A self-disturbance control-based photovoltaic micro-grid energy storage control strategy

Abstract

The application discloses a kind of photovoltaic microgrid energy storage control strategies based on active disturbance rejection control, belongs to photovoltaic hybrid energy storage microgrid technical field, it is related to the control strategy of hybrid energy storage system.For the overshoot of PI control in the transient stage in the current photovoltaic microgrid hybrid energy storage system control strategy is large, bus voltage fluctuation of sliding mode control is large, the anti-interference ability of traditional linear active disturbance rejection control system is limited by ESO gain coefficient, by introducing total disturbance differential signal into the extended state observer, the anti-interference performance of photovoltaic energy storage microgrid system is optimized, for the disturbance caused by photovoltaic output fluctuation and load switching to bus voltage, the total disturbance of system can be tracked quickly, and disturbance is compensated in time.The steady-state error of direct-current bus voltage is reduced, so that it can quickly enter stable state, and the voltage fluctuation of direct-current bus is more effectively inhibited.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of photovoltaic hybrid energy storage micro-grid, and particularly relates to a photovoltaic micro-grid energy storage control strategy based on active disturbance rejection control, and relates to the control strategy design of a hybrid energy storage system. BACKGROUND

[0002] Due to the fluctuation, intermittence and unpredictability of photovoltaic distributed power, power supply and demand are imbalanced, so an energy storage unit needs to be configured to balance the imbalance of supply and demand power and ensure the stability of the micro-grid. Whether the stability of the DC bus voltage is a key factor for measuring whether the photovoltaic micro-grid can work normally. In order to stabilize the DC bus voltage, the energy storage unit needs to be controlled.

[0003] At present, the control method of the hybrid energy storage in the photovoltaic energy storage micro-grid includes PI control, sliding mode control, active disturbance rejection control and the like. The traditional PI double closed-loop control can achieve the purpose of suppressing the fluctuation of the DC bus voltage, and has good effect on the steady state stage, but still has a large overshoot in the transient state. The adaptive global sliding mode control can ensure the dynamic characteristics of the photovoltaic storage micro-grid system, but the bus voltage fluctuation is still large. The active disturbance rejection control (ADRC) enhances the anti-interference performance of the system, so that the DC bus voltage is maintained stable. However, too many control parameters make it difficult to adjust the parameters. The linear active disturbance rejection control (LADRC) simplifies the parameter setting, improves the power quality of the system, can better suppress the bus voltage fluctuation, and improves the anti-interference ability of the system. The anti-interference ability of the linear active disturbance rejection control depends on the gain coefficient of the extended state observer (ESO), the larger the gain coefficient, the stronger the anti-interference ability. However, too large coefficient increases the influence of high-frequency noise on the system, thereby limiting the further improvement of the anti-interference ability of the hybrid energy storage system. SUMMARY

[0004] For the control strategy of the current photovoltaic micro-grid hybrid energy storage system, the existing PI control has a large overshoot in the transient state; the sliding mode control can ensure the dynamic characteristics of the photovoltaic storage micro-grid system, but the bus voltage fluctuation is still large; and the photovoltaic micro-grid hybrid energy storage system using the traditional linear active disturbance rejection control can better suppress the bus voltage fluctuation, but the anti-interference ability of the system is limited by the gain coefficient of the extended state observer (ESO), and cannot be further improved.

[0005] The application provides a photovoltaic microgrid hybrid energy storage control strategy based on improved LADRC.

[0006] In order to achieve the above-mentioned purpose, the application adopts the following technical solutions:

[0007] A photovoltaic microgrid energy storage control strategy based on active disturbance rejection control, comprising the following steps:

[0008] Step 1, building a photovoltaic microgrid structure, constructing a hybrid energy storage system control strategy;

[0009] Step 2, improving linear active disturbance rejection control LADRC,

[0010] Step 3, according to the improved linear active disturbance rejection control LADRC, designing a tracking differentiator, designing an improved extended state observer ESO, designing an error feedback controller and improving the voltage loop.

