Island DC micro-grid electricity-hydrogen hybrid energy storage hierarchical cooperative control method considering communication time delay

Abstract

The invention provides an isolated island direct current micro-grid electricity-hydrogen hybrid energy storage layered cooperative control method considering communication time delay. The method comprises the following steps: firstly, establishing droop control based on power frequency division, and distributing a high-frequency component of unbalanced power of a system to storage battery energy storage and a low-frequency component to hydrogen energy storage according to dynamic characteristics of storage battery energy storage and hydrogen energy storage; then designing a consistency variable for average voltage recovery and energy storage power sharing; designing a global consistency variable average estimator for dynamic compensation of the communication time delay, and estimating an average value of global consistency variables according to the consistency variables and the communication time delay information; based on the average value, a self-adaptive consistency algorithm is adopted to generate a secondary control signal; and finally, constructing a system small signal model, and analyzing the tolerable maximum communication delay boundary of the secondary control signal according to the model. According to the invention, dynamic power distribution, energy balance and bus voltage stabilization of electricity-hydrogen hybrid energy storage can be realized under a non-ideal communication condition.

Description

Technical Field

[0001] This invention belongs to the field of coordinated control technology for islanded DC microgrid electric-hydrogen hybrid energy storage systems, and particularly relates to a hierarchical coordinated control method for islanded DC microgrid electric-hydrogen hybrid energy storage systems that takes into account communication latency. Background Technology

[0002] Isolated DC microgrids need to be connected to energy storage systems to maintain power balance and voltage stability. While single-type energy storage can provide fast response, the battery capacity is limited, and frequent charging and discharging can affect battery life.

[0003] Hydrogen energy storage, as an emerging green energy technology, boasts an energy density several to tens of times higher than battery energy storage, effectively overcoming the capacity limitations of battery storage. Compared to single-type energy storage, the control objectives of distributed electric-hydrogen hybrid energy storage systems (HESS) are more complex. They not only require consideration of power coordination control and bus voltage stability among different sets of electric-hydrogen HESS systems, but also the differences in dynamic response, energy characteristics, and lifetime degradation mechanisms among different types of energy storage components.

[0004] To achieve the above objectives, a distributed control method based on consensus algorithms is usually used to control each group of HESS. However, the distributed control method is affected by network communication delays, causing each energy storage unit to receive asynchronous information, which leads to consensus algorithm divergence, resulting in energy storage power allocation errors and system voltage instability.

[0005] Therefore, it is necessary to study the hierarchical collaborative control strategy of HESS (Hydrogen-Electricity Synchronous Array) for isolated DC microgrids. Summary of the Invention

[0006] This invention proposes a hierarchical collaborative control method for hybrid electric-hydrogen energy storage in islanded DC microgrids, taking into account communication latency, to solve the problems existing in the prior art.

[0007] To achieve the above objectives, this invention provides a hierarchical collaborative control method for hybrid electric-hydrogen energy storage in islanded DC microgrids, taking into account communication latency, comprising the following steps:

[0008] Establish a droop control based on power frequency division. According to the dynamic characteristics of battery energy storage and hydrogen energy storage, the high-frequency component of the unbalanced power of the system is allocated to battery energy storage and the low-frequency component is allocated to hydrogen energy storage.

[0009] Based on the bus voltage and energy storage status, a consistency variable is constructed for average voltage recovery and energy storage power sharing;

[0010] Design a global consistency variable average estimator for dynamic compensation of communication delay, and estimate the average value of the global consistency variable based on the consistency variable and communication delay information;

[0011] Based on the average value output of the global consensus variable average estimator, an adaptive consensus algorithm is used to generate a secondary control signal;

[0012] Construct a small-signal model of the system, and analyze the maximum communication delay boundary that the secondary control signal can tolerate based on the small-signal model.

[0013] Optionally, establishing droop control based on power frequency division includes:

[0014] A filter is constructed based on the virtual capacitance droop coefficient of the battery energy storage and the virtual resistance droop coefficient of the hydrogen energy storage.

