A photovoltaic power generation unit power generation stability monitoring control method and system

Abstract

The present application relates to photovoltaic power generation technical field, disclose a kind of photovoltaic power generation unit power generation stability monitoring control method and system, comprising: deployment voltage sensor in photovoltaic power generation unit key node, real-time acquisition voltage data;Establish dynamic voltage margin model, analyze voltage margin and calculate load margin index;Assess the stability of system under different load conditions;Voltage and frequency output by inverter are controlled using vector control algorithm.The present application is by deployment voltage sensor in photovoltaic power generation unit key node, real-time acquisition voltage data, establishes dynamic voltage margin model and calculates load margin index, can comprehensively analyze the voltage stability of system.By assessing the stability under different load conditions, ensure that system remains stability under complex operating conditions.Effectively improve the voltage control precision and dynamic response capability of photovoltaic power generation system.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of photovoltaic power generation, in particular to a photovoltaic power generation unit power generation stability monitoring control method and system. BACKGROUND

[0002] As a clean and renewable energy technology, photovoltaic power generation has been widely applied and rapidly developed in recent years. With the increasing emphasis on environmental protection and energy sustainability worldwide, the installed capacity of photovoltaic power generation systems has been growing year by year. However, the volatility and intermittency of photovoltaic power generation pose a series of technical challenges in grid-connected operation. Traditional photovoltaic power generation systems usually rely on fixed inverter control strategies and simple voltage monitoring methods to maintain power quality. However, these methods often struggle to ensure system stability in complex grid environments, especially when load changes and light conditions fluctuate dramatically. On the one hand, traditional voltage monitoring systems mainly rely on single-node data acquisition, which cannot fully reflect the voltage fluctuation of the entire photovoltaic power generation unit, thereby affecting the stability control of the overall system. On the other hand, the existing inverter control algorithms mostly use simple control methods with fixed frequency and voltage, which are difficult to dynamically adapt to rapidly changing loads and grid conditions, resulting in frequent voltage deviation, frequency instability, and other problems, affecting the stability and reliability of power supply.

[0003] Existing photovoltaic power generation technologies have attempted to improve system stability by increasing the number of voltage sensors, optimizing control algorithms, and other means, but still have many shortcomings. For example, although multi-point voltage monitoring technology can more comprehensively obtain voltage information, due to the lack of effective data processing and dynamic modeling methods, these data often cannot be fully utilized, and accurate regulation of system voltage cannot be achieved. In addition, the Load Margin Index (LMI) as an important evaluation standard for system stability has not been effectively applied in existing technologies, making it difficult for the system to respond quickly and adjust in the case of rapid load changes. Existing inverter control algorithms lack real-time adjustment capability when facing complex grid environments, and cannot fully consider the dynamic changes of load characteristics and voltage margin, thereby affecting the overall stability of the photovoltaic power generation unit. SUMMARY

[0004] In view of the above problems, the present application is proposed.

[0005] Therefore, the technical problem solved by the present application is: how to ensure the stability of power output while improving the response speed and adaptability of the existing photovoltaic power generation system.

[0006] To solve the above technical problems, the present application provides the following technical solution: a photovoltaic power generation unit power generation stability monitoring control method, comprising:

[0007] The voltage sensor is arranged at a key node of the photovoltaic power generation unit to collect voltage data in real time.

[0008] A dynamic voltage margin model is established to analyze the voltage margin and calculate the load margin index.

[0009] The stability of the system under different load conditions is evaluated.

[0010] The vector control algorithm is used to control the voltage and frequency of the inverter output.

[0011] As a preferred scheme of the photovoltaic power generation unit power generation stability monitoring control method, the voltage data collection includes selecting the measurement range of the sensor according to the voltage level of the photovoltaic power generation unit, determining the key installation node, installing the voltage sensor at the output end of the photovoltaic array, the input end of the inverter, the output end of the inverter, and the grid connection point, starting the system to perform real-time voltage monitoring, ensuring stable operation of the system, and being able to timely capture voltage change conditions.

[0012] The photovoltaic power generation unit includes a photovoltaic array, a DC-AC inverter, and an electric energy metering device.

[0013] As a preferred scheme of the photovoltaic power generation unit power generation stability monitoring control method, the dynamic voltage margin model establishment includes establishing a dynamic voltage margin model, capturing the dynamic voltage change of the system at different time points, and using a state space model to describe the dynamic behavior of the system.

