Intelligent monitoring and adjusting method for photovoltaic power station

Abstract

The invention discloses an intelligent monitoring and adjusting method for a photovoltaic power station, and belongs to the technical field of intelligent control of photovoltaic power stations. According to the method, a photoelectric conversion efficiency analysis model is established based on collected photovoltaic module parameter data and cooling system control data, and the influence on the generated power of the photovoltaic module under different photovoltaic module surface temperatures and surface illumination intensities is analyzed; a cooling control analysis model is established, the influence efficiency on the surface temperature of the photovoltaic module under different water flows and temperature differences is analyzed, and the data management analysis capability of photovoltaic electronics is improved; according to the established photoelectric conversion efficiency analysis model, the established cooling control analysis model and the surface temperature and surface illumination intensity of the current photovoltaic module, the starting electric power threshold value of the cooling system is determined, the optimal water flow is calculated, the starting, closing and water flow of the cooling system are adaptively adjusted, the control of the cooling system is more accurate, and the service life of the cooling system is prolonged. And the power generation efficiency of the photovoltaic power station is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent control of photovoltaic power stations, and in particular to an intelligent monitoring and adjustment method for photovoltaic power stations. Background Art

[0002] Intelligent monitoring and regulation of photovoltaic power stations refers to the use of advanced sensor technology, data acquisition systems, automated control and data analysis technology to monitor, analyze and optimize the operating status of photovoltaic power stations in real time to improve work efficiency and reduce operation and maintenance costs. In photovoltaic power stations, intelligent monitoring and regulation systems play an important role in the cooling control of photovoltaic modules. Through precise monitoring and automatic adjustment, it can ensure that photovoltaic modules work at a suitable temperature and improve power generation efficiency.

[0003] In the process of photovoltaic power stations absorbing solar energy to generate electricity through photovoltaic modules, the energy conversion efficiency of photovoltaic modules will directly affect the working efficiency of photovoltaic power stations; factors such as module aging and obstructions have a small impact on the power generation power of photovoltaic modules in the same time period, while for direct sunlight, the surface temperature of photovoltaic modules will produce huge differences in the process of absorbing solar energy, affecting the energy conversion efficiency of photovoltaic modules. The cooling system can effectively cool the photovoltaic modules, thereby reducing the impact on the photovoltaic modules. However, in the prior art, it is difficult for the system to intelligently control the cooling system according to current conditions, and the adjustment of the cooling system is not precise enough, making it difficult to maximize the total power generation efficiency of the photovoltaic power station. Summary of the invention

[0004] The purpose of the present invention is to provide a photovoltaic power station intelligent monitoring and adjustment method to solve the problems raised in the above background technology.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: a photovoltaic power station intelligent monitoring and adjustment method, the method comprising the following steps:

[0006] S10, collecting parameter data during the photovoltaic module photoelectric conversion process; the parameter data includes the change of the photovoltaic module surface temperature, the change of the surface light intensity and the corresponding photovoltaic module power generation; collecting control data during the operation of the cooling system; the control data includes the change of the water flow of the cooling system and the corresponding cooling system power consumption;

[0007] S20, establish a database, and store the collected parameter data and control data as historical data in the database; establish a photoelectric conversion efficiency analysis model based on the historical parameter data and historical control data in the database, and analyze the influence of different photovoltaic module surface temperatures and surface light intensities on the photovoltaic module power generation; establish a cooling control analysis model, and analyze the influence of different water flow rates and temperature differences on the photovoltaic module surface temperature efficiency;

[0008] S30, determining the startup power threshold of the cooling system; judging whether the cooling system needs to be started according to the established photoelectric conversion efficiency analysis model, cooling control analysis model, startup power threshold of the cooling system, surface temperature of the photovoltaic module and surface light intensity; if necessary, executing step S40; if not, executing step S50;

[0009] S40, starting the cooling system, calculating the optimal water flow of the cooling system according to the established photoelectric conversion efficiency analysis model, the cooling control analysis model, the current surface temperature of the photovoltaic module and the surface light intensity, and adjusting the water flow of the cooling system according to the calculated optimal water flow;

[0010] S50: Turn off the cooling system.

