInternal state X of distributed power supplyiAmount of change in state
Constructing an internal state augmentation vector X for a distributed power supplyi(t)；
Internal state augmentation vector X based on distributed power supplyi(t) bounded noise interference vector wi(t) and the control input equation ui(t) establishing a state change equation of the distributed power supply
Wherein,
the superscript T denotes transpose, and
e is the power supply capacitance value, S is the voltage load regulation effect coefficient, R is the maximum active power,
establishing a voltage output equation Y of the distributed power supply based on a state change equation of the distributed power supplyi(t)＝CXi(t), wherein C ═ 10]。
Optionally, the system equation building module is specifically configured to:
constructing a state error system equation of all leader power supplies in the micro-grid system relative to the power supply expectation model based on the neighbor error equation of each leader power supply
Constructing a state error system equation of all follower power supplies in the micro-grid system relative to the power supply expectation model based on the neighbor error equation of each follower power supply
Wherein ∈ col { epsilon1,ε2,...,εn}，ζ＝col{ζn+1,ζn+2,...,ζn+m}，wL＝col{w1,w2,...,wn}，wF＝col{wn+1,wn+2,...,wn+m}，IN，IMAre respectively an N-dimension unit matrix and an M-dimension unit matrix,
represents the kronecker product, L11,L21,L22Respectively, sub-matrices in the laplacian matrix L,
optionally, the stability control conditions are: if a constant λ exists1>0, dimensional matrix K1And a positive definite matrix Q satisfying
If so, all leader power supplies in the microgrid system are capable of achieving group consistency, wherein,
wherein the element represents an element R symmetrical to the element RT。
Optionally, the stability control conditions are: if a constant λ exists2>0, dimensional matrix K2And a positive definite matrix Q satisfying
If so, all follower power supplies in the microgrid system can achieve population consistency, wherein,
wherein the element represents an element R symmetrical to the element RT。
Optionally, the disturbance suppression condition is: if there is a constant lambda1>0, interference suppression parameter 0 < gamma < 1 and positive definite matrix Q, satisfying
And if so, all distributed power supplies in the microgrid system have disturbance suppression performance.
In a third aspect, there is provided a central controller, which includes a processor and a memory, where at least one instruction, at least one program, a set of codes, or a set of instructions is stored in the memory, and the at least one instruction, the at least one program, the set of codes, or the set of instructions is loaded and executed by the processor to implement the method for controlling a microgrid distributed power supply enclosure based on a directed topology network according to the first aspect.
In a fourth aspect, a computer-readable storage medium is provided, where at least one instruction, at least one program, a set of codes, or a set of instructions is stored in the storage medium, and the at least one instruction, the at least one program, the set of codes, or the set of instructions is loaded and executed by a processor to implement the method for controlling enclosure of a microgrid distributed power supply based on a directed topology network according to the first aspect.
In summary, the present application has the following beneficial effects:
by adopting the microgrid distributed power supply enclosure control method based on the directed topology network, the directed network topology idea is introduced into information interaction of distributed power supplies in the microgrid, a second-order dynamic system model of the distributed power supplies is constructed to model the power supply state, then a state error system equation of the microgrid system relative to a preset power supply expected model is established, and l is introduced2-l∞And analyzing the state error system equation and the performance index function by utilizing the Lyapunov stability theory to obtain a stability condition and a disturbance suppression condition, so that a control gain coefficient capable of realizing the stability of the micro-grid system can be obtained by solving the stability condition and the disturbance suppression condition. Thus, the micro-grid system is dividedThe distributed power supply state modeling is realized, the enclosure control gain coefficient of the distributed power supply is obtained through mathematical analysis, and the distributed power supply can be accurately controlled in real time by using the power controller, so that the group consistency of the micro-grid system can be effectively realized.
Drawings
Fig. 1 is a schematic view of a scenario architecture of a microgrid system in an embodiment of the present application;
fig. 2 is a flowchart of a distributed power enclosure control method in an embodiment of the present application;
fig. 3 is a schematic structural diagram of a distributed power enclosure control device in an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is further described in detail below with reference to fig. 1-3 and the embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
The embodiment of the application provides a microgrid distributed power supply enclosure control method based on a directed topology network, which can be applied to a microgrid system shown in fig. 1 and can be specifically executed by a central controller of the microgrid system, wherein the microgrid system can comprise the central controller and a plurality of distributed power supplies, and each distributed power supply corresponds to one controller. The central controller may perform data interaction with controllers (hereinafter, simply referred to as power controllers) of each distributed power source in the microgrid system, for example, obtain internal state data of the distributed power source from the power controllers, and send control gain coefficients to the power controllers. The central controller may further have a data processing and analyzing function, that is, the central controller may be configured to process and analyze the internal state data and the state change data of the distributed power source to obtain the control gain coefficient loaded in the controller of the distributed power source.