[0014] The voltage margin ΔV(t) represents the difference between the current system voltage and the allowed minimum voltage, and the formula is as follows:

[0015] ΔV(t) = V(t) - V min

[0016] Wherein, V(t) represents the system voltage at the current time t; V min represents the minimum voltage allowed by the system.

[0017] The dynamic voltage equation is established to describe the dynamic change of the system voltage, and the formula is as follows:

[0018]

[0019] Wherein, represents the change rate of the voltage margin; P load (t) represents the current load power; P pv (t represents the photovoltaic power generation power; Q(t) represents the reactive power; f(·) represents a multivariate function.

[0020] According to the current voltage margin and the dynamic model, the voltage margin at future time t+Δt is predicted, which is expressed as:

[0021]

[0022] Where τ represents an intermediate variable for integration, and the integral represents the cumulative change of voltage margin from t to t+Δt.

[0023] As a preferred scheme of the photovoltaic power generation unit power generation stability monitoring control method, the calculation of the load margin index includes predicting future load power, calculating the maximum load power that the system can withstand under the predicted voltage margin, which is expressed as:

[0024] P max (t+Δt)=h(ΔV(t+Δt))

[0025] Where h(·) represents a function fitted from the voltage-power curve by experiment, and the maximum load power under a given voltage margin;

[0026] Based on historical data and load model, the load power P load (t+Δt) at future time is predicted, which is expressed as:

[0027] P load (t+Δt)=P load (t)+ΔP load

[0028] Where ΔP load represents the predicted increment of load power, which can be predicted by time series analysis or machine learning model;

[0029] The load margin index LMI(t+Δt) is calculated, which represents the additional load proportion that the system can withstand before the voltage drops to the minimum allowed value, which is expressed as:

[0030]

[0031] Where P max (t+Δt) represents the maximum load power that the system can withstand at future time t+Δt; P load (t+Δt) represents the predicted load power of the system at future time.

[0032] As a preferred scheme of the photovoltaic power generation unit power generation stability monitoring control method, the stability under different load conditions includes quantifying the stability state of the system, defining a comprehensive stability evaluation index S(t), and evaluating it in combination with the voltage margin and the load margin index, which is expressed as:

[0033]

[0034] where, a and b are weight coefficients, reflecting the relative importance of voltage margin and load margin to system stability; AV(t) / V min is the normalized voltage margin, reflecting the relative gap between the current voltage and the minimum allowed voltage; LMI(t) is the load margin index, reflecting the additional load capacity that the system can withstand under the current voltage condition;

[0035] Stability judgment and response, real-time calculation of S(t) value, and comparison with the set stability threshold S th ; if S(t) is greater than or equal to the threshold S th , the system is stable and does not need to be adjusted; if S(t) is less than the threshold S th , the system is unstable, at which time the load reduction, reactive power compensation, adjustment of inverter output response measures are triggered to restore system stability.

[0036] As a preferred scheme of the photovoltaic power generation unit power generation stability monitoring control method, the vector control algorithm includes: when the d-q coordinate transformation is performed, the three-phase voltage and current are converted from the a-b static coordinate system to the d-q coordinate system, and the active power and the reactive power are independently controlled respectively; wherein the d-axis current i d controls the active power, and the q-axis current i q controls the reactive power; the voltage regulation is adjusted by controlling the d-axis voltage V d of the inverter to adjust the output voltage, so that the system voltage is kept within the stable range;

[0037] The output frequency is adjusted by controlling the q-axis voltage V q , so that it is synchronized with the grid frequency.

[0038] As a preferred scheme of the photovoltaic power generation unit power generation stability monitoring control method, the control of the voltage and frequency of the inverter output includes current control; according to the real-time voltage and load demand, the d-axis and q-axis current reference values and The calculation formula is represented as:

[0039]

[0040] Where, P ref and Q ref are the reference values of active power and reactive power respectively; represents the reference value of the d-axis current; represents the reference value of the q-axis current; V inv (t) represents the output voltage of the inverter at time t;

[0041] The PI controller is used to regulate the d-axis and q-axis voltage output:

[0042]