[0011] Further, the photovoltaic microgrid structure refers to a small-scale power generation and distribution system composed of photovoltaic distributed power, energy storage devices, energy conversion devices, loads and the like, and contains a hybrid energy storage system (HESS) composed of photovoltaic cells, DC loads, super capacitors and storage batteries. The photovoltaic cell converts the output DC power into stable voltage DC power through a DC-DC converter and outputs the stable voltage DC power to a DC bus for power supply to DC loads; the energy storage devices in the hybrid energy storage system are connected with the DC-DC converter respectively and perform bidirectional energy transmission with the DC bus.

[0012] Further, the hybrid energy storage system control strategy refers to a control strategy adopted for the hybrid energy storage system composed of storage batteries and super capacitors in the photovoltaic microgrid structure. The control strategy includes two parts, i.e., improved LADRC control for controlling the voltage of the hybrid energy storage system and PI control for controlling the super capacitor current and the storage battery current; wherein the voltage loop adopts improved LADRC control and uses a low-pass filter to take the low-frequency component of the voltage loop output signal as the storage battery reference current and the high-frequency component as the super capacitor reference current.

[0013] When the load consumption is higher than the photovoltaic output, the hybrid energy storage system HESS discharges to the load; when the load consumption is lower than the photovoltaic output, the excess power charges the hybrid energy storage system HESS; that is, it satisfies:

[0014] P v -P load=P bat +P sc

[0015] Where: P v Represents the output power of photovoltaic cells; P load Indicates the power consumed by the load; P bat Indicates the output power of the battery; P sc Indicates the output power of the supercapacitor.

[0016] Furthermore, the improved linear active disturbance rejection control (LADRC) system consists of a tracking differentiator, an improved extended state observer (ESO), and a feedback controller. The tracking differentiator (TD) is used to pre-arrange the transient process, track the input signal, and extract the tracking signal of the input signal. The improved extended state observer (ESO) is used to estimate the total disturbance tracking signal of internal and external disturbances in the system, as well as the tracking signal of the output signal, and compensate for it in feedback, eliminating the impact of disturbances through compensation, thereby achieving interference rejection. The feedback controller (LSEF) performs control and disturbance compensation based on the error between the tracking signal obtained by the tracking differentiator and the tracking signal of the output signal observed by the improved extended state observer. Let v represent the input signal; x1 represents the tracking signal of the input signal v; u represents the control variable; b0 represents the compensation factor; y represents the output signal; z1 represents the tracking signal of y; z2 represents the tracking signal of the total disturbance; and u0 represents the virtual control variable.

[0017] Furthermore, the tracking differentiator is expressed as:

[0018] x1(t+1)=x1(t)-hr0fal[e,a,δ]

[0019] e=x1(t)-v(t)

[0020] Where: v represents the input signal; x1 represents the tracking signal of the input signal v; t is the time variable; h is the sampling period; r0 is the speed factor; fal[e,a,δ] is the optimal control function; e is the error value between x1(t) and v(t), a is the nonlinear factor; δ is the filter factor.

[0021] Furthermore, the specific method of improving the extended state observer ESO is:

[0022] First, the traditional ESO is expressed as:

[0023]

[0024] Where: λ1 and λ2 are the gain parameters of the traditional ESO; y is the output signal; z1 is the tracking signal of y; z2 is the tracking signal of the total disturbance; e1 is the error between z1 and y; b0 is the compensation factor;

[0025] The λ1 and λ2 are configured as follows:

[0026]

[0027] Thus, z1 and z2 are expressed as:

[0028]

[0029] Wherein: ω o is the bandwidth of the observer; s is the differential operator.