The process flow shown in fig. 2 will be described in detail below with reference to the specific embodiments, and the contents may be as follows:
In an implementation, the central controller may record all online distributed power sources in the microgrid system, select n distributed power sources from all distributed power sources as leader power sources, and determine the remaining m distributed power sources as follower power sources. In other words, n + m distributed power supplies are arranged in the microgrid, the n distributed power supplies are set as leader power supplies, the rest m distributed power supplies are set as follower power supplies, and both n and m are positive integers. Then, a directed topology network can be introduced into the central controller, and an undirected graph G is taken to describe the communication network topology relationship between the leader and the follower in the microgrid, so that the information interaction relationship between any two distributed power supplies is generated.
Alternatively, the information interaction relationship may be expressed by using an adjacency matrix, and accordingly, the processing of step 201 may be as follows: setting all distributed power supplies as nodes in a directed topology network by using graph theory knowledge; generating adjacency matrix A ═ alpha of directed topology networkij]Wherein i and j are adjacent distributed power sources, i, j is 1,2ij1 indicates that information interaction exists between the ith distributed power supply and the jth distributed power supply, and the element alphaij0 means that there is no information interaction between the ith distributed power source and the jth distributed power source.
In implementation, the central controller may introduce graph theory knowledge to identify information interaction relationships between distributed power sources in the microgrid system using a directed topology network. Specifically, the distributed power source may be set as a node in the directed topology network, and then an adjacency matrix a ═ α of the directed topology network may be generatedij]Wherein i and j are adjacent distributed power sources, i, j is 1,2ijThat is, the information interaction weight between the ith distributed power supply and the jth distributed power supply, when the element alphaij1 indicates that information interaction exists between the ith distributed power supply and the jth distributed power supply, and the element alphaij0 denotes the ith and jth distributionsWith no information interaction between the power supplies, e.g. alpha12And 0, no information interaction exists between the 1 st distributed power source and the 2 nd distributed power source. Further, α may be definediiAnd 0, namely, the information interaction weight value of each distributed power supply and the distributed power supply is 0. It is worth mentioning that in the present embodiment, the leader power source is set as the 0 th distributed power source, α, by defaultijThe information interaction weight between follower power supplies can be weighted.
In practice, considering that a desired steady state is reached in the microgrid system, the association of the distributed power sources with other distributed power sources, particularly with the desired steady state, needs to be fully considered when setting the control input of each distributed power source controller. Therefore, after the central controller generates the information interaction relation among the distributed power supplies in the micro-grid system, a preset power supply expectation model can be obtained, and the power supply expectation model is the consistency standard for realizing enclosure in the micro-grid system. Then, for the ith distributed power supply, a control input equation u of the ith distributed power supply containing the control gain coefficient to be solved and including the control gain coefficient can be constructed by combining the information interaction relationship between the ith distributed power supply and other distributed power supplies (including the leader power supply and the follower power supply) in the microgrid system and the internal states of the distributed power suppliesi，i＝1,2,...,n+m。
Optionally, the control input equation may be constructed separately for the leader power supply and the follower power supply when constructing the control input equation, and accordingly, the process of step 202 may be as follows: loading a preset power supply expected model, wherein the power supply expected model comprises an expected state change equation
And desired output voltage equation Y0(t)＝CX0(t) wherein X0To a desired internal state, r0For desired control input, Y0Is the desired output voltage. A, B and C are respectively an adaptive system matrix; based on the adjacency matrix A ═ alphaij]Internal state X of each leader power supplyiAnd X0Constructing a neighbor error equation for each leader power supply
Constructing a control input equation u of each leader power supply based on the neighbor error equation of each leader power supplyi＝K1εi+ Γ r, where i ═ 1,2, ·, n, K1Γ is the control gain to be solved; based on the adjacency matrix A ═ alphaij]Internal state X of each follower power supplyiAnd X0Constructing a neighbor error equation for each follower power supply
Constructing a control input equation of each follower power supply based on a neighbor error equation of each follower power supply
Wherein i is n +1, n +2,.., n + m; k2Γ is the control gain to be solved;
inverse L of Laplace L-1Ith row in the matrix