[0043] where V d d represents the d-axis voltage, used to control the active power output of the inverter; V q q represents the q-axis voltage, used to control the reactive power output of the inverter; K pd , K id represent the proportional gain and integral gain of the d-axis PI controller; K pq , K iq represent the proportional gain and integral gain of the q-axis PI controller; i d represents the actual d-axis current; i q represents the actual q-axis current; represents the reference value of the d-axis and q-axis current;

[0044] Adjust the output voltage V inv (t) and frequency f inv (t) of the inverter to synchronize and stabilize with the grid, the calculation formula is:

[0045] V inv (t) = V ref + ΔV d

[0046] f inv (t) = f grid + Δf

[0047] where f inv (t) represents the output frequency of the inverter at time t; V ref represents the voltage reference value, used to set the target voltage of the inverter output; ΔV d represents the voltage increment adjusted by the d-axis voltage controller, used to adjust the output voltage; f grid represents the reference frequency of the grid; Δf represents the frequency increment adjusted by the q-axis voltage controller;

[0048] Continuously monitor the adjusted voltage V inv (t) and frequency f inv (t), and real-time evaluate the stability index S(t) of the collapse; when the system voltage and frequency recover to stable, the stability index S(t) reaches and exceeds the threshold S th , gradually restore the inverter to normal working mode.

[0049] A photovoltaic power generation unit power generation stability monitoring control system using the method as claimed in any one of the present invention, comprising:

[0050] The data acquisition module comprises a voltage sensor, a data acquisition unit and a communication unit, and is configured to monitor key voltage points of the photovoltaic power generation unit in real time, and collect and transmit voltage data.

[0051] The dynamic voltage margin modeling and analysis module is configured to establish a dynamic voltage margin model based on the collected voltage data, analyze the voltage margin, and calculate a load margin index.

[0052] The system stability evaluation module is configured to evaluate the voltage stability of the system according to the system state under different load conditions.

[0053] The inverter control and regulation module is configured to control the output voltage and frequency of the inverter based on the system stability evaluation result by using a vector control algorithm.

[0054] A computer device comprises a memory and a processor, and the memory stores a computer program, and the processor executes the computer program to implement the steps of the method of any one of the embodiments.

[0055] A computer readable storage medium stores a computer program, and the computer program is executed by a processor to implement the steps of the method of any one of the embodiments.

[0056] The present application has the following advantages: by deploying voltage sensors at key nodes of the photovoltaic power generation unit, collecting voltage data in real time, establishing a dynamic voltage margin model and calculating a load margin index, the voltage stability of the system can be comprehensively analyzed. On this basis, by evaluating the stability under different load conditions and using a vector control algorithm to accurately control the voltage and frequency output of the inverter, the stability of the system under complex operating conditions can be ensured. This method effectively improves the voltage control accuracy and dynamic response capability of the photovoltaic power generation system, and improves the reliability and power quality of power supply. BRIEF DESCRIPTION OF DRAWINGS

[0057] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor. Among them:

[0058] Figure 1 A photovoltaic power generation unit power generation stability monitoring and control method according to the first embodiment of the present application is provided. DETAILED DESCRIPTION

[0059] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the specific embodiments of the present application will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor should belong to the protection scope of the present application.

[0060] Embodiment 1, refer to Figure 1 For an embodiment of the present application, a photovoltaic power generation unit power generation stability monitoring control method is provided, comprising:

[0061] S1: deploying a voltage sensor at a key node of the photovoltaic power generation unit to collect voltage data in real time.

[0062] Further, collecting voltage data includes selecting the measurement range of the sensor according to the voltage level of the photovoltaic power generation unit, determining the key installation node, at the output end of the photovoltaic array: this node is the initial point of power generation of the photovoltaic power generation unit, measuring the voltage here can obtain the voltage information of the photovoltaic array output. The input end of the inverter: the input end of the inverter is the node before the photovoltaic array output accesses the inverter, measuring the voltage here helps to monitor the voltage condition of the photovoltaic power generation unit input to the inverter. The output end of the inverter: the inverter converts the direct current into alternating current and outputs to the power grid or load, measuring the voltage here can ensure the voltage quality of the inverter output. The grid connection point: this node is the connection point of the photovoltaic power generation unit and the power grid, measuring the voltage here can monitor the voltage condition of the photovoltaic power generation unit after being connected to the grid.

[0063] Further, the photovoltaic power generation unit includes a photovoltaic array, a direct current-alternating current (DC-AC) inverter and an electric energy metering device. The system is started to monitor the voltage in real time, to ensure stable operation of the system, and to timely capture the voltage change condition, to support the subsequent power generation stability monitoring and control strategy execution.