[0011] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: based on the collected photovoltaic module parameter data and cooling system control data, a photoelectric conversion efficiency analysis model is established to analyze the influence of different photovoltaic module surface temperatures and surface light intensities on the photovoltaic module power generation power; a cooling control analysis model is established to analyze the influence of different water flow rates and temperature differences on the photovoltaic module surface temperature efficiency, thereby improving the data management and analysis capabilities of photovoltaic electronics; according to the startup power threshold of the cooling system and the calculated optimal water flow rate, the startup, shutdown and water flow of the cooling system are adaptively adjusted, thereby making the control of the cooling system more precise and improving the power generation efficiency of the photovoltaic power station. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 It is a schematic diagram of the steps in an embodiment of a photovoltaic power station intelligent monitoring and adjustment method of the present invention. DETAILED DESCRIPTION

[0013] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0014] See also Figure 1 , the present invention provides a technical solution:

[0015] See also Figure 1In this embodiment, a method for intelligent monitoring and regulation of a photovoltaic power station is provided. The surface temperature of the photovoltaic modules is managed by water cooling. When the photovoltaic modules in the photovoltaic power station perform photoelectric conversion, the heat generated by the photovoltaic panels is absorbed and transferred by the circulating water system, thereby improving the power generation efficiency. The method includes the following steps:

[0016] S10. Collect parameter data during the photovoltaic module photoelectric conversion process; the parameter data include changes in the surface temperature of the photovoltaic module, changes in the surface light intensity and the corresponding photovoltaic module power generation; collect control data during the operation of the cooling system; the control data include changes in the water flow of the cooling system and the corresponding cooling system power consumption.

[0017] Furthermore, the photovoltaic module is used to convert solar energy into electrical energy through the photovoltaic effect; the cooling system is used to cool the photovoltaic module by circulating water in the pipeline; wherein a temperature sensor and a light intensity sensor are installed on the photovoltaic module; the temperature sensor is used to determine the change in surface temperature of the photovoltaic module; the light intensity sensor is used to determine the change in light intensity on the surface of the photovoltaic module; a flow sensor is installed in the cooling system; the flow sensor is used to determine the change in water flow in the pipeline; the water flow in the pipeline is the water flow of the cooling system.

[0018] Furthermore, the pipeline is installed on the back of the photovoltaic module. When the cooling system is started, the surface temperature of the photovoltaic module is indirectly controlled by controlling the change of water flow in the pipeline; wherein the photovoltaic module and the cooling system are respectively interconnected with the power monitoring module; the power monitoring module is used to determine the power generation power of the photovoltaic module under the corresponding surface temperature and surface light intensity, and determine the power consumption of the cooling system under the corresponding water flow in the pipeline.

[0019] In this embodiment, the cooling system absorbs heat from the surface of the photovoltaic modules through circulating water, thereby reducing the temperature of the photovoltaic modules; when the cooling system is started, cooling water flows out of the water tank, flows through the back of the photovoltaic modules through the pipes, absorbs the heat generated by the photovoltaic modules and becomes hot water, and then flows back to the water tank for cooling, repeating the cycle to cool the surface of the photovoltaic modules.

[0020] S20. Establish a database and store the collected parameter data and control data as historical data in the database; establish a photoelectric conversion efficiency analysis model based on the historical parameter data and historical control data in the database to analyze the impact of different photovoltaic module surface temperatures and surface light intensities on the photovoltaic module power generation; establish a cooling control analysis model to analyze the impact of different water flow rates and temperature differences on the photovoltaic module surface temperature efficiency.

