Optical storage cooperative management platform system

Abstract

The present disclosure relates to the field of new energy technology, and provides a light storage collaborative management platform system, which comprises a data access module, a photovoltaic management module forming a group of photovoltaic management graphical interfaces, including a photovoltaic power station overview interface with a jump path, a photovoltaic power station operation dashboard interface, and an inverter monitoring interface; an energy storage management module forming a group of energy storage management graphical interfaces, including an energy storage power station overview interface with a jump path, an energy storage power station operation dashboard interface, an energy storage power station topology interface, and an energy storage cabinet operation information interface. The prediction strategy module comprises a meteorological fluctuation compensation prediction unit, which determines that at least one of the photovoltaic power stations has a fluctuation in power generation at the future time in response to predicted irradiation data corresponding to predicted meteorological data, and determines a predicted power compensation amount based on a fluctuation deviation amount. The present disclosure realizes visual management of full information of a light storage system, and predicts photovoltaic power generation fluctuation and compensates based on local measured meteorological data, thereby improving system stability.

Description

Technical Field

[0001] This disclosure relates to the field of new energy technology, and in particular to a photovoltaic-storage collaborative management platform system. Background Technology

[0002] With the large-scale grid-connected application of distributed photovoltaic (PV) and energy storage systems, PV-storage systems have become the mainstream form of grid-connected new energy power generation due to the advantages of on-site PV power generation and energy storage for smoothing out fluctuations. Currently, the industry has gradually built PV-storage management systems, which can realize the collection and simple monitoring of basic PV and energy storage operation data. However, existing PV-storage management systems still have obvious technical shortcomings and are difficult to adapt to the refined operation and maintenance and collaborative scheduling needs of clustered PV-storage power plants.

[0003] On the one hand, existing photovoltaic-storage collaborative management platforms lack intuitive operation and maintenance control. Current conventional management platforms only display photovoltaic and energy storage operation data in a scattered manner, failing to provide a macro-level overview of the overall operation status of photovoltaic and energy storage power plants; at the same time, the internal interfaces of the platforms are independent of each other. Operation and maintenance personnel cannot quickly drill down from the macro-level site overview to the underlying equipment such as individual inverters, individual energy storage cabinets, and battery clusters, resulting in time-consuming equipment fault location and low operation and maintenance efficiency.

[0004] Therefore, the existing photovoltaic and energy storage management systems suffer from problems such as insufficient visualization management capabilities, which have become technical issues that the industry urgently needs to address. Summary of the Invention

[0005] In view of the shortcomings of the prior art described above, the purpose of this disclosure is to provide a photovoltaic-storage collaborative management platform system to solve the problems in the related technologies.

[0006] The first aspect of this disclosure provides a photovoltaic-storage collaborative management platform system for managing a photovoltaic power generation system and an energy storage system. The photovoltaic power generation system includes various photovoltaic power stations, each including a photovoltaic panel array and an inverter. The energy storage system includes various energy storage power stations, each including one or more energy storage cabinets containing a battery stack composed of multiple battery clusters. The photovoltaic-storage collaborative management platform system includes: a data access module for collecting and updating first operating data of the photovoltaic power generation system, second operating data of the energy storage system, and meteorological data of the photovoltaic power generation system's distribution area; and a photovoltaic management module for forming a set of photovoltaic management graphical interfaces based on the first operating data for display on a user terminal connected to the photovoltaic-storage collaborative management platform system, including: a photovoltaic power station overview interface for displaying an overview of each photovoltaic power station on an electronic map, a photovoltaic power station operation dashboard interface for displaying operating information of each photovoltaic power station, and an inverter monitoring interface for displaying operating information of the inverters in the photovoltaic power stations; wherein a jump path is formed between the photovoltaic power station overview interface, the photovoltaic power station dashboard interface, and the inverter monitoring interface. The energy storage management module is used to form a set of energy storage management graphical interfaces for display on the user terminal based on the second operating data. These interfaces include: an energy storage power station overview interface for displaying an overview of each energy storage power station on an electronic map; an energy storage power station operation dashboard interface for displaying the operating information of each energy storage power station; an energy storage power station topology interface for displaying the topology information of each energy storage cabinet in the energy storage power station; and an energy storage cabinet operation information interface for displaying the operating information of the energy storage cabinets. A jump path is formed between the energy storage power station overview interface, the energy storage power station operation dashboard interface, the energy storage power station topology interface, and the energy storage cabinet operation information interface. A prediction strategy module, coupled to the data access module, includes: a meteorological fluctuation compensation prediction unit, used to predict future meteorological data based on the actual meteorological data of each photovoltaic power station; in response to determining that at least one photovoltaic power station experiences power generation fluctuations in the future time based on the predicted irradiance data corresponding to the predicted meteorological data; and in response to determining that the fluctuations affect the load power supply of the photovoltaic power station, determining the compensation output object in the future time and the predicted power compensation amount corresponding to the power generation deviation of the fluctuations.

