Photovoltaic MPPT control method based on improved sliding mode reaching law

Abstract

The invention discloses a photovoltaic MPPT (Maximum Power Point Tracking) control method based on an improved sliding mode reaching law, belonging to the technical field of photovoltaic system power generation. Comprising the following steps: establishing a photovoltaic power generation system and analyzing working characteristics; selecting a sliding mode surface, and obtaining an improved multi-power combination function reaching law according to a fast power reaching law, a double-power reaching law and a saturation function; and selecting a sliding mode control law and analyzing sliding mode control stability, and performing photovoltaic maximum power tracking on the photovoltaic power generation system. According to the invention, the index parameter can be automatically adjusted according to the distance from the sliding mode surface, so that the approaching speed of the system is further divided and changed, and the multi-term power function of the approaching law under different distances is changed, thereby obtaining different approaching speeds, accelerating the approaching process of the system in each stage, ensuring that the system stably reaches the sliding mode surface, and improving the tracking precision.

Description

Technical Field

[0001] The present invention relates to the technical field of photovoltaic system power generation, and in particular to a photovoltaic MPPT control method based on an improved sliding mode reaching law. Background Art

[0002] The traditional energy structure no longer meets the requirements of new social development, and it is of great significance to improve the utilization efficiency of solar clean resources. The utilization of solar clean energy mainly relies on photovoltaic power generation technology. The power generation of photovoltaic systems is mainly determined by factors such as solar radiation intensity and temperature. Using specific methods to maximize the output power of photovoltaic systems can effectively improve the photoelectric conversion efficiency, change the traditional energy structure, and achieve sustainable development.

[0003] The maximum power point tracking (MPPT) technology can be used to improve the photoelectric conversion efficiency of photovoltaic systems. At present, the MPPT algorithms for photovoltaic power generation mainly include constant voltage tracking method, conductance increment method, disturbance observation method, etc. However, the traditional MPPT algorithm is difficult to meet the actual control needs when large disturbances such as solar radiation intensity and temperature occur. In recent years, various nonlinear control algorithms such as fuzzy control, sliding mode control, predictive control, and adaptive control have been widely used in photovoltaic power generation systems. Among them, sliding mode control has the advantages of simple control algorithm, rapid response, low model dependence, and strong anti-disturbance ability. It has good applicability for systems such as photovoltaic power generation with frequency-varying working environment parameters. However, the switching function contained in the traditional sliding mode control photovoltaic MPPT method causes the control law to continuously cross the sliding mode surface, causing a chattering problem, which makes the steady-state output power of the photovoltaic oscillate with a large amplitude, reduces the stability of the sliding mode control, and even damages the control system. Chinese patent "CN115840488A A tracking control method for the maximum power point of photovoltaic power generation based on sliding mode control" proposes an improved reaching law to enhance the photovoltaic MPPT effect, but this method uses a hyperbolic function, resulting in too many reaching law parameters, complex calculations, and requires selection through trial and error of a large amount of data, which has certain limitations on the applicability to photovoltaic systems; in addition, this method divides the system state into three stages for adjustment, but the reaching law is always composed of four power functions, of which only one power exponent value changes to achieve speed adjustment, and the approach rate is always at a faster speed, making it easy to cross the sliding surface when approaching the sliding surface, aggravating the jitter and reducing the tracking accuracy.

[0004] Therefore, a photovoltaic MPPT control method based on an improved sliding mode reaching law is needed to improve tracking accuracy, reduce jitter, and achieve precise control of photovoltaic maximum power point tracking. Summary of the invention

[0005] The purpose of the present invention is to propose a photovoltaic MPPT control method based on an improved sliding mode reaching law, comprising the following steps:

[0006] Establish photovoltaic power generation systems and analyze operating characteristics;

[0007] Select the sliding surface, and obtain the improved multi-power combination function reaching law according to the fast power reaching law, the double power reaching law and the saturation function;

[0008] The improved multi-power combination function reaching law is:

[0009]

[0010] in:

[0011]

[0012] Where: k 1 , k 2 , k 3 , k 4 are the proportional coefficients of the four power functions, where k 1 >0;k 2 >0;k 3 >0;k 4 >0; a, b, c, d are the power term exponent values, where a>1; 0<b<1; 0<d<1; φ, δ are the interval division thresholds, where 0<φ<1; δ=1;

[0013] The sliding mode control law is selected and the sliding mode control stability is analyzed to perform photovoltaic maximum power tracking on the photovoltaic power generation system.

