Consistency-based self-adaptive distributed hierarchical control method for energy storage system

Abstract

The invention discloses a consistency-based self-adaptive distributed hierarchical control method for an energy storage system. The method comprises the following steps: establishing a photovoltaic water electrolysis hydrogen production system model consisting of a photovoltaic battery, a lithium battery, an electrolytic bath, a constant-power load and a DC / DC converter; in a communication layer, energy storage units in the system are regarded as agents, an average state estimator is designed based on multi-agent consistency, the average value of state variables is calculated and transmitted to adjacent energy storage units through an adjacent communication network, dependence on a centralized controller is reduced, and communication burden is relieved; in the main control layer, an improved droop control method is adopted, a droop coefficient is improved based on a sigmoid function, load current distribution is adaptively adjusted to achieve charge state balance, and an acceleration factor improved based on a normal distribution function is added; and in a secondary control layer, designing a unit virtual voltage drop balance item, eliminating the influence of line impedance, designing an average bus voltage compensation item, and compensating the average bus voltage to a reference value.

Description

Technical Field

[0001] The present invention belongs to the field of control of new energy microgrid energy storage systems, and relates to an adaptive distributed hierarchical control method for energy storage systems based on consensus, and particularly relates to an adaptive state of charge equalization method for energy storage systems. Background Art

[0002] Under the new situation of the "dual carbon" goal and energy security, the photovoltaic power generation industry has grown rapidly. The randomness and volatility of photovoltaics have led to a large number of "light curtailment" phenomena. At present, establishing an off-grid photovoltaic electrolytic hydrogen production system is regarded as an effective strategy for consuming photovoltaic power, which can eliminate the impact of photovoltaic power generation grid connection on the stability and power quality of the main grid, and at the same time reduce the cost of hydrogen production. Under the condition of lacking the support of the main grid, a photovoltaic hydrogen production system is often configured with an energy storage system to balance the power fluctuations between photovoltaic power generation and electrolysis load. With the expansion of the off-grid hydrogen production scale, the energy storage system usually consists of multiple parallel energy storage units to increase the energy storage capacity and improve the reliability of the energy storage system power supply. At present, the control method of energy storage units often adopts the droop control strategy. However, in long-term operation, the fixed droop coefficient and the difference in line impedance make there an inherent contradiction between voltage drop and accurate current distribution in droop control, which will lead to uneven state of charge of energy storage units. Some energy storage units will prematurely exit operation due to overcharging and over-discharging, affecting the stability of the electrolytic hydrogen production system. Therefore, at the present stage, achieving the state of charge balance of energy storage units is a necessary measure to maintain the stability of the photovoltaic hydrogen production system. This goal can be achieved by formulating and implementing an energy storage system state of charge equalization strategy, realizing accurate shunt by eliminating the influence of line impedance, and setting a compensation term to restore the bus voltage drop. Summary of the Invention

[0003] In order to solve the problems of uneven state of charge of energy storage units, low current distribution accuracy, and bus voltage drop in an off-grid photovoltaic hydrogen production system, the technical solution adopted by the present invention is: an adaptive distributed hierarchical control method for an energy storage system based on consensus, including the following steps:

[0004] Establish a photovoltaic electrolytic water hydrogen production system model composed of a photovoltaic cell, a lithium battery, an electrolyzer, a constant power load, and a DC / DC converter;

[0005] Based on the off-grid photovoltaic electrolytic water hydrogen production system model, an improved droop hierarchical control method for an energy storage system based on multi-agent consensus is used to achieve the state of charge balance of the energy storage system, eliminate the influence of line impedance to achieve accurate shunt, and at the same time restore the bus voltage drop.

[0006] Furthermore: The off-grid photovoltaic electrolytic water hydrogen production system model and the improved droop hierarchical control method for the energy storage system based on multi-agent consensus achieve the balance of the state of charge of the energy storage system, eliminate the influence of line impedance to achieve precise shunt, and restore the bus voltage drop as follows:

[0007] In the communication layer, the energy storage units in the photovoltaic electrolytic water hydrogen production system are regarded as agents. Based on multi-agent consensus, an average state estimation method is designed to calculate the average values of the state of charge of lithium batteries, unit virtual voltage, and output voltage, and the average values are transmitted to adjacent energy storage units through the adjacent communication network;

[0008] In the main control layer, an improved droop control method is adopted. The droop coefficient is improved based on the sigmoid function to achieve adaptive adjustment of the output current distribution of lithium batteries to achieve the balance of the state of charge. An acceleration factor improved based on the normal distribution function is added to accelerate the balance speed of the state of charge of lithium batteries in the later stage;

[0009] In the secondary control layer, a unit virtual voltage drop balance term is designed to eliminate the influence of line impedance and achieve the distribution of output current according to the rated capacity of lithium batteries. An average bus voltage compensation term is designed to compensate the average bus voltage to the reference value.

