Method and system for monitoring and controlling power generation stability of photovoltaic power generation unit

Abstract

The invention relates to the technical field of photovoltaic power generation, and discloses a photovoltaic power generation unit power generation stability monitoring control method and system, and the method comprises the steps: deploying a voltage sensor at a key node of a photovoltaic power generation unit, and collecting voltage data in real time; establishing a dynamic voltage margin model, analyzing a voltage margin and calculating a load margin index; evaluating the stability of the system under different load conditions; and controlling the voltage and frequency output by the inverter by using a vector control algorithm. According to the method, the voltage sensors are deployed at the key nodes of the photovoltaic power generation units, the voltage data are collected in real time, the dynamic voltage margin model is established, the load margin index is calculated, and the voltage stability of the system can be comprehensively analyzed. And by evaluating the stability under different load conditions, the stability of the system is ensured to be kept under complex operation conditions. And the voltage control precision and the dynamic response capability of the photovoltaic power generation system are effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of photovoltaic power generation, and in particular to a method and system for monitoring and controlling power generation stability of a photovoltaic power generation unit. Background Art

[0002] Photovoltaic power generation, as a clean and renewable energy technology, has been widely used and developed rapidly in recent years. With the global attention to environmental protection and sustainable energy development, the installed capacity of photovoltaic power generation systems has increased year by year. However, the volatility and intermittent characteristics of photovoltaic power generation make it face 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 are often difficult to ensure the stability of the system when dealing with complex power grid environments, especially when load changes and light conditions fluctuate violently. On the one hand, the traditional voltage monitoring system mainly relies on data collection from a single node, 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 inverter control algorithm in the prior art mostly adopts a simple control method of fixed frequency and fixed voltage, which is difficult to dynamically adapt to rapidly changing loads and grid conditions, resulting in frequent problems such as voltage deviation and frequency instability, 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 and optimizing control algorithms, but there are still many shortcomings. For example, although multi-point voltage monitoring technology can obtain voltage information more comprehensively, due to the lack of effective data processing and dynamic modeling methods, these data are often not fully utilized, and it is impossible to achieve accurate regulation of system voltage. In addition, the load margin index (LMI), as an important evaluation criterion for system stability, has not been effectively applied in existing technologies, resulting in the system being difficult to respond and adjust quickly when the load changes rapidly. Existing inverter control algorithms lack real-time adjustment capabilities when facing complex power grid environments, and cannot fully consider the dynamic changes of load characteristics and voltage margins, thereby affecting the overall stability of photovoltaic power generation units. Summary of the invention

[0004] In view of the above-mentioned problems, the present invention is proposed.

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

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions: a photovoltaic power generation unit power generation stability monitoring and control method, comprising:

[0007] Deploy voltage sensors at key nodes of photovoltaic power generation units to collect voltage data in real time;

[0008] Establish a dynamic voltage margin model, analyze voltage margin and calculate load margin indicators;

[0009] Evaluate the stability of the system under different load conditions;

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

[0011] As a preferred solution of the photovoltaic power generation unit power generation stability monitoring and control method described in the present invention, wherein: 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 nodes, installing voltage sensors at the photovoltaic array output end, the inverter input end, the inverter output end, and the grid connection point, starting the system to perform real-time voltage monitoring to ensure stable operation of the system and timely capture voltage changes;

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

[0013] As a preferred solution of the photovoltaic power generation unit power generation stability monitoring and control method described in the present invention, wherein: the establishment of a dynamic voltage margin model includes establishing a dynamic voltage margin model to capture the dynamic changes of the system voltage 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 minimum allowed voltage, and the formula is:

[0015] ΔV(t)=V(t)-V min

[0016] Where V(t) represents the system voltage at the current time t; V min Indicates the lowest voltage allowed by the system;

[0017] A dynamic voltage equation is established to describe the dynamic changes of system voltage. The formula is expressed as:

[0018]

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

[0020] The voltage margin at the future time t+Δt is predicted based on the current voltage margin and the dynamic model. The formula is expressed as:

[0021]

[0022] Among them, τ represents the intermediate variable of the integration, and the integral represents the cumulative change of the voltage margin in the time period from t to t+Δt.

