CN115347582A - Micro-grid system based on state prediction consistency algorithm and frequency modulation strategy thereof - Google Patents
Micro-grid system based on state prediction consistency algorithm and frequency modulation strategy thereof Download PDFInfo
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Abstract
The embodiment of the invention provides a micro-grid system based on a state prediction consistency algorithm and a frequency modulation strategy thereof, belonging to the technical field of micro-grid frequency modulation. The frequency modulation strategy comprises the steps of obtaining the output frequency of an energy storage inverter in the microgrid; and carrying out primary frequency modulation according to the output frequency of the energy storage inverter. According to the micro-grid system based on the state prediction consistency algorithm and the frequency modulation strategy thereof, after primary frequency modulation is carried out on all energy storage inverters of the micro-grid, the frequency mean value of the energy storage inverters and the adjacent energy storage inverters is collected, and the frequency mean value of the energy storage inverters is calculated and obtained, so that the frequency of all the energy storage inverters in the micro-grid is regulated to be consistent with the rated frequency, and the micro-grid system can realize rapid and stable frequency recovery after load fluctuation occurs; meanwhile, the active power of all the energy storage inverters is guaranteed to be equally divided, and the power of the micro-grid is not required to be equally divided, so that the structure of the secondary controller is greatly simplified.
Description
Technical Field
The invention relates to the technical field of micro-grid frequency modulation, in particular to a micro-grid system based on a state prediction consistency algorithm and a frequency modulation strategy thereof.
Background
A Micro Grid (MG) is a small electrical system with multiple distributed power supplies and loads, and has both grid-connected and island modes of operation. How to maintain the safe, stable and economic operation of the microgrid in an island mode is the key of microgrid research. When the microgrid operates in an island mode, an energy storage inverter for constructing the microgrid usually adopts droop control or Virtual Synchronous Generator (VSG) control, and the two control modes are both voltage frequency difference control, so that the voltage frequency of a system changes along with the change of load and cannot be stabilized in the operation range required by the system all the time. Therefore, in order to improve the power supply quality of the microgrid and improve the robustness of the microgrid, efficient and stable secondary control is of great importance.
The secondary frequency modulation control is mainly divided into two types, one type is a centralized control mode, and the other type is a distributed control mode. Distributed quadric modulation control has been widely studied in recent years due to its better reliability and scalability. In the prior art, for the condition that a plurality of VSGs participate in secondary frequency modulation, a PI controller and a frequency deviation feedback coefficient are added in an active frequency control loop of the VSG, so that the differential frequency modulation of a microgrid is realized, and the load power can be automatically distributed according to the capacity of each VSG. In addition, a distributed power control strategy based on adaptive virtual impedance is also provided in the prior art, so that the reasonable distribution of load power among DGs is realized. In the prior art, the secondary frequency modulation function of the microgrid is realized by changing a droop coefficient and increasing the output active power of the VSG, although the frequency can be controlled within the frequency quality allowable range of the microgrid by the method, the frequency fluctuation is large, the frequency is not stabilized at an ideal rated value, and the requirement of a sensitive load cannot be met. The prior art also provides a communication-free secondary frequency modulation method for droop of the island operation multi-parallel inverter, and the frequency stability of an island multi-parallel inverter system is enhanced through a secondary frequency modulation stabilizer based on an integral advanced correction link, but the frequency modulation speed of the method is too low. In order to make the control of the microgrid more flexible and reduce the dependency of the system on the central controller, the prior art also proposes a distributed consistency control strategy, which regards the distributed power supply as an intelligent agent and applies it to the microgrid. The prior art also provides a finite time consistency microgrid distributed secondary control strategy, which realizes the aims of no static difference of frequency and voltage and proportional power distribution, but the control targets are respectively provided with algorithms for control, so that a control system is relatively complex.
The inventor finds that the scheme in the prior art has the defects of low secondary frequency modulation speed of the microgrid, poor frequency control effect, complex controller design and the like in the process of realizing the invention.
Disclosure of Invention
The micro-grid system based on the state prediction consistency algorithm and the frequency modulation strategy thereof have the advantages of high frequency modulation speed, good control effect and simplified controller structure.
In order to achieve the above object, an aspect of the embodiments of the present invention provides a frequency modulation strategy of a microgrid system based on a state prediction consistency algorithm, including:
acquiring the output frequency of an energy storage inverter in the microgrid;
performing primary frequency modulation according to the output frequency of the energy storage inverter;
acquiring a frequency mean difference value of the energy storage inverter and the adjacent energy storage inverters in the microgrid;
carrying out secondary frequency modulation according to the energy storage inverter and the frequency mean difference value of the adjacent energy storage inverters to obtain a frequency regulation value, wherein the frequency regulation value comprises the following steps:
calculating the frequency average value of the secondary frequency modulation of the energy storage inverter according to the formula (1),
wherein,
is the frequency average value of the ith energy storage inverter, i is an integer number, f i (t) is the output frequency of the ith energy storage inverter, tau is a time constant, tau belongs to (0, t), j is an energy storage inverter adjacent to the ith energy storage inverter, j is an integer number, N i For the set of tank inverters adjacent to the ith tank inverter,
is the difference value of the frequency mean values of the jth energy storage inverter and the ith energy storage inverter when the time constant is tau, a ij Weight for data transmission from the jth of said tank inverters to the ith of said tank inverters, a ij Taking a value of 0 or 1,a ij No communication line from the jth energy storage inverter to the ith energy storage inverter when =0, a ij When the current is 1, communication lines are arranged from the jth energy storage inverter to the ith energy storage inverter;
and adjusting the frequency of the corresponding energy storage inverter according to the frequency adjusting value of each energy storage inverter.
