CN117559499A - Photovoltaic power generation intelligent energy storage system - Google Patents

Photovoltaic power generation intelligent energy storage system Download PDF

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Publication number
CN117559499A
CN117559499A CN202311542995.XA CN202311542995A CN117559499A CN 117559499 A CN117559499 A CN 117559499A CN 202311542995 A CN202311542995 A CN 202311542995A CN 117559499 A CN117559499 A CN 117559499A
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energy storage
module
power generation
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time
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CN117559499B (en
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肖丽军
冯金生
舒名华
李直元
叶文斌
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Guangzhou Felicity Solar Technology Co ltd
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Guangzhou Felicity Solar Technology Co ltd
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/28—Arrangements for balancing of the load in a network by storage of energy
    • H02J3/32—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/003—Load forecast, e.g. methods or systems for forecasting future load demand
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/004—Generation forecast, e.g. methods or systems for forecasting future energy generation
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/381—Dispersed generators
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/20—The dispersed energy generation being of renewable origin
    • H02J2300/22—The renewable source being solar energy
    • H02J2300/24—The renewable source being solar energy of photovoltaic origin

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  • Engineering & Computer Science (AREA)
  • Power Engineering (AREA)
  • Charge And Discharge Circuits For Batteries Or The Like (AREA)
  • Photovoltaic Devices (AREA)

Abstract

The invention provides a photovoltaic power generation intelligent energy storage system, which comprises a photoelectric conversion module, an energy storage module, an information acquisition module, an intelligent control module and an inversion output module, wherein the photoelectric conversion module is connected with the energy storage module; the photoelectric conversion module is used for carrying out photovoltaic power generation, the energy storage module is used for storing electric energy generated by the photovoltaic power generation, and the information acquisition module is used for acquiring power generation influence information of the system; the intelligent control module is used for adjusting an energy storage strategy according to the electric energy demand and the power generation influence information, and the inversion output module is used for outputting the electric quantity of the photoelectric conversion module and the energy storage module to the grid connection according to the grid connection electric energy demand; according to the method, the energy storage strategy can be dynamically adjusted by predicting the energy storage electric quantity in the prediction period and combining the required electric quantity, so that the service life of the energy storage equipment can be prolonged, and the energy utilization efficiency can be improved.

