A distributed secondary regulation method based on quantization state and event-triggered communication

Abstract

The present invention discloses a distributed secondary regulation method based on quantization state and event-triggered communication, belonging to the field of distributed secondary control of DC microgrids. Compared with the existing distributed secondary control methods, the present invention takes into account the capacity limitation of the communication network. The communication network only transmits the discrete values after state quantization, occupying less bandwidth. In addition, the transmission of information only occurs at the event-triggered moment, rather than continuously or periodically, reducing the number of communications. The combination of the above two jointly reduces the burden on the communication network. Through theoretical analysis, the Zeno phenomenon is excluded, verifying the feasibility of the proposed scheme. In addition, since this method does not require the DC bus voltage as a feedback signal, the design process is simple and easy to implement. The selection of control parameters is very flexible, and a sufficient balance can be achieved between control performance and communication burden by adjusting the corresponding parameters.

Description

Technical Field

[0001] The present invention belongs to the field of distributed secondary control of DC microgrids, and more specifically, relates to a distributed secondary regulation method and device based on quantized states and event-triggered communication. Background Art

[0002] The proportion of renewable energy, such as wind energy and solar energy, is increasing day by day. Such renewable energy is mostly collected and connected to the power grid in a distributed form and has strong uncertainty. Therefore, it will have an adverse impact on the safe operation of traditional power grids. The microgrid, as a system concept that can well integrate power resources and process renewable energy, has emerged as the times require. A microgrid is a local controllable power generation, distribution, and power consumption system formed by aggregating multiple distributed generation devices, storage units, energy conversion devices, loads, etc. It can well help the distribution system to accept distributed energy, and when the power grid fails, it can ensure the power supply of critical loads and improve the power supply reliability. It can be used to solve the power supply problems of users in remote areas, islands, and deserts. Microgrids can be divided into AC microgrids, DC microgrids, and hybrid microgrids. Among them, DC microgrids have been widely used due to their advantages such as simple structure, no reactive power generation, and good controllability. In a single-bus island DC microgrid, the regulation of the bus voltage and the power distribution of power sources are two fundamental control objectives. Although traditional droop control can achieve proportional current distribution, an excessive droop coefficient will cause the bus voltage to drop and deviate from the rated value. Therefore, distributed secondary control is introduced on the basis of droop control, and the power supply ends can interact information in the communication network to compensate for voltage deviation while ensuring current sharing accuracy. However, existing distributed secondary control methods all assume that the communication network is ideal and unconstrained, and do not consider the problems of limited communication network rate and energy constraints. Summary of the Invention

[0003] In view of the above defects or improvement requirements of the prior art, the present invention provides a distributed secondary regulation method and device based on quantized states and event-triggered communication, aiming to reduce the burden of network communication in DC microgrids.

[0004] To achieve the above object, according to one aspect of the present invention, a distributed secondary regulation method based on quantized states and event-triggered communication is provided, including:

[0005] S1. Establish a hierarchical control framework for each distributed power source and a communication network between the distributed power sources;

[0006] S2. Use the difference between the real-time value of the local state observer of converter i and the value at the previous event-triggered moment as the state measurement error. When the state measurement error reaches a set threshold, an event is triggered, and at the same time, the state measurement error is cleared;

[0007] S3. Quantify the transmitted state at the event triggering moment;

[0008] S4. Design a secondary controller based on the quantified signal and add it to the droop control to obtain an updated voltage reference value;

[0009] S5. Repeat steps S3 - S4 until the bus voltage reaches the reference value and each converter achieves the desired current sharing.

[0010] Furthermore, the event trigger function is:

[0011]

[0012] where sup represents the supremum, represents the k - th event triggering moment of the i - th converter, ∈ i represents the threshold of event triggering, e i is the state measurement error, representing the gap between the real - time value of the observer and the value at the previous event triggering moment.

[0013] Furthermore, the specific process of quantifying the transmitted state is:

[0014]

[0015] q s (x) is a new quantizer combining logarithmic and uniform quantization strategies, where x represents the input of the quantizer, and where represents the largest integer less than or equal to a, Δ = |q l (x th ) - x th | is the uniform quantizer parameter, q l (·) represents the logarithmic quantizer, x th represents the threshold at which the quantizer switches between the uniform quantization scheme and the logarithmic quantization scheme.