[0023] As a preferred solution of the photovoltaic power generation unit power generation stability monitoring and control method described in the present invention, the calculation of the load margin index includes predicting the future load power and calculating the load limit power. Under the predicted voltage margin, the maximum load power that the system can withstand is expressed as follows:

[0024] P max (t+Δt)=h(ΔV(t+Δt))

[0025] Where h(·) represents the maximum tolerable power under a given voltage margin, which is a function obtained by experimental fitting from the voltage-power curve;

[0026] Based on historical data and load models, predict the load power P at future times load The (t+Δt) formula 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 models;

[0029] Calculate the load margin index. The load margin index LMI (t+Δt) indicates the proportion of additional load that the system can withstand before the voltage drops to the minimum allowable value. The formula is:

[0030]

[0031] Among them, P max (t+Δt) represents the maximum tolerable power of the system at the future time t+Δt; P load (t+Δt) represents the predicted load power of the system at the future moment.

[0032] As a preferred solution of the photovoltaic power generation unit power generation stability monitoring and control method described in the present invention, the stability under different load conditions includes quantifying the stability state of the system, defining a comprehensive stability evaluation index S(t), and combining the voltage margin and load margin indicators for evaluation, and the formula is expressed as:

[0033]

[0034] Among them, α and β are weight coefficients, reflecting the relative importance of voltage margin and load margin to system stability; ΔV(t) / V min It is the normalized voltage margin, which reflects the relative gap between the current voltage and the minimum allowable voltage; LMI(t) is the load margin index, which reflects the additional load capacity that the system can withstand under the current voltage conditions;

[0035] Stability judgment and response, real-time calculation of S(t) value, and compared with the set stability threshold S th Compare; 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, and load reduction, reactive power compensation, and inverter output adjustment response measures are triggered to restore system stability.

[0036] As a preferred solution of the photovoltaic power generation unit power generation stability monitoring and control method described in the present invention, the vector control algorithm includes: when the dq coordinate is transformed, the three-phase voltage and current are converted from the α-β stationary coordinate system to the dq coordinate system, and the active power and reactive power are independently controlled; wherein the d-axis current i d Control active power, q-axis current i q Control reactive power; voltage regulation is achieved by controlling the d-axis voltage V of the inverter d To adjust the output voltage and keep the system voltage within a stable range;

[0037] By controlling the q-axis voltage V q To adjust the output frequency to synchronize it with the grid frequency.

[0038] As a preferred solution of the photovoltaic power generation unit power generation stability monitoring and control method described in the present invention, wherein: the control of the voltage and frequency output by the inverter includes current control; calculating the d-axis and q-axis current reference values ​​according to the real-time voltage and load requirements and The calculation formula is expressed as:

[0039]

[0040] Among them, P ref and Q ref are the reference values ​​of active power and reactive power respectively; Indicates the reference value of the d-axis current; Indicates 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 adjust the voltage output of the d-axis and q-axis:

[0042]

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

[0044] Adjust the inverter output voltage V inv (t) and frequency f inv (t), so that it can be synchronized with the power grid and maintain stability, the calculation formula is:

[0045] V inv (t) = V ref +ΔV d

[0046] f inv (t) = f grid +Δf

[0047] Among them, f inv (t) represents the output frequency of the inverter at time t; V ref Indicates the voltage reference value, which is used to set the target voltage of the inverter output; ΔV d represents the voltage increment adjusted by the d-axis voltage controller, which is used to adjust the output voltage; f grid represents the reference frequency of the power 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), real-time evaluation of the collapsed stability index S(t); when the system voltage and frequency return to stability, the stability index S(t) reaches and exceeds the threshold S th When the inverter is turned on, it gradually returns to normal operating mode.

[0049] A photovoltaic power generation unit power generation stability monitoring and control system using any method described in the present invention comprises:

[0050] 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, and collects and transmits voltage data;

[0051] Dynamic voltage margin modeling and analysis module, based on the collected voltage data, establishes a dynamic voltage margin model, analyzes the voltage margin, and calculates the load margin index;

[0052] System stability assessment module, which assesses the voltage stability of the system according to the system status under different load conditions;

[0053] The inverter control and regulation module controls the output voltage and frequency of the inverter using a vector control algorithm based on the system stability assessment results.

[0054] A computer device comprises: a memory and a processor; the memory stores a computer program, comprising: the steps of implementing any one of the methods of the present invention when the processor executes the computer program.

[0055] A computer-readable storage medium stores a computer program, comprising: when the computer program is executed by a processor, the steps of implementing any one of the methods of the present invention are implemented.