[0007] In an embodiment of the first aspect, the photovoltaic power station overview interface displays representative icon controls for each photovoltaic power station on an electronic map. The representative icon controls allow user operation to display the current operating thumbnail information of the represented photovoltaic power station in an adjacent thumbnail information area. The current operating thumbnail information includes at least one of the following: the photovoltaic power station's daily power generation, current power, and daily revenue.

[0008] In the first aspect of the embodiment, the photovoltaic power station operation dashboard interface displays information including: power generation data and revenue data over a preset time period; and inverter thumbnail cards for each inverter in the photovoltaic power station, wherein the inverter thumbnail cards display some key operating information of the inverter, including at least one of: inverter identifier, equipment model, operating status, peak power, rated AC power, real-time power generation, and daily power generation.

[0009] In an embodiment of the first aspect, each inverter thumbnail card further includes a jump control for jumping to the inverter monitoring interface of the corresponding inverter; the inverter monitoring interface displays detailed operating information of the corresponding inverter, including at least one of the following: inverter identifier, manufacturer, equipment model, component peak power, rated AC power, grid type, annual power generation hours, power generation efficiency, power generation trend data, current power generation, maximum power generation on the day, DC side detection information, AC side detection information, and power generation / revenue.

[0010] In an embodiment of the first aspect, the energy storage power station overview interface displays representative icon controls for each of the energy storage power stations on an electronic map. The representative icon controls allow user operation to display the current operating thumbnail information of the represented energy storage power station in an adjacent thumbnail information area. The current operating thumbnail information of the energy storage power station includes at least one of the following: the energy storage power station's daily charge / discharge amount, current power, and daily revenue.

[0011] In the first aspect of the embodiment, the information displayed on the energy storage power station operation dashboard interface includes at least one of: charging / discharging statistics, revenue statistics, and charging / discharging power statistics; a thumbnail card for each energy storage cabinet in the energy storage power station; a jump control for jumping to the energy storage power station topology interface; the thumbnail card for each energy storage cabinet includes a jump control that allows user operation to jump to the energy storage cabinet operation information interface; and / or, the energy storage power station topology interface includes: a topology diagram of the energy storage power station and its constituent energy storage cabinets, and a topology diagram of the battery stacks composed of multiple battery clusters contained in each energy storage cabinet, wherein the battery stacks include multiple battery clusters connected in parallel; the topology diagram corresponding to each The information displayed by each energy storage cabinet includes at least one of the following: rechargeable capacity, dischargeable capacity, cumulative charging capacity, cumulative discharging capacity, current, voltage, power, and remaining capacity of the battery stack in the energy storage cabinet; the information displayed by each battery cluster in the topology diagram includes at least one of the following: charging / discharging statistics, revenue statistics, charging / remaining capacity, health status, highest voltage, lowest voltage, operating status, charging / discharging status, highest temperature, and lowest temperature; and / or, the information displayed on the energy storage cabinet operation information interface includes: energy storage cabinet manufacturer, equipment model, battery manufacturer, installation location, rated capacity, real-time power, remaining capacity, peak shaving and valley filling power curve, daily charging capacity, and daily discharging capacity. The system includes at least one of the following: power consumption, cumulative charging amount, cumulative discharging amount, revenue statistics, a PCS (Power Control System) abbreviated card for monitoring the energy storage converter of the corresponding energy storage cabinet, and an EMS (Energy Management System) abbreviated card for monitoring the battery stack of the corresponding energy storage cabinet; wherein the PCS abbreviated card and the EMS abbreviated card respectively include jump controls for switching to the energy storage converter monitoring interface and the energy management system monitoring interface; wherein the PCS abbreviated card displays some key operating information of the corresponding energy storage converter, including at least one of: conversion efficiency, battery voltage, temperature, alarm status, and fault status; the information displayed on the energy storage converter monitoring interface includes: equipment status, AC side real-time data, and DC side real-time data. The fault state is one of the equipment states; the EMS abbreviation card displays some key operating information of the battery stack, including at least one of the following: the highest voltage of a single cell, the lowest voltage of a single cell, the highest temperature of a single cell, and the lowest temperature of a single cell; the information displayed on the energy management system monitoring interface includes at least one of the following: the real-time operating status of the battery stack, voltage, current, power, remaining power, health status, dischargeable capacity, rechargeable capacity, single discharge capacity, single charge capacity, cumulative discharge capacity, cumulative charge capacity, minimum temperature of a single cell, maximum temperature of a single cell, minimum voltage of a single cell, maximum voltage of a single cell, minimum cluster voltage, maximum cluster voltage, maximum remaining power of a cluster, and minimum remaining power of a cluster.