[0021] Specifically, the method steps are:

[0022] Retrieve historical parameter data and historical control data from the database for analysis; determine the surface temperature X of the photovoltaic module at different timestamps t based on the historical parameter data. t , surface illumination intensity Y t and power generation Z t ; According to the historical control data, determine the water flow Q of the cooling system at different timestamps t t And power consumption P t According to Q t and P t , determine the corresponding power consumption under different cooling system water flow rates, and obtain the mapping function P(Q);

[0023] Based on the historical parameter data before the cooling system is started, a photoelectric conversion efficiency analysis model is established; the surface temperature X and surface light intensity Y of the photovoltaic module are used as independent variables, and the power generation power Z of the photovoltaic module is used as the dependent variable. The influence of different photovoltaic module surface temperatures and surface light intensities on the power generation power of the photovoltaic module is analyzed, and the relationship curve of X, Y and Z is obtained:

[0024] Z=Y(ae -bX +c)+d;

[0025] Among them, a, b, c, and d are all constants; according to the corresponding X in the historical parameter data before the cooling system is started t , Y t and Z t , determine the constant values ​​of a, b, c, and d respectively;

[0026] It should be noted that, according to the start-up and shutdown time of the cooling system, the historical parameter data and the historical control data are divided into before the cooling system is started and after the cooling system is started; based on the historical parameter data before the cooling system is started, a photoelectric conversion efficiency analysis model is established, so that the obtained relationship curve of X, Y and Z is not affected by the cooling system, which improves the accuracy of data analysis; X, Y and Z in the relationship curve correspond to X in the historical parameter data, respectively. t , Y t and Z t , the X in the historical parameter data t , Y t and Z t Substitute them into the relationship curve for fitting and determine the constant values ​​of a, b, c, and d. Among them, due to the influence of factors such as aging of photovoltaic components, the closer the timestamp corresponding to the historical parameter data selected for analysis is, the more accurate the fitting relationship curve will be.

[0027] It should be noted that the current of the photovoltaic module is mainly determined by the number of electron-hole pairs. When the light intensity is low, the number of electron-hole pairs is proportional to the light intensity. As the light intensity increases, the material and structure of the photovoltaic module limit the number of electron-hole pairs. At this time, the current of the photovoltaic module reaches a saturation value; when the light intensity reaches the saturation region, the power generation power of the photovoltaic module reaches a maximum value and the maximum value is fixed, which is not applicable to the relationship curve calculation formula. Therefore, in this implementation, by selecting larger and more efficient photovoltaic modules, the applicable range of the relationship curve calculation formula of X, Y and Z is within the linear region.

[0028] Based on the historical parameter data and historical control data after the cooling system is started, a cooling control analysis model is established. t , Y t and Z t , calculate the water flow Q at different time stamps t t Under this condition, the influence value W on the surface temperature of photovoltaic modules t :

[0029]

[0030] Where K represents the heat transfer coefficient of the photovoltaic module; A represents the surface area of ​​the photovoltaic module; ε represents the integral variable at the time, t-1≤ε≤t; Y ε and Z ε They represent the surface illumination intensity and power generation of the photovoltaic module at time ε respectively; X t-1 Indicates the surface temperature of the photovoltaic module at time t-1;

[0031] According to W t and Q t , taking the water flow rate Q as the independent variable and the influence value W of the surface temperature of the photovoltaic module as the dependent variable, the influence efficiency of the surface temperature of the photovoltaic module under different water flow rates Q and temperature differences ΔT is analyzed, according to the calculation formula:

[0032] W=η ΔT Q;

[0033] Among them, η ΔT It indicates the efficiency of the water flow rate on the surface temperature of the photovoltaic module under the temperature difference ΔT; ΔT represents the temperature difference between the surface temperature of the photovoltaic module and the cooling water temperature in the cooling system.

[0034] It should be noted that the surface illumination intensity of the photovoltaic module is the solar power irradiated on the photovoltaic module per unit time; the predicted value of the surface temperature change of the photovoltaic module is calculated and the actual value of the PV panel surface temperature change X t -Xt-1 , and get the influence value W t ; W t and Q t As the training analysis data of W and Q, the surface temperature of the photovoltaic module and the cooling water temperature in the cooling system at different timestamps are determined respectively to obtain the temperature difference ΔT. By establishing a cooling control analysis model, the training analysis data corresponding to different water flow rates Q, temperature difference ΔT and the influence value W of the photovoltaic module surface temperature are substituted into the cooling control analysis model to determine the influence efficiency η ΔT ; where η ΔT According to the change of ΔT, when ΔT is larger, the corresponding impact efficiency η ΔT The bigger.