[0010] Furthermore: The process of adopting the improved droop control method, improving the droop coefficient based on the sigmoid function, achieving adaptive adjustment of the output current distribution of lithium batteries to achieve the balance of the state of charge, and adding an acceleration factor improved based on the normal distribution function to accelerate the balance speed of the state of charge of lithium batteries in the later stage also includes:

[0011] Based on the voltage-current double closed-loop control, in the voltage outer loop, an improved droop control, a unit virtual voltage balance term, and an average bus voltage compensation term are added after the reference voltage. The output voltage of the energy storage unit is the feedback of the voltage loop. The reference current of the current inner loop is obtained through the first PI controller, and then the difference is made with the inductor current of the DC / DC converter. The PWM modulation signal is obtained through the second PI controller. The PWM modulation signal controls the on-off of the IGBT in the DC / DC converter to achieve the rapid balance of the state of charge of lithium batteries, the precise distribution of output current according to the rated capacity, and the compensation of the average bus voltage.

[0012] Furthermore: The process of adopting the improved droop control method, improving the droop coefficient based on the sigmoid function, and achieving adaptive adjustment of the output current distribution of lithium batteries to achieve the balance of the state of charge is as follows:

[0013] When the lithium battery is charging, the difference in the charging depth of each unit is established based on the sigmoid function, that is, the relationship between the difference between the charging depth and its average value and the droop coefficient. At the same time, the ratio of the balance coefficient to the rated capacity is introduced into the droop coefficient;

[0014] When the lithium battery discharges, the relationship between the difference in the depth of discharge of each unit, that is, the difference between the depth of discharge and its average value, and the droop coefficient is established based on the sigmoid function. At the same time, the ratio of the balance coefficient to the rated capacity is introduced into the droop coefficient.

[0015] Further: The process of accelerating the equalization speed of the state of charge of the lithium battery in the later stage by adding an acceleration factor improved based on the normal distribution function is as follows:

[0016] When the lithium battery is charging, an acceleration factor based on the normal distribution function is introduced into the improved droop coefficient. The acceleration factor takes the square value of the charging depth difference as a variable, and at the same time, a regulation factor is added to change the equalization speed in the later stage of the state of charge;

[0017] When the lithium battery discharges, an acceleration factor based on the normal distribution function is introduced into the improved droop coefficient. The acceleration factor takes the square value of the discharge depth difference as a variable, and at the same time, a regulation factor is added to change the equalization speed in the later stage of the state of charge.

[0018] Further: The process of designing the unit virtual voltage drop balance term to eliminate the influence of line impedance and realizing the distribution of the output current according to the rated capacity of the lithium battery is as follows:

[0019] Multiply the droop coefficient by the output current of the energy storage unit to obtain the virtual voltage drop.

[0020] The ratio of the virtual voltage drop to the maximum offset of the bus voltage is the unit virtual voltage drop. A PI controller is used to equalize the unit virtual voltage drop to the average unit virtual voltage drop. The consistency of the unit virtual voltage drops of each energy storage unit makes the output current distribution only related to the droop coefficient, thereby eliminating the influence of line impedance on the accurate shunt of the output current and the equalization of the state of charge. The output current can be distributed proportionally according to the rated capacity of each energy storage unit during the equalization of the state of charge.

[0021] Further: The process of designing the average bus voltage compensation term to compensate the average bus voltage to the reference value is as follows:

[0022] The average bus voltage is the average value of the output voltages of all energy storage units. An integral controller is used to make the average bus voltage tend to the bus voltage reference value to maintain the stability of the bus voltage.

[0023] Further, it is characterized in that: The improved droop coefficient is expressed as:

[0024]

[0025] Where: R vi (S i ), ρ(S i ) and k Dis the improved droop coefficient, variable acceleration factor, and balance factor of energy storage unit i, and μ is the adjustment factor of the acceleration factor; the charge and discharge deviation values ζ and σ are expressed as:

[0026] ζ = S avgi (t) - S i (t) (8)

[0027] σ = D avgi (t) - D i (t) (9)

[0028] Among them, S avgi and D avgi are the dynamic average values of S i and D i of energy storage unit i.