Column elements, laplace matrix L ═ degree matrix D-adjacency matrix a, degree matrix
In implementation, when the central controller constructs a control input equation of the follower power supply, a preset power supply expectation model may be loaded first, and the power supply expectation model may be in the form of a second-order dynamical system equation, that is, may contain an expectation stateEquation of state change
And desired output voltage equation Y0(t)＝CX0(t) wherein X0To a desired power state, r0For desired control input, Y0For the desired output voltage, A, B, C are the adaptive system matrix,
e is the power supply capacitance value, S is the voltage load regulation effect coefficient, R is the maximum active power, and C is 10]；
Next, the central controller may construct a neighbor error equation of the distributed power supply by using the power supply expectation model as a reference, and combining the internal state of the distributed power supply and the information interaction relationship between the distributed power supply and other distributed power supplies. On one hand, for the ith leader power supply, from adjacency matrix a ═ αij]The information interaction weight value alpha of the ith leader power supply and other leader power supplies is obtainediqAnd acquiring the information interaction weight a of the ith leader power supply and the expected power supply modeli0The internal states X of the various leader power supplies can then be combinedqAnd desired power state X0Constructing a neighbor error equation for the leader power supply
Further, based on the neighbor error equation, a corresponding control input equation u for the leader power supply may be constructedi＝K1εi+ Γ r, where i ═ 1, 2., n, K1Γ is the control gain to be solved, and r is the desired control input.
On the other hand, for the ith follower power supply, the slave adjacency matrix a ═ αij]The information interaction weight alpha of the ith follower power supply and other distributed power supplies is obtainediqThe method can be divided into an information interaction weight with a leader power supply and an information interaction weight with a follower power supply. In turn, the internal states X of the various distributed power sources can be combinedqBuild the follower electricityNeighbor error equation of source
Furthermore, based on the neighbor error equation, a corresponding control input equation of the follower power supply can be constructed
Wherein, i ═ n +1, n +2,. cndot, n + m; k2Γ is the control gain to be solved;
inverse matrix L being Laplace matrix L-1Ith row in the matrix
Column elements, laplace matrix L ═ degree matrix D-adjacency matrix a, degree matrix
And step 203, establishing a second-order dynamic system model of each distributed power supply and a state error system equation of the micro-grid system relative to the power supply expected model.
In implementation, when the distributed power supplies in the microgrid system run, the state values and changes of the distributed power supplies can be fitted by a second-order dynamical system model, and further, the stability among a plurality of distributed power supplies can be reflected by the state errors between the distributed power supplies and the power supply expectation model. Therefore, aiming at each distributed power supply, the central controller can establish a second-order dynamic system model of the distributed power supply and establish a state error system equation between the micro-grid system and the power supply expected model.
Optionally, the second order dynamical system model of the distributed power source in step 203 may specifically include: internal state X based on each distributed power supplyiAmount of state change
Bounded noise disturbance wiAnd controlSystem input equation uiAnd establishing a second-order dynamic system model of each distributed power supply.
In implementation, when a second-order dynamic system model of the distributed power supply is constructed, the internal state and the state variation of the distributed power supply, the control input of the power supply controller to the distributed power supply and the influence of bounded noise interference on the distributed power supply can be considered, so that the internal state X of the distributed power supply can be based oniAmount of change in state
Bounded noise disturbance wiAnd control input equation uiAnd establishing a second-order dynamic system model of the distributed power supply.
Further, the process of establishing the second order dynamical system model of the distributed power supply may specifically be as follows: internal state X based on each distributed power supplyiAmount of change in state
Constructing an internal state augmentation vector X for a distributed power supplyi(t); internal state augmentation vector X based on distributed power supplyi(t) bounded noise interference vector wi(t) and control input equation ui(t) establishing a state change equation of the distributed power supply
Wherein,
the superscript T denotes transpose, and
e is the power supply capacitance value, S is the voltage load regulation effect coefficient, R is the maximum active power,
voltage output equation Y of distributed power supply is established based on state change equation of distributed power supplyi(t)＝CXi(t), wherein C ═ 10]。
In an implementation, the internal state augmentation vector of the distributed power supply may be set to Xi(t)，Xi(t) may be comprised of an internal state XiAmount of change in state
An augmented vector of, i.e.
