Maximum power point dynamic tracking method for offshore double-sided photovoltaic system

Abstract

The invention provides a maximum power point dynamic tracking method for an offshore double-sided photovoltaic system, and the method is characterized in that the method comprises the steps: collecting the dynamic parameters of an environment where the offshore double-sided photovoltaic power generation system is located in real time; establishing a time-varying nonlinear mathematical model of the output power of the offshore double-sided photovoltaic module with respect to the pitching inclination angle of the photovoltaic module; determining a voltage upper boundary and a voltage lower boundary corresponding to the convex hull region; the method comprises the following steps: designing and controlling a Lyapunov function, and constructing a Sontag auxiliary controller for controlling the Lyapunov function; establishing a nonlinear state-space equation of the Boost converter; designing an economic performance index function; designing an economic model prediction controller; controlling the state of the offshore double-sided photovoltaic system in a disturbance feasible region based on an economic model prediction controller so as to obtain an optimal control quantity; and realizing maximum power point dynamic tracking of the offshore double-sided photovoltaic system under wave disturbance based on the optimal control quantity. And the purposes of better stability and higher accuracy are achieved.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of new energy control, and particularly relates to a maximum power point dynamic tracking method for an offshore double-sided photovoltaic system. BACKGROUND

[0002] An offshore floating double-sided photovoltaic power generation system has become an important direction of new energy development due to its high power generation capacity, land resource saving, and synergistic potential with offshore wind power, hydrogen production, and other industries. However, the complexity of the marine environment, such as large waves, typhoons, salt spray corrosion, and the like, causes photovoltaic components to face severe shaking and irradiance mutations, leading to unstable output power. In particular, the change in the pitch angle of the photovoltaic panel caused by wave motion dynamically changes the irradiance distribution received by the front and back surfaces of the double-sided component, resulting in a multi-peak characteristic of the power curve, which significantly increases the difficulty of maximum power point tracking.

[0003] Traditional maximum power point tracking algorithms, such as the perturbation and observation method and the incremental conductance method, perform well in terrestrial photovoltaic systems. However, the offshore double-sided photovoltaic system is exposed to a complex environment of dynamic coupling of wind, waves, and flow for a long time. Traditional maximum power point tracking algorithms are designed based on static or single disturbance assumptions and are difficult to adapt to the high-frequency random disturbance of the marine environment and the spatiotemporal non-uniformity of energy distribution, which easily falls into local optimization. At the same time, in the face of high-frequency changes in irradiance caused by sea wave disturbance, traditional algorithms are difficult to quickly track the global maximum power point due to calculation delay, resulting in power oscillation and energy loss. Therefore, how to build a stable maximum power point tracking model under dynamic coupling disturbance has become a key problem for improving the energy efficiency of offshore double-sided photovoltaic systems.

[0004] Economic model predictive control has received great attention from the industry and academia because it can integrate process economic optimization and feedback control into an optimal control framework. Although economic model predictive control can balance the collaborative optimization needs of photovoltaic array operation economy and dynamic tracking efficiency, in the controller design process for strong nonlinear systems, multiple steady-state dynamics and inequality constraints make the optimal control behavior more complex. Under these conditions, how to ensure the asymptotic stability of the closed-loop system and achieve rapid convergence of economic performance indicators under the constraint of limited computing resources has become a key challenge for the development of offshore photovoltaic systems. SUMMARY

[0005] In view of the problems in the prior art, the present application provides a maximum power point dynamic tracking method for an offshore double-sided photovoltaic system, which at least partially solves the problem of difficulty in quickly tracking the global maximum power point in the prior art.

[0006] The present application provides a maximum power point dynamic tracking method for an offshore double-sided photovoltaic system, which at least partially solves the problem of difficulty in quickly tracking the global maximum power point in the prior art.