[0014] Furthermore, the improved multi-power combination function reaching law includes the following situations:

[0015] When the system state is |s|≥δ, it is expressed as

[0016]

[0017] c=max{a,|s|}

[0018] When the system state is φ≤|s|<δ, it is expressed as

[0019]

[0020]

[0021] When the system state is |s|<φ, it is expressed as

[0022]

[0023] Furthermore, the photovoltaic power generation system is composed of a photovoltaic array component, a Boost circuit, and an MPPT control module.

[0024] Furthermore, the sliding surface is:

[0025]

[0026] Where: I pv is the output current of the photovoltaic cell; U pv is the output voltage of the photovoltaic cell; P pv is the output power of the photovoltaic cell.

[0027] Furthermore, the sliding mode control law is:

[0028]

[0029] Where: u eq is the control function when the system state trajectory moves on the sliding surface, u n is the switching control law, U o is the output voltage of the Boost converter, U pv is the output voltage of the photovoltaic cell, and L is the inductance of the Boost converter.

[0030] The beneficial effects of the present invention are:

[0031] The present invention uses the Boost circuit as the control object, utilizes the IU output characteristics of photovoltaics, and further designs the sliding mode approaching law power term exponent as different piecewise functions. The power function is combined with the exponential approaching term. In the process of the system state approaching the sliding mode surface, the exponential parameter can be automatically adjusted according to the distance from the sliding mode surface, so that the system approaching speed is further divided and changed. The approaching law multiple power functions change at different distances, thereby obtaining different approaching speeds, accelerating the approaching process of the system at each stage, ensuring that the system reaches the sliding mode surface smoothly, and improving the tracking accuracy. Then, the precise control of photovoltaic maximum power point tracking is realized, which is helpful to improve the photovoltaic power generation capacity. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 It is a flow chart of the photovoltaic MPPT control method based on the improved sliding mode reaching law of the present invention.

[0033] Figure 2 It is a structural diagram of a photovoltaic power generation system in a specific implementation manner of the present invention.

[0034] Figure 3 It is a structural diagram of sliding mode control in a specific implementation manner of the present invention.

[0035] Figure 4 It is a flow chart of photovoltaic MPPT control under improved sliding mode control in a specific implementation manner of the present invention.

[0036] Figure 5 It is a power characteristic curve diagram of photovoltaic startup time in a specific implementation manner of the present invention.

[0037] Figure 6 It is a power characteristic curve diagram under a variable temperature environment in a specific implementation manner of the present invention.

[0038] FIG. 7( a ) and FIG. 7( b ) are partial enlarged views of the power characteristic curve under a variable temperature environment in a specific implementation manner of the present invention.

[0039] Figure 8 It is a power characteristic curve diagram under a shaded environment in a specific implementation manner of the present invention.

[0040] FIG. 9( a ) and FIG. 9( b ) are partial enlarged views of the power characteristic curve in a shaded environment according to a specific embodiment of the present invention. DETAILED DESCRIPTION

[0041] The present invention proposes a photovoltaic MPPT control method based on an improved sliding mode reaching law, which will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0042] Figure 1 This is a flow chart of the photovoltaic MPPT control method based on the improved sliding mode reaching law of the present invention, which is as follows:

[0043] (1) Establish a photovoltaic power generation system and analyze its working characteristics.

[0044] The photovoltaic power generation system structure involved in the present invention is as follows Figure 2 As shown, it is mainly composed of photovoltaic array components, Boost circuit and MPPT control module.

[0045] Photovoltaic array components: Photovoltaic array components are composed of multiple photovoltaic cells connected in series and parallel. In the photovoltaic cell model, the output current I pv With output voltage U pv The mathematical relationship between them is:

[0046]

[0047] Where: I ph is the photocurrent; I o is the saturation current; n is the diode ideality factor; k is the Boltzmann constant; T is the battery temperature; and q is the electron charge.

[0048] It is difficult to solve the above equation directly, so the short-circuit current I is usually used. sc , open circuit voltage U oc , maximum power point current and voltage (I m and U m)Simplify the above model to:

[0049]

[0050] The relevant parameters in the formula are all under standard working conditions (S = 1kW / m 2 , T=25℃) value.