[0015] Based on the frequency response characteristics of the filter, the unbalanced current flowing into the hybrid energy storage system is separated by frequency;

[0016] The high-frequency component is assigned to the battery energy storage response, and the low-frequency component is assigned to the hydrogen energy storage response.

[0017] Optionally, the consistency variables designed for average voltage recovery and energy storage power sharing include:

[0018] Based on the voltage of each bus, a voltage consistency variable is designed to estimate the average bus voltage;

[0019] Based on the state of charge of the battery energy storage and the state of hydrogen storage, the power sharing state variables of the battery energy storage and the power sharing state variables of the hydrogen energy storage are designed respectively.

[0020] The state variables are used to achieve a balanced power distribution among the battery energy storage units and among the hydrogen energy storage units according to their states.

[0021] Optionally, the global consistency variable averaging estimator for dynamic compensation of communication delay includes:

[0022] The consistency error is calculated based on the local consistency variables and the delay consistency variables from neighboring nodes.

[0023] An additional consistency variable is introduced, and the error caused by communication delay is dynamically compensated based on the consistency error and the additional consistency variable of the neighboring nodes.

[0024] The average estimate of the globally consistent variable is obtained by integrating the compensated error.

[0025] Optionally, the step of generating the secondary control signal using an adaptive consensus algorithm includes:

[0026] The deviation is calculated based on the average value output by the global consistency variable average estimator and the corresponding local consistency variable;

[0027] A sign function is introduced into the deviation, and the secondary control signal is generated based on the sign function and preset control parameters;

[0028] The secondary control signal is used to correct the voltage reference value in the droop control.

[0029] Optionally, the step of generating the secondary control signal specifically includes:

[0030] The voltage correction term and the power correction term are calculated based on the average value of the output of the global consistency variable average estimator.

[0031] The secondary control signal is synthesized based on the voltage correction term, the power correction term, and the preset control gain.

[0032] Optionally, the step of analyzing the maximum communication delay boundary that the secondary control signal can tolerate based on the small-signal model includes:

[0033] The hierarchical collaborative control system is linearized at the system's steady-state operating point to obtain the small-signal model.

[0034] Performing a Laplace transform on the small-signal model yields a characteristic equation containing a time delay exponent term;

[0035] Analyze the critical eigenvalues ​​of the characteristic equation at the stability boundary, and calculate the maximum communication delay boundary based on the critical eigenvalues.

[0036] Optionally, the method further includes:

[0037] Based on the maximum communication delay boundary and the preset control gain, the control parameters in the adaptive consensus algorithm are adjusted to maintain system stability.

[0038] Compared with the prior art, the present invention has the following advantages and technical effects:

[0039] This invention, by introducing a globally consistent variable averaging estimator that considers time delay compensation and a secondary controller based on an adaptive consensus algorithm into a hierarchical collaborative control framework, can effectively suppress the adverse effects of communication delay on the stability of distributed control, significantly improve the robustness and dynamic response coordination capability of islanded DC microgrids under non-ideal communication conditions, realize efficient power coordination and energy balance management between battery energy storage and hydrogen energy storage, ensure rapid recovery and stable operation of the system bus voltage, and take into account the differences in dynamic characteristics and service life of different types of energy storage devices. It provides an effective control solution for the reliable and economical operation of DC microgrids containing hybrid electric-hydrogen energy storage. Attached Figure Description

[0040] The accompanying drawings, which form part of this application, are used to provide a further understanding of this application. The illustrative embodiments and descriptions of this application are used to explain this application and do not constitute an undue limitation of this application. In the drawings:

[0041] Figure 1 This is a diagram of an islanded microgrid structure containing multiple sets of electric-hydrogen HESS according to an embodiment of the present invention;

[0042] Figure 2 This is a diagram illustrating the hierarchical control strategy architecture of the electro-hydrogen HESS according to an embodiment of the present invention.

[0043] Figure 3 This is an overall flowchart of the control strategy according to an embodiment of the present invention;

[0044] Figure 4 The following are experimental diagrams of the power response of the electric-hydrogen HESS under a communication delay boundary of 10ms according to an embodiment of the present invention, wherein (a) is the power response diagram of the first group of HESS, (b) is the power response diagram of the second group of HESS, (c) is the power response diagram of the third group of HESS, and (d) is the power response diagram of the fourth group of HESS.