[0035] S30. Determine the startup power threshold of the cooling system; determine whether the cooling system needs to be started based on the established photoelectric conversion efficiency analysis model, cooling control analysis model, the startup power threshold of the cooling system, the surface temperature of the photovoltaic module and the surface light intensity; if necessary, execute step S40; if not, execute step S50.

[0036] Specifically, the method steps are:

[0037] Determine the startup power threshold P of the cooling system min , and determine the min The corresponding cooling system water flow Q min The startup power threshold of the cooling system represents the minimum power required to maintain the operation of the cooling system and cool down the photovoltaic components;

[0038] According to the surface temperature X and surface light intensity Y, Q of the photovoltaic module min , the established photoelectric conversion efficiency analysis model and cooling control analysis model are used to predict the impact value P of the photovoltaic module power generation after the cooling system is started. y :

[0039]

[0040] Among them, X0, Y0 and Z0 respectively represent the surface temperature, surface light intensity and power generation of the photovoltaic module at the corresponding timestamp when judging whether the cooling system needs to be started;

[0041] P y With P min Compare; if P y >P min , the cooling system needs to be started at this time; if P y ≤P min , there is no need to start the cooling system at this time.

[0042] It is understandable that after the cooling system is turned on, the water flow Q min When the impact value on the power generation of photovoltaic components can meet the power consumption required for the cooling system to start, it means that the impact of temperature on the energy conversion efficiency of photovoltaic components is too large. At this time, the cooling system is started to cool down the photovoltaic components, thereby increasing the total power generation of the photovoltaic power station.

[0043] In this embodiment, the startup power threshold of the cooling system is determined according to the minimum power of the cooling system in the photovoltaic power station when it is in operation; because during the operation of the cooling system, it is necessary not only to do work on the control of the water flow, but also to do work on the startup of other equipment in the cooling system, so by predicting the impact of the startup of the cooling system on the power generation of the photovoltaic components, it is determined whether the power storage of the photovoltaic power station can be increased after the startup of the cooling system, so as to control the startup of the cooling system, make the regulation and control of the cooling system more precise, and at the same time improve the power generation efficiency of the photovoltaic power station.

[0044] S40, start the cooling system, calculate the optimal water flow of the cooling system according to the established photoelectric conversion efficiency analysis model, cooling control analysis model, current photovoltaic module surface temperature and surface light intensity, and adjust the water flow of the cooling system according to the calculated optimal water flow.

[0045] Specifically, the method steps are:

[0046] Determine the surface temperature of the photovoltaic module at the current timestamp t0 and surface illumination intensity

[0047] According to X t0 , Y t0 , establish the photoelectric conversion efficiency analysis model and cooling control analysis model, calculate the optimal water flow of the cooling system at the current timestamp t0 make The formula to meet the conditions is:

[0048]

[0049] Among them, R max Indicates that the surface temperature of the photovoltaic module is The surface light intensity is And the optimal water flow rate of the cooling system is When , the total power generation of the photovoltaic power station;

[0050] According to the calculated Regulate the water flow in the cooling system.

[0051] It should be noted that the total power generation of the photovoltaic power station represents the power generation of the photovoltaic modules minus the power consumption of the cooling system; by adjusting the water flow of the cooling system, when the water flow increases, the heat exchange with the photovoltaic modules increases, thereby reducing the surface temperature of the photovoltaic modules and improving the power generation efficiency of the photovoltaic modules; and because the cooling system adjusts the water flow, the power consumption of the cooling system corresponding to different water flow rates is also different. By calculating the total power generation, the photovoltaic power station is always maintained at the maximum power generation efficiency, thereby improving the data analysis capability of the photovoltaic power station; wherein, without considering factors such as wear of the cooling system, the mapping function P(Q) of the cooling system water flow and power consumption is fixed.