[0029] An adaptive distributed hierarchical control method for a consistency-based energy storage system provided by the present invention is an adaptive hierarchical control strategy for parallel energy storage units in an electrolytic hydrogen production system to improve the reliability of the power supply. In this strategy, distributed communication and a multi-agent consistency design average state estimation method are used to obtain the average value of state variables. In the primary control layer, a sigmoid function is proposed to improve the droop coefficient to achieve state of charge equilibrium, and a new acceleration factor based on the normal distribution function is designed to accelerate the speed of state of charge equilibrium in the later stage. In the secondary control layer, a unit virtual voltage drop equalization term and an average bus voltage compensation term are designed to eliminate the influence of line impedance and restore the average bus voltage deviation. Through stability analysis, it is confirmed that the proposed method has strong stability. Finally, a photovoltaic hydrogen production simulation model is established on the Matlab / Simulink platform to simulate and verify the proposed control strategy. The results show that the proposed control strategy can achieve rapid state of charge balance and accurate load current distribution under various complex operating conditions and has excellent average bus voltage compensation ability. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0031] Figure 1 is the off-grid photovoltaic electrolytic water hydrogen production system that is the research object of the present invention;

[0032] Figure 2 is the adaptive distributed hierarchical control structure of the consistency-based energy storage system proposed by the present invention;

[0033] As shown in Figure 3 (a), the improved droop coefficient R proposed by the present invention vi is a graph showing the variation with the state of charge difference ζ. (b) shows the new acceleration factor ρ(S i ) varying with the state of charge difference ζ;

[0034] Figure 4 is the equivalent linearized model of the control strategy of the present invention taking two energy storage units as an example;

[0035] Figure 5 is the root locus of the important parameters of the system of the present invention. Figure (a) shows the root locus varying with the state of charge difference ΔS = S 1 - S 2 changing. Figure (b) shows the root locus varying with the cut-off frequency ω c changing. Figure (c) shows the root locus varying with the balance factor k D changing. Figure (d) shows the root locus varying with the adjustment factor μ;

[0036] Figure 6 is the simulation result diagram of Case 1 of the present invention. (a) shows the state of charge change curves of three energy storage units in Case 1 of the present invention. (b) shows the output current change curves of three energy storage units in Case 1 of the present invention. (c) shows the average bus voltage change curve in Case 1 of the present invention;

[0037] Figure 7 is the simulation result diagram of Case 2 of the present invention. (a) shows the state of charge change curves of three energy storage units in Case 2 of the present invention. (b) shows the output current change curves of three energy storage units in Case 2 of the present invention. (c) shows the average bus voltage change curve in Case 2 of the present invention;

[0038] Figure 8 is the simulation result diagram of Case 3 of the present invention. (a) shows the state of charge change curves of three energy storage units in Case 3 of the present invention. (b) shows the output current change curves of three energy storage units in Case 3 of the present invention. (c) shows the average bus voltage change curve in Case 3 of the present invention. Detailed implementation manners

[0039] It should be noted that, without conflict, the embodiments in the present invention and the features in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the drawings and in combination with the embodiments.

[0040] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. The following description of at least one exemplary embodiment is actually only illustrative and in no way restricts the present invention and its application or use. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0041] An adaptive distributed hierarchical control method for an energy storage system based on consistency, comprising the following steps:

[0042] S1: Establish an off-grid photovoltaic electrolytic water hydrogen production system model including a photovoltaic cell, a lithium battery, an electrolytic cell, a DC load, and a DC / DC converter through Matlab / Simulink; perform precise simulation construction on the system, and configure appropriate capacities and initial values for each unit;

[0043] S2: Based on the off-grid photovoltaic electrolytic water hydrogen production system model, an improved droop hierarchical control method for the energy storage system based on multi-agent consistency is used to achieve the balance of the state of charge of the energy storage system, eliminate the influence of line impedance to achieve precise shunt, and at the same time restore the bus voltage drop.

[0044] Steps S1 / S2 are executed sequentially;

[0045] As Figure 1 shown is the composition diagram of the off-grid photovoltaic electrolytic water hydrogen production system, which is the object of the distributed hierarchical control method of the energy storage system implemented by itself, and is composed of devices such as a photovoltaic cell, a lithium battery, an electrolytic cell, a DC load, an AC load, and a DC / DC converter. Photovoltaic is a distributed power source, which is connected to the DC bus through an electronic power converter to achieve clean power generation. The energy storage unit is connected to the bus through a bidirectional DC / DC converter to maintain voltage stability and balance the system power fluctuation. At the same time, the DC microgrid can also be connected to the AC grid through a DC / AC converter to achieve the conversion of AC-DC energy. The present invention only considers the island operation mode of the DC microgrid and does not consider grid connection.