Wherein the superscript T denotes transpose, and
Xisubscripts 1 and 2 of (a) are used only for distinction, in combination with the bounded noise interference vector w that the distributed power supply may be subjected toi(t), and corresponding control input equation ui(t), equations of state change for the distributed power sources can be established
Wherein i is 1,2, 1, n, A, B, D is an adaptive system matrix,
e is a power supply capacitance value, and S and R are both to-be-determined values associated with power supply hardware parameters, and before the power supply is put into use, a technician can determine corresponding specific values according to the power supply hardware parameters, where S is a voltage load regulation effect coefficient, and R is maximum active power, and values of E, R, S corresponding to different distributed power supplies of the microgrid system in this embodiment are all the same. Here, the possible bounded noise interference vector w of the distributed power supplyi(t) can be obtained by sorting and analyzing a large amount of actually measured data, and specifically, the maximum value of actually measured noise interference can be obtained. In addition, the voltage output equation Y of the distributed power supplyi(t) vector X may be augmented by internal states of the distributed power supplyi(t) is established directly, i.e. Yi(t)＝CXi(t), wherein C is an adaptive system matrix, C ═ 10]。
Optionally, the establishing process of the state error system equation may include two parts, namely a leader power supply and a follower power supply, and the specific processing may be as follows: constructing a state error system equation of all leader power supplies in the micro-grid system relative to a power supply expectation model based on the neighbor error equation of each leader power supply
Based on the neighbor error equation of each follower power supply, a state error system equation of all follower power supplies in the micro-grid system relative to a power supply expectation model is constructed
Wherein ∈ col { ε1,ε2,...,εn}，ζ＝col{ζn+1,ζn+2,...,ζn+m}，wL＝col{w1,w2,...,wn}，wF＝col{wn+1,wn+2,...,wn+m}，IN，IMAre respectively an N-dimensional identity matrix and an M-dimensional identity matrix,
represents the kronecker product, L11,L21,L22Respectively, sub-matrices in the laplacian matrix L,
in implementation, after the neighbor error equations of the distributed power supplies are constructed, the central controller can utilize the neighbor error equations to construct state error system equations of all the distributed power supplies relative to a power supply expectation model, and the construction process can be specifically divided into two parts, namely a leader power supply and a follower power supply. For the leader Power, the neighbor error equation ε can be at each of the previously constructed leader PoweriOn the basis of (1), constructState error system equation with leader power source relative to power source expectation model
Similarly, for follower power supplies, the neighbor error equation ζ for each follower power supply that can be constructed as described aboveiOn the basis, a state error system equation of all follower power supplies relative to a power supply expectation model is constructed
In implementation, the central controller may be subject to a bounded noise interference introduction/for each distributed power supply2-l∞Performance index function
On the premise that power supply interference exists in the micro-grid system, the voltage output of each distributed power supply can be always kept within a boundary, so that the voltage and other state parameters of the distributed power supplies can be guaranteed not to exceed the instantaneous range, and the safety performance requirement of the micro-grid system is met.
And step 205, analyzing the state error system equation and the performance index function respectively through the Lyapunov stability theory to generate a stability control condition and a disturbance suppression condition of the microgrid system.
In practice, the lyapunov stability theory is a theory for studying the stability of a system, that is, a balance state of the system is sought, and when the system is in the balance state, the system finally tends to return to the balance state no matter what external disturbance exists. Therefore, the state error system equation and the performance index function can be analyzed based on the Lyapunov stability theory to calculate the control condition to be met and the suppression condition of the bounded noise interference when the micro-grid system has the equilibrium state, namely the stability control condition and the disturbance suppression condition of the micro-grid system are generated.