[0051] I sc , U oc ,I m , U m They will change with the intensity of light radiation and temperature. When the environment changes, the above formula is corrected to:

[0052]

[0053] Among them, I sc , U oc ,I m , U m They are:

[0054]

[0055] U o ' c =U o ' c (1-bΔT)ln(e+cΔS)

[0056]

[0057] U′ m =U′ m (1-bΔT)ln(e+cΔS)

[0058] ΔT=TT ref

[0059]

[0060] Where a = 0.0025°C, b = 0.00288°C, c = 0.5

[0061] It can be seen from the above formula that the voltage and current at the maximum power output point will change accordingly with changes in temperature and light intensity. Therefore, it is necessary to control the output voltage and current to move toward the maximum power point to ensure that the system is always in the maximum power output state.

[0062] Boost circuit: Boost circuit has simple structure, easy control and high operating efficiency. Figure 2 It can be seen that the Boost circuit is mainly composed of inductor L, input capacitor C 1 , output capacitor C 2, switch power tube N, diode D, and load R. If u is the control signal for controlling the switch power tube, when u=1, the switch power tube is turned on, and when u=0, the switch power tube is turned off.

[0063] Under steady-state conditions, it can be approximately considered that I pv =I L ; By analyzing the circuit, we know that the state equation of the Boost circuit is:

[0064]

[0065] in:

[0066]

[0067] MPPT control module: It uses sliding mode control to output the control signal u of the switching power tube. By controlling the on and off of the switching tube, it adjusts the working voltage and makes the working point of the photovoltaic cell close to the maximum power point.

[0068] (2) Select the sliding surface and obtain the improved reaching law of multi-power combination function according to the fast power reaching law, double power reaching law and saturation function.

[0069] B1. Select the sliding surface

[0070] From the working characteristics of photovoltaic cells, we can know that when photovoltaic cells work at the maximum power point:

[0071]

[0072] When the system is stable at the maximum power point, it can continuously output the maximum power, so the sliding surface s can be selected as:

[0073]

[0074] Where: I pv is the output current of the photovoltaic cell; U pv is the output voltage of the photovoltaic cell; P pv is the output power of the photovoltaic cell.

[0075] When s>0, the system works on the left side of the maximum power point. It is necessary to control the switch power tube to be turned on to increase the working voltage to approach the maximum power point. When s<0, the system works on the right side of the maximum power point. It is necessary to control the switch power tube to be turned off to reduce the working voltage to make the working point close to the maximum power point.

[0076] B2. Improved sliding mode reaching law

[0077] Fast power reaching law:

[0078] Bi-power reaching law:

[0079] Simple analysis shows that the above two reaching laws are essentially continuous. When the system state reaches the sliding surface, i.e., when s = 0, the reaching speed slowly decreases to 0, completing a smooth transition and controlling the generation of chattering.

[0080] Due to the discontinuity of the sign function sgn(·), system chattering and low control accuracy occur. To solve this problem, the saturation function sat(·) shown in the following formula is used to replace the sign function sgn(·). When |s| ≤ Δ, linear feedback is performed within the boundary layer through the saturation function, making the transition of the sliding mode smoother and weakening system chattering.

[0081]

[0082] In the formula: Δ > 0, which is the boundary layer thickness.

[0083] On this basis, in order to make the system have a larger reaching speed at each stage of reaching the sliding surface and reduce the chattering that occurs when the system slides on the sliding surface, by combining the above two power reaching laws, an improved multi-power combination function reaching law is proposed:

[0084]

[0085] Where:

[0086]

[0087] In the formula: k 1 , k 2 , k 3 , k 4 are the proportionality coefficients of the four power functions respectively, where k 1 > 0; k 2 > 0; k 3 > 0; k 4 > 0; a, b, c, d are the exponential values of the power terms respectively, where a > 1; 0 < b < 1; 0 < d < 1; φ, δ are the interval division thresholds, where 0 < φ < 1; δ = 1.

[0088] The improved reaching law continuously combines and changes at different stages of the system sliding approach. As a whole, it is mainly composed of a power function approaching term and an exponential approaching term. The power approaching term can achieve a smooth entry into the sliding mode, but the speed becomes slower as it gets closer to the switching surface; the exponential approaching term has a faster convergence speed when far from the sliding surface, and the larger the k value, the faster the approaching rate. This enables the system to quickly respond to control requirements. Combining with the power approaching term can more effectively reduce the overshoot of the system and improve the stability of the system. The combination of the two functions is beneficial for the system to have a faster convergence speed, a better chattering suppression effect, and an improved dynamic quality.