Description

Photovoltaic power generation intelligent energy storage system
Technical Field
The invention relates to the technical field of photovoltaic power generation systems, in particular to an intelligent energy storage system for photovoltaic power generation.
Background
With the worldwide increasing awareness of sustainable energy and environmental protection, renewable energy is becoming more and more interesting. Particularly, solar energy is used as an endless and clean energy source, and is widely popularized and applied in the global scope; however, solar power generation also faces some difficulties such as unstable power supply, inefficient energy storage, and scheduling difficulties for the grid.
Referring to the related published technical scheme, the technology with publication number of CN209731138U proposes and discloses an energy storage system for photovoltaic power generation, which converts electric energy generated by photovoltaic array through photoelectric conversion into alternating current through an electric energy conversion module, and a circuit distribution device distributes the converted alternating current to corresponding loads for power supply, and distributes residual electric quantity to the energy storage module for storage; the photovoltaic array of the scheme converts solar energy into electric energy by utilizing the photovoltaic effect so as to realize the utilization of clean energy and reduce environmental pollution; meanwhile, the residual electric quantity of the photovoltaic array converted electric energy can be stored through the energy storage module, so that the utilization rate of clean energy is further improved, the economy of photovoltaic power generation is improved, the stored residual electric quantity can be released in the power utilization peak period, the impact on a power grid is reduced, and the power utilization stability and safety are improved; however, the scheme lacks dynamic adjustment and intelligent control, cannot realize intelligent adjustment under the conditions of different weather and power requirements, and has poor energy utilization rate and protection for energy storage equipment.
Disclosure of Invention
The invention aims to provide a photovoltaic power generation intelligent energy storage system aiming at the defects existing at present.
The invention adopts the following technical scheme:
the intelligent energy storage system for photovoltaic power generation is characterized by comprising a photoelectric conversion module, an energy storage module, an information acquisition module, an intelligent control module and an inversion output module;
the photoelectric conversion module is used for carrying out photovoltaic power generation, the energy storage module is used for storing electric energy generated by the photovoltaic power generation, and the information acquisition module is used for acquiring power generation influence information of the system; the intelligent control module is used for adjusting an energy storage strategy according to the electric energy demand and the power generation influence information, and the inversion output module is used for outputting the electric quantity of the photoelectric conversion module and the energy storage module to the grid connection according to the grid connection electric energy demand;
the photoelectric conversion module generates electricity through photoelectric conversion of a photovoltaic array in the photoelectric conversion module, and the photoelectric conversion of the photovoltaic array meets the following model:
；
wherein,for the actual power of the generation, +.>The loss coefficient is in the range of +.>；/>For rated power of electricity generation, +.>For the actual solar radiation intensity +.>Is the standard radiation intensity; />The temperature conversion coefficient can be set through experiments; />For the actual temperature of the photovoltaic array surface, +.>The surface standard temperature of the photovoltaic array is set;
the information acquisition module comprises a geographic information acquisition unit and a prediction information acquisition unit; the geographic information acquisition unit is used for acquiring geographic position information of the system location, including longitude and latitude information, so that the sunshine duration of the system location can be acquired; the prediction information acquisition unit is used for acquiring temperature prediction information and weather prediction information of a system location;
further, the intelligent control module predicts the electric energy supply in the prediction period and completes the adjustment of the energy storage strategy by combining the electric energy demand in the prediction period, the adjustment of the energy storage strategy is specifically the adjustment of the charging efficiency of the energy storage module, and the specific adjustment mode of the energy storage strategy to the energy storage strategy is as follows:
setting the estimated electric energy storage capacity in the estimated time period asThe electric energy demand electric quantity of non-sunshine time in the prediction period is +.>The minimum safe energy storage electric quantity of the energy storage module is +.>When->At this time, the energy storage strategy is adjusted as follows:
；
wherein,for charging efficiency, +.>The maximum charging efficiency that can be achieved by the energy storage module under the condition of meeting the requirement of the electric energy supply of sunshine time; />The maximum safe charging efficiency of the energy storage module is set;
when (when)At this time, the energy storage strategy is adjusted as follows:
；
wherein,for the real-time energy storage electric quantity in the energy storage module, +.>Ideal charging efficiency for the set energy storage module;
further, the estimated electric energy storage capacityThe method comprises the following steps of:
wherein,for the predicted amount of electric energy supply in the predicted period, < >>The electric energy demand for the sunshine duration in the forecast period;
further, the predicted amount of power supply during the predicted periodThe method comprises the following steps of:
；
the predicted period is set to be one day, wherein,for the predicted period of time of day sunshine duration +.>For the time from sunrise, satisfy +.>；/>For a solar radiation model within a prediction period +.>In the weather forecast information, the temperature which changes with the time of day of the forecast period from sunrise;