Optionally, the obtaining a frequency average difference between the energy storage inverter and the adjacent energy storage inverter in the microgrid includes:
calculating the frequency mean value difference value of the jth energy-storage inverter and the ith energy-storage inverter when the time constant is tau according to the formula (2),
wherein,
is the frequency average of the jth of the tank inverters,
for the frequency of the i-th said energy-storage inverterAnd (4) average value.
Optionally, performing secondary frequency modulation according to the energy storage inverter and the difference between the average values of the frequencies of the adjacent energy storage inverters to obtain a frequency adjustment value further includes:
acquiring frequency mean difference values of the energy storage inverter and state predictors of the adjacent energy storage inverters;
calculating the frequency regulation value of the state predictor of the secondary frequency modulation of the energy storage inverter according to the formula (3),
wherein,
is the frequency adjustment value of the state predictor, gamma is the influence factor of the state predictor,
the frequency mean value difference value of the state predictors of the ith energy storage inverter and the jth energy storage inverter when the time constant is tau.
Optionally, obtaining a frequency mean difference value of the state predictors of the energy storage inverter and the adjacent energy storage inverters comprises:
acquiring the frequency average value of the state predictor of the energy storage inverter and the frequency average value of the state predictors of the adjacent energy storage inverters;
calculating the frequency mean value difference value of the state predictors of the ith energy storage inverter and the jth energy storage inverter when the time constant is tau according to a formula (4),
wherein,
is the ith oneThe frequency average of the state predictor of the tank inverter,
and the frequency average value of the state predictor of the jth energy storage inverter is obtained.
Optionally, the obtaining the frequency average of the state predictor of the energy storage inverter and the frequency average of the state predictors of the adjacent energy storage inverters includes:
calculating the frequency average value of the state predictor of the ith energy storage inverter according to the formula (5),
wherein,
is the frequency average value of the kth energy storage inverter when the time constant is tau, k is an integer number, a ik Weight for data transmission from the kth of the energy storage inverter to the ith of the energy storage inverter, a ik Taking a value of 0 or 1,a ik No communication line from the k-th energy storage inverter to the i-th energy storage inverter when =0, a ik And if the number of the energy storage inverters is more than 1, communication lines are arranged from the kth energy storage inverter to the ith energy storage inverter.
Optionally, the obtaining the frequency average of the state predictor of the energy storage inverter and the frequency average of the state predictors of the adjacent energy storage inverters further includes:
calculating the frequency mean difference value of the state predictor of the jth energy storage inverter according to the formula (6),
wherein,
is a time constant of tauThe frequency mean value of the p-th energy storage inverter, p is an integer number, N j The adjacent energy storage inverter set of the jth energy storage inverter; a is jp Weight for data transmission from the p-th to the j-th energy storage inverter, a jp Values of 0 or 1,a jp No communication line from the p-th to the j-th energy storage inverters when =0, a jp And the communication line is from the p-th energy storage inverter to the j-th energy storage inverter when the number of the inverter is 1.
Optionally, performing secondary frequency modulation according to the energy storage inverter and the difference between the average values of the frequencies of the adjacent energy storage inverters to obtain a frequency adjustment value further includes:
and calculating the frequency regulation value of the energy storage inverter according to the formula (7).
Wherein,
is the frequency adjustment value.
Optionally, adjusting the frequency of the energy storage inverter according to the frequency adjustment value of each energy storage inverter includes:
inputting the difference value between the frequency regulation value and the rated frequency into a PI controller to obtain a secondary frequency regulation quantity;
and adjusting the frequency of the energy storage inverter and the active power sharing of the energy storage inverter according to the secondary frequency adjustment quantity.
On the other hand, the invention also provides a micro-grid system based on the state prediction consistency algorithm, which comprises the following steps:
a direct current power supply;
the energy storage inverters are connected with the direct current power supply at one end;
the loads are respectively connected with the other ends of the energy storage inverters;
and the plurality of distributed processors are respectively connected with the plurality of energy storage inverters and used for executing the frequency modulation strategy.
In yet another aspect, the present disclosure also provides a computer-readable storage medium storing instructions for reading by a machine to cause the machine to execute a frequency modulation strategy as described in any one of the above.
