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    • 专利摘要:
    Method of optimizing the repowering of photovoltaic solar plants through predictive and intelligent preventive maintenance. The invention is a method of optimizing the repowering of solar photovoltaic plants by taking advantage of intelligent preventive and predictive maintenance that detects the failures of modules or cells within the modules, aerial inspections by infrared thermography and/or by electroluminescence. In the method object of the invention, the defective modules detected are separated into groups of different types of failures: A - irreversible failure; B - reversible failure and C - partially reusable failure. The repowering consists in replacing the modules with type A failure with new, higher power modules, and regrouping them connected in series in the same branches (1). Modules with type B failure are repaired and replaced in their original location, and modules C either regroup into branches in series, or are replaced by new modules of higher power, which will also be connected in series in branches (one). (Machine-translation by Google Translate, not legally binding)
    公开号:ES2690176A1
    申请号:ES201730710
    申请日:2017-05-19
    公开日:2018-11-19
    发明作者:Hugo José RODRÍGUEZ SAN SEGUNDO；Antonio CALO LÓPEZ；Cristina VICENTE SUSO
    申请人:Hugo José RODRÍGUEZ SAN SEGUNDO；
    IPC主号:
    专利说明:

    Technical sector
    The invention is part of the renewable energy technical sector, more specifically in the field of photovoltaic solar energy. Within this sector, it is part of its operation and maintenance segment. State of the art
    90% of the global photovoltaic solar market is based on the technology called "crystalline". These solar modules are composed of crystalline silicon solar cells, both monocrystalline and multicrystalline, connected to each other by electrical connection, usually in series. In turn, in a solar plant the modules join each other in series up to a certain figure, which depends on the voltage and intensity that they want to obtain, forming branches. Each of these branches in series is connected in series or parallel to others, to form the complete photovoltaic solar plant.
    Globally, and according to the latest reports, such as the one issued annually by the International Energy Agency, in 2017 there are more than 300 gigawatt peak (GWp) of installed photovoltaic power. 60% of them are large plants with a megawatt peak (MWp) of power.
    The profitability of these plants is especially sensitive to failures in solar modules, since they are increasingly based on price competitiveness and therefore on narrower margins. For a long time, the main faults that occur in solar modules have been known quite well, both at the level of a single cell and at the module level. One of the latest reports that update the potential failures of solar modules and cells is the one carried out by the Photovoltaic Systems Program of the International Energy Agency (IEA-PVPS), entitled “Review of Faults of Photovoltaic Modules ”, March 2014. This report details that approximately 2% of the total existing modules will fail after 10-12 years of life, and before the end of their useful life. The main consequence of any of these failures is that, being several cells and several modules electrically connected in series, the failure of a single cell or a single module can "shut down" the entire series and cause a more or less significant loss of performance. These failures are generally electrical and are due to various causes, most of which can be detected by the higher temperature increase of the affected areas by infrared emission (IR) thermographic techniques, or by the lower electrical conductivity of the affected areas , measured by emission of electroluminescence (EL).
    The preventive maintenance that has mostly been carried out, however, has been more aimed at preventing dirt accumulation, or checking the final electrical connections in the AC / DC inverter, wiring conservation, etc., than to detect failures within the modules or in solar cells. The introduction of IR and EL techniques, which allow early detection and therefore intelligent predictive maintenance, has begun to become popular only very recently with the rise of unmanned aerial vehicles or drones, which allow a cost-effective inspection speed. Until the introduction of drones, the inspection was carried out at ground level and was intensive in time and resource consumption, and therefore unfeasible to introduce into a standard maintenance plan. The rise of these techniques is accompanied by an increase in patent applications dedicated to inspection methods of photovoltaic plants preferably with drones, both with IR (for example, patents KR20150022121 and KR20150022119), as with EL (patents CN104883128, CN204392177 and CN103595351) , as with both (US20150229269). In addition, its use in maintenance has been introduced, for example, in the latest recommendations of the US National Renewable Energy Laboratory report. (NREL, for its acronym in English), entitled "Best Practices in Operation and Maintenance of Photovoltaic Systems", whose second and up to the last edition is December 2016. And even a specific standard for measurement is being made right now. IR in solar plants: in March 2017 the last vote on the first edition of the international standard IEC 64426-3 TS, entitled “Photovoltaic Systems - Requirements for testing, documentation and maintenance - Part 3: Thermography infrared exterior of modules and photovoltaic plants ”, which in its current version, not yet approved, suggests (does not require) a thermographic inspection every 4 years maximum, or more frequent inspections if there are circumstances that foresee potential failures or fire risk as in Large photovoltaic installations on deck. All these documents are laying the foundations for intelligent predictive maintenance for the early detection of module failures, and we will see improvements in the coming years.