[0007] Real-time acquisition of dynamic parameters of the environment where the offshore bifacial photovoltaic power generation system is located, the dynamic parameters including a pitch angle of the photovoltaic component and a solar irradiance at an observation point;

[0008] Based on a dynamic relationship between the solar irradiance at the observation point and the pitch angle of the photovoltaic component, a time-varying nonlinear mathematical model of output power of the offshore bifacial photovoltaic component with respect to the pitch angle of the photovoltaic component is established;

[0009] Based on the time-varying nonlinear mathematical model, a convex hull region where a global maximum power point is located is identified, and an upper boundary and a lower boundary of voltage corresponding to the convex hull region are determined;

[0010] A control Lyapunov function is designed, and a Sontag auxiliary controller of the control Lyapunov function is constructed;

[0011] A nonlinear state space equation of a Boost converter is established;

[0012] Based on the nonlinear state space equation of the Boost converter, the upper boundary and the lower boundary of voltage corresponding to the convex hull region, output power of the bifacial photovoltaic system and switching loss of the power converter, an economic performance index function is designed;

[0013] Based on the control Lyapunov function, the Sontag auxiliary controller and the economic performance index function, an economic model predictive controller is designed;

[0014] Based on the economic model predictive controller, states of the offshore bifacial photovoltaic system are controlled in a disturbance feasible region, so that an optimal control amount is obtained;

[0015] Based on the optimal control amount, dynamic tracking of a maximum power point of the offshore bifacial photovoltaic system under wave disturbance is realized.

[0016] Optionally, the dynamic parameters further include wave parameters, the wave parameters including a wave height or a sea wave frequency.

[0017] Optionally, the time-varying nonlinear mathematical model of output power of the offshore bifacial photovoltaic component with respect to the pitch angle of the photovoltaic component is established based on a dynamic relationship between the solar irradiance at the observation point and the pitch angle of the photovoltaic component, and includes:

[0018] Supposing that scattered irradiance and reflected irradiance are isotropic, direct irradiance received by the back of the bifacial photovoltaic component is ignored, and atmospheric transparency is in an ideal state, effective irradiance received by the bifacial photovoltaic component is For example,

[0019] ,

[0020] where, a front irradiance received by the bifacial photovoltaic component is and a back irradiance The calculation formula is as follows:

[0021]

[0022]

[0023] In the formula, is a double-sided factor, is the horizontal total radiation of the observation point, is the horizontal direct irradiance, is the horizontal diffuse irradiance, , is the sea surface reflectivity, is the component tilt angle, is the incident angle of the sun's direct light at any moment.

[0024] Optionally, the nonlinear state space equation of the Boost converter is established, comprising:

[0025] The state vector is defined as the inductor current , the photovoltaic terminal voltage and the voltage across the capacitor , and the input vector is the switch state ;

[0026] The dynamic mathematical model for realizing the maximum power point tracking function of the offshore double-sided photovoltaic power generation system based on the Boost converter is:

[0027]

[0028] In the formula: is the switch state of the Boost switch tube, are input and output filter capacitors respectively, is the inductance of the Boost converter, is the current flowing through the inductor , is the voltage across the capacitor , is the photovoltaic terminal voltage, is the photovoltaic terminal current, is time.

[0029] Optionally, the control Lyapunov function is designed, and the Sontag auxiliary controller of the control Lyapunov function is constructed, wherein the Sontag auxiliary controller is used to quickly drive the system state back to the feasible region inside when the system state exceeds the disturbance feasible region.

[0030] Optionally, based on the nonlinear state space equation of the Boost converter, the upper and lower voltage boundaries corresponding to the convex hull region, the output power of the bifacial photovoltaic system, and the switching loss of the power converter, an economic performance index function is designed, including:

[0031] The economic performance index of the offshore bifacial photovoltaic power generation system is represented as:

[0032]

[0033] In the formula: Pout represents the output power of the offshore bifacial photovoltaic power generation system, Pout is used to calculate the output power, Psw represents the switching loss value, Psw is used to calculate the switching loss, Pout represents the output power of the offshore bifacial photovoltaic power generation system, Psw represents the switching loss,

[0034] Optionally, based on the nonlinear state space equation of the Boost converter, the upper and lower voltage boundaries corresponding to the convex hull region, the output power of the bifacial photovoltaic system, and the switching loss of the power converter, an economic performance index function is designed, including:

[0035] The economic objective function of the offshore bifacial photovoltaic power generation system is represented as:

[0036]

[0037] is a linear weight coefficient.