[0056] The beneficial effects of the present invention are as follows: by deploying voltage sensors at key nodes of photovoltaic power generation units, collecting voltage data in real time, establishing a dynamic voltage margin model and calculating load margin indicators, the voltage stability of the system can be comprehensively analyzed. On this basis, by evaluating the stability under different load conditions, the voltage and frequency output of the inverter are accurately controlled using a vector control algorithm to ensure that the system maintains stability under complex operating conditions. This method effectively improves the voltage control accuracy and dynamic response capability of the photovoltaic power generation system, and improves the reliability of power supply and the quality of power. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. Among them:

[0058] Figure 1 An overall flow chart of a photovoltaic power generation unit power generation stability monitoring and control method provided for the first embodiment of the present invention. DETAILED DESCRIPTION

[0059] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0060] Example 1, reference Figure 1 , as an embodiment of the present invention, provides a photovoltaic power generation unit power generation stability monitoring and control method, comprising:

[0061] S1: Deploy voltage sensors at key nodes of photovoltaic power generation units to collect voltage data in real time.

[0062] Furthermore, 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 nodes, and at the output end of the photovoltaic array: this node is the initial point where the photovoltaic power generation unit generates electricity. Measuring the voltage here can obtain the voltage information of the photovoltaic array output. Inverter input: The inverter input is the node before the photovoltaic array output is connected to the inverter. Measuring the voltage here helps monitor the voltage condition of the photovoltaic power generation unit input to the inverter. Inverter output: The inverter converts direct current into alternating current and outputs it to the grid or load. Measuring the voltage here can ensure the voltage quality of the inverter output. Grid connection point: This node is the connection point between the photovoltaic power generation unit and the grid. Measuring the voltage here can monitor the voltage condition of the photovoltaic power generation unit after it is connected to the grid.

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

[0064] Furthermore, the data acquisition module includes a voltage sensor, a data acquisition unit, and a communication unit, which monitor the key voltage points of the photovoltaic power generation unit in real time and collect and transmit voltage data.

[0065] Furthermore, voltage sensors are deployed at key nodes of the photovoltaic power generation system to collect voltage data in real time.

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

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

[0068] It should be noted that through multi-point voltage monitoring, the voltage status of the photovoltaic power generation system throughout its life cycle can be dynamically tracked. Compared with the traditional single-point monitoring method, this multi-point real-time monitoring provides more comprehensive voltage status data. These data can not only reflect the operating status of the system in real time, but also provide accurate data support for subsequent voltage margin analysis and load margin index calculation, thus laying the 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] Furthermore, the establishment of a dynamic voltage margin model includes establishing a dynamic voltage margin model to capture the dynamic changes of the system voltage 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, reflecting the voltage stability of the system, and the formula is expressed as:

[0071] ΔV(t)=V(t)-V min

[0072] Where V(t) represents the system voltage at the current time t; V min Indicates the lowest voltage allowed by the system.

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

[0074]

[0075] in, Indicates the rate of change of voltage margin; P load (t) represents the current load power; P pv (t) represents the photovoltaic power generation; Q(t) represents the reactive power; f(·) represents a multivariable function that describes how the voltage margin changes with time, load, power generation and other factors.

[0076] Furthermore, the future voltage margin (ΔV(t+Δt)) is predicted. The voltage margin at the future time t+Δt is predicted based on the current voltage margin and the dynamic model. The formula is expressed as:

[0077]

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

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

[0080] P max (t+Δt)=h(ΔV(t+Δt))

[0081] Where h(·) is a function obtained from the voltage-power curve (PV curve) or by experimental fitting, which represents the maximum tolerable power under a given voltage margin.

[0082] Furthermore, the calculating of the load margin indicator includes predicting future load power.

[0083] Furthermore, based on historical data and load models, the load power P at future moments is predicted. load (t+Δt):

[0084] P load (+Δt)=P load (t)+ΔP load

[0085] Where ΔP load Represents the predicted increment of load power, which can be predicted by time series analysis or machine learning models such as ARIMA LSTM.

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

[0087] Furthermore, the load margin index LMI(t+Δt) indicates the proportion of additional load that the system can withstand before the voltage drops to the minimum allowable value. The formula is:

[0088]

[0089] Among them, P max (t+Δt) represents the maximum tolerable power of the system at the future time t+Δt; P load (t+Δt) represents the predicted load power of the system at the future moment.