[0052] S50: Turn off the cooling system.

[0053] like Figure 1 As shown, in this embodiment, the intelligent monitoring of the photovoltaic power station is started, and it is determined whether to stop the operation; if the operation continues, steps S10-S50 are repeated; if the operation is stopped, the intelligent monitoring of the photovoltaic power station is terminated.

[0054] Furthermore, an interactive display platform is provided to digitally display the surface temperature of the photovoltaic module, the surface light intensity, the power generation power of the photovoltaic module, the water flow of the cooling system and the power consumption of the cooling system; among them, the management personnel can directly control the start and stop of the cooling system through the interactive display platform.

[0055] In this embodiment, at a certain moment, when the manager directly controls the cooling system to start through the interactive display platform, step S40 is repeatedly executed until the manager shuts down the cooling system.

[0056] Finally, it should be noted that the above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A photovoltaic power station intelligent monitoring and adjustment method, characterized in that: The method comprises the following steps: S10, collecting parameter data during the photovoltaic module photoelectric conversion process; the parameter data includes the change of the photovoltaic module surface temperature, the change of the surface light intensity and the corresponding photovoltaic module power generation; collecting control data during the operation of the cooling system; the control data includes the change of the water flow of the cooling system and the corresponding cooling system power consumption; S20, establish a database, and store the collected parameter data and control data as historical data in the database; establish a photoelectric conversion efficiency analysis model based on the historical parameter data and historical control data in the database, and analyze the influence of different photovoltaic module surface temperatures and surface light intensities on the photovoltaic module power generation; establish a cooling control analysis model, and analyze the influence of different water flow rates and temperature differences on the photovoltaic module surface temperature efficiency; S30, determining the startup power threshold of the cooling system; judging whether the cooling system needs to be started according to the established photoelectric conversion efficiency analysis model, cooling control analysis model, startup power threshold of the cooling system, surface temperature of the photovoltaic module and surface light intensity; if necessary, executing step S40; if not, executing step S50; S40, starting the cooling system, calculating the optimal water flow of the cooling system according to the established photoelectric conversion efficiency analysis model, the cooling control analysis model, the current surface temperature of the photovoltaic module and the surface light intensity, and adjusting the water flow of the cooling system according to the calculated optimal water flow; S50: Turn off the cooling system.

2. A photovoltaic power station intelligent monitoring and adjustment method according to claim 1, characterized in that: The photovoltaic module is used to convert solar energy into electrical energy through the photovoltaic effect; the cooling system is used to cool the photovoltaic module by circulating water in the pipeline; wherein a temperature sensor and a light intensity sensor are installed on the photovoltaic module; the temperature sensor is used to determine the change in surface temperature of the photovoltaic module; the light intensity sensor is used to determine the change in light intensity on the surface of the photovoltaic module; a flow sensor is installed in the cooling system; the flow sensor is used to determine the change in water flow in the pipeline; the water flow in the pipeline is the water flow of the cooling system.

3. A photovoltaic power station intelligent monitoring and adjustment method according to claim 2, characterized in that: The pipeline is installed on the back of the photovoltaic module. When the cooling system is started, the surface temperature of the photovoltaic module is indirectly controlled by controlling the change of water flow in the pipeline; wherein the photovoltaic module and the cooling system are respectively connected to the power monitoring module; the power monitoring module is used to determine the power generation power of the photovoltaic module under the corresponding surface temperature and surface light intensity, and determine the power consumption of the cooling system under the corresponding water flow in the pipeline.