[0012] In the first aspect of the embodiment, the information displayed on the energy management system monitoring interface further includes: a jump control for jumping to the energy storage battery cluster monitoring interface; the information displayed on the energy storage battery cluster monitoring interface includes: battery cluster operation information, including at least one of the following: number of managed battery cells, real-time operating status, charge / discharge status, number of charging cycles, number of discharging cycles, rechargeable capacity, average temperature of individual cells, maximum temperature of individual cells, minimum temperature of individual cells, average voltage of individual cells, maximum voltage of individual cells, minimum voltage of individual cells, average remaining capacity of individual cells, maximum remaining capacity of individual cells, minimum remaining capacity of individual cells, cumulative charging capacity, cumulative discharging capacity, discharging capacity, current, voltage, power, group negative electrode insulation resistance, group positive electrode insulation resistance, remaining capacity of battery cluster, and battery cluster health status; a range of voltage and temperature consistency values ​​that can be set between individual cells; and voltage and temperature data of individual cells, including individual cell voltage, average voltage difference, voltage consistency value, individual cell temperature, average temperature difference, and temperature consistency value.

[0013] In the first aspect of the embodiment, the meteorological data includes: local sky images captured by a full-sky imager located at the photovoltaic power station, and local irradiance values ​​measured by an irradiance meter located at the photovoltaic power station; the meteorological fluctuation compensation prediction unit is configured to perform the following process, including: identifying cloud clusters by extracting image features from consecutive frames of the sky images in the meteorological data, obtaining motion vector data of each cloud cluster using optical flow, predicting the shading time of each cloud cluster arriving at the shading area above the photovoltaic array based on the motion vector data, and determining the predicted shading cloud amount based on the set of shading cloud clusters in the shading area at future time; and calculating the amount of cloud clusters in the shading area at future time based on the grayscale values ​​of the clouds in the sky images using a cloud thickness optical mapping model pre-calibrated to characterize the mapping relationship between grayscale values ​​and cloud thickness values. The system calculates the predicted average cloud thickness of the obstructing cloud clusters; obtains a local irradiance attenuation coefficient based on the ratio of the currently collected local irradiance value to the clear-sky reference irradiance value; wherein the clear-sky reference irradiance value is obtained based on the local irradiance value collected by the irradiance meter under a clear-sky reference weather scenario; predicts the predicted local irradiance value at the future time based on the predicted average cloud thickness of the obstructing cloud clusters, the predicted cloud cover, and the local irradiance attenuation coefficient; obtains time-varying data of the corresponding predicted power generation based on the update of the predicted local irradiance value; determines the predicted power compensation amount corresponding to the power generation deviation of the energy storage system during fluctuations in response to the time-varying data of the predicted power generation, based on the determination that fluctuation conditions are met; and determines a compensation strategy for obtaining the predicted power compensation amount from the energy storage system and / or the power grid at the future time.

[0014] In an embodiment of the first aspect, the compensation strategy for determining the predicted power compensation amount obtained from the energy storage system and / or the power grid at the future time includes one of the following: 1) determining whether the predicted power compensation amount is within the power grid's cost-free compensation power range; if so, the power grid independently compensates the predicted power compensation amount; if not, the power grid compensates with the maximum cost-free compensation power, and the energy storage system discharges to make up to the predicted power compensation amount; 2) determining the cloud distribution type based on the distribution of the cloud clusters, including a first type of continuous cloud clusters and a second type of scattered cloud clusters; in response to the cloud distribution type being the first type, the energy storage system is preferentially used to compensate for the real-time power generation deviation according to the predicted power compensation amount; in response to the cloud distribution type being the second type, the power grid is preferentially used to compensate for the real-time power generation deviation according to the predicted power compensation amount; if the predicted power compensation amount exceeds the power grid's cost-free compensation power range, the power grid compensates with the maximum cost-free compensation power, and the energy storage system discharges to make up to the predicted power compensation amount.