[0030] Then, the improved ESO with a disturbance differential term is introduced as:

[0031]

[0032] In the formula: z1 is the tracking signal of y; z2 is the tracking signal of the total disturbance; z3 is the differential signal of the total disturbance; β1, β2 and β3 are the gain coefficients of the improved ESO; the characteristic analysis of the improved ESO is as follows:

[0033] The poles of β1, β2 and β3 are configured as:

[0034]

[0035] The transfer function of z1, z2 and z3 is expressed as:

[0036]

[0037] A first-order linear active disturbance rejection control (LADRC) is adopted, so:

[0038]

[0039] The disturbance transfer function of the improved ESO is:

[0040]

[0041] Similarly, the disturbance transfer function of the traditional ESO is:

[0042]

[0043] The amplitude-phase characteristic curves are obtained by comparison, as shown in Figure 4 The frequency domain analysis diagrams of the disturbance terms of the two ESOs are shown. Through the frequency domain response characteristic analysis, the bandwidth of the improved ESO adopted in the present application is obviously increased, the disturbance observation ability of the ESO is enhanced, the phase lag in the medium frequency band is reduced, the response speed of the ESO is faster, and the faster tracking of the total disturbance is realized.

[0044] Further, the error feedback controller is expressed as:

[0045]

[0046]

[0047] Wherein: k represents the controller gain coefficient; x1 is the tracking signal of v; z1 is the tracking signal of y; z2 is the tracking signal of total disturbance; b0 is the compensation factor; u0 is the virtual control variable; e2 represents the error value of x1 and z1.

[0048] Further, the improvement of the voltage loop is specifically: in the LADRC control, the input quantity is the given voltage reference signal The control variable is I ref , and the output quantity is the bus voltage sampling signal U dc ; the improved LADRC control model of the voltage loop is represented as:

[0049]

[0050] Wherein, z1 is the tracking signal of y; z2 is the tracking signal of total disturbance; z3 is the differential signal of total disturbance; β1, β2 and β3 are gain coefficients of the improved ESO; U dc is the bus voltage sampling signal; I ref is the current reference value; b0 is the compensation factor; k represents the controller gain coefficient; x1 is the tracking signal of v.

[0051] Compared with the prior art, the present application has the following advantages:

[0052] The photovoltaic micro-grid energy storage control strategy based on the active disturbance rejection control introduces the differential signal of total disturbance into the extended state observer, effectively enhances the disturbance observation capability of the extended state observer, optimizes the anti-interference performance of the photovoltaic energy storage micro-grid system, realizes fast tracking of the total disturbance of the system and timely compensation of the disturbance, reduces the steady-state error of the DC bus voltage, makes the DC bus voltage quickly enter the stable state, and more effectively suppresses the voltage fluctuation of the DC bus. BRIEF DESCRIPTION OF DRAWINGS

[0053] Figure 1 It is a photovoltaic energy storage micro-grid structure schematic diagram;

[0054] Figure 2 It is a control strategy overall structure schematic diagram;

[0055] Figure 3 It is a LADRC control structure schematic diagram;

[0056] Figure 4 It is a frequency domain analysis schematic diagram of two kinds of ESO disturbance terms;

[0057] Figure 5 Improved LADRC system structure schematic diagram

[0058] Figure 6 Improved LADRC disturbance term frequency domain analysis schematic diagram

[0059] Figure 7 Improved LADRC and traditional LADRC disturbance term frequency domain analysis schematic diagram

[0060] Figure 8 Power waveform schematic diagram of each unit of the photovoltaic microgrid

[0061] Figure 9 DC bus voltage waveform schematic diagram

[0062] Figure 10 Power waveform schematic diagram of each unit of the photovoltaic microgrid

[0063] Figure 11 DC bus voltage waveform schematic diagram DETAILED DESCRIPTION

[0064] Embodiment 1

[0065] A photovoltaic microgrid energy storage control strategy based on active disturbance rejection control, comprising the following steps:

[0066] Step 1, build a photovoltaic storage microgrid structure, and construct a hybrid energy storage system control strategy;

[0067] Step 2, improve the linear active disturbance rejection control LADRC,

[0068] Step 3, according to the improved linear active disturbance rejection control LADRC, design a tracking differentiator, design an improved extended state observer ESO, design an error feedback controller, and improve the voltage loop.

[0069] The photovoltaic storage microgrid structure refers to a small-scale power generation and distribution system composed of photovoltaic distributed power supply, energy storage devices, energy conversion devices, and loads, etc., and contains a hybrid energy storage system (HESS) composed of photovoltaic cells, DC loads, super capacitors, and storage batteries. The photovoltaic cells convert the output DC power into stable voltage DC power through a DC-DC converter and output the stable voltage DC power to a DC bus for power supply to DC loads. The energy storage devices in the hybrid energy storage system are connected with the DC-DC converter and perform bidirectional energy transmission with the DC bus. For example, Figure 1 The photovoltaic storage microgrid structure is shown in the schematic diagram.