    The ultimate goal of this predictive maintenance is to detect those defective modules in time. However, today there is no clear method of what exactly to do with these modules, how to manage their replacement, repair or simply if it is more convenient to let them be.
    On the other hand, all this development is not exploited to its maximum potential, which can reach the repowering of solar plants. When today we are thinking about repowering solar plants to obtain better performance, we usually refer to replacing all the old, less powerful modules, with more powerful new modules, taking advantage of the existing infrastructure. This consideration is usually made only in case of general failure of the plant, or, more commonly, at the end of its useful life. As far as the knowledge of the authors goes, no more optimized repowering method has been proposed, and in no case taking into account the data obtained with the maintenance of the plants.
    The present invention proposes a method for continuously optimized repowering throughout the life of a solar plant using the new cost-effective methods of intelligent preventive and predictive maintenance, so that knowledge of the modules that fail to use is used. , through its optimal management, constantly reorganize the solar plant with the ultimate goal of generating at all times the largest production of electricity. And with that ensure the highest possible return on investment. Explanation of the invention.
    The present invention is a method for optimizing the repowering of a photovoltaic solar plant taking advantage of intelligent preventive and predictive maintenance based on the detection of module failures by means of aerial thermography (IR) and electroluminescence (EL).
    Said optimized repowering method differs with respect to the normal repowering performed today at several points:
    - It is not performed at a certain point in time, for example at the end of the life of the plant, but is carried out continuously.
    - It does not indiscriminately replace all modules, including those that continue to function and give their maximum power, but focuses only on those that begin to fail, their failure is anticipated in a short period of time, or they fail completely.
    - Therefore, it maximizes the initial investment of the modules that continue to operate, since they will continue to belong to the plant until they obtain their full performance (until the end of their useful life or until they fail).
    - And it also minimizes the investment in repowering, which is being done gradually and only in those areas of the plant that have worse yields.
    In order to perform this optimization of the enhancement, it must be taken into account that not all module failures lead to the same outcome. Depending on the type of failure, this may be:
    a.) Irreversible, having to replace the module with a new one, which, due to the unstoppable advance of technology, will always be of greater power. b.) Reversible, being able to repair the module getting the same power restored.
    c.) Partially usable, for example in modules in which a branch stops working but does not affect the total operation of the module or jeopardizes the operation of the plant, obtaining a product still useful but of less power.
    It must also be taken into account that for the operation of a solar plant to be optimal, all modules of very similar power (with power variations between them of standard deviation ± 5%) must be combined in series connected branches, and these branches, in turn, in parallel with others of different powers, preferably even to a separate inverter, if possible.
    Thus, the method of the present invention consists of the following steps:
    one. Perform an inspection of the plant, for example by thermography and / or aerial electroluminescence.
    2. Analyze the inspection data.
    3. Detect the modules that have faults according to the previous categories A, B and C.
    Four. Replace the modules that fall into category A with new ones, which will have greater power.
    5. Repair the modules that fall into category B, recovering their original power.
    6. Group the modules A, B and C by power, and replace them so that each branch in series contains modules with very similar powers, with a maximum standard deviation of ± 5%. If it were not profitable to continue with the C modules of lower power, these would be destined for other uses outside the plant (for example, selling them for other users, obtaining another revenue), and would be replaced by new ones of greater power, which would be grouped correspondingly.
    7. Repeat the process with the stipulated frequency, for example annually taking advantage of regular intelligent maintenance inspections, so that continuous optimization of the solar plant is carried out. Description of the drawings
    Figure 1 shows the modules of a solar plant to which an inspection has been carried out, in which a certain number of modules with type A (irreversible) fault have been detected, another number of modules with type B (reversible) failure, and another number of modules with type C failure (partially usable), all of them randomly distributed throughout the solar plant. The boxes (1) show several branches of modules within the plant, in which the modules that compose them are connected in series.
    Figure 2 shows the modules of a solar plant after optimizing the repowering. In it, the modules that have failed according to a type A fault have been replaced by new ones of greater power, and are aligned on the same branch (1) in series, separated from the others by parallel connection. The modules that have failed according to a type B fault have been recovered and placed back in their original place, since they have recovered their original power and do not affect the branch in which they were inserted. And the modules C have been regrouped within the same branch (1) in series, separated from the others by parallel connection. Embodiments of the invention
    In a possible but not exclusive embodiment, there is a 10 MWp solar photovoltaic plant on the ground, consisting of 40,000 modules of 250 Wp each, distributed in 1,000 branches of 40 modules in series.