[0045] Figure 5 This is a diagram illustrating the power response of a distributed HESS according to an embodiment of the present invention.

[0046] Figure 6 This is an experimental diagram of bus voltage variation under a communication delay boundary of 10ms according to an embodiment of the present invention;

[0047] Figure 7 This is a graph showing the average bus voltage curves under different time delay boundaries in an embodiment of the present invention. Detailed Implementation

[0048] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0049] It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0050] Example 1

[0051] like Figure 3 As shown, this embodiment provides a hierarchical collaborative control method for an islanded DC microgrid with hybrid electric-hydrogen energy storage that takes into account communication latency, including the following steps:

[0052] Establish a droop control based on power frequency division. According to the dynamic characteristics of battery energy storage and hydrogen energy storage, the high-frequency component of the unbalanced power of the system is allocated to battery energy storage and the low-frequency component is allocated to hydrogen energy storage.

[0053] Based on the bus voltage and energy storage status, a consistency variable is designed for average voltage recovery and energy storage power sharing;

[0054] Design a global consistency variable average estimator for dynamic compensation of communication delay, and estimate the average value of the global consistency variable based on the consistency variable and communication delay information;

[0055] Based on the average value output of the global consensus variable average estimator, an adaptive consensus algorithm is used to generate a secondary control signal;

[0056] Construct a small-signal model of the system, and analyze the maximum communication delay boundary that the secondary control signal can tolerate based on the small-signal model;

[0057] Based on the maximum communication delay boundary and the preset control gain, the control parameters in the adaptive consensus algorithm are adjusted to maintain system stability.

[0058] Specifically, the following steps are included:

[0059] Step 1: Propose a dynamic power allocation method for the electric-hydrogen HESS based on frequency division droop control;

[0060] Establishing droop control based on power frequency division includes: constructing a filter based on the virtual capacitance droop coefficient of the battery energy storage and the virtual resistance droop coefficient of the hydrogen energy storage; separating the unbalanced current flowing into the hybrid energy storage system according to frequency based on the frequency response characteristics of the filter; allocating the high-frequency component to the battery energy storage response and the low-frequency component to the hydrogen energy storage response.

[0061] In an electric-hydrogen energy storage system (HESS), batteries have a fast response speed but low energy density, making them suitable for handling high-frequency, instantaneous power fluctuations; hydrogen storage has a slow response speed but high energy density, making it suitable for handling low-frequency, continuous power fluctuations. Considering these characteristics, this paper proposes a power frequency division droop control strategy to achieve coordinated power distribution and balanced response speed in an electric-hydrogen HESS.

[0062] Define the current flowing into the i-th HESS as If the direction of current flowing from the bus into the converter is defined as the positive direction, then the droop control equations for the BSU and HSU (including the electrolyzer and fuel cell) are as follows:

[0063] (1)

[0064] In the formula, This is the voltage reference value; and These are the output voltage and output current of the battery energy storage, respectively. and These are the output voltage and output current of the AEL electrolytic cell, respectively. and These are the output voltage and output current of the fuel cell, respectively. This is the virtual capacitance droop factor; This is the virtual resistance droop factor; This represents the unbalanced current flowing into the HESS.

[0065] In steady state, the voltages of battery energy storage and hydrogen energy storage are the same. Therefore, the current distribution relationship between battery energy storage and hydrogen energy storage is as follows:

[0066] (2)

[0067] In the formula, , and This represents the transfer function.

[0068] In equation (2), Its function is similar to a high-pass filter, that is, the battery energy storage is responsible for responding to the high-frequency components in the unbalanced current; , Its function is similar to a low-pass filter, meaning that the electrolyzer and fuel storage are responsible for responding to the low-frequency components in the unbalanced current.

[0069] In the frequency division droop control strategy, the virtual resistor and the virtual capacitor together form an RC filter, and the frequency response characteristics of this filter are shown in the following equation:

[0070] (3)

[0071] In the formula, This is the angular frequency of the filter; is the time constant.