[0070] The control strategy of the hybrid energy storage system refers to a control strategy adopted by the hybrid energy storage system composed of the battery and the super capacitor in the photovoltaic micro-grid structure, which includes an improved LADRC control for controlling the voltage of the hybrid energy storage system and a PI control for controlling the super capacitor current and the battery current; wherein the voltage loop adopts the improved LADRC control, and a low-pass filter is used to take the low-frequency component of the voltage loop output signal as the battery reference current and the high-frequency component as the super capacitor reference current.

[0071] When the load consumption is higher than the photovoltaic output, the hybrid energy storage system HESS discharges to the load; when the load consumption is lower than the photovoltaic output, the excess power charges the hybrid energy storage system HESS; that is, it satisfies:

[0072] P v -P load =P bat +P sc

[0073] In the formula, P v represents the output power of the photovoltaic cell; P load represents the power consumed by the load; P bat represents the output power of the battery; and P sc represents the output power of the super capacitor. As shown in the overall structure diagram of the control strategy. Figure 2

[0074] The improved linear active disturbance rejection control LADRC is composed of a tracking differentiator, an improved extended state observer, and a feedback controller. The tracking differentiator (TD) is used to arrange the transition process in advance, track the input signal, and extract the tracking signal of the input signal; the improved extended state observer (ESO) is used to estimate the total disturbance tracking signal of the internal and external disturbances of the system, and the tracking signal of the output signal, and compensate in the feedback, so as to eliminate the influence of the disturbance, thereby having the anti-interference effect; the feedback controller (LSEF) is based on the error between the tracking signal obtained by the tracking differentiator and the tracking signal of the output signal observed by the improved extended state observer, and then controls and compensates the disturbance. V represents the input signal; x1 represents the tracking signal of the input signal v; u represents the control amount; b0 represents the compensation factor; y represents the output signal; z1 represents the tracking signal of y; z2 represents the tracking signal of the total disturbance; and u0 represents the virtual control amount. As shown in the control structure diagram of the LADRC. Figure 3

[0075] The tracking differentiator is represented as:

[0076] x1(t+1)=x1(t)-hr0fal[e,a,δ]

[0077] ​​e = x1(t) - v(t)

[0078] where v represents the input signal; x1 represents the tracking signal of the input signal v; t is the time variable; h is the sampling period; r0 is the speed factor; fal[e, a, δ] is the optimal control function; e is the error value of x1(t) and v(t), a is the nonlinear factor; and δ is the filtering factor.

[0079] Improved extended state observer (ESO):

[0080] First, the traditional ESO is expressed as:

[0081]

[0082] where λ1 and λ2 are gain parameters of the traditional ESO; y is the output signal; z1 is the tracking signal of y; z2 is the tracking signal of the total disturbance; e1 is the error value of z1 and y; b0 is the compensation factor; and

[0083] λ1 and λ2 are configured as follows:

[0084]

[0085] z1 and z2 are expressed as:

[0086]

[0087] where ω o is the bandwidth of the observer; and s is the differential operator.

[0088] Then, the improved ESO with the disturbance differential term is expressed as:

[0089]

[0090] where z1 is the tracking signal of y; z2 is the tracking signal of the total disturbance; z3 is the differential signal of the total disturbance; β1, β2, and β3 are gain coefficients of the improved ESO; and the characteristic analysis of the improved ESO is as follows:

[0091] β1, β2, and β3 are configured as poles as follows:

[0092]

[0093] The transfer functions of z1, z2, and z3 are expressed as:

[0094]

[0095] A first-order linear active disturbance rejection control (LADRC) is used, so that

[0096]

[0097] The disturbance transfer function of the improved ESO is:

[0098]

[0099] Similarly, the disturbance transfer function of the traditional ESO is:

[0100]

[0101] The amplitude-phase characteristic curves are obtained by comparison, as shown in the following figure: Figure 4 The frequency domain analysis of the disturbance terms of the two ESOs is shown in the following figure. Through the frequency domain response characteristic analysis, the bandwidth of the improved ESO adopted in this paper is significantly increased, which enhances the disturbance observation capability of the ESO. The phase lag in the medium frequency band is reduced, which makes the response speed of the ESO faster, and realizes faster tracking of the total disturbance.