[0090] It should be noted that traditional technologies usually rely on static voltage monitoring and cannot dynamically respond to complex changes within the system. The present invention captures the instantaneous state of the system through a dynamic model, uses the state space method to accurately describe the dynamic behavior of the voltage, and combines the load margin index to comprehensively evaluate the system's carrying capacity. This method not only improves the accuracy of voltage monitoring, but also significantly improves the system's resilience, allowing 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] Furthermore, 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 load margin indicators, and the formula is expressed as follows:

[0093]

[0094] Among them, α and β are weight coefficients, reflecting the relative importance of voltage margin and load margin to system stability; ΔV(t) / V min It is the normalized voltage margin, which reflects the relative gap between the current voltage and the minimum allowable voltage; LMI(t) is the load margin index, which reflects the additional load capacity that the system can withstand under the current voltage conditions.

[0095] Furthermore, stability judgment and response, real-time calculation of S(t) value, and compared with the set stability threshold S th Compare; 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, and load reduction, reactive power compensation, and inverter output adjustment response measures are triggered to restore system stability.

[0096] It should be noted that by calculating the stability evaluation index in real time and comparing it with the set stability threshold, early warning can be given before the voltage or load becomes abnormal, triggering corresponding control measures. This predictive adjustment can significantly improve the system's response speed and control accuracy, and reduce the risk of system downtime or damage caused by instability.

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

[0098] Furthermore, the vector control algorithm includes, when the dq coordinates are transformed, the three-phase voltage and current are converted from the α-β stationary coordinate system to the dq coordinate system, and the active power and reactive power are controlled independently; wherein the d-axis current i d Control active power, q-axis current i q Control reactive power; voltage regulation is achieved by controlling the d-axis voltage V of the inverter d To adjust the output voltage and keep the system voltage within a stable range.

[0099] Furthermore, by controlling the q-axis voltage V q To adjust the output frequency to synchronize it with the grid frequency.

[0100] Furthermore, the control of the voltage and frequency output by the inverter includes current control; calculating the d-axis and q-axis current reference values ​​according to the real-time voltage and load requirements. and The calculation formula is expressed as:

[0101]

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

[0103] Furthermore, a PI controller is used to adjust the voltage output of the d-axis and q-axis:

[0104]

[0105] Among them, V d Represents the d-axis voltage, which is used to control the active power output of the inverter; V q Represents the q-axis voltage, which is used to control the reactive power output of the inverter; K pd , K id represents the proportional gain and integral gain of the d-axis PI controller; K pq , K iq represents the proportional gain and integral gain of the q-axis PI controller; i d Indicates the actual d-axis current; i q Indicates the actual q-axis current; Indicates the reference value of the d-axis and q-axis current.

[0106] Furthermore, the output voltage V inv (t) and frequency f inv (t), so that it can be synchronized with the power grid and maintain stability, the calculation formula is:

[0107] V inv (t) = V ref +ΔV d

[0108] f inv (t) = f grid +Δf

[0109] Among them, f inv (t) represents the output frequency of the inverter at time t; V ref Indicates the voltage reference value, which is used to set the target voltage of the inverter output; ΔV drepresents the voltage increment adjusted by the d-axis voltage controller, which is used to adjust the output voltage; f grid represents the reference frequency of the power grid; Δf represents the frequency increment adjusted by the q-axis voltage controller.

[0110] Furthermore, the adjusted voltage V inv and frequency f inv (t), real-time evaluation of the collapsed stability index S(t); when the system voltage and frequency return to stability, the stability index S(t) reaches and exceeds the threshold S th When the inverter is turned on, it gradually returns to normal operating mode.

[0111] It should be noted that the basis of the vector control algorithm is the dq coordinate transformation. This transformation converts the three-phase voltage and current from the stationary abc coordinate system to the rotating dq 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 independently control the active power and reactive power, thereby achieving more precise power regulation. d-axis current controls active power: In the dq coordinate system, the d-axis current i d Mainly responsible for active power control. By adjusting the d-axis voltage V d , can directly affect the active power output by the inverter, so that the system can stably provide power to the load or grid. q-axis current controls reactive power: q-axis current i q It is responsible for reactive power control. By adjusting the q-axis voltage V q ,The output of reactive power can be adjusted to control the output frequency of the inverter so that it is synchronized with the grid frequency.

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

[0113] 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 and collects and transmits voltage data.

[0114] 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.

[0115] The system stability assessment module assesses the voltage stability of the system according to the system status under different load conditions.