According to the technical scheme, the micro-grid system based on the state prediction consistency algorithm and the frequency modulation strategy thereof provided by the invention collect the frequency mean values of the energy storage inverter and the energy storage inverter adjacent to the energy storage inverter after performing primary frequency modulation on all the energy storage inverters of the micro-grid, calculate and acquire the frequency mean value of the energy storage inverter so as to adjust the frequencies of all the energy storage inverters in the micro-grid to be consistent with the rated frequency, and further enable the micro-grid system to realize rapid and stable frequency recovery after load fluctuation occurs; meanwhile, the active power of all the energy storage inverters is guaranteed to be equally divided, and the power of the micro-grid is not required to be equally divided, so that the structure of the secondary controller is greatly simplified.
Additional features and advantages of embodiments of the present invention will be described in the detailed description which follows.
Drawings
The accompanying drawings, which are included to provide a further understanding of the embodiments of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the embodiments of the invention without limiting the embodiments of the invention. In the drawings:
FIG. 1 is a flow diagram of a frequency tuning strategy for a microgrid system based on a state prediction consistency algorithm, according to an embodiment of the present invention;
FIG. 2 is a flow diagram of obtaining frequency adjustment values in a frequency modulation strategy of a microgrid system based on a state prediction consistency algorithm according to one embodiment of the present invention;
fig. 3 is a flow diagram of adjusting the frequency of the storage inverter in a frequency modulation strategy of the microgrid system based on a state prediction consistency algorithm according to an embodiment of the present invention;
fig. 4 is a three-level nine-node low-voltage alternating current island microgrid model in a microgrid system based on a state prediction consistency algorithm according to an embodiment of the invention;
FIG. 5 is a block diagram of energy storage inverter control in a microgrid system based on a state prediction consistency algorithm, according to an embodiment of the present invention;
FIG. 6 is a simulated waveform diagram of droop control output frequencies of three energy storage inverters in a microgrid system based on a state prediction consistency algorithm according to an embodiment of the present invention;
FIG. 7 is a simulated waveform diagram of the consistency secondary frequency adjustment amount of the energy storage inverter when a state predictor is not started in the microgrid system based on a state prediction consistency algorithm according to an embodiment of the invention;
FIG. 8 is a simulated waveform diagram of output frequencies of three tank inverters when a state predictor is not started in a microgrid system based on a state prediction consistency algorithm according to an embodiment of the present invention;
FIG. 9 is a simulation waveform of active-frequency of three tank inverters when a state predictor is not started in a microgrid system based on a state prediction consistency algorithm according to an embodiment of the present invention;
FIG. 10 is a simulated waveform of active power output of three tank inverters when a state predictor is not started in a microgrid system based on a state prediction consistency algorithm according to an embodiment of the present invention;
FIG. 11 is a simulated waveform diagram of the tank inverter consistency secondary frequency adjustment when the state predictor is started in the microgrid system based on the state prediction consistency algorithm according to an embodiment of the present invention;
fig. 12 is a simulated waveform diagram of output frequencies of three energy storage inverters when the microgrid system starts a state predictor based on a state prediction consistency algorithm according to an embodiment of the invention;
fig. 13 is a simulation waveform of active-frequency of three tank inverters when a state predictor is started in a microgrid system based on a state prediction consistency algorithm according to an embodiment of the present invention;
FIG. 14 is a simulated waveform of active power output of three tank inverters when a state predictor is started in a microgrid system based on a state prediction consistency algorithm according to an embodiment of the present invention;
FIG. 15 is a directed graph of an example of a microgrid system in a microgrid system based on a state prediction consistency algorithm according to an embodiment of the present invention;
FIG. 16 is a trace diagram of an example global coherency state convergence trajectory for the microgrid system in the microgrid system based on a state predictive coherency algorithm according to one embodiment of the present invention.
Detailed Description
The following detailed description of embodiments of the invention refers to the accompanying drawings. It should be understood that the detailed description and specific examples, while indicating embodiments of the invention, are given by way of illustration and explanation only, not limitation.
Fig. 1 is a flow diagram of a frequency tuning strategy for a microgrid system based on a state prediction consistency algorithm according to an embodiment of the present invention. In fig. 1, the frequency modulation strategy may include:
in step S10, the output frequency of the energy storage inverter in the microgrid is obtained. The output frequency can be directly acquired at the output end of the energy storage inverter.
In step S11, primary frequency modulation is performed according to the output frequency of the storage inverter. After the output frequency of the energy storage inverter is obtained, the frequency of the energy storage inverter is adjusted by adopting droop control. Specifically, the expression of the droop control may be as shown in equation (8),
wherein f is i For the ith energy storage inverter, i is an integer number, f 0 Rated system frequency, m, for the ith energy storage inverter i Active droop coefficient for ith energy storage inverter，P i Active power, P, output for the ith energy-storage inverter 0 Rated output active power for the ith energy storage inverter, E i Actual output voltage for the ith energy storage inverter, E 0 Rated voltage amplitude, n, for the ith energy-storage inverter i For the reactive droop coefficient, Q, of the i-th energy storage inverter i For the reactive power, Q, output by the i-th energy-storage inverter 0 And rated reactive power of the ith energy storage inverter is provided.