[0102] The error feedback controller is represented as:

[0103]

[0104]

[0105] Wherein: k represents the controller gain coefficient; x1 is the tracking signal of v; z1 is the tracking signal of y; z2 is the tracking signal of the total disturbance; b0 is the compensation factor; u0 is the virtual control quantity; e2 represents the error value of x1 and z1.

[0106] Improvement of the voltage loop: in the LADRC control, the input quantity is the given voltage reference signal The control quantity is I ref , and the output quantity is the bus voltage sampling signal U dc ; the improved LADRC control model of the voltage loop is represented as:

[0107]

[0108] Wherein: z1 is the tracking signal of y; z2 is the tracking signal of the total disturbance; z3 is the differential signal of the total disturbance; β1, β2 and β3 are the gain coefficients of the improved ESO; U dc is the bus voltage sampling signal; I ref is the current reference value; b0 is the compensation factor; k represents the controller gain coefficient; x1 is the tracking signal of v.

[0109] Example 2: Analysis of the anti-disturbance performance of the improved LADRC

[0110] The frequency domain analysis of the traditional LADRC and the improved LADRC is carried out, and the anti-disturbance performance of the two is compared by comparing the amplitude-phase curves of the disturbance transfer functions of the two. The frequency domain analysis of the traditional LADRC and the improved LADRC is carried out, and the anti-disturbance performance of the two is compared by comparing the amplitude-phase curves of the disturbance transfer functions of the two.

[0111]

[0112] Where: v represents the input signal; x1 represents the tracking signal of the input signal v; u represents the control quantity; y represents the output signal; k represents the controller gain coefficient; b0 is the compensation factor; ω o is the bandwidth of the observer; s is the differential operator.

[0113] Improve the LADRC system structure such as Figure 5 As shown in the schematic diagram of the improved LADRC system structure, the closed-loop transfer function of the system can be obtained:

[0114]

[0115] Where: y represents the output signal; x1 represents the tracking signal of the input signal v; k represents the controller gain coefficient; ω o is the bandwidth of the observer; f is the disturbance signal received by the system; s is the differential operator.

[0116] The output y of the system contains tracking terms and disturbance terms. The tracking term is related to k. The larger k is, the better the tracking effect is. The disturbance term is related to k and ω. o related. Figure 6 is the frequency domain characteristic curve of the disturbance term. Let k = 40, ω o =20, 40, 60, 80, 100, it can be seen that increasing ω o , which can reduce the gain of the mid- and low-frequency bands and enhance the system's anti-interference ability.

[0117] Finally, the anti-interference performance of traditional LADRC and improved LADRC is compared.

[0118] Depend on Figure 7 It can be seen that the high-frequency bands of the two curves are almost overlapping, indicating that the improved LADRC has no impact on the high-frequency band. In addition, in the medium and low frequency bands, the disturbance gain of the improved LADRC is smaller, indicating that the improved LADRC has better anti-interference ability.

[0119] Example 3 Simulation Verification

[0120] To validate the proposed strategy, this example used Matlab simulation software to build a PV-storage microgrid model. The initial PV output power was set to 5.4 kW; the DC bus voltage was rated at 500 V; the battery voltage was rated at 200 V; and the supercapacitor voltage was rated at 220 V. The performance of the improved LADRC was compared with that of traditional LADRC and traditional PI. Both load switching and light intensity were subjected to step changes.

[0121] 3.1 Simulation analysis under load step change

[0122] The DC load power consumption is set to 5.4kW at 0s, the load drops sharply to 2.4kW at 0.5s, and increases to 6.4kW at 1.0s. Figure 9 The power waveforms of photovoltaic, load, battery and supercapacitor. Figure 10 Figure 3 is the DC bus voltage waveform obtained when the HESS uses three different control methods under load step changes.