[0038] Optionally, based on the control Lyapunov function, the Sontag auxiliary controller, and the economic performance index function, an economic model predictive controller is designed, including: a first mode and a second mode;

[0039] The first mode is to solve the economic model predictive control optimization problem of the objective function online when the system state is located in the disturbance feasible region, and embed the Lyapunov function stability constraint, and output the optimal control amount in real time;

[0040] The second mode is to switch to the Sontag auxiliary controller when the system state exceeds the disturbance feasible region but is located in the ideal feasible region, and use the Sontag auxiliary controller to drive the system state back to the disturbance feasible region, and then switch back to the first state.

[0041] Optionally, the economic model predictive control optimization problem embedded with the Lyapunov function stability constraint includes:

[0042] ​​​The mixed integer nonlinear programming algorithm is used for online rolling solution, and an optimal switch state sequence at the current time is obtained.

[0043] Optionally, the prediction step in the first mode The control step The control switching time The 15s is selected, and the dynamic response process termination time is taken .

[0044] The maximum power point dynamic tracking method for the offshore double-sided photovoltaic system provided by the application is based on the relationship between irradiance and component pitch angle, and a dynamic mathematical model of the offshore double-sided photovoltaic system component is constructed. By finding the global maximum power point located between the convex hull domain of the power-voltage characteristic curve of the two voltage boundaries, the constraint conditions in the two operating modes are determined, the optimization search space is reduced, the calculation complexity is reduced, and the real-time control demand in the complex environment is met. After the control algorithm design process is derived in detail, a stable economic model predictive controller is designed, which effectively suppresses the power oscillation caused by the irradiance mutation caused by the wave disturbance, and realizes the dynamic tracking of the maximum power point in the complex multi-peak scene. The double-mode operation mechanism of the Sontag auxiliary controller designed based on the Lyapunov function can optimize and adjust the control input in real time, and takes into account the stability of the system and the economy of regulation and control, further improving the tracking speed. The tracking target can be more accurately realized, the system optimization calculation amount is greatly reduced, the stability is better, and the accuracy is higher. BRIEF DESCRIPTION OF DRAWINGS

[0045] The above and other objects, features and advantages of the present disclosure will become more apparent from the following detailed description of exemplary embodiments thereof, taken in conjunction with the accompanying drawings in which like reference characters designate the same parts throughout the several views.

[0046] Figure 1 A flowchart of the maximum power point dynamic tracking method for the offshore double-sided photovoltaic system provided by the embodiment of the present disclosure is provided.

[0047] Figure 2 A schematic diagram of finding a dynamic voltage constraint boundary for the offshore double-sided photovoltaic power generation system provided by the embodiment of the present disclosure is provided.

[0048] Figure 3 A control structure block diagram of the stability economic model predictive control provided by the embodiment of the present disclosure is provided. DETAILED DESCRIPTION

[0049] The embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings.

[0050] It should be apparent that the following description illustrates by way of example only the embodiments of the disclosure and that other advantages and benefits can be realized by persons skilled in the art from consideration of the disclosure. It is expressly understood that the described embodiments are merely examples of the disclosure and are not the only structures to which the disclosure is applicable. The disclosure can be practiced in other embodiments that are apparent to those skilled in the art from consideration of the specification or practicing the disclosure without modifying the fundamental principles specified in the disclosure. It is therefore intended that the disclosure covers all modifications and variations of this disclosure provided they come within the scope of the appended claims and their equivalents. It is intended that the application be construed as including all such embodiments and equivalents.

