WO2020212206A1 - Procédé de commande d'un dispositif de refroidissement d'une installation photovoltaïque ainsi qu'installation photovoltaïque pourvue d'un dispositif de refroidissement - Google Patents

Procédé de commande d'un dispositif de refroidissement d'une installation photovoltaïque ainsi qu'installation photovoltaïque pourvue d'un dispositif de refroidissement Download PDF

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Publication number
WO2020212206A1
WO2020212206A1 PCT/EP2020/059911 EP2020059911W WO2020212206A1 WO 2020212206 A1 WO2020212206 A1 WO 2020212206A1 EP 2020059911 W EP2020059911 W EP 2020059911W WO 2020212206 A1 WO2020212206 A1 WO 2020212206A1
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WO
WIPO (PCT)
Prior art keywords
photovoltaic system
cooling device
photovoltaic
value
temperature
Prior art date
Application number
PCT/EP2020/059911
Other languages
German (de)
English (en)
Inventor
Christian Jahn
Original Assignee
Innogy Se
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Innogy Se filed Critical Innogy Se
Publication of WO2020212206A1 publication Critical patent/WO2020212206A1/fr

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Classifications

    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02S—GENERATION OF ELECTRIC POWER BY CONVERSION OF INFRARED RADIATION, VISIBLE LIGHT OR ULTRAVIOLET LIGHT, e.g. USING PHOTOVOLTAIC [PV] MODULES
    • H02S40/00—Components or accessories in combination with PV modules, not provided for in groups H02S10/00 - H02S30/00
    • H02S40/40—Thermal components
    • H02S40/42—Cooling means
    • H02S40/425—Cooling means using a gaseous or a liquid coolant, e.g. air flow ventilation, water circulation
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02S—GENERATION OF ELECTRIC POWER BY CONVERSION OF INFRARED RADIATION, VISIBLE LIGHT OR ULTRAVIOLET LIGHT, e.g. USING PHOTOVOLTAIC [PV] MODULES
    • H02S50/00—Monitoring or testing of PV systems, e.g. load balancing or fault identification
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E10/00—Energy generation through renewable energy sources
    • Y02E10/50—Photovoltaic [PV] energy