According to the formula (8), when the microgrid system is suddenly loaded, the energy storage inverter can output more power due to the increase of the power demand, and the frequency and the voltage of the microgrid system are correspondingly reduced after droop control. Therefore, droop control is poor control, the frequency can change along with the change of load disturbance, small fluctuation of the frequency of the microgrid system can greatly affect the stability and the power quality of the system, and further secondary adjustment control is needed for the frequency after primary frequency modulation.
In step S12, a frequency mean difference between the energy storage inverter in the microgrid and the adjacent energy storage inverters is obtained. In order to obtain the value of the secondary frequency modulation of the microgrid system, the frequency mean difference value of the energy storage inverter and the energy storage inverter adjacent to the energy storage inverter at the previous moment is also required to be acquired.
In step S13, a secondary frequency modulation is performed according to the frequency mean difference of the energy storage inverter and the adjacent energy storage inverter to obtain a frequency adjustment value. Specifically, the method comprises the following steps:
calculating the frequency average value of the secondary frequency modulation of the energy storage inverter according to the formula (1),
wherein,
is the frequency average value of the ith energy storage inverter, i is an integer number, f i (t) is the output of the ith energy storage inverter for acquisitionAnd (3) obtaining the frequency, wherein tau is a time constant, tau belongs to (0, t), j is an energy storage inverter adjacent to the ith energy storage inverter, j is an integer number, and N i For the set of tank inverters adjacent to the ith tank inverter,
is the difference value of the frequency mean value of the jth energy storage inverter and the ith energy storage inverter when the time constant is tau, a ij Weight for data transmission from the jth tank inverter to the ith tank inverter, a ij Values of 0 or 1,a ij No communication line from the jth energy storage inverter to the ith energy storage inverter when =0, a ij And if the current is not less than 1, communication lines are arranged from the jth energy storage inverter to the ith energy storage inverter. And obtaining the frequency regulating value of the energy storage inverter according to the calculated frequency average value of the ith energy storage inverter at the current moment. In particular, each energy storage inverter of the microgrid system may be considered a distributed multi-agent system, and the microgrid system may be considered a multi-agent system.
For the consistency problem of a multi-agent system, algebraic graph theory is a common analysis tool, that is, the communication network structure among agents is represented by a directed graph form, each agent can be regarded as a node of the directed graph, communication lines among agents can be regarded as edges of the directed graph, so that an expression shown in formula (9) can be obtained,
G＝{V,E}， (9)
wherein G is a directed graph, V is a set of nodes, i.e., a set of energy storage inverters, and V = {1,2, \8230;, n }, n is an integer number, E is a set of edges, and
the nodes adjacent to the ith agent are grouped into N i And N is i And (j) E, namely a node set of the ith energy storage inverter.
In algebraic graph theory, it is usual to use A = [ a ] ij ]∈ R n×n To describe the relationship between nodes, called the adjacency weight matrix of the directed graph G, where the elementsElement a ij Representing the weight of data transmitted from the jth node (energy storage inverter) to the ith node (energy storage inverter), i.e. the coupling degree of the communication line, and the diagonal element a ii And =0. If the jth node has an edge pointing to the ith node
For unweighted graph a ij Can only take 0 or 1. In particular, when a ij If not only 0 or 1, the graph G is called a weighted graph. If the communication line between two nodes is bidirectional, an equation as shown in equation (10) can be obtained,
wherein, a ji Representing the weight of data passing from the ith node (energy storage inverter) to the jth node (energy storage inverter).
The laplacian matrix L = D-a of the directed graph G is defined, which is another matrix describing the topology of the directed graph G, having a similar structure as the adjacency matrix a, wherein the in-degree matrix D may be defined as an expression as shown in equation (11),
D＝diag(d 1 ,d 2 ,…,d i ,…),di＝∑ j≠i a ij ， (11)
wherein diag () is a diagonal matrix function, d i Is the value of the ith row and the ith column in the in-degree matrix.
The laplace matrix satisfies the expression of equation (12),
wherein l ii ＝∑ j≠i a ij ,l ij ＝-a ij 。
If a root node in the directed graph G can reach any other node through a path, the directed graph G can be considered to contain a spanning tree, when the directed graph G has the spanning tree, 0 is a characteristic value of a Laplace matrix of the directed graph G, and the convergence of the coordination consistency algorithm can be ensured when the directed graph G is a connected graph.
For a microgrid system comprising a plurality of energy storage inverters, taking the ith energy storage inverter as an example, the data obtained from the adjacent energy storage inverter j is assumed to have an output frequency value f j And the mean value f of the uniformity frequency i p ，fi Is composed of Measured value of the output frequency of the energy storage inverter unit, N i Is the set of nodes adjacent to the ith storage inverter cell. According to the multi-agent consistency algorithm, the current energy storage inverter unit frequency f can be obtained according to the formula (1) i Frequency mean of
For any i e {1,2, \8230;, n }, frequency mean value
Convergence to global consistency, as shown in equation (13),
the convergence speed of the consistency algorithm depends on the algebraic connectivity, i.e. the minimum non-zero eigenvalue λ of the Laplace matrix 2 The size of (2).