[0016] Furthermore, the specific expression of the secondary controller is:

[0017]

[0018] V i d is the virtual voltage drop, is the value of the local state observer, q s (·) is the quantizer, κ is a positive constant, a ij is an element in the adjacency matrix of the communication network graph, t k is the event triggering moment.

[0019] The present invention also provides a distributed secondary regulation device based on quantization state and event-triggered communication, including:

[0020] A hierarchical control and communication network construction module, configured to establish a hierarchical control framework for each distributed power source and a communication network among the distributed power sources;

[0021] An event trigger module, configured to use the difference between the real-time value of the local state observer of converter i and the value at the previous event trigger moment as the state measurement error, trigger an event when the state measurement error reaches a set threshold, and at the same time clear the state measurement error;

[0022] A signal quantization module, configured to quantize the transmitted state at the event trigger moment;

[0023] A secondary control module, configured to design a secondary controller based on the quantized signal and add it to the droop control to obtain an updated voltage reference value;

[0024] An iterative execution module, configured to repeatedly execute the functions of the event trigger module, the signal quantization module, and the secondary control module until the bus voltage reaches the reference value and each converter achieves the desired current distribution.

[0025] Generally speaking, compared with the prior art by the above technical solution conceived by the present invention, the following beneficial effects can be achieved.

[0026] Based on the traditional droop control, the present invention designs a distributed secondary regulation method, which combines state quantization and event-triggered communication strategies, can not only achieve two control objectives of the DC microgrid simultaneously, but also effectively reduce the communication frequency between nodes and relieve the burden on the communication network.

[0027] Compared with the existing distributed secondary control methods, the present invention takes into account the capacity limitation of the communication network. The communication network only transmits discrete values after state quantization, occupying less bandwidth. In addition, the transmission of information only occurs at the event trigger moment, rather than continuously or periodically, reducing the number of communications. The combination of the above two jointly relieves the burden on the communication network, and proves and excludes the Zeno phenomenon, verifying the feasibility of the present solution; in addition, since this method does not require the DC bus voltage as a feedback signal, the design process is simple and easy to implement; the selection of control parameters is very flexible, and a full balance can be achieved between control performance and communication burden by adjusting the corresponding parameters. Description of the Drawings

[0028] Figure 1 It is a hierarchical control structure diagram of a DC microgrid based on quantization state interaction;

[0029] Figure 2The secondary regulation design diagram proposed by the present invention;

[0030] Figure 3 The quantizer function relationship mapping diagram selected by the present invention. Specific implementation manners

[0031] In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0032] The method of the present invention includes the following steps:

[0033] Step 1: For each DC / DC bidirectional converter, establish a hierarchical control framework for the DC microgrid;

[0034] As Figure 1 shown. Where V i and I i are respectively the output voltage and output current of the i-th DC / DC converter, i = 1, 2... N, the DC bus voltage is V B , the rated voltage of the power supply end is V s , and the impedance of the transmission line is R i . The hierarchical control framework includes primary control and secondary control, where the primary control includes voltage-current double-loop PI control and droop control. In the primary control, the reference voltage V i ref provides an interface for regulating the entire DC microgrid. The reference voltage is designed as:

[0035] V i ref = V * - k i I i + u i

[0036] where, V * is the rated voltage of the DC microgrid, k i is the droop control coefficient, and u i is the secondary control signal. Combining Kirchhoff's law, the bus voltage can be obtained as:

[0037] V B = V * -(R i + k i )I i + u i

[0038] Denote the “virtual voltage drop” as V i d =(R i +k i )I i , the above formula can be simplified to:

[0039] V B =V * -V i d +u i

[0040] The purpose of this method is to achieve voltage regulation and current distribution of the microgrid by controlling the converter on the power supply side. Ensure that the bus voltage reaches the rated voltage value, and at the same time ensure that the output current of the distributed energy nodes is distributed according to a predetermined ratio, that is, achieve:

[0041] V B =V *

[0042]

[0043] Meanwhile, the limitations such as bandwidth and rate in the actual communication network need to be considered.

[0044] Step 2: Establish a communication network among the distributed power sources; use the figure to describe the communication network among the converters; is the set of nodes, and the element i in it represents the i-th node, represents the edge of the figure , represents the adjacency matrix, and its definition is as follows:

[0045]

[0046] is the set of neighbors of node i, that is, the set of all nodes that can interact with node i; L is the Laplacian matrix of the graph, and its elements are:

[0047]

[0048] If there is a path between any two nodes in the graph, then the graph is called strongly connected.