[0089] When the system state is in |s|≥δ, the reaching law can be expressed as:

[0090]

[0091] At this time, the reaching law is a combination of multiple power functions. Since the system state in this stage starts from an arbitrary initial position and is far away from the sliding surface, it needs to approach the sliding surface at a faster speed. At this time, c = max{a,|s|}, and the system has four power functions, which greatly speeds up the reaching speed.

[0092] When the system state is φ≤|s|<δ, the reaching law can be expressed as:

[0093]

[0094] At this time, the system state is relatively close to the sliding surface but still has a certain distance, and the overall approach speed is lower than the previous stage. The approach law is a combination of power and exponential approach terms, c = min{d,|s|}, the power exponential term of the first term on the right side of the equal sign is reduced to 1, and the second term changes from a power function to an exponential approach term -k 2 s. It can ensure the approach speed while making the system smoothly enter the sliding mode stage and eliminate chattering.

[0095] When the system state is in |s|<φ, the reaching law can be expressed as:

[0096]

[0097] At this time, the system state is infinitely close to 0 within a very small range of s = 0, and the power exponent value of the third term on the right side of the equal sign is further reduced. As the system state gets closer and closer to the sliding surface, the approaching speed of each term in the approaching law is getting smaller and smaller, so the total approaching speed is constantly decreasing. Therefore, the chattering that occurs when the system reaches the sliding surface also decreases.

[0098] (3) Select the sliding mode control law and analyze the sliding mode control stability to perform photovoltaic maximum power tracking on the photovoltaic power generation system.

[0099] When designing the sliding mode control function of photovoltaic maximum power tracking, the sliding mode control function can be understood as two parts, namely the equivalent control law u eq and the switching control law u n , and then control the switch tube to turn on or off. The control structure diagram is as follows Figure 3 As shown, the sliding mode control law function can be expressed as:

[0100] u=u eq +u n

[0101] When the system state trajectory moves on the sliding surface, its control function can be expressed by the equivalent control law u eq express:

[0102]

[0103] Where: U o is the Boost converter output voltage.

[0104] Switching control law u n It affects the switching speed of the sliding mode control and the size of the chattering on the sliding mode surface. Its function is expressed as:

[0105]

[0106] Where: L is the inductance of the Boost converter.

[0107] The control signal u is obtained through the above process. However, the control signal cannot exceed the control range, and saturation control must be added. The size of the control signal should be between 0 and 1, that is,

[0108]

[0109] Since it is difficult to set s = 0 in actual systems, especially in digital simulation, ε is taken as a small positive number for bandwidth limitation. When |s|≤ε, s = 0 is assumed by default. According to the above control law design process, the flowchart of the proposed sliding mode control for photovoltaic maximum power tracking is shown in Figure 4 shown.

[0110] The sliding mode control stability of the system includes:

[0111] C1. Sliding mode existence and reachability analysis

[0112] Take the Lyapunov function V = s 2 / 2, if the derivative of the function V(s) with respect to time is less than or equal to zero, it means that the sliding surface is reachable. After taking its derivative:

[0113]

[0114] For any s, s·sat(s)>0. If k 1 >0;k 2 >0;k 3 >0;k 4 >0,Δ>0:

[0115] When |s|≥δ:

[0116]

[0117] When |s|<δ:

[0118]

[0119] For any s, it satisfies If and only if s = 0 Therefore, for the improved sliding mode reaching law, the sliding mode variable s can move to the equilibrium point s = 0 under its action, satisfying the existence and reachability of the sliding mode.

[0120] C2. Steady-state chattering analysis

[0121] For the improved sliding mode reaching law, when s→0 + With s→0 - When , the reaching law can be written as That is, the system will hardly produce chattering phenomenon when it is in critical steady state.

[0122] C3. Approach rate analysis

[0123] For the improved sliding mode reaching law, if the initial state of s is s 0 , then the system can reach the sliding surface and converge to 0 in a finite time, and its convergence time is less than T 1 +T 2 +T 3 +T 4 +T 5 , where T 1 , T 2 , T 3 , T 4 , T 5 They are:

[0124]

[0125] Therefore, under the control of the improved sliding mode reaching law, the system can reach the sliding mode surface within a certain time and accelerate the convergence speed by reasonably designing parameters.