[0123] Depend on Figure 8 As can be seen, before 0.5 seconds, the load consumption equals the PV output power, and the HESS neither charges nor discharges. At 0.5 seconds, the load consumption is less than the PV output power, and the remaining energy is stored in the HESS. At 1 second, the load consumption exceeds the PV output power, and the HESS discharges. Furthermore, when the load is switched on and off, the supercapacitor can quickly compensate for high-frequency power, while the battery can compensate for low-frequency power.

[0124] Depend on Figure 9 As can be seen, during the HESS charging process, the bus voltage only increased by 1.1V under the improved LADRC control and returned to the rated value in just 0.03s. Under the traditional LADRC control, it increased by 2.8V and returned to the rated value in 0.25s. Under the traditional PI control, it increased by 10.4V and took 0.21s to return to the rated value.

[0125] During the HESS discharge process, the bus voltage dropped by only 1.2V under the improved LADRC control, reaching the rated value in just 0.03s. Under the traditional LADRC control, the bus voltage dropped by 3.4V, recovering to the rated voltage in 0.35s. Under the traditional PI control, the bus voltage dropped by 11.3V, taking 0.22s to return to the rated value.

[0126] Table 1 Comparison of performance indicators of different control strategies

[0127]

[0128] 3.2 Simulation analysis under step change of light intensity

[0129] The DC load power consumption is set to 5.4kW and the initial light intensity is 750W / m 2 , rising to 1000W / m in 0.5s 2 , 1s type is reduced to 500W / m 2 .Depend on Figure 11 It can be seen that at 0.5s, the load consumption is lower than the photovoltaic output power, and the remaining energy is used to charge the HESS; at 1s, the load consumption is greater than the photovoltaic output power, and the remaining energy is used to discharge the HESS. Figure 11 The DC bus voltage waveforms corresponding to different control methods.

[0130] Depend onFigure 11 It can be seen that, in the HESS charging process, the bus voltage under the improved LADRC control is only increased by 1.0V, and reaches the rated value only after 0.01s. Under the traditional LADRC control, the bus voltage is increased by 1.8V, and it takes 0.22s to recover to the rated voltage. Under the traditional PI control, the bus voltage is increased by 6.4V, and it takes 0.25s to recover.

[0131] In the HESS discharging process, the bus voltage under the improved LADRC control is only decreased by 0.9V, and reaches the rated value only after 0.02s. Under the traditional LADRC control, the bus voltage is decreased by 3.6V, and it takes 0.23s to recover to the rated voltage. Under the traditional PI control, the bus voltage is decreased by 13.1V, and it takes 0.31s to recover to the rated value.

[0132] Table 2 Comparison of performance indicators of different control strategies

[0133]

[0134] In summary, under the two working conditions, the improved LADRC proposed in the application can significantly reduce the overshoot and regulation time of the system, quickly recover the stability of the DC bus voltage, effectively suppress the interference, and maintain the smooth operation of the microgrid.

[0135] The contents not described in detail in the specification of the application belong to the prior art known to those skilled in the art. Although the above describes the specific embodiments of the application for the purpose of facilitating those skilled in the art to understand the application, it should be clear that the application is not limited to the scope of the specific embodiments, and for those skilled in the art, it is obvious that various changes are within the spirit and scope of the application defined and limited by the appended claims, and all the application and creation utilizing the concept of the application are within the scope of protection.