[0015] In the first aspect of the embodiment, the energy storage cabinet operation information interface further includes a setting card for the energy storage strategy mode of the energy storage cabinet, and has a switching control for accepting operations to select the operation mode; the operation mode includes at least two of the following: automatic mode, manual mode, and agent mode; and / or, the information displayed on the energy storage cabinet operation information interface further includes: a fire protection thumbnail card for the fire protection system under the energy storage cabinet, the information displayed on the fire protection thumbnail card includes at least one of the following: water immersion, smoke detection, and intrusion; the fire protection thumbnail card further includes a jump control for jumping to the fire protection system monitoring interface; and / or, the energy storage cabinet operation information interface further includes a temperature control thumbnail information card, the information displayed on the temperature thumbnail information card includes: the temperature and humidity information of the energy storage cabinet.

[0016] As described above, this disclosure relates to the field of new energy technology and provides a photovoltaic-storage collaborative management platform system. The system includes: a data access module; a photovoltaic management module forming a set of photovoltaic management graphical interfaces, including: a photovoltaic power station overview interface with jump paths, a photovoltaic power station operation dashboard interface, and an inverter monitoring interface; and an energy storage management module forming a set of energy storage management graphical interfaces, including: an energy storage power station overview interface with jump paths, an energy storage power station operation dashboard interface, an energy storage power station topology interface, and an energy storage cabinet operation information interface. A prediction strategy module includes a meteorological fluctuation compensation prediction unit, which, in response to determining that at least one of the photovoltaic power stations will experience power generation fluctuations in the future time based on predicted irradiance data corresponding to predicted meteorological data, determines the predicted power compensation amount based on the fluctuation deviation. This achieves visualized management of all information in the photovoltaic-storage system and predicts and compensates for photovoltaic power generation fluctuations based on locally measured meteorological data, thereby improving system stability. Attached Figure Description

[0017] Figure 1A schematic diagram of the modules of a photovoltaic-storage collaborative management platform system is shown in one embodiment of this disclosure.

[0018] Figure 2 A schematic diagram showing an overview interface of a photovoltaic power plant in one embodiment of this disclosure.

[0019] Figure 3 A schematic diagram showing the operation dashboard interface of a photovoltaic power station in one embodiment of this disclosure.

[0020] Figure 4 A schematic diagram of an inverter monitoring interface is shown in one embodiment of this disclosure.

[0021] Figure 5 A schematic diagram showing an overview interface of an energy storage power station in one embodiment of this disclosure.

[0022] Figure 6 A schematic diagram showing the operation dashboard interface of an energy storage power station in one embodiment of this disclosure.

[0023] Figure 7 A schematic diagram showing the topology interface of an energy storage power station in one embodiment of this disclosure is provided.

[0024] Figure 8 A schematic diagram showing the operation information interface of the energy storage cabinet in one embodiment of this disclosure.

[0025] Figure 9 A schematic diagram showing the monitoring interface of an energy storage converter in one embodiment of this disclosure is provided.

[0026] Figure 10 A schematic diagram illustrating a method for compensating photovoltaic power generation based on weather forecasts in one embodiment of this disclosure is shown.

[0027] Figure 11 A schematic diagram illustrating the photovoltaic power generation compensation process based on weather forecasts in another specific embodiment of this disclosure is shown.

[0028] Figure 12 A diagram used to illustrate the sun's altitude and azimuth.

[0029] Figure 13 A schematic diagram illustrating the calculation principle of the sun's orientation relative to a photovoltaic panel.

[0030] Figure 14 A schematic diagram of the structure of a computer device according to an embodiment of the present disclosure is shown. Detailed Implementation

[0031] The following specific examples illustrate the implementation of this disclosure. Those skilled in the art can easily understand other advantages and effects of this disclosure from the information disclosed herein. This disclosure can also be implemented or applied through other different specific embodiments, and various details in this disclosure can be modified or changed according to different viewpoints and application modules without departing from the spirit of this disclosure. It should be noted that, unless otherwise specified, the embodiments and features in the embodiments of this disclosure can be combined with each other.

[0032] The embodiments of this disclosure will now be described in detail with reference to the accompanying drawings, so that those skilled in the art to which this disclosure pertains can readily implement it. This disclosure may be embodied in many different forms and is not limited to the embodiments described herein.