[0046] As Figure 2The figure shows an adaptive distributed hierarchical control structure for an energy storage system based on consensus, which mainly includes a communication layer, a primary control layer, and a secondary control layer. In the communication layer, each energy storage unit is regarded as an agent, an adjacent communication network is established, and an average state estimation method is designed based on multi-agent consensus. The droop coefficient is improved based on the sigmoid function, so that the droop coefficient can be adaptively adjusted according to the state of charge, and the state of charge of each energy storage unit finally tends to the average value. In the secondary control layer, a virtual voltage term is used to make the output current of the energy storage unit proportional to the capacity, and at the same time, the bus voltage drop is restored through the average bus voltage compensation term.

[0047] Through secondary control correction, the output voltage value of the lithium battery can be expressed as:

[0048] u oi =U nom -R vi i oi +δu 1i +δu 2i (1)

[0049] Among them, δu 1i is the unit virtual voltage balance term of energy storage unit i, and δu 2i is the average bus voltage compensation term of energy storage unit i.

[0050] Communication layer: In a multi-agent system, consensus refers to the process by which all agents finally converge to a unified state. This consensus algorithm does not rely on a central controller or a strong communication link, and is only achieved through local information processing and adjacent communication between agents. The present invention studies an undirected strongly connected network with N agents. Its nodes are i ∈ V = {1, 2,..., N}, is the node pair in this energy storage system, that is, (i, j) ∈ E. If (j, i) ∈ E, it means that i and j are adjacent nodes and can transmit data to each other. The Laplacian matrix L of network R N×N =[l ij ∈R N×N can be expressed as:

[0051]

[0052] Among them, a ij is the communication weight between nodes. If i and j are adjacent nodes, then a ij =1, otherwise a ij =0. The adaptive distributed hierarchical control method for the energy storage system based on consensus can be expressed as:

[0053]

[0054] Among them, ξi (t) and ξ j (t) are the state variables of agent i and agent j respectively, and is the local input signal. In the case of communication failure, if the undirected strongly connected network of the energy storage system contains at least one spanning tree, then (3) can be satisfied

[0055] The present invention selects a ring topology as the communication topology between energy storage units, where each energy storage unit communicates only with adjacent energy storage units, and designs an average state estimator based on multi-agent consensus to estimate the average value of each state variable. From the above principle, it can be seen that even if communication fails between two energy storage units, it can ensure the convergence of the average value of state variables to the same value.

[0056] In the main control layer: The present invention integrates the state of charge parameter into the droop control to achieve the balance of the state of charge, and proposes a distributed state of charge balance control method. The control objective of the state of charge equalization strategy can be expressed as follows:

[0057]

[0058] For the convenience of expression, the state of charge SoC i (t) is written as S i (t); DoD i (t) (the depth of discharge DoD of energy storage unit i i (t) = 1 - S i (t)) is written as D i (t). Assuming that the charge and discharge efficiencies of two energy storage units are equal, taking the differential of formula (3) gives the ratio of the state of charge change rates of the two energy storage units:

[0059]

[0060] It can be seen from formula (5) that if the control objective of state of charge equalization is to be achieved, it is necessary to eliminate the interference of line impedance on state of charge equalization, and at the same time consider the influence of the rated capacity of the energy storage unit in the droop coefficient. Therefore, on the premise of considering the rated capacity of the energy storage unit, the present invention uses the sigmoid function to establish the relationship between the state of charge difference and the droop coefficient. The improved droop coefficient can be expressed as:

[0061]

[0062] Where: R vi (S i ), ρ(S i ) and k Dare the improved droop coefficient, variable acceleration factor, and balance factor of energy storage unit i, μ is the adjustment factor of the acceleration factor; the charge and discharge deviation values ζ and σ are expressed as:

[0063] ζ = S avgi (t) - S i (t) (8)

[0064] σ = D avgi (t) - D i (t) (9)

[0065] Where: S avgi and D avgi are the dynamic average values of S i and D i of energy storage unit i.

[0066] The dynamic average value of the state of charge of each energy storage unit adopts a consensus-based average state estimation method, and the local estimated dynamic average value of S i is updated through the dynamic average value S avgj of this unit and the adjacent energy storage units. Combining Equation (3), the average state of charge can be expressed as the following formula. In addition, the methods for the average DoD and other average state parameters are similar. avgi .