Definitions

  • the invention relates to a method for controlling a cooling device of a photovoltaic system and a photovoltaic system with a cooling device.
  • the ideal temperature for operating a photovoltaic system is, depending on
  • cooling systems are sometimes used to regulate the temperature of the photovoltaic modules.
  • Cooling systems are switched on when the temperature of the photovoltaic modules exceeds a certain, previously set temperature limit, and are switched off when a lower target temperature that has also been set previously is reached. As soon as the set temperature limit is reached again, the cooling process starts again.
  • cooling is activated when a predetermined temperature limit is reached.
  • a photovoltaic module has reached the temperature limit value, electricity generation is still guaranteed, but this is no longer as high as at the ideal operating temperature at which electricity generation reaches a maximum. The one caused by the cooling
  • the investment for the cooling system and in particular the power consumption required for the operation of the cooling system is too high compared to the increased output of the photovoltaic system achieved with the cooling system.
  • the present invention is based on the object of providing an improved method for controlling a cooling device of a photovoltaic system as well as a photovoltaic system with a cooling device, with which a better ratio of increase in performance and operating costs is achieved.
  • this object is achieved by a method for controlling a cooling device of a photovoltaic system, in which environmental data and / or
  • Operating data are obtained, based on the environmental data and / or
  • Cooling device depending on the calculated value for the forecast
  • Temperature is controlled. It was recognized that the regulation of previous cooling devices on the basis of currently measured temperature values and predetermined temperature limit values is not ideal.
  • control does not take place on the basis of a current temperature value but rather on the basis of
  • optimized operational management can take place in particular, in that the most reliable predictions possible about the temperature development of the photovoltaic modules can be made using environmental data and / or operational data, so that the photovoltaic system can be operated as continuously as possible in the ideal range by appropriate control of the cooling device and the yields thereby can be optimized.
  • the predicted temperature value can be, for example, a predicted T emperaturwert act of a single photovoltaic module or a predicted mean temperature value of several Ph oto vol ta i km od ul ⁇ e of the photovoltaic system. It is also conceivable to have several forecasted
  • the environmental data and / or operating data can in particular be received continuously and values for the predicted temperature of the photovoltaic system can in particular be continuously calculated on the basis of the received environmental data and / or operating data. In this way, the
  • Temperature development in particular the predicted temperature development of the photovoltaic system, can be continuously tracked so that the photovoltaic system can be operated as continuously as possible in an ideal range by means of a corresponding continuous control of the cooling device.
  • the temperature prognosis is based in particular on received environmental data.
  • the environmental data can for example from one or more local
  • Measuring devices are obtained, in particular measuring devices for measuring the
  • Ambient temperature, solar radiation, wind speed, precipitation, air pressure and / or cloud cover Alternatively or additionally, environmental data, in particular values for the ambient temperature, for solar radiation, for wind speed, for precipitation, the
  • Air pressure and / or for the cloud cover can be received via a communication link from an external source, for example a meteorological service.
  • the environmental data preferably contain values of measured variables of the current weather situation, in particular at the location of the photovoltaic system. In this way, a reliable forecast of the temperature at a future point in time is made possible.
  • the received and for the calculation of the Predicted temperature environmental data used values of two or more than two measured quantities, in particular of two or more of the following measured quantities: ambient temperature, solar radiation, wind speed, precipitation, air pressure and / or cloudiness.
  • the temperature is forecast, in particular on the basis of operating data received, in particular operating data of the photovoltaic system.
  • the operating data can in particular be obtained from one or more measuring devices on the photovoltaic system, for example from current or voltage measuring devices, or from a control device of the photovoltaic system.
  • the value for the forecast temperature is the
  • Photovoltaic system preferably calculated on the basis of a value for the power generation of the photovoltaic system, in particular a value for the current strength of the current generated or a value for the current output of the
  • the photovoltaic system preferably has a measuring device for determining a value for the current generation of electricity
  • Photovoltaic system By taking into account the generation of electricity, in particular the current strength or power of the photovoltaic system, the prognosis of the temperature development can be improved, in particular by taking into account heating effects due to the Joule heat produced by the generated electricity when calculating the prognosticated temperature.
  • a high electricity production typically causes a high temperature in the photovoltaic modules.
  • the operating data can in particular values for the
  • a photovoltaic system in particular a photovoltaic open-space system, with a
  • a plurality of photovoltaic modules with a controllable cooling device comprising cooling elements that are set up to cool the individual photovoltaic modules, and with a control device for controlling the cooling device, the control device being set up to control the cooling device according to the method described above or an embodiment thereof.
  • Photovoltaic system described the individual embodiments applying to both the method and the photovoltaic system. Furthermore, the individual embodiments can be combined with one another.