[0072] The corner frequency is a key parameter in filter design, closely related to the overall system response speed. As the corner frequency changes, the response speed of the HESS also changes. Increasing the corner frequency speeds up the system response, while decreasing it slows it down. In practical applications, while ensuring the overall HESS response speed, the slow dynamic characteristics of the electrolyzer should also be fully considered, and the system's corner frequency should be selected according to the manufacturer's specifications to extend the equipment's lifespan.

[0073] Step 2: Design of Consistency Variables;

[0074] Design consistency variables include:

[0075] Based on the voltage of each bus, a voltage consistency variable is designed to estimate the average bus voltage; based on the state of charge of battery energy storage and the state of hydrogen storage, power sharing state variables for battery energy storage and hydrogen energy storage are designed respectively; the state variables are used to achieve power distribution between battery energy storage and hydrogen energy storage according to state.

[0076] In a multi-bus DC microgrid, the droop control in step 1 and the presence of line impedance will cause the voltage of each node to deviate from its rated value. To reduce the bus voltage deviation, secondary voltage compensation is required for the voltage reference value in the HESS droop control equation. When line impedance exists, controlling all bus voltages to their rated values ​​will affect the power distribution of the droop control. Therefore, the average voltage of each node is usually controlled at its rated value. To achieve average bus voltage control, a voltage observer based on a consensus algorithm can be used to estimate the average bus voltage, as shown in the following expression:

[0077] (4)

[0078] In the formula, The average voltage estimated by the voltage observer; For communication weights.

[0079] Under the condition of an integrator initial value of 0 and ideal communication, the average voltage estimate of each bus in steady state. It converges to the arithmetic mean of all bus voltages, i.e. Based on the obtained average voltage estimate, in order to ensure the voltage quality of the microgrid, the average voltage of each bus should be restored to the rated voltage of the bus, i.e., to achieve... The voltage control target.

[0080] System Occurrence (SoC) is a key indicator for measuring the degree of battery charge and discharge. To avoid overcharging and over-discharging of individual cells, SoC management needs to be considered in the secondary control strategy of the electric-hydrogen HESS. However, if the initial SoC values ​​of each energy storage unit are different, directly controlling the SoC of each unit to be consistent will lead to mutual charging and discharging between batteries, causing circulating currents and resulting in reduced battery efficiency and lifespan. To avoid this phenomenon, this paper defines a state variable for shared energy storage power. As shown in the following formula:

[0081] (5)

[0082] In the formula, Let i be the output power of the i-th battery; Let be the rated capacity of the i-th battery; , These are the upper and lower limits for the i-th battery SoC, respectively.

[0083] Similarly, the state of hydrogen storage (SoH) is an important indicator characterizing the energy storage and utilization efficiency of the hydrogen storage unit (HSU). Both excessively low and excessively high SoH values ​​will affect the HSU's electro-hydrogen energy conversion efficiency and shorten its lifespan. Therefore, a state variable for hydrogen energy storage power sharing is defined. As shown in the following formula:

[0084] (6)

[0085] In the formula, The net output power of hydrogen energy storage, ; Let be the rated pressure of the i-th hydrogen storage tank; , These are the upper and lower limits of SoH for the i-th hydrogen storage tank, respectively.

[0086] Taking the energy storage and discharge process as an example, in the power state variable , Under this influence, energy storage cells with larger SoC(SoH) will increase their output power, resulting in a faster SoC(SoH) decay rate; energy storage cells with smaller SoC(SoH) will decrease their output power, resulting in a slower SoC(SoH) decay. During this process, the SoC(SoH) of each cell will not completely converge, but will converge in the same direction.

[0087] when ; At that time, the state variables of BSU and HSU state variables The unbalanced power of the system tends to be consistent, thereby achieving the control objective of allocating the unbalanced power of each HESS group according to SoC (SoH).

[0088] Step 3: Design a globally consistent variable average estimator model for dynamic compensation of communication delay;

[0089] The design of a globally consistent variable averaging estimator for dynamic compensation of communication delay includes:

[0090] The consistency error is calculated based on the local consistency variable and the latency consistency variable information from neighboring nodes. An additional consistency variable is introduced, and the error caused by communication latency is dynamically compensated based on the consistency error and the additional consistency variables from neighboring nodes. The average estimated value of the global consistency variable is obtained by integrating the compensated error.