[0067]

[0068] In the secondary control layer: The control link designed in the present invention mainly serves to eliminate the influence of line impedance on the state of charge balance and output current shunting, and at the same time solve the problem of bus voltage deviation caused by droop control. Its control objective can be defined as:

[0069]

[0070] After the state of charge of each energy storage unit reaches equilibrium, the output current can be allocated according to the rated capacity, and the average bus voltage can also be restored to the nominal value. To achieve the above objectives, the secondary control layer in this section includes a unit virtual voltage drop balance term and an average bus voltage compensation term. The unit virtual voltage drop balance term calculates the local unit virtual voltage drop:

[0071]

[0072] Where, ΔU max is the maximum bus voltage deviation value, and in this application, ΔU max = 5%U nom . At the same time, the average unit virtual voltage drop is calculated based on consensus The PI controller is used to adjust and The difference between them, and thus the additional term δu 1i can be written as follows:

[0073]

[0074] where K PL and K IL are the proportional and integral gains of the unit virtual voltage drop balancing term, can be expressed as:

[0075]

[0076] The balancing term designed by Eqs. (14) and (15) can ultimately make the unit virtual voltage drops of each energy storage unit tend to be consistent, and can be simplified to the following formula:

[0077] R v1 i o1 = R v2 i o2 = Λ = R vN i oN (16)

[0078] When the state of charge of each energy storage unit reaches equilibrium, R vi = 1 / C i , Eq. (15) can be simplified to:

[0079] i o1 :i o2 :Λ:i oN = C 1 :C 2 :Λ :C N (17)

[0080] The average voltage compensation term restores the average bus voltage to the nominal bus voltage. Through the regulation of the integrator, the average bus voltage is compensated under the control of the correction term:

[0081]

[0082] where K IU is the integral gain of the average voltage compensation term, and the average bus voltage u avgoi can be expressed as:

[0083]

[0084] As Figure 3 (a) shows the graph of the improved droop coefficient R vi varying with the state of charge difference ζ proposed by the present invention, and (b) shows the new acceleration factor ρ(S i)Images varying with the state of charge difference ζ. For energy storage units with different initial states of charge, their droop coefficients increase as k = k D / C i increases, resulting in an increased power distribution difference between energy storage units, thus accelerating the state of charge balance between energy storage units. However, in the later stage of state of charge balance, the difference in droop coefficients between energy storage units gradually shrinks, and simply modifying the k value is not sufficient to achieve the necessary rapid state of charge balance. As shown in Figure 3 (a), while keeping the k value constant, gradually increasing the ρ value, as ζ approaches zero, the slope of the droop coefficient will gradually increase. This change exacerbates the difference in droop coefficients between energy storage units, thus increasing the power distribution difference. However, an excessively high ρ value will hinder the balance speed in the initial balance stage of state of charge regulation. Therefore, this study introduces an acceleration factor based on the normal distribution function, denoted as ρ(S i ), which replaces the traditional ρ value in the droop coefficient. By adjusting the adjustment factor μ in the acceleration factor, the ρ value remains low in the initial balance stage of state of charge regulation and gradually increases in the subsequent balance stage, thus accelerating the overall state of charge balance rate.

[0085] As shown in Figure 4 is the equivalent linearization model of the control strategy of the present invention with two energy storage units as an example. Assuming no delay in the communication system, the closed-loop transfer function of the DC voltage can be expressed as follows:

[0086]

[0087] where τ is the time constant under the action of the switch. The converter output current is filtered by a low-pass filter and input into the control system loop, and its transfer function can be expressed as:

[0088]

[0089] where ω c is the cut-off frequency of the low-pass filter.

[0090] The transfer functions of the PI regulator for the unit virtual voltage drop balance term and the integrator for the average voltage compensation term are:

[0091]

[0092]

[0093] From Figure 4 the following relationships can be obtained:

[0094]

[0095] From Figure 4The following expressions can be obtained:

[0096]

[0097] Since the bandwidth of the droop control loop is designed to be much smaller than the switching frequency, the τ value is very small and its delay effect can be neglected. Other system parameters are shown in Table 1. Combining (20)-(26), the energy storage unit 1 The closed-loop transfer function between the output voltage and the reference voltage of the energy storage unit can be expressed as:

[0098]

[0099] where λ = R v1 α 1 +R v2 α 2 +R v1 β + R v2 β,

[0100] The process of adopting the improved droop control method, improving the droop coefficient based on the sigmoid function, realizing the adaptive adjustment of the output current distribution of lithium batteries to achieve the state of charge balance, and adding an acceleration factor improved based on the normal distribution function to accelerate the equalization speed of the state of charge of lithium batteries in the later stage also includes:

[0101] Based on the voltage-current double closed-loop control, in the voltage outer loop, an improved droop control, a unit virtual voltage equalization term, and an average bus voltage compensation term are added after the reference voltage. The output voltage of the energy storage unit is the feedback of the voltage loop. The reference current of the current inner loop is obtained through the first PI controller, and then the difference is made with the inductor current of the DC / DC converter. The PWM modulation signal is obtained through the second PI controller, and the on-off of the IGBT in the DC / DC converter is controlled by the PWM modulation signal to realize the rapid equalization of the state of charge of lithium batteries, the accurate distribution of the output current according to the rated capacity, and the average bus voltage compensation.