  • a value for a predicted temperature of the photovoltaic system at a future point in time is calculated on the basis of the environmental data and on the basis of operating data of the photovoltaic system.
  • Calculating the forecast temperature can improve the accuracy of the forecast.
  • the operation of the cooling device is further controlled as a function of a value for the generation of electricity, in particular for the current strength or power, of the photovoltaic system.
  • the regulation of the cooling device can be further improved.
  • the control of the cooling device can be adjusted if the actual
  • Power generation of the photovoltaic system differs from power generation forecast, for example, using a predetermined power curve.
  • a predefined power curve of the photovoltaic system can be used when calculating the predicted temperature, in particular when training a self-learning system, and / or when controlling the cooling device, in particular for specifying comparison values for a target / actual comparison between the power curve and operating data the photovoltaic system.
  • a value for a predicted temperature of the photovoltaic system at a future point in time is calculated on the basis of the environmental data and / or operating data and on the basis of system data of the photovoltaic system. It was recognized that the temperature development of the
  • Photovoltaic system also by taking system data into account
  • Photovoltaic system can be better forecast, for example through
  • good forecasts can be made about the heating of the photovoltaic modules as a function of the
  • Input parameters are calculated.
  • the cooling device can be activated and / or its operating parameters can be adjusted so that the ideal temperature range of the photovoltaic system is maintained before limit values are reached.
  • the best possible operational management of a photovoltaic system can be achieved.
  • Calculated temperature of the photovoltaic system at a point in time which is in the range from 10 minutes to 2 hours, preferably in the range from 15 minutes to 45 minutes after the current time.
  • the temperature development in this time window can be forecast quite easily and reliably and, on the other hand, the time interval to the current point in time enables it to be taken of countermeasures if an undesired increase in temperature is forecast.
  • the cooling capacity of the cooling device is controlled depending on the calculated value for the forecast temperature.
  • the start and end times and / or the duration for the activation of the cooling device can be controlled as a function of the calculated value for the predicted temperature.
  • the power with which the cooling device cools can also be controlled.
  • the cooling time and / or the cooling capacity can be dependent on a difference in the calculated value for the forecast
  • Temperature can be controlled to a reference value. This enables dynamic regulation of the cooling device in which the cooling time and / or
  • Cooling capacity is adapted to the forecast cooling requirement.
  • the operation of the cooling device is controlled depending on the calculated value for the predicted temperature and depending on the cooling behavior of the cooling device.
  • the cooling behavior of the cooling device can for example contain information about latency times that the
  • Cooling device required between activation and provision of the cooling capacity, or via the cooling capacity of the cooling device, possibly depending on environmental data such as the ambient temperature and / or operating data such as the current power generation. In this way, the behavior of the cooling device is also taken into account when it is being controlled, so that the required cooling power is provided with pinpoint accuracy and thus better control of the temperature is achieved.
  • the temperature of the photovoltaic system is calculated using a self-learning system, in particular a system for machine learning, for example using an artificial neural network or a fuzzy logic system.
  • a self-learning system can be trained with training data, for example with environmental data and associated data for temperature development, so that the self-learning system is able to determine a temperature of the
  • Photovoltaic system based on environmental data and / or operating data
  • the self-learning system can in this way recognize dependencies of the training data used and use these recognized dependencies when calculating the forecast temperature.
  • the temperature forecast can be dynamically adapted to the respective photovoltaic system and the scenarios that occur.
  • the self-learning system can also use control data from the cooling device to regulate the temperature of the photovoltaic system depending on the
  • forecast temperature can be trained by controlling the cooling device, so that the self-learning system is enabled to control the cooling device depending on the forecast temperature development.
  • the self-learning system can in this way recognize dependencies of the training data used and use these recognized dependencies in controlling the cooling device.
  • Environmental and / or operational data checked. This way, the Environmental data and / or operating data are examined for the possible occurrence of a fault. This enables, for example, a warning message to be output via a user interface, which draws the user's attention to a possible error, so that the user can correct this error if necessary. Furthermore, as a result of the consistency check, inconsistent environmental data and / or operating data can be disregarded when calculating the value for the forecast temperature, so that a falsification of the forecast is avoided. For this purpose, environmental data and / or operating data that are determined consistently are preferably only used to calculate the value for the predicted temperature.
  • the environmental data and / or operating data obtained it can be checked, for example, whether the environmental data and / or operating data obtained are within predetermined limits. If the environmental data include, for example, a value for an ambient temperature, in particular the
  • Air temperature it can be checked whether the value obtained is within reasonable limits, for example within a range of -20 ° C and + 50 ° C. If the value for the ambient temperature is outside this range, it is likely that the value is incorrect, for example due to a defective temperature sensor. If the operating data include, for example, values for the power generation of individual photovoltaic modules, then, if from the