[0126] Proof: Assume s 0 >a>1, the process of the system approaching 0 can be divided into five stages. 0 to s(t 1 )→a, the improved reaching law can be written as:

[0127]

[0128] Because |-k 1 s a -k 2 s b -k 3 s s |>|-k 1 s a -k2 s|, so the system's approach time in the above formula must be less than the approach law -k 1 s a -k 2 s, through the approach time controlled by Solution:

[0129]

[0130] Assume that there is an intermediate variable u=s 1-a , then:

[0131]

[0132] Integrate both sides of the above equation:

[0133]

[0134] To simplify the constant part, let C 2 =C 1 (1-a), then:

[0135]

[0136] make Then we have:

[0137]

[0138] After simplification, we can get:

[0139]

[0140] Since t = 0, s = s(0) = s 0 , so the constant c is:

[0141]

[0142] The combined derivation yields:

[0143]

[0144] Therefore, from s 0 to s(t 1 )→a The time required should be less than T 1 :

[0145]

[0146] Similarly, we can obtain the system from s(t 1 ) to s(t 2 )→1 is less than T 2 , from s(t 2 ) to s(t3 )→d is less than T 3 , from s(t 3 ) to s(t 4 )→φ is less than T 4 , from s(t 4 ) to s(t 5 )→0 is less than T 5 . Eventually, the system converges in less than T 1 +T 2 +T 3 +T 4 +T 5 .

[0147] C4. Steady-state error bound analysis

[0148] When the system is disturbed by external uncertainties, the reaching law can only allow the system to reach a neighborhood near the equilibrium point. For uncertain nonlinear systems, assuming that there are external disturbance variables, the derivative of the sliding surface s will become:

[0149]

[0150] Where d is a bounded disturbance variable, that is, d≤D, and D is a constant greater than 0.

[0151] At this time, the state of the system can converge to the following area in a finite time:

[0152]

[0153] This shows that the system's motion state is still stable after being disturbed by external uncertain disturbances, and it will gradually converge under the control of the reaching law. The stability error bound can be reduced by adjusting the parameters, making the system have better anti-interference ability.

[0154] Proof: Choose the Lyapunov function V = s 2 / 2, then:

[0155]

[0156] The above formula can be further rewritten into two forms:

[0157] 1.

[0158] 2.

[0159] (1) For the first case:

[0160] When k 4 |s| d -D≥0, that is at this time

[0161]

[0162] From the above formula, we can see that in a finite time the system will converge to the region

[0163] Similarly, when k 2 |s| b -D≥0, converges to the region When k 3 |s| c -D≥0, converges to the region

[0164] (2) For the second situation:

[0165] When k 1 |s| a -D≥0, that is at this time

[0166]

[0167] From the above formula, we can see that in a finite time the system will converge to the region

[0168] In summary, the state s will converge to the region shown in the following formula in a finite time

[0169]

[0170] The technical effect of the present invention is described below through a specific implementation.

[0171] In order to verify the effectiveness of the photovoltaic MPPT control method based on the improved sliding mode reaching law proposed in this invention in tracking the photovoltaic maximum power performance, a photovoltaic power generation system model was built using the Matlab / Simulink simulation platform. The power tracking performance of the control method proposed in this invention (Improve Slide Model Control, ImSMC) was compared with that of the perturbation and observation method (P&O), the fast power law sliding mode control (FPLSMC), and the double power law sliding mode control (DPLSMC) method in three different environments at the start-up time, sudden change of light temperature, and sudden change of light radiation intensity, and the correctness and superiority of the proposed control method were analyzed.

[0172] In the system simulation, the photovoltaic system consists of a 15×5 photovoltaic array, and the photovoltaic cell component parameters are: open circuit voltage U oc =21V, short circuit current I sc =4.7A, maximum power point voltage U mp =19V, maximum power point current I mp =4.21A. Boost main circuit parameters are: input capacitor C 1 =100μF, output capacitor C 1 =0.001F, inductance L=5mH.