[0102] The process of adopting the improved droop control method, improving the droop coefficient based on the sigmoid function, and realizing the adaptive adjustment of the output current distribution of lithium batteries to achieve the state of charge balance is as follows:

[0103] When the lithium battery is charging, based on the sigmoid function, the difference in the charging depth of each unit is established, that is, the relationship between the difference between the charging depth and its average value and the droop coefficient. At the same time, the ratio of the balance coefficient to the rated capacity is introduced into the droop coefficient;

[0104] When the lithium battery is discharging, based on the sigmoid function, the difference in the discharging depth of each unit is established, that is, the relationship between the difference between the discharging depth and its average value and the droop coefficient. At the same time, the ratio of the balance coefficient to the rated capacity is introduced into the droop coefficient.

[0105] The process of adding an acceleration factor improved based on the normal distribution function to accelerate the equalization speed of the state of charge of the lithium battery in the later stage is as follows:

[0106] When the lithium battery is charging, an acceleration factor based on the normal distribution function is introduced into the improved droop coefficient. The acceleration factor takes the square value of the charging depth difference as a variable, and a regulation factor is added at the same time to change the equalization speed in the later stage of the state of charge;

[0107] When the lithium battery is discharging, an acceleration factor based on the normal distribution function is introduced into the improved droop coefficient. The acceleration factor takes the square value of the discharge depth difference as a variable, and a regulation factor is added at the same time to change the equalization speed in the later stage of the state of charge.

[0108] The process of designing the unit virtual voltage drop balance term to eliminate the influence of line impedance and achieve the distribution of output current according to the rated capacity of the lithium battery is as follows:

[0109] The product of the droop coefficient and the output current of the energy storage unit is used to obtain the virtual voltage drop.

[0110] The ratio of the virtual voltage drop to the maximum deviation of the bus voltage is the unit virtual voltage drop. A PI controller is used to equalize the unit virtual voltage drop to the average unit virtual voltage drop. The consistency of the unit virtual voltage drops of each energy storage unit makes the output current distribution only related to the droop coefficient, thereby eliminating the influence of line impedance on the accurate shunt of the output current and the equalization of the state of charge. The output current can be proportionally distributed according to the rated capacity of each energy storage unit during the equalization of the state of charge.

[0111] The process of designing the average bus voltage compensation term to compensate the average bus voltage to the reference value is as follows:

[0112] The average bus voltage is the average value of the output voltages of all energy storage units. An integral controller is used to make the average bus voltage tend to the bus voltage reference value to maintain the stability of the bus voltage.

[0113] As Figure 5 shown is the root locus of the important parameters of the system. Figure (a) is the root locus varying with the state of charge difference ΔS = S 1 -S 2 variation, Figure (b) is the root locus varying with the cut-off frequency ω c variation, Figure (c) is the root locus varying with the balance factor k D variation, and Figure (d) is the root locus varying with the regulation factor μ;

[0114] For the adaptive distributed hierarchical control method of the consistency-based energy storage system, the parameters of each supply unit selected are shown in Table 1.

[0115] Table 1 Parameters of the Adaptive Distributed Hierarchical Control Method of the Consistency-Based Energy Storage System

[0116]

[0117] From Figure 5 (a), it can be seen that when the state-of-charge difference between energy storage units changes, the system can remain stable. From Figure 5 (b), it can be seen that the increase in the cut-off frequency ω c will cause all poles to move away from the imaginary axis, thereby improving the stability margin of the system. However, the movement of the conjugate poles p 1 and p 2 away from the real axis indicates a decrease in the system damping ratio, which may lead to current oscillation and system instability. Therefore, the cut-off frequency ω c must be maintained within a reasonable range. From Figure 5 (c) and (d), it can be seen that as the adjustment coefficients of the balance factor k D and the acceleration factor μ increase, the pole p 3 gradually approaches the imaginary axis, and the stability margin of the system decreases. Therefore, it is necessary to control k D and μ to prevent them from becoming too large, so as to ensure the stability of the system.