[0033] In this disclosure, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic represented in connection with that embodiment or example is included in at least one embodiment or example of this disclosure. Furthermore, the specific features, structures, materials, or characteristics represented may be combined in any suitable manner in any one or a group of embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples represented in this disclosure, as well as the features of those different embodiments or examples.

[0034] Furthermore, the terms "first" and "second" are used for illustrative purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the representation of this disclosure, "a set" means two or more, unless otherwise explicitly specified.

[0035] For the purpose of clarity, devices unrelated to the description are omitted, and the same or similar components throughout the specification are given the same reference numerals.

[0036] Throughout this specification, when it is said that a device is "connected" to another device, this includes not only "direct connection" but also "indirect connection" by placing other components in between. Furthermore, when it is said that a device "comprises" a certain constituent element, unless otherwise stated otherwise, this does not exclude other constituent elements, but rather implies that other constituent elements may be included.

[0037] While the terms first, second, etc., are used in some examples herein to refer to various elements, these elements should not be limited by these terms. These terms are used only to distinguish one element from another. For example, first interface and second interface, etc., are used. Furthermore, as used herein, the singular forms “a,” “an,” and “the” are intended to also include the plural forms unless the context indicates otherwise. It should be further understood that the terms “comprising,” “including,” indicate the presence of the stated feature, step, operation, element, module, item, kind, and / or group, but do not exclude the presence, occurrence, or addition of one or more other features, steps, operations, elements, modules, items, kinds, and / or groups. The terms “or” and “and / or” as used herein are interpreted as inclusive, or mean any one or any combination thereof. Thus, “A, B, or C” or “A, B, and / or C” means “any one of: A; B; C; A and B; A and C; B and C; A, B, and C.” Exceptions to this definition will only occur if the combination of elements, functions, steps, or operations is inherently mutually exclusive in some way.

[0038] The technical terms used herein are for reference only to specific embodiments and are not intended to limit the scope of this disclosure. The singular form used herein includes the plural form unless the statement explicitly indicates otherwise. The word "comprising" as used in this specification means to specify a particular characteristic, region, integer, step, operation, element, and / or component, and does not exclude the presence or addition of other characteristics, regions, integers, steps, operations, elements, and / or components.

[0039] Although not explicitly defined, all terms, including technical and scientific terms used herein, shall have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure pertains. Terms defined in commonly used dictionaries shall be further interpreted as having a meaning consistent with the relevant technical literature and the message of the present disclosure, and shall not be over-interpreted as having an ideal or overly formulaic meaning unless otherwise defined.

[0040] With the large-scale grid-connected application of distributed photovoltaic (PV) and energy storage systems, PV-storage systems have become the mainstream form of grid-connected new energy power generation due to the advantages of on-site PV power generation and energy storage for smoothing out fluctuations. Currently, the industry has gradually built PV-storage management systems, which can realize the collection and simple monitoring of basic PV and energy storage operation data. However, existing PV-storage management systems still have obvious technical shortcomings and are difficult to adapt to the refined operation and maintenance and collaborative scheduling needs of clustered PV-storage power plants.

[0041] Existing photovoltaic-energy storage collaborative management platforms lack intuitive operation and maintenance control. Current conventional management platforms only display photovoltaic and energy storage operation data in a scattered manner, failing to provide a macro-level overview of the overall operation status of photovoltaic and energy storage power plants. Furthermore, the internal interfaces of these platforms are independent of each other. Maintenance personnel cannot quickly drill down from the macro-level site overview to individual inverters, energy storage cabinets, battery clusters, and other lower-level devices, resulting in time-consuming equipment fault location and low operation and maintenance efficiency.

[0042] In view of this, this disclosure provides a photovoltaic-storage collaborative management platform system. On the one hand, it can form a set of photovoltaic management graphical interfaces and a set of energy storage management graphical interfaces that are visually accessible to users and have a jump relationship, thereby solving the problem of management efficiency of all data of the photovoltaic-storage system. On the other hand, it can also provide compensation strategies when photovoltaic power generation fluctuates due to meteorological reasons in the photovoltaic-storage collaborative cooperation scenario through a strategy prediction model.

[0043] like Figure 1 The diagram shows a schematic of the modules of a photoelectric storage collaborative management platform system in one embodiment of this disclosure.