[0049] As Figure 2 shown, establish a communication network among N DC converters. This network is restricted, that is, the number of bits and the rate are both limited, which is more in line with practical applications. The local converter i communicates with its neighbor converter j, j ∈ N i , and obtains the signal to achieve local state estimation.

[0050] Step 3: Design an event-triggering function based on the state measurement error:

[0051] First, according to the value of the state observer Define the state measurement error as:

[0052]

[0053] where is the value of the local state observer of converter i, and the state measurement error e i represents the difference between the real-time value of the observer and the value at the previous event-triggering moment.

[0054] By monitoring the magnitude of the state measurement error e i Design the event-triggering function as:

[0055]

[0056] where sup represents the supremum, represents the k-th event-triggering moment of the i-th converter, ∈ i represents the threshold for event triggering.

[0057] If this deviation reaches the set threshold ∈ i , then the event is triggered, and at the same time, the state measurement error e i is cleared, and then the monitoring of the next event trigger is carried out. Therefore, this event-triggering function can ensure that the state measurement error is always less than or equal to the threshold ∈ i , and is cleared at each event-triggering moment. This limitation plays a very important role in the convergence of the state observer and the realization of the system control objective. The threshold ∈ i can be dynamically adjusted. It can be intuitively seen that the smaller its value, the more frequent the event trigger, and the better the corresponding control performance. On the contrary, the fewer the trigger times, the worse the control performance.

[0058] It should be noted that the system operates in a steady state most of the time, so the error will not fluctuate violently, that is, the event will not be triggered frequently. Therefore, compared with traditional continuous communication, adopting the event-triggering strategy can reduce the number of signal transmissions and relieve the burden on the communication network.

[0059] In addition, to meet the feasibility requirements, infinite triggering within a finite time (Zeno phenomenon) needs to be excluded. By proving that there is a lower bound on the time interval between any two event triggers, the Zeno phenomenon can be excluded.

[0060] Different from traditional fixed communication methods, event-triggered control performs signal sampling and transmission when the triggering condition is reached. Therefore, it is possible to trigger infinitely many times within a finite time (Zeno phenomenon), which is not desirable for communication resources and devices. Therefore, it is necessary to prove that there is a lower bound on the time interval between any two event triggers to rule out the Zeno phenomenon.

[0061] At time within, according to the inherent characteristics of the event-triggering function, we can obtain:

[0062]

[0063]

[0064] Combined with the system's dynamic equation and controller design, we have:

[0065]

[0066] where \(c_0\) is a constant related to system parameters such as \(\in\) i , \(\Delta\) q , etc. Combining the above three equations, we can obtain: Thus, the Zeno phenomenon can be ruled out.

[0067] Step 4: Design the secondary control signal

[0068] Considering the limited network bandwidth and the requirements of digital communication in the actual system, data usually needs to be processed by a quantizer before being transmitted through the network.

[0069] Uniform quantization and logarithmic quantization are two main methods for realizing data quantization. The quantization level of the logarithmic quantizer is variable, which makes it possible to reduce the quantization error when the input signal is relatively small. Correspondingly, as the input signal increases, the quantization level inevitably becomes coarser, which may reduce the performance of the system and even lead to instability. The quantizer \(q\) s (·) adopted in the present invention combines a logarithmic quantizer and a uniform quantizer. Specifically, it adopts a logarithmic quantization strategy when the input signal is small and a uniform quantization strategy when the input signal is large. In this way, the advantages of the two quantizers can be fully combined to obtain better performance than any single quantizer. Its specific design is as follows:

[0070]

[0071] where represents the largest integer less than or equal to \(a\), \(\Delta = |q\) l (x th ) - x th| is the parameter of the uniform quantizer, q l (·) represents the logarithmic quantizer, and its form is as follows:

[0072]

[0073] The value range of the logarithmic quantizer is Γ = {±ω (i) : ω (i) = ρ i ω (0) , i = 0, ±1, ±2,...} ∪ {0}, where ρ ∈ (0, 1), ω (0) > 0, In addition, the quantization error satisfies:

[0074]

[0075] The quantizer q s (·)'s function mapping diagram is as Figure 3 shown.