[0173] The standard environment of the photovoltaic system is set as follows: light temperature T = 25°C, light radiation intensity S = 1kW / m 2 At this time, the ideal maximum output power of photovoltaic is about P m =6kW. Figure 5 The power characteristic curves of the four methods, P&O, FPLSMC, DPLSMC and ImSMC, at the photovoltaic startup moment in this environment are shown in Figure 2. Figure 5 From the different power curves, it can be seen that the four methods can eventually reach the maximum photovoltaic output power of about 6kW and achieve maximum power point tracking. From the local enlarged image, it can be seen that the P&O power tracking speed is obviously slower than the sliding mode control. This is because P&O needs to continuously apply disturbances to determine the output power during the control process, which leads to a slower response speed and poor dynamic tracking performance. It takes about 0.07s after startup to reach the maximum power point, and there is jitter in the power after stabilization, and the error fluctuates by about 0.27% compared to the maximum power point. The sliding mode control effects under different reaching laws are different. The time for FPLSMC, DPLSMC, and ImSMC methods to stabilize at the maximum power point are 0.025, 0.013, and 0.014s, respectively, and the steady-state power error fluctuates by approximately 0.08%, 0.18%, and 0.06%, respectively, compared to the maximum power point. Combined with Figure 5 From (a) and (b), we can see that FPLSMC can reach the sliding surface faster than P&O, and the final average power is stabilized at around 6±0.0025kW, with high tracking accuracy. Although DPLSMC has a faster tracking response speed than FPLSMC, the steady-state power oscillation is more obvious and it cannot always stabilize at the rated power value. The maximum fluctuation error is about 12.5W, and the tracking accuracy is relatively low. ImSMC combines the advantages of the two convergence laws, adjusts the approach speed according to the distance from the sliding surface, and achieves a faster response speed to reach the convergence state than FPLSMC. Compared with DPLSMC, it greatly reduces the jitter amplitude, and can finally achieve maximum power point tracking quickly and accurately, effectively improving the problems of slow response speed and significant jitter of sliding mode control.

[0174] To verify the power tracking performance of the control method under ambient temperature changes, the light radiation intensity S is set to 1kW / m2 The light temperature T increased from 25℃ to 35℃ at 0.4s and returned to 25℃ at 0.7s. Figure 6 7 is a power characteristic curve diagram of the control method proposed by the present invention and three comparative methods under variable temperature environment and a partial enlarged diagram of the transformation process. Figure 6 It can be seen that at the standard 25℃, all four methods can reach near the maximum power. As the temperature increases, the maximum photovoltaic power value decreases. After the temperature recovers, the photovoltaic power can also recover to the initial maximum power. Further observation of the local enlarged Figure 7(a) and Figure 7(b) during the transition process shows that the tracking time to reach the new stable point under different controls is different. When the temperature rises from 25℃ to 35℃, the tracking time of the four controls to reach the new stable point is 0.014s, 0.006s, 0.0015s, and 0.0015s respectively; when the temperature returns to 25℃, the tracking time is 0.018s, 0.0057s, 0.0018s, and 0.0018s respectively. Among them, P&O has not reached a stable state in the local enlarged figure. The corresponding power waveform in Figure 7(a) first drops to 5.4kW and then rises to 5.46kW and continues to oscillate. There is a certain error compared with the rated maximum power of 5.49kW in this environment. The tracking time of DPLSMC to reach the new steady-state point is consistent with that of ImSMC, and the tracking response speed is the fastest. However, it can be seen from Figure 7(a) and Figure 7(b) that the power fluctuation of this method is obvious and it cannot be continuously stabilized at the maximum power point. After ImSMC quickly recovers to the steady state, the power can accurately reach the maximum power point, with higher tracking accuracy and smaller power jitter. From the above comparison, it can be seen that the control method ImSMC proposed in the present invention has the best tracking performance in a variable temperature environment.