[0064] Further, the data acquisition module includes a voltage sensor, a data acquisition unit and a communication unit, which monitors the key voltage points of the photovoltaic power generation unit in real time, collects and transmits voltage data.

[0065] Further, the voltage sensor is deployed at the key node of the photovoltaic power generation system to collect voltage data in real time.

[0066] Further, the data acquisition unit collects data from each voltage sensor and performs preliminary filtering and noise suppression processing.

[0067] Further, the communication unit transmits the collected voltage data to the central controller through wired or wireless communication.

[0068] It should be noted that through the way of multi-point voltage monitoring, the voltage state of the photovoltaic power generation system throughout the life cycle can be dynamically tracked. Compared with the traditional single-point monitoring method, this multi-point real-time monitoring provides more comprehensive voltage state data. These data not only can reflect the running condition of the system in real time, but also provide accurate data support for subsequent voltage margin analysis and load margin index calculation, thereby laying a foundation for power generation stability control.

[0069] S2: Establish a dynamic voltage margin model, analyze the voltage margin and calculate the load margin index.

[0070] Further, the establishment of the dynamic voltage margin model includes establishing a dynamic voltage margin model, capturing the dynamic changes of the system at different time points, and using a state space model to describe the dynamic behavior of the system; the voltage margin ΔV(t) represents the difference between the current system voltage and the allowed minimum voltage, reflecting the voltage stability of the system, and the formula is expressed as:

[0071] ΔV(t) = V(t) - V min

[0072] Wherein, V(t) represents the system voltage at the current time t; V min represents the minimum voltage allowed by the system.

[0073] Further, the dynamic voltage equation: the dynamic change of the system voltage can be described by the following differential equation:

[0074]

[0075] Wherein, represents the change rate of the voltage margin; P load (t) represents the current load power; P pv (t) represents the photovoltaic power generation power; Q(t) represents the reactive power; f(·) represents a multivariate function, which describes how the voltage margin changes with time, load, power generation power, etc.

[0076] Further, the future voltage margin (ΔV(t+Δt)) is predicted, the voltage margin at the future time t+Δt is predicted according to the current voltage margin and the dynamic model, and the formula is expressed as:

[0077]

[0078] Wherein, τ represents an intermediate variable of integration; the integral represents the cumulative change of the voltage margin in the period from t to t+Δt.

[0079] Further, the load limit power (P maxP(t+Δt) is the maximum load power the system can withstand under the predicted voltage margin max P(t+Δt) is the maximum load power the system can withstand under the predicted voltage margin

[0080] P(t+Δt) is the maximum load power the system can withstand under the predicted voltage margin max P(t+Δt) is the maximum load power the system can withstand under the predicted voltage margin

[0081] P(t+Δt) is the maximum load power the system can withstand under the predicted voltage margin

[0082] Further, the calculation of the load margin index includes predicting future load power.

[0083] Further, based on historical data and load model, the load power P(t+Δt) at future time is predicted. load

[0084] P(t+Δt) is the maximum load power the system can withstand under the predicted voltage margin load P(t+Δt) is the maximum load power the system can withstand under the predicted voltage margin load P(t+Δt) is the maximum load power the system can withstand under the predicted voltage margin load

[0085] P(t+Δt) is the maximum load power the system can withstand under the predicted voltage margin load P(t+Δt) is the maximum load power the system can withstand under the predicted voltage margin

[0086] Further, the load margin index (LMI) is calculated, and the load margin index (LMI(t+Δt)) is dynamically calculated.

[0087] Further, the load margin index LMI(t+Δt) represents the additional load ratio the system can withstand before the voltage drops to the minimum allowed value, and the formula is:

[0088]

[0089] P(t+Δt) is the maximum load power the system can withstand under the predicted voltage margin max P(t+Δt) is the maximum load power the system can withstand under the predicted voltage margin load P(t+Δt) is the maximum load power the system can withstand under the predicted voltage margin

[0090] It should be noted that traditional technology usually relies on static voltage monitoring and cannot dynamically respond to complex changes within the system. The present application captures the instantaneous state of the system through a dynamic model, accurately describes the dynamic behavior of the voltage using state space method, and comprehensively evaluates the carrying capacity of the system by combining the load margin index. This method not only improves the accuracy of voltage monitoring, but also significantly improves the system's resilience, enabling the photovoltaic power generation system to remain stable under different operating conditions.