[0091] Specifically, as shown in step 2, the secondary control objective of this system is to achieve power sharing among the HESS groups and restore the average bus voltage to its rated value. Therefore, a voltage correction term is introduced. and power correction terms Then the secondary voltage control variable It can be represented as:

[0092] (7)

[0093] In the formula, , is the secondary voltage compensation term; This is a voltage correction term; This is a power correction term; To control the gain; This is a bias variable used to combine the two independent control objectives of voltage recovery and power sharing into a single control signal, thereby simplifying the controller structure. The voltage correction term... and power correction terms As shown in the following formula:

[0094] (8)

[0095] In the formula, This is the average voltage estimate; This is a reference estimate for the state variable. When hour and When the values ​​of the two components approach zero, the controller converges, and the system reaches a steady state.

[0096] Substituting equation (8) into equation (7), we obtain the following equation:

[0097] (9)

[0098] In the formula, , All calculations must be performed using a consistent variable estimator. Under the action of frequency division droop control, in steady state, the electro-hydrogen HESS maintains system power balance through hydrogen energy storage, and the output power of the electrical energy storage is 0. It can be seen that in steady state... , .

[0099] To simplify the structure of the consistency variable average estimator, a global consistency variable for the electric-hydrogen HESS is defined. As shown in the following formula:

[0100] (10)

[0101] In the formula, Let be the estimated average voltage of the bus where the i-th HESS is located at time t; Let be the average estimated value of the state variables of hydrogen energy storage in the i-th HESS at time t. In steady state, the for each group of electro-hydrogen HESS... , They tend to converge.

[0102] Based on the above analysis, in order to achieve global consistency variable estimation under non-ideal communication, this invention proposes a global consistency variable averaging estimator for the electric-hydrogen HESS, as shown in the following equation:

[0103] (11)

[0104] In the formula, , representing the average estimate of the i-th HESS global consistency variable; Input variables locally; , To control the gain, all values ​​are greater than 0; For communication weights; An additional consistency variable is added to receive and offset errors caused by communication delays. This includes local input variables. It can be represented as:

[0105] (12)

[0106] Under non-ideal communication conditions, the proposed observer equation (11) has strong robustness and can still converge to the average value of the uniformity variables with zero steady-state error even with time delay information, as shown in the following equation:

[0107] (13)

[0108] Step 4: Propose a secondary control method for the electric-hydrogen HESS based on an adaptive consensus algorithm;

[0109] Furthermore, the generation of the secondary control signal using the adaptive consensus algorithm includes:

[0110] The deviation is calculated by comparing the average value output by the global consistency variable average estimator with the corresponding local consistency variable. A sign function is introduced into the deviation, and a secondary control signal is generated based on the sign function and preset control parameters. The secondary control signal is used to correct the voltage reference value in the droop control.

[0111] Specifically, the voltage correction term and the power correction term are calculated based on the average value of the output of the global consistency variable average estimator.

[0112] A secondary control signal is synthesized based on the voltage correction term, the power correction term, and the preset control gain.

[0113] Specifically, under the action of the estimator proposed in step 3, the system state variables eventually converge. However, as the communication delay boundary increases, the convergence time of the estimator slows down, and the system stability deteriorates. To reduce the convergence time and transient deviation of the state variables, this paper designs a distributed electric-hydrogen HESS secondary control strategy with fast convergence under communication delay based on the idea of ​​finite-time consistent convergence. The secondary controller design of the BSU is shown in the following equation:

[0114] (14)

[0115] The secondary controller design of the HSU is shown in the following formula:

[0116] (15)

[0117] In the formula, the function ; For control parameters, ; The symbolic function is shown in the following equation:

[0118] (16)

[0119] Under the action of the consistency variable observer, the steady-state convergence values ​​of the global consistency variables of BSU and HSU are shown in the following equation:

[0120] (17)

[0121] In the formula, , These represent the steady-state values ​​of the globally consistent variables for BSU and HSU, respectively. This represents the steady-state voltage value of bus i; This represents the steady-state value of the power state variable of the HSU.