[0051] It is to be understood that the following description is merely descriptive in nature and is not intended to limit the scope of the embodiments described in the appended claims. As such, the aspects described herein can be embodied in a multitude of different forms and should not be limited to only the forgoing or the expressly identified examples. No admission is made that any of the aspects of the disclosure have not been previously invented general background

[0052] It should also be noted that the figures provided in the following embodiments are only to schematically illustrate the basic concept of the disclosure, and only the components related to the disclosure are shown in the figures, not drawn according to the number, shape and size of the components in actual implementation, and the shape, number and proportion of each component in actual implementation can be arbitrarily changed, and the layout pattern of the components can also be more complex.

[0053] In addition, in the following description, specific details are provided in order to facilitate a thorough understanding of the examples. However, one skilled in the art will understand that the aspects described can be practiced without these specific details.

[0054] Aiming at the problems of significant wave disturbance influence, difficulty in adapting to dynamic multi-peak characteristics and ensuring closed-loop stability in the maximum power point tracking process of the current offshore bifacial photovoltaic power generation system, an in-depth study of a high-performance solution is urgently needed. This requires considering the complex environmental changes faced by offshore bifacial photovoltaic systems, especially based on the relationship between irradiance and component tilt angle, to establish a dynamic mathematical model of the component tilt angle. At the same time, it is necessary to solve the shortcomings of existing methods in reducing the stable economic model predictive control online calculation burden and overcome the problem of easy loss of stability of traditional economic model predictive control under dynamic disturbance. Therefore, the proposed dual-mode strategy that combines Lyapunov stability constraints and economic model predictive control achieves power oscillation suppression and global maximum power point fast tracking under wave disturbance through dynamic voltage boundaries and Sontag auxiliary controllers, providing reliable technical support for offshore photovoltaic systems.

[0055] For ease of understanding, as Figure 1 shown, the embodiment discloses a maximum power point dynamic tracking method for an offshore bifacial photovoltaic system, specifically a maximum power point dynamic tracking method for an offshore bifacial photovoltaic system that suppresses wave influence, and the specific steps include:

[0056] S1: Real-time acquisition of dynamic parameters of the environment in which the offshore bifacial photovoltaic power generation system is located, including wave parameters such as wave height, sea wave frequency, floating body pitch tilt angle and observation point solar irradiance.

[0057] S2: Based on the dynamic relationship between irradiance and photovoltaic component pitch tilt angle, considering the influence of component attitude changes caused by wave motion on effective irradiance reception, a time-varying nonlinear mathematical model of offshore bifacial photovoltaic component output power with respect to component tilt angle is established. Specifically, it includes:

[0058] Combined with the law of the sun's movement, assuming that the scattered irradiance and the reflected irradiance are isotropic, ignoring the direct irradiance received by the back of the bifacial photovoltaic component, and when the atmospheric transparency is in an ideal state, the effective irradiance received by the bifacial photovoltaic component is As:

[0059] ,

[0060] where the front irradiance and the back irradiance received by the bifacial photovoltaic component are calculated as follows:

[0061] ,

[0062] ,

[0063] where, is the bi-facial factor, is the observed horizontal total irradiance, is the horizontal direct irradiance, is the horizontal diffuse irradiance, , is the sea surface reflectance, is the component tilt angle , is the incident angle of the direct solar radiation at any time.

[0064] An array of rows columns of bi-facial photovoltaic cells (the number of rows is is the number of photovoltaic cells in series on each branch, the number of columns is the number of parallel branches) has an electrical output characteristic of:

[0065] ,

[0066] ,

[0067] ,

[0068] ,

[0069] ,

[0070] ,

[0071] The output power of the offshore bi-facial photovoltaic power generation system under non-standard conditions is as follows:

[0072] ,

[0073] S3: In order to reduce the complexity of online calculation and narrow the optimization search space, the power-voltage characteristic curve of the photovoltaic array under the current environmental condition is analyzed. By identifying the convex hull region where the global maximum power point is located, the upper boundary (Vmax) and the lower boundary (Vmin) corresponding to the global maximum power point are determined. Vmax is determined by the lowest irradiance component, and Vmin is the equivalent curve when all components are subjected to the same minimum irradiance. The constraint conditions under two operating modes of stable economic model predictive control are set. The specific process is shown in Figure 2