    Taking advantage of an aerial thermographic inspection carried out as part of the annual intelligent predictive and preventive maintenance, the following defective modules have been detected:
    -400 type A fault modules (irreversible).-240 type B fault modules (reversible).
    - 160 type C fault modules, of which 80 lose half their power (staying at 125 Wp) and the other 80 lose a fifth of their power (staying at 200 Wp).
    5 With the repowering method in this embodiment, the 400 type A fault modules are replaced by new generation modules, which have 300 Wp each, and are grouped into 10 branches of 40 modules in series each.
    The 240 type B fault modules are recovered, returning to their original power and 10 are placed in the same place they occupied before inspection.
    The 160 type C fault modules are regrouped and distributed in four branches, two with 40 modules each of new power 125 Wp, and two with 40 modules each of new power 200 Wp.
    15 In this way, the solar plant continues to operate at its optimum point and has managed to repower from 10 MWp (nominal power, although in reality it would be lower, since there were 800 solar modules in poor condition) up to 10,006 MWp.
    20 In another possible, but not exclusive, configuration with the same number and distribution by defective module types, the modules with type A and B failures follow the same procedure, while the 160 modules with type C failure are resold abroad, replacing them in this plant for new modules of 300 Wp of power each, and distributed in four branches (1) of 40 modules in series each. The repowering
    25 achieved thus rises to 10,028 MWp.
    权利要求:
    Claims (1)
    [1]
    1. Method of optimizing the repowering of photovoltaic solar plants
    through intelligent predictive and preventive maintenance characterized by 5 that
    to. In a first step, an aerial inspection is performed by infrared thermography and / or electroluminescence to detect the defective modules;
    b. during the analysis of the results of said inspection, they are selected
    10 the defective modules for each of the following three types of failure: A - irreversible, B - reversible and C - partially usable;
    C. modules with type A fault are replaced by new, higher power modules, which are grouped into branches (1) in which they are connected
    15 in series and have powers with a standard deviation of less than ± 5% of each other;
    d. Modules with type B failure are repaired, recovering their original power, and once repaired they are returned to their original location within the plant.
    20 e. modules with type C failure are regrouped according to their new power (always lower) in groups within branches (1) in which they are connected in series and have powers with a standard deviation of less than ± 5% of each other, or they are destined to other plants and are replaced by new, more powerful modules, which are grouped into branches
    25 (1) in which they are connected in series and have powers with a standard deviation of less than ± 5% of each other.
    Figure 1
    Figure 2
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    同族专利:
    公开号 | 公开日
    EP3627695B1|2021-09-15|
    EP3627695A1|2020-03-25|
    ES2690176B2|2019-04-09|
    WO2018211163A1|2018-11-22|
    US20200159204A1|2020-05-21|
    PT3627695T|2021-12-16|
    引用文献:
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    ES2482891A1|2013-02-01|2014-08-04|Barlovento Recursos Naturales, S.L.|System and procedure for detecting defective panels in photovoltaic installations by thermography |
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    法律状态:
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    优先权:
    申请号 | 申请日 | 专利标题
    ES201730710A|ES2690176B2|2017-05-19|2017-05-19|Method of optimizing the repowering of photovoltaic solar plants through predictive and intelligent preventive maintenance|ES201730710A| ES2690176B2|2017-05-19|2017-05-19|Method of optimizing the repowering of photovoltaic solar plants through predictive and intelligent preventive maintenance|
    US16/611,371| US20200159204A1|2017-05-19|2018-05-17|Method for Optimising the Power Enhancement of Photovoltaic Solar Plants Using Smart Preventive and Predictive Maintenance|
    EP18765151.8A| EP3627695B1|2017-05-19|2018-05-17|Method for optimising the power enhancement of photovoltaic solar plants using smart preventive and predictive maintenance|
    PT187651518T| PT3627695T|2017-05-19|2018-05-17|Method for optimising the power enhancement of photovoltaic solar plants using smart preventive and predictive maintenance|
    PCT/ES2018/070362| WO2018211163A1|2017-05-19|2018-05-17|Method for optimising the power enhancement of photovoltaic solar plants using smart preventive and predictive maintenance|
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