[0122] Substituting equation (17) into equations (14) and (15), we get:

[0123] (18)

[0124] From the above equation, it can be seen that, in steady state, each HESS group in the microgrid satisfies , The busbars connected to each HESS group meet the requirements. This enables energy balance in the electro-hydrogen HESS and recovery control of average voltage deviation across multiple buses.

[0125] Step 5: Construct a small-signal model of the system and analyze the upper bound of the delay that the controller can tolerate;

[0126] The steps for analyzing the maximum communication delay boundary based on the small-signal model include:

[0127] The hierarchical collaborative control system is linearized at the steady-state operating point of the system to obtain a small-signal model; the small-signal model is then subjected to a Laplace transform to obtain a characteristic equation containing a time delay exponential term; the critical eigenvalues ​​of the characteristic equation at the stability boundary are analyzed, and the maximum communication time delay boundary is calculated based on the critical eigenvalues.

[0128] Specifically, such as Figure 2 As shown, the proposed electric-hydrogen HESS control strategy consists of a primary control layer and a secondary control layer. The primary control layer comprises frequency division droop control and voltage-current dual closed-loop control, independent of communication, and is responsible for generating PWM control signals to apply to the converter, thereby achieving fast response of the electric-hydrogen HESS and balancing power fluctuations between the power source and load in the microgrid. The secondary control layer is a secondary voltage control that takes into account communication delays, responsible for generating the upper-level control signals for the HESS. and This corrects the reference voltage value in the frequency division droop control, achieving power balance and bus voltage control for each HESS group. A small-signal model of the system is constructed based on the control system structure proposed in this invention, as detailed below.

[0129] Linearizing the entire system around its steady-state operating point, we obtain the small-signal model of the system as shown in the following equation:

[0130] (19)

[0131] In the formula, This represents a state variable vector containing system power, bus voltage, and secondary control variables. A vector representing the state variables of the current; , Represents the system state matrix; Represents the state matrix affected by time delay; The input matrix represents the output current of the energy storage unit. The impact on its own state variables.

[0132] According to Kirchhoff's laws, the relationship between the currents at each node can be derived as follows:

[0133] (20)

[0134] In the formula, , These represent the grid-connected admittance for battery energy storage and hydrogen energy storage, respectively. For line admittance; Indicates load power; Indicates the power of distributed power sources; Let i represent the voltage of bus i. Equation (20) can be rewritten in matrix form as follows:

[0135] (twenty one)

[0136] In the formula, , This is the equivalent admittance matrix; ; .

[0137] From equation (21) and the relationship between the port voltage and output current of the energy storage unit The network equation can be obtained as shown in the following formula:

[0138] (twenty two)

[0139] In the formula, , representing the output current of the energy storage unit; ; , representing the port voltage of the energy storage unit.

[0140] To simplify the analysis, a sparse matrix is ​​defined. , making ,make Substituting equation (22) into equation (19), we obtain the complete small-signal model of the system, as shown in the following equation:

[0141] (twenty three)

[0142] In the formula, Applying the Laplace transform to equation (23), we obtain its characteristic equation as shown below:

[0143] (twenty four)

[0144] According to Lyapunov's stability theory, the system is asymptotically stable when all eigenvalues ​​of equation (24) lie to the left of the complex plane. Due to the exponential term... The existence of this equation means that the system has an infinite number of eigenvalues, making it extremely difficult to directly solve for all eigenvalues ​​in the above equation. Therefore, this paper only analyzes the critical eigenvalues ​​that cause the system to change from stable to unstable, without ever determining the upper bound of the critical delay that leads to system instability. .

[0145] When the system is at the boundary between stability and instability, the characteristic equation has at least one pair of conjugate pure imaginary roots. ,in .Will Substituting into equation (24), as shown in the following equation:

[0146] (25)

[0147] The critical frequency in the above formula is derived using the direct method. and critical delay The characteristic root locus of equation (25) is shown in the following equation:

[0148] (26)

[0149] when When the characteristic roots cross the imaginary axis to the right, the system changes from stable to unstable; when When the characteristic root crosses the imaginary axis to the left, the system changes from unstable to stable. Equation (26) can be used to determine the system's time delay tolerance boundary. As shown in the following formula:

[0150] (27)

[0151] In the formula, Indicates all that satisfy of Minimum value.