[0074] ​​​S4: Establish the nonlinear state space equation of Boost converter, define the state vector as the inductor current , the photovoltaic terminal voltage , the capacitor voltage , the input vector is the switch state . Specifically, it includes:

[0075] Considering the dynamic mathematical model based on the following Boost converter to realize the maximum power point tracking function of the offshore double-sided photovoltaic power generation system:

[0076] ,

[0077] In the formula: is the switch state of the Boost switch tube, are the input and output filter capacitors respectively, is the inductance of the Boost converter, is the current flowing through the inductor , and is the voltage across the capacitor .

[0078] Define as the state vector, as the input vector, let , then the state space equation is formula:

[0079] ,

[0080] In the formula:

[0081] , ,

[0082] .

[0083] S5: Introduce Sontag auxiliary controller based on Lyapunov stability theory. Design a continuous and differentiable control Lyapunov function which is radially unbounded, and construct the corresponding Sontag feedback control law, which is used to quickly drive the system state back to the feasible region when the system state exceeds the disturbance feasible region, and ensure the asymptotic stability of the closed-loop system. Specifically, it includes:

[0084] For the system without considering constraints, Sontag uses a constructive design method, and for all , set the following continuous and origin asymptotically stable Sontag feedback control law:

[0085] ,

[0086] S6: Combine the system model of the nonlinear state space equation, the voltage boundary constraints, state vector constraints, input vector constraints determined in step S3, and the system stability requirements, and comprehensively consider the maximization of the output power of the offshore photovoltaic power generation system and the minimization of the switching loss of the power converter to design the optimal economic performance indicator function. Specifically including:

[0087] The constraints of the system are:

[0088] ,

[0089] ,

[0090] ,

[0091] ,

[0092] ,

[0093] The economic performance index of the offshore bifacial photovoltaic power generation system is expressed as:

[0094] ,

[0095] Where: represents the output power of the offshore bifacial photovoltaic power generation system, The formula used to calculate the output power is, Indicates the switching loss value, The calculation formula for switching loss is: represents the output power of the offshore bifacial photovoltaic power generation system, represents the switching loss, .

[0096] Combined linear weight coefficient , the economic objective function of the offshore bifacial photovoltaic power generation system is expressed as:

[0097] ,

[0098] The offshore bifacial photovoltaic power generation system can be transformed into the following operation optimization problem for solution:

[0099] ,

[0100]

[0101]

[0102]

[0103]

[0104]

[0105]

[0106]

[0107] where, and are the current time and switching time, respectively. Since the prediction horizon of economic model predictive control is limited, the closed-loop stability of the control system cannot be guaranteed. Therefore, the CLF is applied to the economic model predictive control framework, and the stable economic model predictive control framework is reconstructed by introducing an auxiliary constraint condition. Among them, is the auxiliary control law based on Lyapunov method, is the corresponding CLF of the control system. The introduction of the Lyapunov stability constraint condition enables the economic model predictive control to inherit the stability characteristics of the state feedback control law , and at the same time, due to the online optimization advantage of economic model predictive control, the optimal control output in the prediction horizon can be solved while complying with the system constraint condition.

[0108] S7: Design a dual-mode stable economic model predictive controller based on the principle of economic model predictive control:

[0109] (1) First mode (Mode 1): When the system state is located in the disturbance feasible region, the economic model predictive control optimization problem defined in step S6 with the economic performance index as the objective function and embedded Lyapunov stability constraint is solved online to output the optimal control amount in real time.

[0110] (2) Second mode (Mode 2): When the system state is outside the disturbance feasible region but within the ideal feasible region, switch to the Sontag auxiliary controller designed in step S5, and use the Sontag controller to drive the system state back to the disturbance feasible region, and then switch back to Mode 1.