Taking the micro-grid system shown in fig. 15 and including three energy storage inverters DG1, DG2 and DG3 shown in fig. 15 as an example, the adjacent matrix of the micro-grid system can be shown as formula (14),
the laplace matrix can be shown as equation (15),
the algebraic connectivity of the microgrid system, namely the minimum non-zero eigenvalue lambda of the Laplace matrix 2 =3, assume that the initial values of frequency states of three storage inverters DG in the system are f (0) = [49.8,49.58,50.03]The state trajectory of the frequency state adjusted by the primary consistency algorithm is shown in fig. 16, i.e., after the primary secondary frequency modulation. Since the directed graph of the microgrid system is a connected graph, after a global consistency algorithm is applied, the frequency states can be converged to be consistent, the consistent value is a frequency mean value, and the formula (13) is verified.
In step S14, the frequency of the corresponding energy storage inverter is adjusted according to the frequency adjustment value of each energy storage inverter. After the frequency regulating value of the energy storage inverter is obtained, the frequency regulating quantity of each energy storage inverter frequency is obtained according to the frequency regulating value, and the frequency of the corresponding energy storage inverter, namely the translation droop curve, is regulated according to each frequency regulating quantity, so that the frequency is recovered to a rated value, and the effective regulation of the secondary control of the energy storage inverter frequency can be realized.
In steps S10 to S14, the output frequency of the energy storage inverter is obtained, and the droop control is adopted to perform primary adjustment on the output frequency, so as to obtain the difference value of the average frequency value between the energy storage inverter and the energy storage inverter adjacent to the energy storage inverter. And calculating the frequency mean value of all energy storage inverters at the current moment according to the formula (1) and the frequency secondary frequency modulation, and finally adjusting the frequency of the energy storage inverter corresponding to the micro-grid system according to the frequency mean value of each energy storage inverter.
The traditional secondary frequency modulation control mode of the distributed micro-grid system comprises the step of realizing the secondary frequency modulation function of the micro-grid in a mode of increasing the output active power of the VSG by changing a droop coefficient, but the method does not stabilize the frequency at an ideal rated value and cannot meet the requirement of a sensitive load. In addition, the frequency stability of the island multi-parallel inverter system is enhanced through a secondary frequency modulation stabilizer based on an integral advance correction link, but the frequency modulation speed of the method is too slow. And a micro-grid distributed secondary control strategy with limited time consistency realizes the aims of no static difference of frequency and voltage and proportional power distribution, but the control targets are respectively provided with algorithms for control, so that a control system is more complex. In the embodiment of the invention, a mode of calculating the frequency mean value of the energy storage inverter is adopted to carry out globally consistent secondary frequency modulation on the micro-grid system, so that the micro-grid system can realize quick and stable frequency recovery after load fluctuation occurs; meanwhile, the active power of all the energy storage inverters is guaranteed to be equally divided, an evenly divided control module of the micro-grid system power is not needed, and the structure of the secondary controller is greatly simplified.
In this embodiment of the present invention, in order to obtain the frequency average difference between the energy storage inverter and the energy storage inverter adjacent to the energy storage inverter, the frequency average of the energy storage inverter and the energy storage inverter adjacent to the energy storage inverter needs to be calculated. Specifically, the frequency modulation strategy may further include:
calculating the frequency mean value difference value of the jth energy-storage inverter and the ith energy-storage inverter when the time constant is tau according to the formula (2),
wherein,
is the frequency average of the jth energy-storage inverter,
the frequency average value of the ith energy storage inverter is obtained. Specifically, the frequency average is a frequency average output by a secondary frequency modulation at a last moment of the corresponding energy storage inverter.
In this embodiment of the present invention, in order to obtain the frequency adjustment value required for the secondary frequency modulation of the energy storage inverter, the average frequency of the energy storage inverter needs to be calculated. Specifically, the frequency modulation strategy may further include steps as shown in fig. 2. Specifically, in fig. 2, the frequency modulation strategy may further include:
in step S20, the frequency average of the state predictor of the i-th tank inverter is calculated according to the formula (5),
wherein,
is the frequency average value of the kth energy storage inverter when the time constant is tau, k is an integer number, a ik Weight for data transmission from the kth to the ith storage inverter, a ik Taking a value of 0 or 1,a ik No communication link exists between the kth energy storage inverter and the ith energy storage inverter when =0, a ik And if the current is 1, communication lines are arranged from the kth energy storage inverter to the ith energy storage inverter.
In step S21, the frequency-average difference of the state predictor of the jth tank inverter is calculated according to equation (6),
wherein,
is the frequency average value of the p-th energy storage inverter when the time constant is tau, p is an integer number, N j A set of adjacent tank inverters that is the jth tank inverter; a is a jp Weight for data transmission from the p-th to the j-th tank inverter, a jp Values of 0 or 1,a jp No communication line from the p-th energy storage inverter to the j-th energy storage inverter when =0, a jp And if the number of the inverter units is not less than 1, communication lines are arranged from the p-th energy storage inverter to the j-th energy storage inverter.