System equation based on the state error
And
if the micro-grid system finally achieves the enclosure control of group consistency, the micro-grid system needs to be controlled
And
all tend to 0. Therefore, a systematic equation of state errors is formed by utilizing the Lyapunov stability theory
And
by analyzing, the following two stability control conditions can be obtained respectively for the leader power supply and the follower power supply:
for the leader Power supply, if there is a constant λ1>0, dimensional matrix K1And a positive definite matrix Q satisfying
If so, then all leader power supplies in the microgrid system are able to achieve population consistency, wherein,
wherein the element represents an element R symmetrical to the element RT；
For follower power supplies, if there is a constant λ2>0, dimensional matrix K2And positive definiteMatrix Q, satisfy
And if so, all follower power supplies in the microgrid system can achieve group consistency, wherein,
wherein the element represents an element R symmetrical to the element RT。
Further, in order to achieve suppression of power supply noise interference, the following disturbance suppression conditions may be obtained: if a constant λ exists1>0, an interference suppression parameter of 0 < gamma < 1 and a positive definite matrix Q, satisfying
And if so, all distributed power supplies in the microgrid system have disturbance suppression performance.
And step 206, solving the control input equation of each distributed power supply by using the stability condition and the disturbance suppression condition of the microgrid system to obtain a control gain coefficient corresponding to the distributed power supply.
In implementation, after the stability control condition and the disturbance suppression condition of the microgrid system are obtained through analysis, the central controller can utilize the stability control condition and the disturbance suppression condition to jointly and reversely solve the control gain coefficient of each distributed power supply in the microgrid system. Specifically, the central controller may uniformly solve the control input equation of the leader power supply and the control input equation of the follower power supply based on the stability control condition and the disturbance suppression condition, so that the control gain coefficients corresponding to all the leader power supplies and the control gain coefficients corresponding to all the follower power supplies may be obtained.
And step 207, loading the control gain coefficient into the controller of each distributed power supply, so that the controller controls the distributed power supplies according to the control gain coefficient.
In the implementation ofAfter determining the control gain coefficients of the distributed power sources, the central controller may send the control gain coefficients to the power controllers of each distributed power source. The power supply controller receives and loads the control gain coefficient, and substitutes the control gain coefficient into a control input equation u of the distributed power supplyiTo obtain a specific control input for each distributed power source, so that the power controller can control the distributed power sources through the specific control input.
By adopting the microgrid distributed power supply enclosure control method based on the directed topology network, the directed network topology idea is introduced into information interaction of the distributed power supplies in the microgrid, a second-order dynamic system model of the distributed power supplies is constructed to model the power supply state, a state error system equation of the microgrid system relative to a preset power supply expected model is further established, and l is introduced2-l∞And analyzing the state error system equation and the performance index function by utilizing the Lyapunov stability theory to obtain a stability condition and a disturbance suppression condition, so that a control gain coefficient capable of realizing the stability of the micro-grid system can be obtained by solving the stability condition and the disturbance suppression condition. Therefore, the distributed power supply state of the micro-grid system is modeled, the encircled control gain coefficient of the distributed power supply is obtained through mathematical analysis, the distributed power supply can be accurately controlled in real time by the power controller, and therefore the group consistency of the micro-grid system can be effectively achieved.
An embodiment of the present application further provides a microgrid distributed power supply enclosure control device based on a directed topology network, as shown in fig. 3, the device includes:
the topological structure analysis module 301 is used for dividing all distributed power supplies in the microgrid system into n leader power supplies and m follower power supplies and generating information interaction relations among the distributed power supplies by utilizing a directed topological network;
a control input analysis module 302 for analyzing the internal state X of each of the distributed power sources according to a preset power source expectation modeliAnd constructing each of the information interaction relationsControl input equation u for distributed power supplyiSaid control input equation uiIncluding the control gain coefficient to be solved;
the system equation building module 303 is configured to build a second-order dynamical system model of each distributed power source and a state error system equation of the microgrid system relative to the power source expectation model;
a noise interference suppression module 304 for suppressing the output voltage Y of each of the distributed power sourcesi(t) and bounded noise disturbance wi(t) introduction of l2-l∞Performance index function of
The stability analysis module 305 is configured to analyze the state error system equation and the performance index function through a lyapunov stability theory, and generate a stability control condition and a disturbance suppression condition of the microgrid system;
a control gain solving module 306, configured to solve a control input equation of each distributed power source by using the stability condition of the microgrid system and the disturbance suppression condition, so as to obtain a control gain coefficient corresponding to the distributed power source;
and a control gain loading module 307, configured to load the control gain coefficient output by the control gain solving module into the controller of each distributor power supply, so that the controller controls the distributor power supplies according to the control gain coefficient.