[0111] In the first operating mode Mode 1, the offshore bifacial photovoltaic system optimizes the comprehensive performance index in the stable domain, and the optimal objective function is obtained by online solving the optimization of economic model predictive control A control variable at the moment; in the second working mode Mode 2, the system state reaches the stable optimal set point by the Sontag auxiliary controller driving system, and the system is forced to realize closed loop stability. The double-mode stable economic model predictive control control strategy effectively overcomes the defects of the traditional economic model predictive control in the frequency modulation process by fusing Lyapunov stability constraint and economic optimization target, and solves the problem of the lack of economic optimization of double-layer model predictive control in the dynamic adjustment stage. The strategy realizes the multi-objective collaborative optimization of the adjustment process under the premise of ensuring the asymptotic stability of the system through the mode switching mechanism. The stable economic model predictive control control structure diagram proposed in the application is as shown in Figure 3 .

[0112] S8: for the economic model predictive control optimization problem in Mode 1, a mixed integer nonlinear programming algorithm is used to solve online rolling to obtain the optimal switch state sequence at the current moment. The mixed integer nonlinear programming algorithm specifically includes the following steps:

[0113] (1) input , is the input variable at the k moment; is the state variable at the k-1 moment.

[0114] (2) use and the predicted state and output , is the output variable at the next moment predicted at the k moment.

[0115] (3) according to the predicted state and output and the corresponding switching vector , calculate the economic objective function .

[0116] (4) select the optimal switching vector: .

[0117] (5) return the optimal switching vector .

[0118] (6) output the optimal switch state .

[0119] To achieve the maximum power point dynamic tracking of the offshore dual-sided photovoltaic power generation system under wave disturbance, an offshore dual-sided photovoltaic power generation simulation system model is built based on the MATLAB / Simulink platform, and multi-scenario comparative analysis is carried out for the stable economic model predictive control and the traditional economic model predictive control strategy. In the simulation verification link, the stable economic model predictive control controller parameter setting is as follows: the auxiliary controller Sontag design in the traditional performance index weight coefficient is an 8-order unit matrix, ; the controller simulation step is 0.1s; in order to fully optimize the comprehensive performance index of the system, in Mode 1, the prediction step ; the control step ; the control switching time is selected as 15s, and the dynamic response process termination time is taken as . In order to more intuitively compare the simulation results, four performance indexes of root mean square error (RMSE), power tracking error, tracking accuracy and average calculation time are selected.

[0120] Further, in order to simulate the dynamic shadow caused by the time-varying disturbance of the irradiance due to wave reflection, two working conditions of normal sea wave and complex sea wave are set respectively, and the simulation results are shown in Tables 1-2.

[0121] Table 1, comparison of maximum power point tracking performance: normal sea wave

[0122]

[0123] Table 2, comparison of maximum power point tracking performance: complex sea wave

[0124]

[0125] The simulation results verify the superiority of the proposed algorithm under complex wave disturbance, which has stronger robustness and adaptability under dynamic shadow conditions, can quickly and effectively track the maximum power point, and reduce the volatility of output.

[0126] The basic principles of the present disclosure are described above in combination with specific embodiments, but it should be pointed out that the advantages, advantages, effects and the like mentioned in the present disclosure are only examples and not limitations, and these advantages, advantages, effects and the like cannot be considered as the must-have of each embodiment of the present disclosure. In addition, the above specific details of the disclosure are only for the purpose of example and understanding, and not for limitation, and the above details do not limit the present disclosure to the above specific details.

[0127] In this disclosure, relational terms such as first and second and the like can be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. The block diagram of the devices, apparatus, equipment, systems referred to in this disclosure is merely illustrative and not intended to imply the necessity or arrangement of the connections, arrangement, configuration as shown in the block diagram. As will be appreciated by those skilled in the art, the devices, apparatus, equipment, systems can be connected, arranged, configured in any manner. The words comprising, including, having and the like are to be open ended. As used in this document, the conjunction "or" is to be interpreted in the inclusive sense, i.e. as meaning one or the other, or both. As used in this document, the words "and" and "or" are to be interpreted as having the meaning indicated in the phrase "and / or". As used in this document, the word "such as" is to be interpreted as meaning "such as, but not limited to". As used in this document, the word "for example" is to be interpreted as meaning "by way of example, not by way of limitation".