  • Photovoltaic system total electricity is generated, it is checked whether the value obtained is above a predetermined minimum electricity generation.
  • a lower power generation can indicate a defect in the corresponding
  • the photovoltaic module The photovoltaic module.
  • the behavior of data of a measured variable can be checked over time. An increase or decrease in a measured variable from one time step to the next, which is above a predetermined maximum change value for the measured variable, can occur to one Indicate errors. Furthermore, the behavior of can receive simultaneously
  • Environmental data and / or operational data are compared with one another.
  • the photovoltaic module and / or the relevant group of photovoltaic modules are the photovoltaic module and / or the relevant group of photovoltaic modules.
  • a self-learning system If a self-learning system is used, it can also be trained with training data to switch between relevant and incorrect data
  • the consistency check in particular the determination of error data, can be carried out with such a self-learning system.
  • a first value for a predicted temperature of a first area of the photovoltaic system and a second value for a predicted temperature of a second area of the photovoltaic system are calculated and a first part of the cooling device assigned to the first area of the photovoltaic system is dependent on the first value and a The second part of the cooling device assigned to the second area of the photovoltaic system is controlled as a function of the second value. That way you can be more focused
  • a large open-air photovoltaic system can be divided into several subfields, each with several photovoltaic modules, the cooling device being controlled separately for the respective subfields.
  • areas with different local influencing factors can occur, for example areas with different or different orientations to the sun
  • the consideration of the respective local influencing factors on the individual areas of the photovoltaic system can be improved in that the first value is based on the environmental data and / or operating data and first location data for the first area of the photovoltaic system and the second value is based on the environmental data and / or operating data and second location data are calculated for the second area of the photovoltaic system. That way you can
  • Influencing factors such as the orientation towards the sun or, for example, time-of-day-dependent shading effects are taken into account when calculating the respective value of the forecast temperature, so that the forecast for the individual areas of the photovoltaic system is improved.
  • Photovoltaic system has a first and a second spatially delimited area, the first and second areas each having a plurality
  • the cooling device has a first part with the cooling elements provided for cooling the photovoltaic modules in the first area and a second part with the cooling elements provided for cooling the photovoltaic modules in the second area, and the first part and the second part of the cooling device with the control device separately controllable.
  • Fig. La-b an embodiment of the photovoltaic system in schematic
  • FIG. 2 an exemplary embodiment of the method in a schematic representation.
  • Fig. La-b show an embodiment of the photovoltaic system in a schematic representation.
  • Fig. La shows a schematic overview representation.
  • Fig. Lb shows a schematic sectional view corresponding to that designated in Fig. La with "Ib"
  • the photovoltaic system 2 shown in Fig. La is a
  • the photovoltaic modules 10 are set up on the substrate 14 by means of a stud frame 12.
  • a movement device [not shown) can be provided in order to align the photovoltaic modules 10 depending on the current position of the sun.
  • the photovoltaic modules 10 are electrically via power electronics [not limited
  • Feed point [not shown) connected to feed the electrical power provided by the photovoltaic modules 10 into the local power grid.
  • the photovoltaic system 2 comprises a cooling device 20 for cooling the individual photovoltaic modules 10.
  • the cooling device 20 comprises a controllable water supply device 22 to which a line system 24 is connected
  • three main lines 26a-c are connected through which the water made available by the water supply device 22 is led to the individual photovoltaic modules 10, where it exits from cooling elements 30 provided with nozzle openings 28 and reaches the collector surface 32 of the individual photovoltaic modules 10 .
  • the respective main lines 26a-c supply the cooling elements 30 of
  • Photovoltaic modules 10 each one of the areas 4, 6, and 8. The
  • Wassermentsseinri rect 22 can also be controlled such that the three main lines 26a-c can be supplied with a desired amount of water independently of each other. In this way, the
  • Cooling device 20 has three parts 34, 36, 38 which are assigned to the respective areas 4, 6 and 8 and can be controlled independently of one another.
  • a control device 40 is provided for controlling the water supply device 22.
  • the control device 40 is set up to collect environmental data on environmental conditions, in particular weather conditions, in the area of
  • one or more sensors 42, 44a-c can be provided, for example, which are installed at the location of the photovoltaic system 2 and record environmental data in the area of the photovoltaic system 2.
  • the sensor 42 can, for example, be a temperature sensor for detecting the ambient temperature, a radiation sensor for detecting solar radiation, a wind sensor for detecting the wind speed, a precipitation sensor for detecting the amount of precipitation, an air pressure sensor for detecting the air pressure or act a cloud sensor to detect the degree of cloudiness. Sensors are preferably provided for recording several of the aforementioned environmental parameters.
  • one or more respective sensors 44a-c in the corresponding areas 4, 6, 8 can be provided which measure the values of one or more of the aforementioned environmental parameters. In this way it can be taken into account, for example, if the temperatures or solar radiation differ in the individual areas 4, 6, 8, for example because of different orientation to the sun (e.g. on differently oriented slopes of a mountain or on different sides of a building) different local sensors 44a-c in the corresponding areas 4, 6, 8 can be provided which measure the values of one or more of the aforementioned environmental parameters. In this way it can be taken into account, for example, if the temperatures or solar radiation differ in the individual areas 4, 6, 8, for example because of different orientation to the sun (e.g. on differently oriented slopes of a mountain or on different sides of a building) different local