In step S22, calculating the frequency mean difference value of the state predictors of the ith energy storage inverter and the jth energy storage inverter when the time constant is tau according to the formula (4),
wherein,
is the frequency average of the state predictor of the ith tank inverter,
is the frequency average of the state predictor of the jth energy storage inverter.
In step S23, the frequency regulation value of the state predictor of the secondary frequency modulation of the energy storage inverter is calculated according to the formula (3),
wherein,
is the frequency adjustment value of the state predictor, gamma is the influence factor of the state predictor,
the frequency mean value difference value of the state predictors of the ith energy storage inverter and the jth energy storage inverter when the time constant is tau.
In step S24, the frequency adjustment value of the storage inverter is calculated according to equation (7).
Wherein,
is a frequency adjustment value.
In the steps S20 to S24, a state predictor is added in a consistency algorithm used for global secondary frequency modulation by adding limited-time communication, so that each energy storage inverter can dynamically predict the future state of the adjacent energy storage inverter, and the speed of the frequency evolution of the microgrid system to the final balance state is increased. For a microgrid system of a distributed energy storage inverter, a conventional control strategy usually only utilizes the current state information of each energy storage inverter, the control strategy is usually suboptimal, and the adjustment response speed of an algorithm is relatively delayed. Compared with the micro-grid system of the multi-energy-storage inverter without the state predictor, the algebraic connectivity of the micro-grid system is increased by introducing the state predictor, so that consistency of a consistency algorithm used for secondary frequency modulation can be achieved more quickly, and the efficiency and the precision of the secondary frequency modulation are further improved.
In this embodiment of the present invention, in order to perform secondary frequency modulation on each energy storage inverter in the microgrid system, a secondary frequency adjustment amount of each energy storage inverter needs to be calculated. Specifically, the frequency modulation strategy may further include steps as shown in fig. 3. Specifically, in fig. 3, the frequency modulation strategy may further include:
in step S30, the difference between the frequency adjustment value and the rated frequency is input to the PI controller to obtain a secondary frequency adjustment amount. And the calculated frequency regulation value of the energy storage inverter is differed from the rated frequency, and the difference value is input into a PI controller for proportional-integral regulation so as to obtain the secondary frequency regulation quantity of the energy storage inverter.
In step S31, the frequency of the storage inverter and the active power sharing of the storage inverter are adjusted according to the secondary frequency adjustment amount. The secondary frequency adjustment amount obtained through proportional-integral adjustment is compensated to each energy storage inverter in the microgrid system, namely, a droop curve of each energy storage inverter is translated, so that the frequency of each energy storage inverter can be quickly and stably recovered. Meanwhile, after the frequency of each energy storage inverter of the micro-grid system is adjusted, the active power of the plurality of energy storage inverters is synchronously and equally divided, and further, a power equally dividing control module of the micro-grid system is not needed to be additionally used, so that the structure of the secondary controller is simplified.
In steps S30 to S31, the difference between the frequency adjustment value and the rated frequency is calculated, and then the difference is input to the PI controller, and the secondary frequency adjustment amount is obtained. And a plurality of distributed processors of the micro-grid system adjust the energy storage inverters controlled by the distributed processors according to the secondary frequency adjustment quantity respectively, so that the accurate and quick compensation adjustment of the frequency of the plurality of energy storage inverters of the micro-grid system is realized. Meanwhile, after the frequency consistency is adjusted, the active power of the energy storage inverters synchronously realizes active power equalization, and the structure of secondary control is optimized.
On the other hand, the invention also provides a micro-grid system based on the state prediction consistency algorithm. In particular, the microgrid system may include a direct current power source, a plurality of energy storage inverters, a plurality of loads, and a plurality of distributed processors.
One end of the energy storage inverter is connected with the direct current power supply, and the plurality of loads are respectively connected with the other ends of the plurality of energy storage inverters, namely the plurality of energy storage inverters are connected in parallel. The plurality of distributed processors are respectively connected with the plurality of energy storage inverters and used for executing any frequency modulation strategy.
In yet another aspect, the present invention also provides a computer-readable storage medium. In particular, the computer-readable storage medium stores instructions for reading by a machine to cause the machine to perform a frequency modulation strategy as any one of the above.
In the embodiment of the invention, in order to verify the effectiveness of the frequency modulation strategy of the microgrid system based on the state prediction consistency algorithm, a low-voltage alternating current isolated island microgrid model with a three-machine nine-node structure is built in an MATLAB/Simulink platform, and three head-end nodes of the model are respectively connected with one energy storage inverter with lower vertical control as primary control, as shown in FIG. 4. Three energy storage inverters are connected with 800V storage battery packs at the direct current side, the system runs under the condition of 380V/50Hz, and partial simulation parameters are shown in Table 1.