[0128] Also, as used in this document, the word "or" in the cases used to introduce list items is to be interpreted in the exclusive sense, i.e. as meaning one or the other, but not both. In addition, the phrase "example of" does not mean an example of the preferred or only example, and the phrases "for example" and "such as" do not mean that a list of following items is an exhaustive list.

[0129] It is also important to note that the systems and methods of the present disclosure can be embodied in a variety of forms including, but not limited to, a data processor, a computer program product, a computer, one or more tangible computer readable storage devices, one or more computer memories, one or more programmable logic devices, one or more application specific devices, one or more processors, one or more microprocessors, one or more microcomputers, one or more microcontrollers, one or more microcontrollers, one or more state machines, one or more registers, one or more other devices, or any combination thereof.

[0130] Various changes, modifications and improvements in the herein described technologies can be made within the teachings of the technology, particularly in view of the foregoing descriptions, which are to be considered as examples only and not as limiting the scope of the technology. Accordingly, the disclosures of the present technology are intended to be illustrative, but not limiting, of the scope of the technology, which is set forth with particularity in the following claims. What is claimed is:

[0131] The previous description of the disclosed aspects is provided to enable any person skilled in the art to make or use the present disclosure. Various modifications to these aspects will be readily apparent to those skilled in the art, and the generic principles defined herein can be applied to other aspects without departing from the scope of the disclosure. Thus, the present disclosure is not intended to be limited to the aspects shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

[0132] The foregoing description has been presented for the purposes of illustration and description. Furthermore, the description is not intended to limit the embodiments of the disclosure to the forms disclosed herein. Although the various example aspects and embodiments have been described herein with regard to particular aspects and embodiments, those skilled in the art will recognize that certain modifications, changes, substitutions, additions and sub-combinations can be made without departing from the spirit of the disclosure.

Claims

1. A method for dynamically tracking the maximum power point of an offshore bifacial photovoltaic system, characterized in that: include: Real-time collection of dynamic parameters of the environment in which the offshore bifacial photovoltaic power generation system is located, including the pitch and tilt angle of the photovoltaic modules and the solar irradiance at the observation point; Based on the dynamic relationship between the solar irradiance at the observation point and the pitch tilt angle of the photovoltaic module, a time-varying nonlinear mathematical model of the output power of the offshore bifacial photovoltaic module with respect to the pitch tilt angle of the photovoltaic module is established. Based on the time-varying nonlinear mathematical model, the convex hull region where the global maximum power point is located is identified, and the upper and lower voltage boundaries corresponding to the convex hull region are determined; Design and control the Lyapunov function and construct the Sontag auxiliary controller for controlling the Lyapunov function; Establish the nonlinear state space equation of Boost converter; Based on the nonlinear state-space equation of the Boost converter, the upper and lower voltage boundaries corresponding to the convex hull region, the output power of the bifacial photovoltaic system, and the switching loss of the power converter, an economic performance indicator function is designed. Design an economic model predictive controller based on the control Lyapunov function, Sontag auxiliary controller and economic performance index function; Based on the economic model predictive controller, the state of the offshore bifacial photovoltaic system is controlled within the disturbance feasible region, thereby obtaining the optimal control quantity; Dynamic tracking of the maximum power point of an offshore bifacial photovoltaic system under wave disturbance is achieved based on the optimal control quantity.

2. The method for dynamic tracking of the maximum power point of an offshore bifacial photovoltaic system according to claim 1, wherein: The dynamic parameters also include wave parameters, which include wave height or wave frequency.