for the solar radiation model, the following are satisfied:
；
wherein,as a function of the ideal solar radiation variation->Setting a cloud layer shielding coefficient through experiments; />The cloud cover quantity is cloud cover percentage of the current day of the prediction period in the weather prediction information;
function of variation for ideal solar radiationThe method meets the following conditions:
；
wherein,maximum solar radiation amount during the daytime for the predicted period of time;
maximum solar radiation amount for the daytime of the dayThe method comprises the following steps:
；
wherein,for maximum solar radiation in equatorial region, < ->For the latitude of the system location, +.>And->For the amplitude coefficient +.>Is a correction coefficient and satisfies +.>，/>。
The beneficial effects obtained by the invention are as follows:
according to the invention, the sunshine duration information is obtained through the geographic position of the system, the estimated electric energy storage electric quantity in the estimated time period is obtained through combining the sunshine duration information, the weather estimated information and the temperature estimated information, and the estimated electric energy storage electric quantity and the estimated electric energy demand electric quantity are compared and analyzed, and the factors of the minimum safe energy storage electric quantity and the maximum safe charging efficiency of the energy storage module are considered, so that the dynamic adjustment of the charging efficiency of the energy storage module is completed, the service life of the energy storage device is ensured, the electric energy waste is reduced, and the operation cost is reduced.
Drawings
The invention will be further understood from the following description taken in conjunction with the accompanying drawings. The components in the figures are not necessarily to scale, emphasis instead being placed upon illustrating the principles of the embodiments. Like reference numerals designate corresponding parts throughout the different views.
FIG. 1 is a schematic diagram of the overall module of the present invention.
Fig. 2 is a schematic flow chart of the intelligent energy storage method for photovoltaic power generation.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in further detail with reference to the following examples thereof; it should be understood that the detailed description and specific examples, while indicating the invention, are intended for purposes of illustration only and are not intended to limit the invention; other systems, methods, and/or features of the present embodiments will be or become apparent to one with skill in the art upon examination of the following detailed description; it is intended that all such additional systems, methods, features and advantages be included within this description; included within the scope of the invention and protected by the accompanying claims; additional features of the disclosed embodiments are described in, and will be apparent from, the following detailed description.
The same or similar reference numbers in the drawings of embodiments of the invention correspond to the same or similar components; in the description of the present invention, it should be understood that, if there is an azimuth or positional relationship indicated by terms such as "upper", "lower", "left", "right", etc., based on the azimuth or positional relationship shown in the drawings, it is only for convenience of describing the present invention and simplifying the description, but it is not indicated or implied that the apparatus or component referred to must have a specific azimuth, construction and operation in which the term is described in the drawings is merely illustrative, and it is not to be construed that the term is limited to the patent, and specific meanings of the term may be understood by those skilled in the art according to specific circumstances.
Embodiment one:
as shown in fig. 1, the embodiment provides a photovoltaic power generation intelligent energy storage system, which is characterized by comprising a photoelectric conversion module, an energy storage module, an information acquisition module, an intelligent control module and an inversion output module;
the photoelectric conversion module is used for carrying out photovoltaic power generation, the energy storage module is used for storing electric energy generated by the photovoltaic power generation, and the information acquisition module is used for acquiring power generation influence information of the system; the intelligent control module is used for adjusting an energy storage strategy according to the electric energy demand and the power generation influence information, and the inversion output module is used for outputting the electric quantity of the photoelectric conversion module and the energy storage module to the grid connection according to the grid connection electric energy demand;
the photoelectric conversion module generates electricity through photoelectric conversion of a photovoltaic array in the photoelectric conversion module, and the photoelectric conversion of the photovoltaic array meets the following model:
；
wherein,for the actual power of the generation, +.>The loss coefficient is in the range of +.>；/>For rated power of electricity generation, +.>For the actual solar radiation intensity +.>Is the standard radiation intensity; />The temperature conversion coefficient can be set through experiments; />For the actual temperature of the photovoltaic array surface, +.>The surface standard temperature of the photovoltaic array is set;
the information acquisition module comprises a geographic information acquisition unit and a prediction information acquisition unit; the geographic information acquisition unit is used for acquiring geographic position information of the system location, including longitude and latitude information, so that the sunshine duration of the system location can be acquired; the prediction information acquisition unit is used for acquiring temperature prediction information and weather prediction information of a system location;
further, the intelligent control module predicts the electric energy supply in the prediction period and completes the adjustment of the energy storage strategy by combining the electric energy demand in the prediction period, the adjustment of the energy storage strategy is specifically the adjustment of the charging efficiency of the energy storage module, and the specific adjustment mode of the energy storage strategy to the energy storage strategy is as follows:
setting the estimated electric energy storage capacity in the estimated time period asThe electric energy demand electric quantity of non-sunshine time in the prediction period is +.>The minimum safe energy storage electric quantity of the energy storage module is +.>When->At this time, the energy storage strategy is adjusted as follows:
；
wherein,for charging efficiency, +.>The maximum charging efficiency that can be achieved by the energy storage module under the condition of meeting the requirement of the electric energy supply of sunshine time; />The maximum safe charging efficiency of the energy storage module is set;
when (when)At this time, the energy storage strategy is adjusted as follows:
；
wherein,for the real-time energy storage electric quantity in the energy storage module, +.>Ideal charging efficiency for the set energy storage module;
further, the estimated electric energy storage capacityThe method comprises the following steps of:
wherein,for the predicted amount of electric energy supply in the predicted period, < >>The electric energy demand for the sunshine duration in the forecast period;
further, prediction within the prediction periodElectric energy supply amountThe method comprises the following steps of:
；
the predicted period is set to be one day, wherein,for the predicted period of time of day sunshine duration +.>For the time from sunrise, satisfy +.>；/>For a solar radiation model within a prediction period +.>In the weather forecast information, the temperature which changes with the time of day of the forecast period from sunrise;
for the solar radiation model, the following are satisfied:
；
wherein,as a function of the ideal solar radiation variation->Setting a cloud layer shielding coefficient through experiments; />The cloud cover quantity is cloud cover percentage of the current day of the prediction period in the weather prediction information;
function of variation for ideal solar radiationThe method meets the following conditions:
；
wherein,maximum solar radiation amount during the daytime for the predicted period of time;
maximum solar radiation amount for the daytime of the dayThe method comprises the following steps:
；
wherein,for maximum solar radiation in equatorial region, < ->For the latitude of the system location, +.>And->For the amplitude coefficient +.>Is a correction coefficient and satisfies +.>，/>。
Embodiment two:
this embodiment should be understood to include at least all of the features of any one of the foregoing embodiments, and be further modified based thereon;
the embodiment provides a photovoltaic power generation intelligent energy storage system, which is characterized by comprising a photoelectric conversion module, an energy storage module, an information acquisition module, an intelligent control module and an inversion output module;
the photoelectric conversion module is used for carrying out photovoltaic power generation, the energy storage module is used for storing electric energy generated by the photovoltaic power generation, and the information acquisition module is used for acquiring power generation influence information of the system; the intelligent control module is used for adjusting an energy storage strategy according to the electric energy demand and the power generation influence information, and the inversion output module is used for outputting the electric quantity of the photoelectric conversion module and the energy storage module to the grid connection according to the grid connection electric energy demand;
the photovoltaic conversion module comprises a photovoltaic array, an MPPT controller, an array support and a photovoltaic conversion monitoring unit, wherein the photovoltaic array is used for carrying out photoelectric conversion to convert solar light energy into electric energy, the MPPT controller is used for ensuring the maximum output power of the photovoltaic array, and the array support is used for adjusting the direction of the photovoltaic array to enable the photovoltaic array to move along with the position of the sun, so that the photovoltaic conversion efficiency of the photovoltaic panel is improved; the photoelectric conversion monitoring unit is used for monitoring the performance and output power of the photovoltaic panel;
the energy storage module comprises an energy storage battery pack and a battery monitoring unit, wherein the energy storage battery pack is used for storing electric energy, and the battery monitoring unit is used for monitoring the health state and capacity information of the battery pack;
the photovoltaic array photoelectric conversion satisfies the following model:
；
wherein,for the actual power of the generation, +.>The loss coefficient is in the range of +.>；/>For rated power of electricity generation, +.>For the actual solar radiation intensity +.>Is the standard radiation intensity; />The temperature conversion coefficient can be set through experiments; />For the actual temperature of the photovoltaic array surface, +.>The surface standard temperature of the photovoltaic array is set;
the information acquisition module comprises a geographic information acquisition unit and a prediction information acquisition unit; the geographic information acquisition unit is used for acquiring geographic position information of the system location, including longitude and latitude information, so that the sunshine duration of the system location can be acquired; the prediction information acquisition unit is used for acquiring temperature prediction information and weather prediction information of a system location;
the intelligent control module predicts the electric energy supply in the prediction period and completes the adjustment of the energy storage strategy by combining the electric energy demand in the prediction period, the adjustment of the energy storage strategy is specifically the adjustment of the charging efficiency of the energy storage module, and the specific adjustment mode of the energy storage strategy to the energy storage strategy is as follows:
setting the estimated electric energy storage capacity in the estimated time period asThe electric energy demand electric quantity of non-sunshine time in the prediction period is +.>Storing upThe minimum safe energy storage electric quantity of the energy module is +.>When->At this time, the energy storage strategy is adjusted as follows:
；