TABLE 1 microgrid System parameters
In order to compare the influence of adding secondary frequency modulation on the frequency adjustment effect of the system. Simulation comparison experiments for single droop control and the addition of a consistent distributed secondary frequency modulation (un-activated state predictor) were now performed. The system parameters are shown in table 1, and the control modes of the three energy storage inverters and the structure of the microgrid system are respectively shown in fig. 5 and 4. The nodes 5, 7 and 8 of the system are connected with loads with the same capacity from the beginning of simulation operation, the loads connected with the nodes 5 are cut off from the 0 th to 5 th s of the operation, the loads connected with the nodes 8 are cut off from the 7 th to 12 th s of the operation, and simulation waveforms are shown in fig. 6 to 10.
From the simulation waveforms of the single droop control shown in fig. 6, it can be seen that the output frequencies of the three energy storage inverters all deviate from the rated values due to the regulation effect of the droop control during the period of time when the system is off the load. The method can be obtained by comparing the system simulation waveform diagrams 7-10 after the secondary frequency modulation is added, although the state predictor is not started after the secondary frequency modulation is added, when the load in the microgrid system changes, the output frequency of the distributed power supply has a regulation trend of recovering to a rated value, the deviation generated by droop control can be finally eliminated after a certain time of transition, and the active power output of three energy storage inverters in the system is distributed according to the proportional relation of droop coefficients. However, the secondary frequency modulation is slow in adjustment speed and basically stable after about 4 seconds, which cannot meet the requirements of a microgrid requiring fast and stable frequency adjustment or having more disturbances.
In this embodiment of the present invention, in order to verify the influence of the state predictor introduced in the present invention on the control effect of the consistency distributed secondary frequency modulation policy, a consistency distributed secondary frequency modulation simulation comparison experiment of whether to start the state predictor is now performed. The system parameters are shown in table 1 above, and the control modes of three energy storage inverters and the structure of the microgrid system are shown in fig. 5 and 4 respectively. The nodes 5, 7 and 8 of the system access loads with the same capacity from the beginning of simulation operation, the loads connected with the nodes 5 are cut off in the 0 th to 5 th s of operation when the state predictor is not started, and the loads connected with the nodes 8 are cut off in the 7 th to 12 th s of operation; the 1 st to 2 nd s of operation after the state predictor is started have shed the load connected to node 5, and the 5 th to 6 th s have shed the load connected to node 8. The simulated waveforms are shown in fig. 11 to 14.
Fig. 7 to 10 show the case where the state predictor is not started in the consistency algorithm, and it can be seen from comparing the consistency distributed secondary frequency modulation algorithm after the state predictor is started in fig. 11 to 14 that the adjustment time of the consistency secondary frequency modulation algorithm is shortened from nearly 4s to less than 0.5s after the state predictor is started, and even if the interval time of load switching is shortened, the system can quickly cope with the disturbance. And the active power output of three energy storage inverters in the system is still distributed according to the proportional relation of droop coefficients. Therefore, the micro-grid system based on the state prediction consistency algorithm and the frequency modulation strategy thereof can well enhance the secondary frequency modulation capability of the micro-grid system.
According to the technical scheme, the micro-grid system based on the state prediction consistency algorithm and the frequency modulation strategy thereof provided by the invention collect the frequency mean values of the energy storage inverter and the energy storage inverter adjacent to the energy storage inverter after performing primary frequency modulation on all the energy storage inverters of the micro-grid, calculate and acquire the frequency mean value of the energy storage inverter so as to adjust the frequencies of all the energy storage inverters in the micro-grid to be consistent with the rated frequency, and further enable the micro-grid system to realize rapid and stable frequency recovery after load fluctuation occurs; meanwhile, the active power of all the energy storage inverters is equally divided, the power of the micro-grid is not required to be equally divided, and the structure of the secondary controller is greatly simplified.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and so forth) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). The memory is an example of a computer-readable medium.
Computer-readable media, including both permanent and non-permanent, removable and non-removable media, may implement the information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Disks (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrases "comprising a," "8230," "8230," or "comprising" does not exclude the presence of additional identical elements in the process, method, article, or apparatus comprising the element.
The above are merely examples of the present application and are not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.
Claims (10)
1. A frequency modulation strategy of a micro-grid system based on a state prediction consistency algorithm is characterized by comprising the following steps:
acquiring the output frequency of an energy storage inverter in the microgrid;
performing primary frequency modulation according to the output frequency of the energy storage inverter;
acquiring the difference value of the frequency mean values of the energy storage inverters and the adjacent energy storage inverters in the microgrid;
according to the energy storage inverter and the difference value of the average frequency values of the adjacent energy storage inverters, secondary frequency modulation is carried out to obtain a frequency regulation value, and the method comprises the following steps:
calculating the frequency average value of the secondary frequency modulation of the energy storage inverter according to the formula (1),
wherein,
the frequency mean value of the ith energy storage inverter is i, i is an integer number, f i (t) is the output frequency of the ith energy storage inverter, tau is a time constant, tau belongs to (0, t), j is an energy storage inverter adjacent to the ith energy storage inverter, j is an integer number, N i For the set of tank inverters adjacent to the ith tank inverter,
is the difference value of the frequency mean values of the jth energy storage inverter and the ith energy storage inverter when the time constant is tau, a ij Weight for data transmission from the jth of said tank inverters to the ith of said tank inverters, a ij Taking a value of 0 or 1,a ij No communication line from the jth energy storage inverter to the ith energy storage inverter when =0, a ij When the current is 1, communication lines are arranged from the jth energy storage inverter to the ith energy storage inverter;
and adjusting the frequency corresponding to the energy storage inverter according to the frequency adjusting value of each energy storage inverter.