3. The method for dynamic tracking of the maximum power point of an offshore bifacial photovoltaic system according to claim 2, wherein: The method establishes a time-varying nonlinear mathematical model of the output power of offshore bifacial photovoltaic modules with respect to the pitch and tilt angle of the photovoltaic modules based on the dynamic relationship between the solar irradiance at the observation point and the pitch and tilt angle of the photovoltaic modules, including: Assuming that the scattered irradiance and reflected irradiance are isotropic, ignoring the direct irradiance received by the back of the bifacial photovoltaic module, and the atmospheric transparency is ideal, the effective irradiance received by the bifacial photovoltaic module is like: ， Among them, the front irradiance of the bifacial photovoltaic module is and back irradiance The calculation formula is as follows: Where, is a two-sided factor, is the total horizontal radiation at the observation point, is the horizontal direct irradiance, is the horizontal diffuse irradiance, , is the sea surface reflectivity, is the component tilt angle, is the incident angle of direct sunlight at any moment.

4. The method for dynamic tracking of the maximum power point of an offshore bifacial photovoltaic system according to claim 3, wherein: The step of establishing a nonlinear state space equation of a Boost converter includes: Define the state vector as the inductor current , photovoltaic terminal voltage and the voltage across the capacitor , the input vector is the switch state ; The dynamic mathematical model of the maximum power point tracking function of the offshore bifacial photovoltaic power generation system based on the Boost converter is as follows: Where: is the switching state of the Boost switch tube, are input and output filter capacitors respectively, is the inductor of the Boost converter, The current flowing through the inductor The current, It is a capacitor The voltage across the terminals, is the photovoltaic terminal voltage, is the photovoltaic terminal current, For time.

5. The method for dynamic tracking of the maximum power point of an offshore bifacial photovoltaic system according to claim 4, characterized in that: The design controls the Lyapunov function and constructs a Sontag auxiliary controller for controlling the Lyapunov function. The Sontag auxiliary controller is used to quickly drive the system state back to the feasible domain when the system state exceeds the disturbance feasible domain.

6. The method for dynamic tracking of the maximum power point of an offshore bifacial photovoltaic system according to claim 5, characterized in that: Based on the nonlinear state-space equations of the Boost converter, the upper and lower voltage boundaries corresponding to the convex hull region, the output power of the bifacial photovoltaic system, and the switching loss of the power converter, an economic performance indicator function is designed, including: The economic performance index of the offshore bifacial photovoltaic power generation system is expressed as: ， Where: represents the output power of the offshore bifacial photovoltaic power generation system, To calculate the output power, Indicates the switching loss value, Used to calculate switching losses, represents the output power of the offshore bifacial photovoltaic power generation system, represents the switching loss, .

7. The method for dynamic tracking of the maximum power point of an offshore bifacial photovoltaic system according to claim 6, wherein: Based on the nonlinear state-space equations of the Boost converter, the upper and lower voltage boundaries corresponding to the convex hull region, the output power of the bifacial photovoltaic system, and the switching loss of the power converter, an economic performance indicator function is designed, including: The economic objective function of the offshore bifacial photovoltaic power generation system is expressed as: ， is the linear weight coefficient.

8. The method for dynamic tracking of the maximum power point of an offshore bifacial photovoltaic system according to claim 7, wherein: Designing an economic model predictive controller based on the control Lyapunov function, the Sontag auxiliary controller and the economic performance index function, including: a first mode and a second mode; The first mode is to solve the objective function online when the system state is within the perturbation feasible region, embed the economic model predictive control optimization problem with the Lyapunov function stability constraint, and output the optimal control quantity in real time; The second mode is when the system state exceeds the disturbance feasible region but is within the ideal feasible region, it switches to the Sontag auxiliary controller, uses the Sontag auxiliary controller to drive the system state back to the disturbance feasible region, and then switches back to the first state.

9. The method for dynamic tracking of the maximum power point of an offshore bifacial photovoltaic system according to claim 8, wherein: The economic model predictive control optimization problem embedded with Lyapunov function stability constraints includes: The mixed integer nonlinear programming algorithm is used to perform online rolling solution to obtain the optimal switching state sequence at the current moment.

10. The method for dynamic tracking of the maximum power point of an offshore bifacial photovoltaic system according to claim 9, wherein: Prediction step size in the first mode ; Control step size ; Control switching time Select 15s, and the termination time of the dynamic response process is .

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