wherein,for charging efficiency, +.>The maximum charging efficiency that can be achieved by the energy storage module under the condition of meeting the requirement of the electric energy supply of sunshine time; />The maximum safe charging efficiency of the energy storage module is set;
the minimum safe energy storage electric quantity of the energy storage module is used for being used as electric quantity storage of a system in emergency situations, such as under the conditions of failure of a photovoltaic array, insufficient illumination conditions and non-sunshine duration, electric energy is released to grid connection, and energy compensation is achieved; when the estimated electric energy storage electric quantity is smaller than or equal to the electric energy demand electric quantity of the non-sunshine time in the estimated time period, namely the electric quantity stored in the estimated time period is possibly insufficient to complete the electric energy demand of the non-sunshine time, the energy storage module is ensured to adopt the maximum safe charging efficiency at the moment, so that the minimum safe energy storage electric quantity prestored by the energy storage module is ensured to have enough electric quantity supply and be minimized in the non-sunshine time period;
when (when)At this time, the energy storage strategy is adjusted as follows:
；
wherein,for the real-time energy storage electric quantity in the energy storage module, +.>Ideal charging efficiency for the set energy storage module;
when the estimated electric energy storage electric quantity is larger than the electric energy demand electric quantity of non-sunshine time in the estimated time period, the charging efficiency is ensured to be the ideal charging efficiency of the energy storage module as much as possible on the premise of meeting the minimum safe energy storage electric quantity in the energy storage module, so that the transitional charging is avoided, the influence of the too fast charging speed on the service life of the battery is prevented, the service life of the equipment is prolonged, and the waste of energy is avoided;
the estimated electric energy storage capacityThe method comprises the following steps of:
wherein,for the predicted amount of electric energy supply in the predicted period, < >>The electric energy demand for the sunshine duration in the forecast period;
predicted amount of power supply during the predicted periodThe method comprises the following steps of:
；
the predicted period is set to be one day, wherein,for the predicted period of time of day sunshine duration +.>For the time from sunrise, satisfy +.>；/>For a solar radiation model within a prediction period +.>In the weather forecast information, the temperature which changes with the time of day of the forecast period from sunrise;
for the solar radiation model, the following are satisfied:
；
wherein,as a function of the ideal solar radiation variation->Setting a cloud layer shielding coefficient through experiments; />The cloud cover quantity is cloud cover percentage of the current day of the prediction period in the weather prediction information;
function of variation for ideal solar radiationThe method meets the following conditions:
；
wherein,for prediction timeMaximum solar radiation amount in daytime on the same day;
maximum solar radiation amount for the daytime of the dayThe method comprises the following steps:
；
wherein,for maximum solar radiation in equatorial region, < ->For the latitude of the system location, +.>And->For the amplitude coefficient +.>Is a correction coefficient and satisfies +.>，/>；
As shown in fig. 2, the embodiment provides an intelligent energy storage method for photovoltaic power generation, which includes the following steps:
s1: setting a prediction period, and acquiring electric energy demand and electric quantity, temperature prediction information and weather prediction information in the prediction period;
s2: acquiring the geographic position of the photovoltaic array, and determining the sunshine duration of the place of the photovoltaic array according to the geographic position and the date;
s3: acquiring solar radiation variation in an ideal state according to the geographic position and the sunlight duration of the photovoltaic array;
s4: establishing a solar radiation model by combining cloud cover shielding amount in weather prediction information;
s5: calculating a predicted electric energy supply amount in a predicted period according to the solar radiation model and the temperature prediction information;
s6: acquiring the predicted electric energy storage electric quantity in the predicted period by combining the electric energy demand of the sunshine time in the predicted period;
s7: when the estimated electric energy storage electric quantity is smaller than or equal to the electric energy demand electric quantity of non-sunshine time in the estimated time period, controlling the charging efficiency of the energy storage module to be the maximum charging efficiency which can be achieved currently, and being smaller than the maximum safe charging efficiency;
s8: when the estimated electric energy storage electric quantity is larger than the electric energy demand electric quantity of non-sunshine time in the estimated time period and the real-time energy storage electric quantity in the energy storage module is smaller than the minimum safe energy storage electric quantity, controlling the charging efficiency of the energy storage module to be the maximum charging efficiency which can be achieved currently and smaller than the maximum safe charging efficiency;
s9: when the estimated electric energy storage electric quantity is larger than the electric energy demand electric quantity of non-sunshine time in the estimated time period and the real-time energy storage electric quantity in the energy storage module is larger than the minimum safe energy storage electric quantity, the charging efficiency of the energy storage module is controlled to be the maximum charging efficiency which can be achieved currently and is smaller than or equal to the ideal charging efficiency.
The foregoing disclosure is only a preferred embodiment of the present invention and is not intended to limit the scope of the invention, so that all equivalent technical changes made by applying the description of the present invention and the accompanying drawings are included in the scope of the present invention, and in addition, elements in the present invention can be updated as the technology develops.