2. A frequency modulation strategy according to claim 1, wherein obtaining a frequency mean difference value of the energy storage inverter and adjacent energy storage inverters in a microgrid comprises:
calculating the frequency mean value difference value of the jth energy-storage inverter and the ith energy-storage inverter when the time constant is tau according to the formula (2),
wherein,
is the frequency average of the jth of the tank inverters,
and the frequency average value of the ith energy storage inverter is obtained.
3. A frequency modulation strategy according to claim 2, wherein performing a second frequency modulation according to the energy storage inverter and the difference between the average frequency values of the adjacent energy storage inverters to obtain a frequency adjustment value further comprises:
acquiring frequency mean difference values of the energy storage inverter and state predictors of the adjacent energy storage inverters;
calculating the frequency regulation value of the state predictor of the secondary frequency modulation of the energy storage inverter according to the formula (3),
wherein,
is the frequency adjustment value of the state predictor, gamma is the influence factor of the state predictor,
the frequency mean value difference value of the state predictors of the ith energy storage inverter and the jth energy storage inverter when the time constant is tau.
4. A frequency modulation strategy according to claim 3, wherein obtaining a frequency mean difference value of state predictors of the tank inverter and neighboring tank inverters comprises:
acquiring a frequency average value of a state predictor of the energy storage inverter and a frequency average value of a state predictor of an adjacent energy storage inverter;
calculating the frequency mean difference value of the state predictors of the ith energy storage inverter and the jth energy storage inverter when the time constant is tau according to the formula (4),
wherein,
the frequency average of the state predictor of the i-th tank inverter,
and the frequency average value of the state predictor of the jth energy storage inverter is obtained.
5. Frequency-modulation strategy according to claim 4, wherein obtaining the mean frequency value of the state predictor of the tank inverter and the mean frequency values of the state predictors of neighboring tank inverters comprises:
calculating the frequency average value of the state predictor of the ith energy storage inverter according to the formula (5),
wherein,
is the frequency average value of the kth energy storage inverter when the time constant is tau, k is an integer number, a ik Weight for data transmission from the kth to the ith energy storage inverter, a ik Values of 0 or 1,a ik No communication line from the k-th energy storage inverter to the i-th energy storage inverter when =0, a ik And when the current is not less than 1, communication lines are arranged from the k-th energy storage inverter to the i-th energy storage inverter.
6. A frequency modulation strategy according to claim 5, wherein obtaining a frequency mean of the state predictor of the tank inverter and a frequency mean of the state predictors of neighboring tank inverters further comprises:
calculating the frequency mean difference value of the state predictor of the jth energy storage inverter according to the formula (6),
wherein,
is the frequency average value of the p-th energy storage inverter when the time constant is tau, p is an integer number, N j The adjacent energy storage inverter set of the jth energy storage inverter; a is jp Weight for data transmission from the p-th to the j-th energy storage inverter, a jp Values of 0 or 1,a jp No communication line from the p-th energy storage inverter to the j-th energy storage inverter when the number is not less than 0, a jp And when the number of the inverter is not less than 1, communication lines are arranged from the p-th energy storage inverter to the j-th energy storage inverter.
7. A frequency modulation strategy according to claim 6, wherein performing a second frequency modulation according to the energy storage inverter and the difference between the average frequency values of the adjacent energy storage inverters to obtain a frequency adjustment value further comprises:
calculating a frequency adjustment value of the energy storage inverter according to formula (7),
wherein,
is the frequency adjustment value.
8. A frequency modulation strategy according to claim 1, wherein adjusting the frequency of the corresponding energy storage inverter according to the frequency adjustment value of each energy storage inverter comprises:
inputting the difference value between the frequency regulation value and the rated frequency into a PI controller to obtain a secondary frequency regulation quantity;
and adjusting the frequency of the energy storage inverter and the active power sharing of the energy storage inverter according to the secondary frequency adjustment quantity.
9. A micro-grid system based on a state prediction consistency algorithm is characterized by comprising the following components:
a direct current power supply;
a plurality of energy storage inverters, one end of which is connected to the DC power supply;
the loads are respectively connected with the other ends of the energy storage inverters;
a plurality of distributed processors respectively connected to a plurality of said storage inverters for implementing a frequency modulation strategy as claimed in any one of claims 1 to 8.
10. A computer readable storage medium having stored thereon instructions for reading by a machine to cause the machine to execute a frequency modulation strategy according to any one of claims 1 to 8.
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