[0116] The inverter control and regulation module controls the output voltage and frequency of the inverter using a vector control algorithm based on the system stability assessment results.

[0117] If the above functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

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

[0119] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0120] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0121] Example 2: The following is an embodiment of the present invention, which provides a method for monitoring and controlling the power generation stability of a photovoltaic power generation unit. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments.

[0122] In order to verify the actual effect of the invention, this embodiment is experimentally verified in a standard photovoltaic power generation system. The photovoltaic power generation system includes a photovoltaic array, a 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 deploying voltage sensors for real-time voltage data collection, using dynamic voltage margin models and load margin indicators to evaluate system stability, and optimizing the output voltage and frequency of the inverter through vector control algorithms.

[0123] First, four voltage sensors are deployed at the key nodes of the photovoltaic power generation unit, 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 voltage data of each node in real time. The measurement range of the sensor is selected according to the voltage level of the system to ensure that all key voltage points from the DC end to the AC end can be covered. The data acquisition module includes a high-precision voltage sensor, a data acquisition unit, and a communication unit. The collected data is transmitted to the central controller in real time through the communication unit to support subsequent analysis and control.

[0124] Based on the data collection, a dynamic voltage margin model of the system was 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 minimum allowed voltage. Using this model, the load margin index (LMI) was further calculated to evaluate the stability of the system under different load conditions. In order to make the experiment representative, the system performance was tested in different time periods (including morning, noon and evening when the light intensity changes greatly) and different load levels (light load, medium load and heavy load, respectively).

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

[0126] Table 1 Part of the test data

[0127]

[0128]

[0129] By analyzing the data in Table 1, it can be concluded that the technical solution adopted by the present invention has significant effects under different load conditions and light intensities. First, in the voltage monitoring results of the photovoltaic system in different time periods, the real-time voltage is maintained within a relatively stable range, while the voltage margin varies according to the load. Under light load conditions, the voltage margin is relatively high, reaching up to 12.0%, indicating that the system has a strong ability to resist voltage fluctuations under low load; under heavy load conditions, the voltage margin is reduced, 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 load margin index (LMI) further illustrates the superiority of the present invention. LMI has a small fluctuation range under different load conditions and remains above 0.85 in most cases, indicating that the system can adjust the output power of the inverter in time according to the real-time voltage and load conditions, thereby effectively avoiding system instability caused by load changes. In addition, by adjusting the inverter output frequency through the vector control algorithm, the system frequency is always maintained between 49.9Hz and 50.3Hz.

[0131] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention 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 invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A photovoltaic power generation unit power generation stability monitoring and control method, characterized in that: include: Deploy voltage sensors at key nodes of photovoltaic power generation units to collect voltage data in real time; Establish a dynamic voltage margin model, analyze voltage margin and calculate load margin indicators; Evaluate the stability of the system under different load conditions; The vector control algorithm is used to control the voltage and frequency of the inverter output.

2. The photovoltaic power generation unit power generation stability monitoring and control method according to claim 1, characterized in that: 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 nodes, installing voltage sensors at the photovoltaic array output end, inverter input end, inverter output end, and grid connection point, and starting the system for real-time voltage monitoring to ensure stable operation of the system and timely capture voltage changes; The photovoltaic power generation unit includes a photovoltaic array, a DC-AC inverter and an electric energy metering device.

3. The photovoltaic power generation unit power generation stability monitoring and control method according to claim 2, characterized in that: The establishing of the dynamic voltage margin model includes establishing the dynamic voltage margin model to capture the dynamic changes of the 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 allowed voltage, and the formula is: ΔV(t)=V(t)-V min Where V(t) represents the system voltage at the current time t; V min Indicates the lowest voltage allowed by the system; A dynamic voltage equation is established to describe the dynamic changes of system voltage. The formula is expressed as: in, Indicates the rate of change of voltage margin; P load (t) represents the current load power; P pv (t) represents photovoltaic power generation; Q(t) represents reactive power; f(·) represents a multivariable function; The voltage margin at the future time t+Δt is predicted based on the current voltage margin and the dynamic model. The formula is expressed as: Among them, τ represents the intermediate variable of the integration, and the integral represents the cumulative change of the voltage margin in the time period from t to t+Δt.