4. The photovoltaic power station intelligent monitoring and adjustment method according to claim 1, characterized in that: The method steps of step S20 are: S201, retrieve historical parameter data and historical control data from the database for analysis; determine the surface temperature X of the photovoltaic module at different timestamps t according to the historical parameter data. t , surface illumination intensity Y t and power generation Z t ; According to the historical control data, determine the water flow Q of the cooling system at different timestamps t t And power consumption P t According to Q t and P t , determine the corresponding power consumption under different cooling system water flow rates, and obtain the mapping function P(Q); S202. Based on the historical parameter data before the cooling system is started, a photoelectric conversion efficiency analysis model is established; the surface temperature X and the surface light intensity Y of the photovoltaic module are used as independent variables, and the power generation power Z of the photovoltaic module is used as the dependent variable. The influence of different photovoltaic module surface temperatures and surface light intensities on the power generation power of the photovoltaic module is analyzed, and the relationship curve of X, Y and Z is obtained: Z=Y(ae -bX +c)+d; Among them, a, b, c, and d are all constants; according to the corresponding X in the historical parameter data before the cooling system is started t , Y t and Z t , determine the constant values ​​of a, b, c, and d respectively; S203, based on the historical parameter data and historical control data after the cooling system is started, a cooling control analysis model is established. t , Y t and Z t , calculate the water flow Q at different time stamps t t Under this condition, the influence value W on the surface temperature of photovoltaic modules t : Where K represents the heat transfer coefficient of the photovoltaic module; A represents the surface area of ​​the photovoltaic module; ε represents the integral variable at the time, t-1≤ε≤t; Y ε and Z ε They represent the surface illumination intensity and power generation of the photovoltaic module at time ε respectively; X t-1 Indicates the surface temperature of the photovoltaic module at time t-1; According to W t and Q t , taking the water flow rate Q as the independent variable and the influence value W of the surface temperature of the photovoltaic module as the dependent variable, the influence efficiency of the surface temperature of the photovoltaic module under different water flow rates Q and temperature differences ΔT is analyzed, according to the calculation formula: W=η ΔT Q; Among them, η ΔT It indicates the efficiency of the water flow rate on the surface temperature of the photovoltaic module under the temperature difference ΔT; ΔT represents the temperature difference between the surface temperature of the photovoltaic module and the cooling water temperature in the cooling system.

5. A photovoltaic power station intelligent monitoring and adjustment method according to claim 4, characterized in that: The method steps of step S30 are: S301: Determine the startup power threshold P of the cooling system min , and determine the min The corresponding cooling system water flow Q min The startup power threshold of the cooling system represents the minimum power required to maintain the operation of the cooling system and cool down the photovoltaic components; S302, based on the surface temperature X and the surface light intensity Y, Q of the photovoltaic module min , the established photoelectric conversion efficiency analysis model and cooling control analysis model are used to predict the impact value Py of the photovoltaic module power generation after the cooling system is started: Among them, X0, Y0 and Z0 respectively represent the surface temperature, surface light intensity and power generation of the photovoltaic module at the corresponding timestamp when judging whether the cooling system needs to be started; S303, P y With P min Compare; if P y >P min , the cooling system needs to be started at this time; if P y ≤P min , there is no need to start the cooling system at this time.

6. A photovoltaic power station intelligent monitoring and adjustment method according to claim 5, characterized in that: The method steps of step S40 are: S401, determining the surface temperature of the photovoltaic module at the current timestamp t0 and surface illumination intensity S402, according to The established photoelectric conversion efficiency analysis model and cooling control analysis model calculate the optimal water flow of the cooling system at the current timestamp t0 make The formula to meet the conditions is: Among them, R max Indicates that the surface temperature of the photovoltaic module is The surface light intensity is And the optimal water flow rate of the cooling system is When , the total power generation of the photovoltaic power station; S403, according to the calculation Regulate the water flow in the cooling system.

7. A photovoltaic power station intelligent monitoring and adjustment method according to claim 6, characterized in that: An interactive display platform is provided to digitally display the surface temperature of photovoltaic modules, surface light intensity, photovoltaic module power generation, water flow of the cooling system and power consumption of the cooling system; managers can directly control the start and stop of the cooling system through the interactive display platform.

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