Optionally, the topology analysis module 301 is specifically configured to:
setting all the distributed power supplies as nodes in a directed topology network by using knowledge of graph theory;
generating an adjacency matrix A ═ α of the directed topology networkij]Wherein i and j are adjacent distributed power sources, i, j is 1,2ij1 indicates that information interaction exists between the ith distributed power supply and the jth distributed power supply, and the element alphaij0 denotes the ith distributionThere is no information interaction between the power supply and the jth distributed power supply.
Optionally, the control input analysis module 302 is specifically configured to:
loading a preset power supply expectation model, wherein the power supply expectation model comprises an expectation state change equation
And desired output voltage equation Y0(t)＝CX0(t) wherein X0To a desired power state, r0For desired control input, Y0For the desired output voltage, A, B, C are the adaptive system matrix,
e is the power supply capacitance value, S is the voltage load regulation effect coefficient, R is the maximum active power, and C is 10]；
Based on the adjacency matrix A ═ alphaij]Internal state X of each of the leader power suppliesiAnd said X0Constructing a neighbor error equation for each of the leader power sources
Constructing a control input equation u for each of the leader power supplies based on the neighbor error equation for each of the leader power suppliesi＝K1εi+ Γ r, where i ═ 1,2, ·, n, K1Γ is the control gain to be solved;
based on the adjacency matrix A ═ alphaij]Internal state X of each follower power supplyiAnd said X0Constructing a neighbor error equation for each of the follower power sources
Based on each of the follower power suppliesThe neighbor error equation of (2) constructing a control input equation for each of the follower power supplies
Wherein i is n +1, n +2,.., n + m; k2Γ is the control gain to be solved;
inverse matrix L being Laplace matrix L-1Ith row in the matrix
Column elements, the Laplace matrix L ═ degree matrix D-the adjacency matrix A, the degree matrix
Optionally, the system equation building module 303 is specifically configured to:
based on the internal state X of each distributed power supplyiAmount of change in state
Bounded noise disturbance wiAnd said control input equation uiAnd establishing a second-order dynamic system model of each distributed power supply.
Optionally, the system equation building module 303 is specifically configured to:
based on internal state X of each distributed power supplyiAmount of change in state
Constructing an internal state augmentation vector X for a distributed power supplyi(t)；
Internal state augmentation vector X based on distributed power supplyi(t) bounded noise interference vector wi(t) and the control input equation ui(t) establishing a state change equation of the distributed power supply
Wherein,
the superscript T denotes transpose, and
e is the power supply capacitance value, S is the voltage load regulation effect coefficient, R is the maximum active power,
establishing a voltage output equation Y of the distributed power supply based on a state change equation of the distributed power supplyi(t)＝CXi(t), wherein C ═ 10]。
Optionally, the system equation building module 303 is specifically configured to:
constructing a state error system equation of all leader power supplies in the micro-grid system relative to the power supply expectation model based on the neighbor error equation of each leader power supply
Based on the neighbor error equation of each follower power supply, constructing state error system equations of all follower power supplies in the micro-grid system relative to the power supply expected model
Wherein ∈ col { epsilon1,ε2,...,εn}，ζ＝col{ζn+1,ζn+2,...,ζn+m}，wL＝col{w1,w2,...,wn}，wF＝col{wn+1,wn+2,...,wn+m}，IN，IMAre respectively an N-dimensional identity matrix and an M-dimensional identity matrix,
represents the kronecker product, L11,L21,L22Respectively, sub-matrices in the laplacian matrix L,
optionally, the stability control conditions are: if there is a constant lambda1>0, dimensional matrix K1And a positive definite matrix Q satisfying
If so, all leader power supplies in the microgrid system are capable of achieving group consistency, wherein,
wherein the element represents an element R symmetrical to the element RT。
Optionally, the stability control conditions are: if a constant λ exists2>0, fitting matrix K2And a positive definite matrix Q satisfying
If so, all follower power supplies in the microgrid system can achieve population consistency, wherein,
the element in (b) represents an element R symmetrical to the element RT。
Optionally, the disturbance suppression condition is: if a constant λ exists1>0, an interference suppression parameter of 0 < gamma < 1 and a positive definite matrix Q, satisfying
And if yes, all distributed power sources in the microgrid system have disturbance suppression performance.
An embodiment of the present application further provides a central controller, where the central controller includes a processor and a memory, where the memory stores at least one instruction, at least one program, a code set, or an instruction set, and the at least one instruction, the at least one program, the code set, or the instruction set is loaded and executed by the processor to implement the method for controlling a microgrid distributed power supply enclosure based on a directed topology network according to the first aspect.