  • Shading conditions e.g. due to buildings or terrain formations
  • different altitudes e.g. in areas of different heights on a mountain slope
  • sensors can also be provided on individual photovoltaic modules 10, with which, for example, the current temperature of the respective
  • the control device 40 can furthermore be set up to receive environmental data via a network 46, for example the Internet, from a remote location
  • the control device 40 is also set up to receive operating data on the operation of the photovoltaic system 2, in particular values for the current one
  • Electricity generation such as a value for the power currently fed into the local power grid and / or values for the current power of the
  • the control device 40 with the power electronics (not shown) of the
  • Photovoltaic system 10 be connected.
  • the control of the cooling device 20 by the control device 40 is the control of the cooling device 20 by the control device 40.
  • FIG. Fig. 2 shows an embodiment of the method for controlling a
  • Cooling device of a photovoltaic system for example the cooling device 20 of Photovoltaic system 2.
  • the control device 40 can be set up to control the cooling device 20 in accordance with the method described below.
  • environmental data 64 are obtained, for example from sensors provided at the location of the photovoltaic system, such as sensors 42 or 44a-c in FIG. la, or from an environmental data service 48.
  • Environmental data 64 contain values of measured variables of the current weather situation at the location of the
  • Photovoltaic system preferably about the ambient temperature
  • the environmental data preferably contain values for at least two different measured variables of the current weather situation. If the photovoltaic system has several areas, for example areas 4, 6, 8 in FIG. 1 a, separate environmental data can be obtained for the individual areas.
  • operating data 65 are obtained, for example from the power electronics of the photovoltaic system 2, with values for the current one
  • Photovoltaic system calculated at a future point in time ti for example a value for the temperature of a photovoltaic module or a value for the average temperature of several photovoltaic modules.
  • Fig. 2 shows (at reference numeral 66) schematically a temperature curve plotted against time for a temperature at the location of the photovoltaic system 2, for example for the temperature at one
  • “to” denotes the current point in time in FIG. 2 and "ti” denotes the future point in time.
  • the difference ti-to is preferably in the range of 10-120 minutes, in particular 15-45 minutes.
  • the dashed curve 68 illustrates the on Based on the environmental data 64 and / or operating data 65, the forecast temperature development of the photovoltaic system 2.
  • the values for the predicted temperature can be calculated, for example, using a predefined method of calculation, for example using a predefined prediction algorithm or a predefined prediction function based on the environmental data and / or operating data.
  • a predefined method of calculation for example using a predefined prediction algorithm or a predefined prediction function based on the environmental data and / or operating data.
  • Control device 40 also include a self-learning system, for example with an artificial neural network, that beforehand is used to forecast the
  • Temperature development was trained on the basis of environmental data and / or operational data.
  • the predicted temperature at time ti, T (ti) can be compared, for example, with a predetermined temperature maximum T max . If T (ti) is above Tm ax , that is, according to the current prognosis, with a temperature increase up to
  • control device activates the cooling device 20 in order to avoid such an undesired
  • the cooling device 20 is controlled on the basis of a prognosis, so that the cooling device 20 can intervene at an early stage if this becomes necessary. On the one hand, this avoids actual exceeding of certain temperature maxima, since the heating is caused by activation of the
  • the predicted temperature can be calculated separately for each area 4, 6, 8 of the photovoltaic system 2 on the basis of the environmental data and / or operating data obtained for the respective area. Exceeds one of the If the predicted temperatures then reach a predetermined maximum temperature, the control device preferably activates the corresponding area of the
  • the control device 40 is preferably also set up to operate the cooling device not only as a function of the predicted value T (ti) for the temperature at time ti but also as a function of the cooling behavior of the
  • Control cooling device For this purpose, in a subsequent step 70 on the basis of the temperature prognosis carried out in step 66 and on the basis of data 72 about the cooling behavior of the cooling device 20, control parameters for controlling the cooling device 20 are calculated.
  • the control parameters can be
  • Cooling device 20 include.
  • control device 40 can, in particular, make further temperature predictions taking into account various parameters
  • the cooling device is then controlled by the control device 40 with the specific set 74 of control parameter values.
  • the data 72 on the cooling behavior of the cooling device 20 can include, for example, latency times or cooling capacities that are dependent on the volume flow. By taking these data 72 into account when determining control parameter values, an even more efficient and more targeted control of the cooling device and thus better temperature management of the photovoltaic system 2 can be achieved.
  • the determination of sets of control parameter values can in turn be carried out separately for each part 34, 36, 38 of the cooling device 20 based on the respective
  • Photovoltaic system and the data 72 take place.
  • the data 72 can also be present and taken into account separately for each part 34, 36, 38.
  • plant data of the photovoltaic plant 2 can also be taken into account in the method described in FIG. 2, for example when calculating the predicted temperature in step 66.