Claims

1. A photovoltaic microgrid energy storage control strategy based on active disturbance rejection control, characterized by: The following steps are involved: Step 1: Build a photovoltaic energy storage microgrid structure and establish a hybrid energy storage system control strategy; Step 2: Improve the linear active disturbance rejection control (LADRC). Step 3: Based on the improved linear active disturbance rejection control (LADRC), design the tracking differentiator, design the improved extended state observer (ESO), design the error feedback controller, and improve the voltage loop. The hybrid energy storage system control strategy refers to the control strategy adopted for the hybrid energy storage system composed of two energy storage devices, batteries and supercapacitors, in the photovoltaic microgrid structure. The control strategy includes two parts: improved LADRC control for controlling the voltage of the hybrid energy storage system and PI control for controlling the supercapacitor current and battery current. Among them, the voltage loop adopts improved LADRC control, and uses a low-pass filter to use the low-frequency component of the voltage loop output signal as the battery reference current, and the high-frequency component as the supercapacitor reference current; When the load consumption is higher than the photovoltaic output, the hybrid energy storage system discharges to the load; when the load consumption is lower than the photovoltaic output, the excess electricity charges the hybrid energy storage system; that is, it satisfies: ； Where: P v Represents the output power of photovoltaic cells; P load Indicates the power consumed by the load; P bat Indicates the output power of the battery; P sc Indicates the output power of the supercapacitor; The specific method of improving the extended state observer ESO is: First, the traditional ESO is expressed as: ； Where: λ1 and λ2 are the gain parameters of the traditional ESO; y is the output signal; z1 is the tracking signal of y; z2 is the tracking signal of the total disturbance; e1 is the error between z1 and y; b0 is the compensation factor; The configurations for λ1 and λ2 are as follows: ； Thus z1 and z2 are expressed as: ； Where: o is the bandwidth of the observer; s is the differential operator; Then, the improved ESO with the introduction of the perturbation differential term is expressed as: ； Where: z3 is the differential signal of the total disturbance; β1, β2 and β3 are the gain coefficients of the improved ESO; u represents the control quantity; the characteristics of the improved ESO are analyzed as follows: Perform pole placement on β1, β2, and β3: ； The transfer functions of z1, z2 and z3 are expressed as: ； Using first-order linear active disturbance rejection control, we have: ； The disturbance transfer function of the improved ESO is: ； The improvement of the voltage loop is as follows: in LADRC control, the input is a given voltage reference signal , the control quantity is the current reference value I ref , the output is the bus voltage sampling signal U dc ; Then the improved LADRC control model of the voltage loop is expressed as: ； Where: k represents the controller gain coefficient; x1 is the tracking signal of v.

2. A photovoltaic microgrid energy storage control strategy based on active disturbance rejection control according to claim 1, characterized in that: The photovoltaic microgrid structure refers to a small power generation and distribution system consisting of photovoltaic distributed power sources, energy storage devices, energy conversion devices, loads, and buses, including a hybrid energy storage system consisting of photovoltaic cells, DC-DC converters, DC loads, supercapacitors, and batteries; photovoltaic cells convert the output DC power into DC power with a stable voltage through a DC-DC converter and output it to the DC bus to power the DC loads; the energy storage devices in the hybrid energy storage system are respectively connected to the DC-DC converters to transmit energy bidirectionally with the DC bus.

3. The photovoltaic microgrid energy storage control strategy based on active disturbance rejection control according to claim 1 is characterized by: The improved linear active disturbance rejection control LADRC is composed of a tracking differentiator, an improved extended state observer, and a feedback controller; The tracking differentiator is used to pre-arrange the transition process, track the input signal, and extract the tracking signal of the input signal; the improved extended state observer is used to estimate the total disturbance tracking signal of the internal and external disturbances of the system, as well as the tracking signal of the output signal, and compensate it in the feedback to eliminate the influence of the disturbance by compensation, thus having an anti-interference effect; The feedback controller performs control and disturbance compensation based on the error between the tracking signal obtained by the tracking differentiator and the tracking signal of the output signal observed by the improved extended state observer.

4. The photovoltaic microgrid energy storage control strategy based on active disturbance rejection control according to claim 1 is characterized by: The tracking differentiator is expressed as: ； ； Where: v(t) represents the input signal; x1(t) represents the tracking signal of the input signal v(t); t is the time variable; h is the sampling period; r0 is the speed factor; fal[e,a, ] is the optimal control function; e is the error value between x1(t) and v(t), a is the nonlinear factor; is the filtering factor.

5. The photovoltaic microgrid energy storage control strategy based on active disturbance rejection control according to claim 1 is characterized by: The error feedback controller is expressed as: ； ； Where: u0 is the virtual control quantity; e2 represents the error value between x1 and z1.

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