[0076] As Figure 2 shown, the secondary controller designed by this method can be given by the following formula:

[0077]

[0078] where κ is a positive constant, a ij is an element in the adjacency matrix of the communication network graph; t k is the event trigger moment determined in step 3, q s (·) is the quantizer, which is an odd function, and its mapping relationship in the first quadrant is as Figure 3 shown, and it maps the values in the continuous space to the discrete space; is the value of the local state observer, and will finally converge to the mean value of the virtual voltage drop V i d , that is Also because So Combined with V i d =(R i + k i )I i It can be known that:

[0079]

[0080] The goal of current sharing is achieved, where k i >> R i . Substitute the designed secondary control signal into the local reference voltage expression. With the interaction and information update among nodes, the regulation of the bus voltage and current sharing are finally realized.

[0081] The distributed secondary controller of the microgrid proposed by the present invention can achieve the control objectives of the DC microgrid in a limited communication network. Specifically, the method quantifies the state before transmission, which can reduce the communication bandwidth it occupies; in addition, the transmission of the state is determined by an event trigger function, rather than continuous or at a fixed period, which can reduce the frequency of communication. Therefore, this method can reduce the dependence of the controller on the communication network, improve the fault tolerance and reliability of the system; this method does not require the DC bus voltage as a feedback signal, making its operation simple when put into use and can better ensure the stable operation of the DC microgrid; the selection of control parameters is very flexible, and by adjusting the corresponding parameters, a balance can be made between control performance and communication burden, making the DC microgrid operate more economically.

[0082] Those skilled in the art can easily understand that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent replacements, and improvements made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A distributed secondary regulation method based on quantization state and event-triggered communication, characterized in that Including: S1. Establish a hierarchical control framework for each distributed power source and a communication network among the distributed power sources; S2. Take the difference between the real-time value of the local state observer of the converter and the value at the previous event trigger moment as the state measurement error. When the state measurement error reaches the set threshold, trigger an event and clear the state measurement error at the same time; S3. Quantify the transmitted state at the event trigger moment; S4. Based on the interaction of the quantified signals in the communication network, design a secondary controller and add it to the droop control to obtain an updated voltage reference value; S5. Repeat steps S3 - S4 until the bus voltage reaches the reference value and each converter achieves the desired current distribution; The event trigger function is: where sup represents the supremum, represents the th event triggering moment of the th converter, represents the threshold for event triggering, is the state measurement error, representing the gap between the real-time value of the observer and the value at the previous event triggering moment; The specific process of quantifying the transmitted state is: is a novel quantizer that combines logarithmic and uniform quantization strategies, where represents the input of the quantizer, represents the largest integer less than or equal to the maximum integer, , is the parameter of the uniform quantizer, represents the logarithmic quantizer, represents the threshold at which the quantizer switches between the uniform quantization scheme and the logarithmic quantization scheme.

2. The distributed secondary regulation method based on quantization state and event-triggered communication according to claim 1, characterized in that The specific expression of the secondary controller is: is the virtual voltage drop, is the value of the local state observer, is the quantizer, is a positive constant, is an element in the adjacency matrix of the communication network graph, is the event triggering time.

3. A distributed secondary regulation device based on quantization state and event-triggered communication, characterized in that, Including: The hierarchical control and communication network construction module is used to establish a hierarchical control framework for each distributed power source and a communication network among the distributed power sources; An event trigger module for a converter uses the difference between the real-time value of the local state observer and the value at the previous event trigger moment as the state measurement error. When the state measurement error reaches a set threshold, an event is triggered and at the same time the state measurement error is cleared; The signal quantification module is used to quantify the transmitted state at the event trigger moment; The secondary control module is used to design a secondary controller based on the quantified signals and add it to the droop control to obtain an updated voltage reference value; The iterative execution module is used to repeatedly execute the functions of the event trigger module, the signal quantification module, and the secondary control module until the bus voltage reaches the reference value and each converter achieves the desired current distribution; The event trigger function is: where sup represents the supremum, represents the th event triggering moment of the th converter, represents the threshold for event triggering, is the state measurement error, representing the gap between the real-time value of the observer and the value at the previous event triggering moment; The specific process of quantifying the transmitted state is: is a novel quantizer that combines logarithmic and uniform quantization strategies, where represents the input of the quantizer, where represents the largest integer less than or equal to , , is the parameter of the uniform quantizer, represents the logarithmic quantizer, represents the threshold at which the quantizer switches between the uniform quantization scheme and the logarithmic quantization scheme.

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