Claims (4)

1. The intelligent energy storage system for photovoltaic power generation is characterized by comprising a photoelectric conversion module, an energy storage module, an information acquisition module, an intelligent control module and an inversion output module;
the photoelectric conversion module is used for carrying out photovoltaic power generation, the energy storage module is used for storing electric energy generated by the photovoltaic power generation, and the information acquisition module is used for acquiring power generation influence information of the system; the intelligent control module is used for adjusting an energy storage strategy according to the electric energy demand and the power generation influence information, and the inversion output module is used for outputting the electric quantity of the photoelectric conversion module and the energy storage module to the grid connection according to the grid connection electric energy demand;
the photoelectric conversion module generates electricity through photoelectric conversion of a photovoltaic array in the photoelectric conversion module, and the photoelectric conversion of the photovoltaic array meets the following model:
；
wherein,for the actual power of the generation, +.>The loss coefficient is in the range of +.>；/>For rated power of electricity generation, +.>For the actual solar radiation intensity +.>Is the standard radiation intensity; />The temperature conversion coefficient can be set through experiments; />For the actual temperature of the photovoltaic array surface, +.>For photovoltaic array surface markingQuasi-temperature;
the information acquisition module comprises a geographic information acquisition unit and a prediction information acquisition unit; the geographic information acquisition unit is used for acquiring geographic position information of the system location, including longitude and latitude information, so that the sunshine duration of the system location can be acquired; the prediction information acquisition unit is used for acquiring temperature prediction information and weather prediction information of the system location.
2. The intelligent energy storage system for photovoltaic power generation according to claim 1, wherein the intelligent control module predicts the supply of electric energy in a prediction period and completes adjustment of an energy storage strategy in combination with the electric energy demand of the prediction period, the adjustment of the energy storage strategy is specifically adjustment of the charging efficiency of the energy storage module, and the energy storage strategy is specifically adjusted in the following manner:
setting the estimated electric energy storage capacity in the estimated time period asThe electric energy demand and the electric quantity of the non-sunshine time in the prediction period areThe minimum safe energy storage electric quantity of the energy storage module is +.>When->At this time, the energy storage strategy is adjusted as follows:
；
wherein,for charging efficiency, +.>The maximum charging efficiency that can be achieved by the energy storage module under the condition of meeting the requirement of the electric energy supply of sunshine time; />The maximum safe charging efficiency of the energy storage module is set;
when (when)At this time, the energy storage strategy is adjusted as follows:
；
wherein,for the real-time energy storage electric quantity in the energy storage module, +.>And the ideal charging efficiency of the energy storage module is set.
3. The intelligent photovoltaic power generation energy storage system of claim 2, wherein the predicted amount of stored electrical energy is the estimated amount of stored electrical energyThe method comprises the following steps of:
wherein,for the predicted amount of electric energy supply in the predicted period, < >>To predict the amount of electrical energy demand for solar time during a period of time.
4. A photovoltaic power generation intelligent energy storage system according to claim 3, wherein the predicted amount of power supply during the predicted period of timeThe method comprises the following steps of:
；
the predicted period is set to be one day, wherein,for the predicted period of time of day sunshine duration +.>For the time of sunrise start, satisfy；/>For a solar radiation model within a prediction period +.>In the weather forecast information, the temperature which changes with the time of day of the forecast period from sunrise;
for the solar radiation model, the following are satisfied:
；
wherein,as a function of the ideal solar radiation variation->Setting a cloud layer shielding coefficient through experiments; />The cloud cover quantity is cloud cover percentage of the current day of the prediction period in the weather prediction information;
function of variation for ideal solar radiationThe method meets the following conditions:
；
wherein,maximum solar radiation amount during the daytime for the predicted period of time;
maximum solar radiation amount for the daytime of the dayThe method comprises the following steps:
；
wherein,for maximum solar radiation in equatorial region, < ->For the latitude of the system location, +.>And->For the amplitude coefficient +.>Is a correction coefficient and satisfies +.>，/>。
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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117973239A (en) * 2024-04-02 2024-05-03 厦门中构新材料科技股份有限公司 Photovoltaic module power generation efficiency simulation device and method based on artificial intelligence