[0152] The following experiments were also conducted in this embodiment:

[0153] To verify the effectiveness of the method in this invention, simulation experiments were conducted using MATLAB / Simulink software. An islanded DC microgrid model with four busbars was constructed, with distributed generation, a HESS system, and DC loads connected to each busbar. Figure 1 As shown in the figure. The specific simulation parameters are shown in the table below.

[0154] Table 1

[0155]

[0156] In this example, the system's response to step load changes and distributed generation fluctuations is simulated, and the power distribution between battery storage and hydrogen storage in each HESS group is observed. Initially, the output power of each distributed generation is 50 kW, and the load powers on each bus are 30 kW, 40 kW, 30 kW, and 35 kW, respectively. Different levels of power disturbance are set at 5 s, 10 s, and 15 s. Under the condition of a maximum communication delay boundary of 5 ms, the power response of each HESS group in the islanded DC microgrid is as follows: Figure 4 As shown.

[0157] During the first 0-5 seconds, the power output exceeds the load consumption, resulting in a power surplus in the system. This surplus is handled by the battery storage and electrolytic cell. At 5 seconds, a sudden load increase occurs, with the load power connected to each bus increasing by 13kW, 10kW, 15kW, and 10kW respectively. The system still has surplus power, but the energy storage system quickly responds and its power decays to zero. In steady state, the electrolytic cell handles the remaining power. At 10 seconds, the power output of each power source decreases by 30kW, resulting in a power deficit. The electrolytic cell stops operating, and the battery and fuel cell discharge to balance the system power. In steady state, the fuel cell handles all the unbalanced power. At 15 seconds, the load power connected to each bus decreases by 5kW, 7kW, 7kW, and 5kW respectively. The power deficit in the system decreases, and the battery and fuel cell respond rapidly. In steady state, the output power of the fuel cell decreases accordingly. Under the action of frequency division droop control, the fast charging and discharging capability of the high-slope BSU is effectively utilized, reducing the pressure of instantaneous power on the low-slope HSU, thereby giving full play to the complementary advantages of the electric-hydrogen HESS.

[0158] like Figure 5 As shown, when a power disturbance occurs in the system, the battery energy storage power in each HESS group responds rapidly and gradually decays to 0, while the hydrogen energy storage power responds more slowly and gradually converges to a uniform level, converging to the average power value in steady state. This is in accordance with the consistency variable... , Under its influence, all energy storage units can charge or discharge together, thus avoiding circulating current between HESS units.

[0159] The changes in voltage at each bus are as follows: Figure 6 As shown, when power surges occur in an islanded microgrid, the dynamic consistency-based secondary control strategy responds rapidly, effectively suppressing the decrease in DC bus voltage. In steady state, the voltage of each bus can recover to its rated value of around 500V, with a maximum deviation of no more than 3V. Under the influence of consistency variables, the average bus voltage... It can quickly and accurately restore the voltage to the rated voltage of 500V and maintain stability.

[0160] like Figure 7As shown, under the three different maximum delay boundaries of communication delay mentioned above, the distributed HESS control strategy proposed in this paper can ensure that the average bus voltage is accurately restored to the rated value of 500V, while realizing power sharing among the HESS groups. Communication delay does not affect the frequency division droop control characteristics; the electrical and hydrogen energy storage of each HESS group responds to the high-frequency and low-frequency components of the power, respectively, ensuring the operational safety and service life of energy storage devices with different characteristics. However, as the maximum communication delay boundary increases, the resulting transient voltage deviation also gradually increases, and the voltage recovery speed becomes relatively slower.

[0161] Based on step 5, the system under different control gains is calculated. , The maximum tolerable delay boundary is shown in Table 2.

[0162] Table 2

[0163]

[0164] As shown in Table 2, when the control gain is increased... or The maximum tolerable time delay boundary of the system While the control gain is reduced, the system's time delay robustness decreases; when the control gain is reduced... or , The system's latency robustness has improved.