[0091] ​S3: evaluate the stability of the system under different load conditions.

[0092] Further, the stability under different load conditions includes quantifying the stability state of the system, defining a comprehensive stability evaluation index S(t), combining voltage margin and load margin index for evaluation, and the formula is expressed as:

[0093]

[0094] Where, a and β are weight coefficients, reflecting the relative importance of voltage margin and load margin to system stability; AV(t) / V min is the normalized voltage margin, reflecting the relative gap between the current voltage and the minimum allowed voltage; LMI(t) is the load margin index, reflecting the additional load capacity that the system can withstand under the current voltage condition.

[0095] Further, stability judgment and response, real-time calculation of S(t) value, and comparison with the set stability threshold S th ; if S(t) is greater than or equal to the threshold S th , the system is stable and does not need to be adjusted; if S(t) is less than the threshold S th , the system is unstable, at which time the load reduction, reactive power compensation, adjustment of inverter output response measures are triggered to restore system stability.

[0096] It should be noted that by real-time calculation of stability evaluation index and comparison with the set stability threshold, early warning can be given before voltage or load appears abnormal, triggering the corresponding control measures. This predictive adjustment can significantly improve the response speed and control accuracy of the system, and reduce the risk of shutdown or damage caused by instability.

[0097] S4: use vector control algorithm to control the voltage and frequency of inverter output.

[0098] Further, the vector control algorithm includes converting three-phase voltage and current from α-β static coordinate system to d-q coordinate system through d-q coordinate transformation, and independently controlling active power and reactive power respectively; where d-axis current i d controls active power, q-axis current i q controls reactive power; voltage regulation adjusts output voltage by controlling the d-axis voltage V d of the inverter, keeping the system voltage within the stable range.

[0099] Further, by controlling the q-axis voltage V q to adjust the output frequency, it is synchronized with the grid frequency.

[0100] Further, the control of the voltage and frequency of the inverter output includes current control; calculating the d-axis and q-axis current reference values according to the real-time voltage and load demand and The calculation formula is:

[0101]

[0102] Wherein, P ref and Q ref are the reference values of active power and reactive power respectively; represents the reference value of the d-axis current; represents the reference value of the q-axis current; V inv (t) represents the output voltage of the inverter at time t.

[0103] Further, PI controllers are used to adjust the d-axis and q-axis voltage output:

[0104]

[0105] Wherein, V d represents the d-axis voltage for controlling the active power output of the inverter; V q represents the q-axis voltage for controlling the reactive power output of the inverter; K pd , K id represent the proportional gain and integral gain of the d-axis PI controller; K pq , K iq represent the proportional gain and integral gain of the q-axis PI controller; i d represents the actual d-axis current; i q represents the actual q-axis current; represents the reference value of the d-axis and q-axis current.

[0106] Further, the output voltage V inv (t) and frequency f inv (t) of the inverter are adjusted to be synchronized with and stable to the power grid, and the calculation formula is:

[0107] V inv (t) = V ref + ΔV d

[0108] f inv (t) = f grid + Δf

[0109] Wherein, f inv (t) represents the output frequency of the inverter at time t; V ref represents the voltage reference value for setting the target voltage of the inverter output; ΔV drepresents the voltage increment adjusted by the d-axis voltage controller, used to regulate the output voltage; f grid represents the reference frequency of the grid; Δf represents the frequency increment adjusted by the q-axis voltage controller.

[0110] Further, the adjusted voltage V inv and frequency f inv (t) are continuously monitored, and the stability index S(t) is evaluated in real time; when the system voltage and frequency recover stability, the stability index S(t) reaches and exceeds the threshold value S th , the inverter gradually recovers to the normal working mode.

[0111] It should be noted that the basis of the vector control algorithm lies in the d-q coordinate transformation. This transformation converts three-phase voltage and current from the stationary abc coordinate system to the rotating d-q coordinate system. The key advantage of this transformation is that it decomposes the originally complex three-phase AC signal into two DC components, the d-axis component and the q-axis component. These two components can be controlled independently to control active power and reactive power, respectively, thereby achieving more precise power regulation. The d-axis current controls active power: in the d-q coordinate system, the d-axis current i d is mainly responsible for the control of active power. By adjusting the d-axis voltage V d , the active power output by the inverter can be directly affected, so that the system can stably provide power to the load or grid. The q-axis current controls reactive power: the q-axis current i q is responsible for the control of reactive power. By adjusting the q-axis voltage V q , the output of reactive power can be adjusted, so that the output frequency of the inverter can be controlled to synchronize with the grid frequency.