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104218875A (en) * 2014-09-10 2014-12-17 中铁第一勘察设计院集团有限公司 Independent photovoltaic power generation railway power supply control system and control method thereof
KR20190100800A (en) * 2018-02-21 2019-08-29 엘에스산전 주식회사 a Photovoltaic system
CN111884585A (en) * 2020-07-20 2020-11-03 深圳库博能源科技有限公司 Photovoltaic power generation intelligent energy storage system
CN116720631A (en) * 2023-08-09 2023-09-08 深圳市洛丁光电有限公司 Distributed photovoltaic power generation electric quantity analysis and prediction method, system and storage medium

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104218875A (en) * 2014-09-10 2014-12-17 中铁第一勘察设计院集团有限公司 Independent photovoltaic power generation railway power supply control system and control method thereof
KR20190100800A (en) * 2018-02-21 2019-08-29 엘에스산전 주식회사 a Photovoltaic system
CN111884585A (en) * 2020-07-20 2020-11-03 深圳库博能源科技有限公司 Photovoltaic power generation intelligent energy storage system
CN116720631A (en) * 2023-08-09 2023-09-08 深圳市洛丁光电有限公司 Distributed photovoltaic power generation electric quantity analysis and prediction method, system and storage medium

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117973239A (en) * 2024-04-02 2024-05-03 厦门中构新材料科技股份有限公司 Photovoltaic module power generation efficiency simulation device and method based on artificial intelligence

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