[0118] As Figure 6 shown, Case 1 is the simulation result when the load is switched and the light intensity changes. The initial state-of-charge of the energy storage units is set to 80%, 70%, and 60% respectively. In addition, in this case, the simulated capacity of all energy storage units is 8 Ah. From Figure 6 (a), it can be seen that the convergence speed of the state-of-charge does not slow down due to the decrease in the state-of-charge difference, but continuously accelerates under the regulation of the acceleration factor, which proves the fast state-of-charge balancing ability of the proposed method. The state-of-charge of all energy storage units converges at about t = 20 s, and the state-of-charge difference approaches 0%. From Figure 6 (b), it can be seen that the state-of-charge balance is achieved through the load current distribution among the energy storage units. From Figure 6 (c), it can be seen that the average bus voltage can recover to the nominal value of 700 V under steady state, and only a small voltage deviation is generated during the changes in RES, EL, and RL powers. The results of Simulation Case 1 show that the proposed control strategy can achieve dynamic state-of-charge balance, accurate load current distribution, and stable bus voltage recovery under the changes in photovoltaic and load powers.

[0119] As Figure 7 shown, Case 2 is the simulation result of energy storage units with different rated capacities when the photovoltaic and load powers change. From Figure 7(a) It can be seen that the proposed method still has a fast convergence rate in the later stage of state of charge (SOC) balancing. Compared with Case 1, due to the reduction of the total capacity of the energy storage units, each energy storage unit achieves the SOC balancing goal at around t = 14 s. From Figure 7 (b) It can be seen that the output current of each energy storage unit is distributed according to the ratio of i o1 :i o2 :i o3 = 4:3:2, which indicates that the proposed control strategy has the ability to distribute the load current proportionally. From Figure 7 (c) It can be seen that the average bus voltage can maintain the nominal value of 700 V under steady state. Although voltage deviations occur during the transient processes of wind / solar and load power fluctuations, these deviations will be quickly corrected back to the nominal value. The results of Simulation Case 2 show that although the rated capacities of the energy storage units are different, the proposed control strategy can achieve the control goals of fast SOC balancing, proportional distribution of load current, and stable bus voltage recovery.

[0120] As Figure 8 shown, Case 3 is the simulation result under the conditions of communication and equipment failures. From Figure 8 (a) It can be seen that after achieving SOC balance at t = 14 s, the proposed method can maintain this balance state even during communication failures. After the energy storage unit 3 terminates operation in advance, its SOC stabilizes at 64.07%, while the SOCs of the energy storage unit 1 and the energy storage unit 2 quickly rebalance. From Figure 8 (b) It can be seen that although the communication between the energy storage unit 1 and the energy storage unit 2 fails, after being distributed according to the rated capacity, the distribution of the load current among the energy storage units is not affected. In the case of the early withdrawal of the energy storage unit 3 , the output currents of the energy storage unit 1 and the energy storage unit 2 increase and continue to be distributed according to the ratio of i o1 :i o2 = 4:3. From Figure 8 (c) It can be seen that under the condition of communication failure, the average bus voltage can still be maintained near the nominal bus voltage, and after the energy storage unit 3 terminates operation in advance, the remaining two energy storage units undertake all the load power, resulting in only a slight decrease of about 2.3 V in the average bus voltage. The results of Simulation Case 3 show that the proposed control strategy can withstand the risks of communication failures and equipment disconnections, and on this premise, it can still maintain fast SOC balancing, accurate load current distribution, and stable bus voltage recovery.

[0121] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some or all of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A consistency-based adaptive distributed hierarchical control method for energy storage systems, characterized in that: The following steps are involved: S1: Establish an off-grid photovoltaic water electrolysis hydrogen production system model including photovoltaic cells, lithium batteries, electrolyzers, constant power loads and DC / DC converters; S2: Based on the off-grid photovoltaic water electrolysis hydrogen production system model, an improved droop hierarchical control method for the energy storage system based on multi-agent consistency is proposed to achieve balanced charge state of the energy storage system, eliminate the influence of line impedance to achieve precise current diversion, and restore the bus voltage drop at the same time.

2. The method for adaptive distributed hierarchical control of energy storage systems based on consistency according to claim 1, characterized in that: The process of improving the droop hierarchical control method of the energy storage system based on the off-grid photovoltaic water electrolysis hydrogen production system model and the multi-agent consistency to achieve the balanced state of charge of the energy storage system, eliminate the influence of line impedance to achieve accurate current diversion, and restore the bus voltage drop is as follows: In the communication layer, the energy storage units in the photovoltaic water electrolysis hydrogen production system are regarded as intelligent agents. Based on the multi-agent consistency, the average state estimation method is designed to calculate the average values ​​of the lithium battery state of charge, unit virtual voltage and output voltage, and then transmit the average values ​​to the adjacent energy storage units through the inter-neighbor communication network. In the main control layer, an improved droop control method is adopted, and the droop coefficient is improved based on the sigmoid function to realize adaptive adjustment of the lithium battery output current distribution to achieve charge state balance. An acceleration factor based on the normal distribution function is added to accelerate the balance speed of the lithium battery charge state in the later stage. In the secondary control layer, the unit virtual voltage drop balance item is designed to eliminate the influence of line impedance, so that the output current is distributed according to the rated capacity of the lithium battery. The average bus voltage compensation item is designed to compensate the average bus voltage to the reference value.