[0112] On the other hand, the embodiment also provides a photovoltaic power generation unit power generation stability monitoring and control system, which comprises:

[0113] A data acquisition module, including a voltage sensor, a data acquisition unit, and a communication unit, which monitors the key voltage points of the photovoltaic power generation unit in real time, acquires and transmits voltage data.

[0114] A dynamic voltage margin modeling and analysis module, which establishes a dynamic voltage margin model based on the collected voltage data, analyzes the voltage margin, and calculates the load margin index.

[0115] A system stability evaluation module, which evaluates the voltage stability of the system according to the system state under different load conditions.

[0116] An inverter control and regulation module, which controls the output voltage and frequency of the inverter based on the system stability evaluation results using the vector control algorithm.

[0117] If the above functions are realized in the form of software function units and sold or used as independent products, they can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present application essentially or parts of the present application that make contributions to the prior art or parts of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk or an optical disk, and various media that can store program codes.

[0118] The logic and / or steps represented in the flowcharts or otherwise described herein, for example, can be considered as a list of executable instructions for implementing logic functions, which can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus or device, such as a computer-based system, a system including a processor or other system that can fetch instructions from an instruction execution system, apparatus or device and execute the instructions, or in conjunction with these instruction execution systems, apparatus or devices. For the purpose of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transport programs for use by or in connection with an instruction execution system, apparatus or device, or in conjunction with these instruction execution systems, apparatus or devices.

[0119] More specific examples (non-exhaustive list) of the computer-readable medium include the following: an electrical connection having one or more wires (electrical devices), a portable computer diskette (magnetic devices), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). In addition, the computer readable medium can even be paper or other suitable medium on which the program can be printed, because the program can be obtained electronically, for example, by optical scanning of the paper or other medium, followed by editing, interpreting or otherwise processing, if necessary, in other suitable ways to obtain the program electronically, and then storing it in a computer memory.

[0120] It should be understood that various aspects of the application can be implemented in hardware, software, firmware or a combination of them. In the above embodiments, various steps or methods can be implemented in software or firmware that is stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, implementation can be with any or a combination of the following technologies, which are all well-known in the art: a discrete logic circuit(s) having logic gates for implementing logic functions upon an application of data signals, an application specific integrated circuit having appropriate combinational logic gates, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0121] The following is an embodiment of the present application, which provides a photovoltaic power generation unit power generation stability monitoring control method. In order to verify the beneficial effects of the present application, economic benefit calculation and simulation experiments are used for scientific demonstration.

[0122] In order to verify the actual effect of the invention, this embodiment carries out experimental verification in a standard photovoltaic power generation system. The photovoltaic power generation system includes a photovoltaic array, a direct current-alternating current (DC-AC) inverter, an electric energy metering device and a grid-connected interface. The total installed capacity of the system is 500kW, and the rated output power of the inverter is 450kW. The main purpose of the experiment is to verify the effect of real-time voltage data acquisition through the deployment of voltage sensors, the evaluation of system stability by using dynamic voltage margin model and load margin index, and the optimization of output voltage and frequency of the inverter through vector control algorithm.

[0123] Firstly, four voltage sensors are deployed at the key nodes of the photovoltaic power generation unit, which are located at the output end of the photovoltaic array, the input end of the inverter, the output end of the inverter and the grid connection point. These sensors can collect real-time voltage data of each node. The measurement range of the sensor is selected according to the voltage level of the system, which ensures that all key voltage points from the direct current end to the alternating current end can be covered. The data acquisition module includes high-precision voltage sensors, data acquisition units and communication units. The collected data is transmitted to the central controller in real time through the communication unit to support subsequent analysis and control.

[0124] On the basis of data acquisition, a dynamic voltage margin model of the system is established. This model can analyze the voltage margin of the system based on real-time voltage data, that is, the difference between the current system voltage and the allowed minimum voltage. Using this model, the load margin index (LMI) is further calculated to evaluate the stability of the system under different load conditions. In order to make the experiment representative, the system performance under different time periods (including morning, noon and evening with large changes in light intensity) and different load levels (light load, medium load and heavy load) is tested.