[0175] In order to verify the power tracking performance of the control method under the change of light radiation intensity, the light temperature T is set to remain unchanged at 25℃, and the light radiation intensity S is increased from 1kW / m 2 Reduced to 0.8kW / m 2 , and recovered to 1kW / m at 0.7s. 2 . Figure 8 9 is a partial enlarged diagram of the power characteristic curves of the control method proposed by the present invention and three comparative methods under a shaded environment and the transformation process thereof. Figure 8It can be seen from the power curve that as the light radiation intensity decreases, the maximum power output of the photovoltaic system also decreases. All four methods can quickly track the new maximum power point after the light intensity changes. However, it can be clearly seen from the partial enlarged Figure 9(a) that the power tracking of P&O oscillates around 4.7kW after the light radiation intensity decreases and returns to a steady state, which is less than the rated maximum power of 4.732kW in this environment, and there is a situation of insufficient photovoltaic power generation; after FPLSMC reaches the rated maximum power at about 0.403s, the power is not stable, and it drops by about 30W and then gradually rises, and gradually tends to a steady state at 0.41s; the DPLSMC power curve always has certain fluctuations; the ImSMC proposed in the present invention takes about 0.003s to track the maximum power point and tends to a steady state, and the power curve is relatively stable and smooth. It can also be concluded from the partial enlarged Figure 9(b) that the method proposed in the present invention has a stable performance when the light radiation intensity changes from 0.8kW / m 2 Return to normal 1kW / m 2 It also has faster tracking response speed and more stable tracking accuracy.

[0176] The photovoltaic MPPT control method based on the improved sliding mode convergence law proposed in the present invention has the main advantage of combining the advantages of FPLSMC and DPLSMC. By designing the sliding mode convergence law power exponential term as different piecewise functions, a piecewise adjustment method for different stages of the convergence process is constructed, and the sliding mode controller design and sliding mode stability proof are given to ensure a faster tracking speed in the early stage of tracking, and at the same time, the maximum power point can be found very accurately in the later stage of tracking. It overcomes the problem of slow tracking speed caused by step-by-step tracking methods such as classic P&O, improves the dynamic response performance of maximum power tracking, and alleviates the phenomenon that the sliding mode surface switching process in the general sliding mode control maximum power tracking is prone to cause large steady-state power fluctuations. It can be applied to MPPT under conditions such as unchanged environment, variable temperature, and shading, with fast response speed, high tracking accuracy, and weak jitter.

[0177] Through the above description, the present invention has a faster dynamic tracking response speed, a smoother power curve, smaller waveform jitter, and higher steady-state tracking accuracy, whether at the startup moment or when the photovoltaic system environment changes. It can achieve accurate tracking and control of the photovoltaic maximum power point, which helps to improve the maximum power fast tracking and smooth control performance of the photovoltaic system under large disturbances. It is of great significance for the study of photovoltaic power generation systems, microgrid operation fields, etc.

Claims

1. A photovoltaic MPPT control method based on an improved sliding mode reaching law, characterized in that: The following steps are involved: Establish photovoltaic power generation systems and analyze operating characteristics; Select the sliding surface, and obtain the improved multi-power combination function reaching law according to the fast power reaching law, the double power reaching law and the saturation function; The improved multi-power combination function reaching law is: in: Where: k1, k2, k3, k4 are the proportional coefficients of the four power functions, where k1>0; k2>0; k3>0; k4>0; a, b, c, d are the exponent values ​​of the power terms, where a>1; 0<b<1; 0<d<1; φ, δ are the interval division thresholds, where 0<φ<1; δ=1; The sliding mode control law is selected and the sliding mode control stability is analyzed to perform photovoltaic maximum power tracking on the photovoltaic power generation system.

2. The photovoltaic MPPT control method based on the improved sliding mode reaching law according to claim 1 is characterized in that: The improved multi-power combination function reaching law includes the following situations: When the system state is |s|≥δ, it is expressed as c=max{a,s} When the system state is φ≤|s|<δ, it is expressed as c=min{d,s} When the system state is |s|<φ, it is expressed as 3. The photovoltaic MPPT control method based on the improved sliding mode reaching law according to claim 2 is characterized in that: The photovoltaic power generation system consists of a photovoltaic array component, a Boost circuit, and an MPPT control module.

4. The photovoltaic MPPT control method based on the improved sliding mode reaching law according to claim 3 is characterized in that: The sliding surface is: Where: I pv is the output current of the photovoltaic cell; U pv is the output voltage of the photovoltaic cell; P pv is the output power of the photovoltaic cell.

5. The photovoltaic MPPT control method based on the improved sliding mode reaching law according to claim 4 is characterized in that: The sliding mode control law is: Where: u eq is the control function when the system state trajectory moves on the sliding surface, u n is the switching control law, U o is the output voltage of the Boost converter, U pv is the output voltage of the photovoltaic cell, and L is the inductance of the Boost converter.

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