3. The method for adaptive distributed hierarchical control of energy storage systems based on consistency according to claim 1, characterized in that: The improved droop control method is adopted to improve the droop coefficient based on the sigmoid function to realize adaptive adjustment of the output current distribution of the lithium battery to achieve charge state balance, and the acceleration factor based on the normal distribution function is added to accelerate the late balance speed of the lithium battery charge state. The process also includes: Based on the voltage-current dual closed-loop control, improved droop control, unit virtual voltage balancing term and average bus voltage compensation term are added after the reference voltage in the voltage outer loop. The output voltage of the energy storage unit is the voltage loop feedback. The reference current of the current inner loop is obtained through the first PI controller, and then the reference current is subtracted from the inductor current of the DC / DC converter. The PWM modulation signal is obtained through the second PI controller. The PWM modulation signal controls the on-off of the IGBT in the DC / DC converter to achieve rapid balancing of the lithium battery charge state, accurate distribution of the output current according to the rated capacity and average bus voltage compensation.

4. The method for adaptive distributed hierarchical control of energy storage systems based on consistency according to claim 2, characterized in that: The process of using the improved droop control method to improve the droop coefficient based on the sigmoid function to achieve adaptive adjustment of the lithium battery output current distribution to achieve charge state balance is as follows: When charging lithium batteries, the difference in charging depth of each unit is established based on the sigmoid function, that is, the relationship between the difference between the charging depth and its average value and the droop coefficient, and the ratio of the balance coefficient to the rated capacity is introduced into the droop coefficient. When the lithium battery is discharged, the relationship between the discharge depth difference of each unit, that is, the difference between the discharge depth and its average value, and the droop coefficient is established based on the sigmoid function. At the same time, the ratio of the balance coefficient to the rated capacity is introduced into the droop coefficient.

5. According to claim 2, a consistency-based adaptive distributed hierarchical control method for energy storage systems is characterized by: The process of adding the acceleration factor based on the normal distribution function to accelerate the late-stage equalization speed of the lithium battery state of charge is as follows: When charging lithium batteries, an acceleration factor based on a normal distribution function is introduced into the improved droop coefficient. The acceleration factor takes the square value of the difference in charging depth as a variable, and an adjustment factor is added to change the speed of the later stage of charge state equilibrium. When the lithium battery is discharged, an acceleration factor based on the normal distribution function is introduced into the improved droop coefficient. The acceleration factor takes the square value of the discharge depth difference as a variable. At the same time, an adjustment factor is added to change the late speed of charge state equilibrium.

6. The method for adaptive distributed hierarchical control of energy storage systems based on consistency according to claim 1, characterized in that: The process of designing the unit virtual voltage drop balance item to eliminate the influence of line impedance and realize the output current distribution according to the rated capacity of the lithium battery is as follows: The virtual voltage drop is obtained by multiplying the droop coefficient by the output current of the energy storage unit. The ratio of the virtual voltage drop to the maximum offset of the bus voltage is the unit virtual voltage drop. A PI controller is used to balance the unit virtual voltage drop to the average unit virtual voltage drop. The unit virtual voltage drops of each energy storage unit are consistent so that the output current distribution is only related to the droop coefficient, thereby eliminating the influence of line impedance on the precise diversion of the output current and the balance of the state of charge. When the state of charge is balanced, the output current can be distributed in proportion to the rated capacity of each energy storage unit.

7. The method for adaptive distributed hierarchical control of energy storage systems based on consistency according to claim 1, characterized in that: The process of designing the average bus voltage compensation term and compensating the average bus voltage to the reference value is as follows: The average bus voltage is the average value of the output voltages of all energy storage units. An integral controller is used to make the average bus voltage approach the bus voltage reference value to maintain bus voltage stability.

8. The method for adaptive distributed hierarchical control of energy storage systems based on consistency according to claim 1, characterized in that: The improved droop coefficient is expressed as: Where: R vi (S i ), ρ(S i ) and k D is the improved droop coefficient, variable acceleration factor and balance factor of energy storage unit i, μ is the adjustment factor of the acceleration factor; the charge and discharge deviation values ​​ζ and σ are expressed as: ζ=S avgi (t)-S i (t) (8) σ=D avgi (t)-D i (t) (9) Among them, S avgi and D avgi is the S of energy storage unit i i and D i The dynamic average value of .

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