[0125] Finally, the voltage and frequency of the inverter output are controlled by the vector control algorithm. In the d-q coordinate system, the d-axis current is controlled to regulate the active power, and the q-axis current is controlled to regulate the reactive power. During the regulation process, the voltage and frequency are adjusted in real time by using the PI controller to ensure that the system can be synchronized with the grid frequency under different load conditions and maintain a stable output voltage.

[0126] Table 1 Partial test data table

[0127]

[0128]

[0129] By analyzing the data in Table 1, the significant effect of the technical solution adopted by the present application under different load conditions and light intensities can be obtained. First, in the voltage monitoring results of the photovoltaic system at different time periods, the real-time voltage is maintained within a relatively stable range, and the voltage margin varies according to the load. Under light load, the voltage margin is higher, reaching a maximum of 12.0%, indicating that the system has strong anti-voltage fluctuation ability under low load; while under heavy load, the voltage margin decreases, but through real-time monitoring and adjustment, it is still maintained above 7.0%, ensuring the safe and stable operation of the system.

[0130] The change of the load margin index (LMI) further illustrates the superiority of the present application. The LMI fluctuates within a small range under different load conditions, mostly remaining above 0.85, indicating that the system can adjust the output power of the inverter in real time according to the real-time voltage and load conditions, thereby effectively avoiding system instability caused by load changes. In addition, through the adjustment of the inverter output frequency by the vector control algorithm, the system frequency is always maintained between 49.9Hz and 50.3Hz

[0131] It should be noted that the above examples are only used to illustrate the technical solutions of the present application and not to limit it. Although the present application has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present application can be modified or replaced equivalently without departing from the spirit and scope of the present application, and all should be covered in the scope of the claims of the present application.

Claims

1. A method for monitoring and controlling the power generation stability of a photovoltaic power generation unit, characterized in that, include: Voltage sensors are deployed at key nodes of the photovoltaic power generation unit to collect voltage data in real time; Establish a dynamic voltage margin model, analyze the voltage margin, and calculate the load margin index; Evaluate the stability of the system under different load conditions; Vector control algorithms are used to control the voltage and frequency of the inverter output. The establishment of the dynamic voltage margin model includes: establishing a dynamic voltage margin model, capturing the dynamic changes in voltage of the system at different time points, and using a state-space model to describe the dynamic behavior of the system. The voltage margin ΔV(t) represents the difference between the current system voltage and the minimum allowable voltage, expressed by the formula: ΔV(t)=V(t)-V min ; Where V(t) represents the system voltage at the current time t; V min Indicates the minimum voltage allowed by the system; A dynamic voltage equation is established to describe the dynamic changes in the system voltage. The formula is as follows: in, P represents the rate of change of voltage margin. load (t) represents the current load power; P pv (t) represents photovoltaic power generation; Q(t) represents reactive power; f() represents a multivariable function; Based on the current voltage margin and the voltage margin predicted by the dynamic model for the future time t+Δt, the formula is expressed as: Where τ represents the intermediate variable of the integral, and the integral represents the cumulative change in voltage margin over the time interval from t to t+Δt. The calculation of load margin indicators includes predicting future load power and calculating the load limit power. Given the predicted voltage margin, the maximum load power that the system can withstand is expressed by the formula: p max (t+Δt)=h(Δv(t+Δt)); Where h() represents the function obtained by experimental fitting from the voltage-power curve, representing the maximum power that can be withstood under a given voltage margin; Based on historical data and load models, predict the load power p at future times. load The formula (t+Δt) is expressed as: p load (t+Δt)=p load (t)+Δp load ; Where, Δp load The predicted increment of load power can be predicted through time series analysis or machine learning models; The load margin index, LMI(t+Δt), represents the percentage of additional load the system can withstand before the voltage drops to the minimum allowable value. The formula is as follows: Among them, P max (t+Δt) represents the maximum power that the system can withstand at a future time t+Δt; P load (t+Δt) represents the predicted load power of the system at future times; The stability under different load conditions includes quantifying the stability state of the system, defining a comprehensive stability evaluation index S(t), and evaluating it by combining voltage margin and load margin indices, expressed by the following formula: Wherein, α and β are weighting coefficients, reflecting the relative importance of voltage margin and load margin to system stability; It is the normalized voltage margin, reflecting the relative difference between the current voltage and the minimum allowable voltage; LMI(t) is the load margin index, reflecting the additional load capacity that the system can withstand under the current voltage conditions. Stability assessment and response: The S(t) value is calculated in real time and compared with the set stability threshold Sth. If S(t) is greater than or equal to the threshold Sth, the system is stable and no adjustment is needed. If S(t) is less than the threshold Sth, the system is unstable. At this time, load reduction, reactive power compensation, and inverter output response adjustment measures are triggered to restore system stability. The vector control algorithm includes performing Clarke transformation to convert the three-phase voltage and current from the α-β stationary coordinate system to the dq coordinate system, and independently controlling the active power and reactive power respectively; wherein the d-axis current id controls the active power and the q-axis current iq controls the reactive power; voltage regulation is achieved by controlling the d-axis voltage vd of the inverter to adjust the output voltage and keep the system voltage within a stable range. The output frequency is adjusted by controlling the q-axis voltage vq to synchronize it with the mains frequency.