It will be understood by those skilled in the art that all or part of the steps for implementing the above embodiments may be implemented by hardware, or may be implemented by a program instructing relevant hardware, where the program may be stored in a computer-readable storage medium, and the above-mentioned storage medium may be a read-only memory, a magnetic disk or an optical disk, etc.
The foregoing is a preferred embodiment of the present application and is not intended to limit the scope of the application in any way, and any features disclosed in this specification (including the abstract and drawings) may be replaced by alternative features serving equivalent or similar purposes, unless expressly stated otherwise. That is, unless expressly stated otherwise, each feature is only an example of a generic series of equivalent or similar features.
Claims (10)
1. A microgrid distributed power supply enclosure control method based on a directed topology network is characterized by comprising the following steps:
dividing all distributed power supplies in the micro-grid system into n leader power supplies and m follower power supplies, and generating an information interaction relation between the distributed power supplies by utilizing a directed topology network;
according to a preset power supply expected model, the internal state X of each distributed power supplyiAnd the information interaction relation, respectively constructing a neighbor error equation of each distributed power supply, and constructing a control input equation u of each distributed power supply based on the neighbor error equation and the information interaction relationiSaid control input equation uiIncluding the control gain coefficient to be solved;
establishing a second-order dynamic system model of each distributed power supply, and performing augmentation processing on the neighbor error equation to obtain a state error system equation of the micro-grid system relative to the power supply expected model;
an output voltage Y for each of the distributed power suppliesi(t) and bounded noise disturbance wi(t) introduction of l2-l∞Performance index function of
Wherein γ is a pending interference suppression parameter;
analyzing the state error system equation and the performance index function respectively through a Lyapunov stability theory to generate a stability control condition and a disturbance suppression condition of the micro-grid system;
solving a control input equation of each distributed power supply by using the stability condition and the disturbance suppression condition of the microgrid system to obtain a control gain coefficient corresponding to the distributed power supply;
loading the control gain factor into a controller of each of the distributed power sources to cause the controller to control each of the distributed power sources according to the control gain factor.
2. The method according to claim 1, wherein the generating information interaction relationships among the distributed power sources by using the directed topology network comprises:
setting all the distributed power supplies as nodes in a directed topology network by using knowledge of graph theory;
generating an adjacency matrix A ═ α of the directed topology networkij]Wherein i and j are adjacent distributed power sources, i, j is 1,2ij1 indicates that information interaction exists between the ith distributed power supply and the jth distributed power supply, and the element alphaij0 means that there is no information interaction between the ith distributed power source and the jth distributed power source.
3. The method of claim 2, wherein the internal state X of each of the distributed power sources is in accordance with a preset power source expectation modeliAnd the information interaction relation is set up,respectively constructing a neighbor error equation of each distributed power supply, and constructing a control input equation u of each distributed power supply based on the neighbor error equation and the information interaction relationiThe method comprises the following steps:
loading a preset power supply expected model, wherein the power supply expected model comprises an expected state change equation
And desired output voltage equation Y0(t)＝CX0(t) wherein X0To a desired power state, r0For desired control input, Y0For the desired output voltage, A, B, C are the adaptive system matrix,
e is the power supply capacitance value, S is the voltage load regulation effect coefficient, R is the maximum active power, and C is 10]；
Based on the adjacency matrix A ═ alphaij]Internal state X of each of the leader power suppliesiAnd said X0Constructing a neighbor error equation for each of the leader power sources
Constructing a control input equation u for each of the leader power supplies based on the neighbor error equation for each of the leader power suppliesi＝K1εi+ Γ r, where i ═ 1,2, ·, n, K1Γ is the control gain to be solved;
based on the adjacency matrix A ═ alphaij]Internal state X of each of the follower power suppliesiAnd said X0Constructing a neighbor error equation for each of the follower power sources
Constructing a control input equation of each follower power supply based on a neighbor error equation of each follower power supply
Wherein i is n +1, n +2,.., n + m; k2Γ is the control gain to be solved;
inverse L of Laplace L-1Ith row in the matrix
Column elements, the Laplace matrix L ═ degree matrix D-the adjacency matrix A, the degree matrix
4. The method of claim 3, wherein said modeling a second order dynamical system of each of said distributed power sources comprises:
based on internal state X of each distributed power supplyiAmount of state change
Bounded noise disturbance wiAnd the control input equation uiAnd establishing a second-order dynamic system model of each distributed power supply.