4. The photovoltaic power generation unit power generation stability monitoring and control method according to claim 3, characterized in that: The calculation of the load margin index includes predicting the future load power and calculating the load limit power. Under the predicted voltage margin, the maximum load power that the system can withstand is expressed as follows: P max (t+Δt)=h(ΔV(t+Δt)) Where h(·) represents the maximum tolerable power under a given voltage margin, which is a function obtained by experimental fitting from the voltage-power curve; Based on historical data and load models, predict the load power P at future times load The (t+Δt) formula is expressed as: P load (t+Δt)=P load (t)+ΔP load Among them, ΔP load Represents the predicted increment of load power, which can be predicted by time series analysis or machine learning models; Calculate the load margin index. The load margin index LMI (t+Δt) indicates the proportion of additional load that the system can withstand before the voltage drops to the minimum allowable value. The formula is: Among them, P max (t+Δt) represents the maximum tolerable power of the system at the future time t+Δt; P load (t+Δt) represents the predicted load power of the system at the future moment.

5. The photovoltaic power generation unit power generation stability monitoring and control method according to claim 4, characterized in that: 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 load margin indicators. The formula is expressed as: Among them, α and β are weight coefficients, reflecting the relative importance of voltage margin and load margin to system stability; ΔV(t) / V min It is the normalized voltage margin, which reflects the relative gap between the current voltage and the minimum allowable voltage; LMI(t) is the load margin index, which reflects the additional load capacity that the system can withstand under the current voltage conditions; Stability judgment and response, real-time calculation of S(t) value, and compared with the set stability threshold S th Compare; 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, and load reduction, reactive power compensation, and inverter output adjustment response measures are triggered to restore system stability.

6. The photovoltaic power generation unit power generation stability monitoring and control method according to claim 5, characterized in that: 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; wherein the d-axis current i d Control active power, q-axis current i q Control reactive power; voltage regulation is achieved by controlling the d-axis voltage V of the inverter d To adjust the output voltage and keep the system voltage within a stable range; By controlling the q-axis voltage V d To adjust the output frequency to synchronize it with the grid frequency.

7. The photovoltaic power generation unit power generation stability monitoring and control method according to claim 6, characterized in that: The control of the voltage and frequency output by the inverter includes current control; calculating the d-axis and q-axis current reference values ​​according to the real-time voltage and load requirements; and The calculation formula is expressed as: Among them, P ref and Q ref are the reference values ​​of active power and reactive power respectively; Indicates the reference value of the d-axis current; Indicates the reference value of the q-axis current; V inv (t) represents the output voltage of the inverter at time t; The PI controller is used to adjust the voltage output of the d-axis and q-axis: Among them, V d Represents the d-axis voltage, which is used to control the active power output of the inverter; V q Represents the q-axis voltage, which is used to control the reactive power output of the inverter; K pd , K id represents the proportional gain and integral gain of the d-axis PI controller; K pq , K iq represents the proportional gain and integral gain of the q-axis PI controller; i d Indicates the actual d-axis current; i q Indicates the actual q-axis current; Indicates the reference value of d-axis and q-axis current; Adjust the inverter output voltage V inv (t) and frequency f inv (t), so that it can be synchronized with the power grid and maintain stability, the calculation formula is: V inv (t)=V ref +ΔV d f inv (t)=f grid +Δf Among them, f inv (t) represents the output frequency of the inverter at time t; V ref Indicates the voltage reference value, which is used to set the target voltage of the inverter output; ΔV d represents the voltage increment adjusted by the d-axis voltage controller, which is used to adjust the output voltage; f grid represents the reference frequency of the power grid; Δf represents the frequency increment adjusted by the q-axis voltage controller; Continuously monitor the adjusted voltage V inv (t) and frequency f inv (t), real-time evaluation of the collapsed stability index S(t); when the system voltage and frequency return to stability, the stability index S(t) reaches and exceeds the threshold S th When the inverter is turned on, it gradually returns to normal operating mode.

8. A photovoltaic power generation unit power generation stability monitoring and control system using the method according to any one of claims 1 to 7, characterized in that: 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, and collects and transmits voltage data; Dynamic voltage margin modeling and analysis module, based on the collected voltage data, establishes a dynamic voltage margin model, analyzes the voltage margin, and calculates the load margin index; System stability assessment module, which assesses the voltage stability of the system according to the system status under different load conditions; The inverter control and regulation module controls the output voltage and frequency of the inverter using a vector control algorithm based on the system stability assessment results.

9. 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, the steps of the photovoltaic power generation unit power generation stability monitoring and control method are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the photovoltaic power generation unit power generation stability monitoring and control method are implemented.

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