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Abstract

L'invention concerne un procédé pour la commande d'un dispositif de refroidissement (20) d'une installation photovoltaïque (2) dans lequel des données d'environnement (64) et/ou des données de fonctionnement (65) sont obtenues et, sur la base des données d'environnement (64) et/ou des données de fonctionnement (65), une valeur (T(tl)) pour une température prévue de l'installation photovoltaïque (2) en un moment futur (tl) est calculée et le fonctionnement du dispositif de refroidissement (20) est commandé en fonction de la valeur calculée (T(tl)) pour la température prévue. L'invention concerne en outre une installation photovoltaïque (2), en particulier une installation photovoltaïque à surface libre, présentant une pluralité de modules photovoltaïques (10), présentant un dispositif de refroidissement (20) pouvant être commandé, comprenant des éléments de refroidissement (30) qui sont conçus pour le refroidissement des différents modules photovoltaïques (10), et présentant un dispositif de commande (40) pour la commande du dispositif de refroidissement (20), le dispositif de commande (40) étant conçu pour la commande du dispositif de refroidissement (20) selon le procédé décrit ci-dessus.
PCT/EP2020/059911 2019-04-17 2020-04-07 Procédé de commande d'un dispositif de refroidissement d'une installation photovoltaïque ainsi qu'installation photovoltaïque pourvue d'un dispositif de refroidissement WO2020212206A1 (fr)

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DE102019110154.9A DE102019110154A1 (de) 2019-04-17 2019-04-17 Verfahren zur Steuerung einer Kühleinrichtung einer Photovoltaikanlage sowie Photovoltaikanlage mit einer Kühleinrichtung
DEDE102019110154.9 2019-04-17

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US20180342979A1 (en) * 2017-05-24 2018-11-29 Tiasha Joardar Method and apparatus for a solar panel

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US20160190983A1 (en) * 2014-12-31 2016-06-30 Eaton Corporation Notification Apparatus Usable With Cooling System or Other System
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Publication number Priority date Publication date Assignee Title
CN117356325A (zh) * 2023-11-01 2024-01-09 宁夏大学 一种大棚高透光柔性光伏板制冷方法及系统
CN117356325B (zh) * 2023-11-01 2024-05-07 宁夏大学 一种大棚高透光柔性光伏板制冷方法及系统

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