5. The method of claim 4, wherein the internal state X based on each of the distributed power sourcesiAmount of state change
Bounded noise disturbance wiAnd the control input equation uiEstablishing a second-order dynamical system model of each distributed power supply, wherein the second-order dynamical system model comprises the following steps:
based on internal state X of each distributed power supplyiAmount of change in state
Constructing an internal state augmentation vector X for a distributed power supplyi(t)；
Internal state augmentation vector X based on distributed power supplyi(t) bounded noise interference vector wi(t) and the control input equation ui(t) establishing a state change equation of the distributed power supply
Wherein,
the superscript T denotes transpose, an
E is the power supply capacitance value, S is the voltage load regulation effect coefficient, R is the maximum active power,
establishing a voltage output equation Y of the distributed power supply based on the state change equation of the distributed power supplyi(t)＝CXi(t), wherein C ═ 10]。
6. The method of claim 5, wherein the augmenting the neighbor error equation to obtain a state error system equation that establishes the microgrid system relative to the expected model of the power source comprises:
constructing a state error system equation of all leader power supplies in the micro-grid system relative to the power supply expectation model based on the neighbor error equation of each leader power supply
Constructing a state error system equation of all follower power supplies in the micro-grid system relative to the power supply expectation model based on the neighbor error equation of each follower power supply
Wherein ∈ col { ε1,ε2,...,εn}，ζ＝col{ζn+1,ζn+2,...,ζn+m}，wL＝col{w1,w2,...,wn}，wF＝col{wn+1,wn+2,...,wn+m}，IN，IMAre respectively an N-dimensional identity matrix and an M-dimensional identity matrix,
represents the kronecker product, L11,L21,L22Respectively, sub-matrices in the laplacian matrix L,
7. the method of claim 6, wherein the stability control condition is: if a constant λ exists1>0, dimensional matrix K1And a positive definite matrix Q satisfying
If so, all leader power supplies in the microgrid system are capable of achieving group consistency, wherein,
wherein the element represents an element R symmetrical to the element RT。
8. The method of claim 6, wherein the stability control condition is: if a constant λ exists2>0, dimensional matrix K2And a positive definite matrix Q satisfying
If so, all follower power supplies in the microgrid system can achieve population consistency, wherein,
wherein the element represents an element R symmetrical to the element RT。
9. The method of claim 1, wherein the disturbance rejection condition is: if a constant λ exists1>0, an interference suppression parameter of 0 < gamma < 1 and a positive definite matrix Q, satisfying
And if so, all distributed power supplies in the microgrid system have disturbance suppression performance.
10. A microgrid distributed power supply enclosure control device based on a directed topology network is characterized in that the device comprises:
the topological structure analysis module is used for dividing all distributed power supplies in the micro-grid system into n leader power supplies and m follower power supplies and generating information interaction relations among the distributed power supplies by utilizing a directed topological network;
a control input analysis module for internal state X of each distributed power supply according to a preset power supply expectation modeliAnd the information interaction relation, respectively constructing a neighbor error equation of each distributed power supply, and constructing each branch based on the neighbor error equation and the information interaction relationControl input equation u of distributed power supplyiSaid control input equation uiIncluding the control gain coefficient to be solved;
the system equation building module is used for building a second-order dynamic system model of each distributed power supply and carrying out augmentation processing on the neighbor error equation to obtain a state error system equation of the micro-grid system relative to the power supply expected model;
a noise interference suppression module for suppressing the output voltage Y of each of the distributed power sourcesi(t) and bounded noise disturbance wi(t) introduction of l2-l∞Performance index function of
Wherein γ is a pending interference suppression parameter;
the stability analysis module is used for analyzing the state error system equation and the performance index function respectively through the Lyapunov stability theory to generate a stability control condition and a disturbance suppression condition of the micro-grid system;
the control gain solving module is used for solving a control input equation of each distributed power supply by using the stability condition and the disturbance suppression condition of the microgrid system to obtain a control gain coefficient corresponding to the distributed power supply;
and the control gain loading module is used for loading the control gain coefficient output by the control gain solving module into the controller of each distributor power supply so as to enable the controller to control the distributor power supply according to the control gain coefficient.
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