2. The photovoltaic power generation unit power generation stability monitoring and control method as described in claim 1, characterized in that: The voltage data acquisition includes selecting the sensor's measurement range based on the voltage level of the photovoltaic power generation unit, determining key installation nodes, installing voltage sensors at the photovoltaic array output, inverter input, inverter output, and grid connection points, starting the system for real-time voltage monitoring, ensuring stable system operation, and timely detection of voltage changes. The photovoltaic power generation unit includes a photovoltaic array, a DC-AC inverter, and an energy metering device.

3. The photovoltaic power generation unit power generation stability monitoring and control method as described in claim 2, characterized in that: The control of the inverter output voltage and frequency includes current control; calculating d-axis and q-axis current reference values ​​based on real-time voltage and load requirements. and The calculation formula is expressed as follows: Where pref and Qref are reference values ​​for active power and reactive power, respectively; Indicates the reference value for the d-axis current; The reference value for the q-axis current is represented; vinv(t) represents the output voltage of the inverter at time t. Using a PI controller to adjust the voltage output of the d-axis and q-axis: Where, vd represents the d-axis voltage, used to control the active power output of the inverter; vq represents the q-axis voltage, used to control the reactive power output of the inverter; kpd and kid represent the proportional gain and integral gain of the d-axis PI controller; kpq and kid represent the proportional gain and integral gain of the q-axis PI controller; id represents the actual d-axis current; and iq represents the actual q-axis current. Indicates the reference values ​​for the d-axis and q-axis currents; Adjust the inverter's output voltage vinov(t) and frequency finv(t) to synchronize with the grid and maintain stability. The calculation formula is as follows: v inv (t)=v ref +Δv d ; f inv (t)=f grid +Δf; Where finv(t) represents the inverter's output frequency at time t; vref represents the voltage reference value, used to set the target output voltage of the inverter; Δvd represents the voltage increment adjusted by the d-axis voltage controller, used to adjust the output voltage; fgrid represents the grid's reference frequency; and Δf represents the frequency increment adjusted by the q-axis voltage controller. Continuously monitor the adjusted voltage vinov(t) and frequency finv(t), and evaluate the stability index s(t) of the disconnection in real time; when the system voltage and frequency return to stability and the stability index s(t) reaches or exceeds the threshold sth, gradually restore the inverter to normal operating mode.

4. A photovoltaic power generation unit power generation stability monitoring and control system employing the method described in any one of claims 1-3, characterized in that: The data acquisition module includes a voltage sensor, a data acquisition unit, and a communication unit, which monitors key voltage points of the photovoltaic power generation unit in real time and collects and transmits voltage data. The dynamic voltage margin modeling and analysis module establishes a dynamic voltage margin model based on the collected voltage data, analyzes the voltage margin, and calculates the load margin index. The system stability assessment module evaluates the voltage stability of the system based on the system state under different load conditions. The inverter control and regulation module controls the inverter's output voltage and frequency using a vector control algorithm based on the system stability assessment results.

5. A computer device, comprising: A memory and a processor; the memory stores a computer program, characterized in that: when the processor executes the computer program, it implements the steps of the photovoltaic power generation unit power generation stability monitoring and control method as described in claims 1-3.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, it implements the steps of the photovoltaic power generation unit power generation stability monitoring and control method as described in claims 1-3.

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