[0165] In summary, this invention proposes a hierarchical collaborative control strategy for an islanded DC microgrid's electric-hydrogen HESS (Hydrogen Energy Saving System) that takes into account communication delay. The proposed control method considers the dynamic response differences between the base station (BSU) and the hydrogen supply unit (HSU), enabling power allocation and energy balance among the electric-hydrogen HESS groups under non-ideal communication conditions, while maintaining voltage stability in the islanded microgrid. The proposed control method has a clear practical background and application value in the research of distributed control methods for electric-hydrogen HESS dynamic response balancing and non-ideal communication conditions.

[0166] The above are merely preferred embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A hierarchical collaborative control method for an islanded DC microgrid electricity-hydrogen hybrid energy storage considering communication time delay, characterized in that, The method comprises the following steps: establishing a droop control based on power frequency division, and distributing high-frequency components of unbalanced power of the system to the battery energy storage and distributing low-frequency components to the hydrogen energy storage according to dynamic characteristics of the battery energy storage and the hydrogen energy storage; designing a consensus variable for average voltage recovery and energy power sharing according to bus voltages and energy storage states; designing a global consensus variable average estimator for dynamic compensation of communication time delay, and estimating an average value of the global consensus variable according to the consensus variable and communication time delay information; generating a secondary control signal by using an adaptive consensus algorithm based on the average value output by the global consensus variable average estimator; constructing a small signal model of the system, and analyzing a maximum communication time delay boundary that can be tolerated by the secondary control signal according to the small signal model.

2. The method of claim 1, wherein, The step of establishing a droop control based on power frequency division comprises: constructing a filter according to a virtual capacitance droop coefficient of the battery energy storage and a virtual resistance droop coefficient of the hydrogen energy storage; separating unbalanced currents flowing into the hybrid energy storage system according to frequency according to frequency response characteristics of the filter; distributing the high-frequency components to the battery energy storage response and distributing the low-frequency components to the hydrogen energy storage response.

3. The method of claim 1, wherein, The step of designing a consensus variable for average voltage recovery and energy power sharing comprises: designing a voltage consensus variable for estimating an average bus voltage according to voltages of buses; designing a battery energy storage power sharing state variable and a hydrogen energy storage power sharing state variable according to a state of charge of the battery energy storage and a hydrogen storage state of the hydrogen energy storage, respectively; The state variables are used to realize equal distribution of power among the battery energy storages and among the hydrogen energy storages according to states.

4. The method of claim 1, wherein, The step of designing a global consensus variable average estimator for dynamic compensation of communication time delay comprises: calculating a consensus error according to a local consensus variable and time delay consensus variable information from neighbor nodes; introducing an additional consensus variable, and dynamically compensating for errors caused by communication time delay according to the consensus error and the additional consensus variable of the neighbor nodes; integrating the compensated error to obtain an average estimation value of the global consensus variable.

5. The method of claim 1, wherein, The step of generating a secondary control signal by using an adaptive consensus algorithm comprises: calculating a deviation according to an average value output by the global consensus variable average estimator and a local corresponding consensus variable; introducing a sign function in the deviation, and generating the secondary control signal according to the sign function and a preset control parameter; The secondary control signal is used to correct a voltage reference value in the droop control.

6. The method of claim 5, wherein, The step of generating a secondary control signal comprises: calculating a voltage correction term and a power correction term according to an average value output by the global consensus variable average estimator; synthesizing the secondary control signal according to the voltage correction term, the power correction term, and a preset control gain.

7. The method of claim 1, wherein, The step of analyzing a maximum communication time delay boundary that can be tolerated by the secondary control signal according to the small signal model comprises: linearizing the hierarchical collaborative control system at a steady-state operating point of the system to obtain the small signal model; performing Laplace transformation on the small signal model to obtain a characteristic equation containing a time delay exponential term; analyzing a critical eigenvalue of the characteristic equation at a stability boundary, and calculating the maximum communication delay boundary according to the critical eigenvalue.

8. The method of claim 1, wherein, The method further comprises: adjusting a control parameter in the adaptive consensus algorithm according to the maximum communication delay boundary and a preset control gain, to maintain system stability.

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