[0044] The photovoltaic energy storage management platform system 100 is used to manage the photovoltaic energy storage system 200. The photovoltaic energy storage system 200 includes a photovoltaic power generation system 210 and an energy storage system 220. In some embodiments, the photovoltaic power generation system 210 includes various photovoltaic power stations 211. The photovoltaic power station 211 includes a photovoltaic panel array 2111 and an inverter 2112. The photovoltaic panel array 2111 is an array of multiple photovoltaic panels. The photovoltaic power generation principle is based on the photovoltaic effect of semiconductors. When sunlight shines on the surface of a photovoltaic cell, the photon energy excites the silicon material inside the cell to generate electron-hole pairs. Under the action of the built-in electric field of the cell's PN junction, electrons and holes undergo directional separation and migration, forming a stable DC potential difference between the positive and negative electrodes of the module, and outputting DC power. It can be understood that the biggest factor in photovoltaic power generation is the intensity of sunlight. The higher the intensity of sunlight, the greater the DC output power of the photovoltaic panel array 2111 (because the current is greater). Conversely, if clouds block the light or the sunlight is attenuated, it will directly cause a sharp drop in DC output power. The photovoltaic array 2111 outputs DC power, which cannot be directly connected to the AC power grid. The inverter 2112 performs the function of converting DC to AC power, boosting and inverting the unstable DC power from the photovoltaic side into AC power with the same frequency and phase as the power grid.

[0045] In some embodiments, the energy storage system 220 includes various energy storage stations 221. Each energy storage station 221 includes one or more energy storage cabinets 2211, each cabinet containing a battery stack 22111 composed of multiple battery clusters 221111, each cluster containing multiple individual batteries connected in series. Each energy storage station 221 may also be equipped with an energy storage converter 22112 (PCS). The PCS enables bidirectional AC-DC inversion and can be used for charging / discharging the battery stacks 22111. The energy storage system 220 may be equipped with an energy management system (EMS), which can be located in each energy storage station 221 to monitor the operating information of each battery stack 22111 in each energy storage cabinet 2211 of each energy storage station 221 (not just the battery stack 22111 as a whole, but also monitoring of individual batteries), to prevent abnormal events such as overcharging and over-discharging. Furthermore, the energy storage system 220 may also be configured with a battery cluster management unit (BCMU) for each battery cluster 221111 in each energy storage cabinet 2211 of each energy storage power station 221 (not just for the battery cluster 22111 as a whole, but also for monitoring individual cells) to prevent abnormal events such as overcharging and over-discharging. It is understood that the battery status information obtained by EMS, BCMU, etc., can come from the data collected by the battery management unit (BMU) of the cell, including but not limited to charge / discharge status, voltage, current, remaining charge (SOC), and state of health (SOH).

[0046] In some embodiments, the photovoltaic power stations of the photovoltaic power generation system 210 and the energy storage power stations 221 of the energy storage system 220 are connected via a power transmission network 300. The power transmission network 300 may be a public power grid or a private power grid.

[0047] The photovoltaic-storage collaborative management platform system 100 includes a data access module 110, a photovoltaic management module 120, an energy storage management module 130, and a prediction strategy module 140.

[0048] The data access module 110 is used to collect and update the first operating data of the photovoltaic power generation system 210, the second operating data of the energy storage system 220, and the meteorological data of the distribution area of ​​the photovoltaic power generation system 210.

[0049] In some embodiments, the first operating data includes, but is not limited to, basic information, operating status, power generation, rated power, peak power, and current / cumulative power generation of the photovoltaic power station as a whole and its included inverters 2112. In some embodiments, the second operating data includes, but is not limited to, information such as the charging / discharging power, charging / discharging capacity, SOC, and SOH of the energy storage power station 221 as a whole and its included energy storage cabinets 2211, and even the PCS of the energy storage cabinet 2211, battery stacks 22111, etc.

[0050] In some embodiments, the meteorological data can be collected by a single meteorological monitoring instrument or a combination of data collected by multiple meteorological monitoring instruments. In some examples, the meteorological monitoring instrument may include an irradiance meter, which measures the irradiance value (or irradiance) and cumulative irradiance (e.g., daily, weekly, monthly) of the environment. Optionally, it may also include meteorological measurement components such as an anemometer, temperature, and / or humidity sensors to measure wind speed, temperature, and / or humidity data of the environment. In some examples, the meteorological monitoring instrument may include a full-sky imager, a high-precision device for continuous automatic monitoring of the entire daytime sky, operating based on the principle of visible light scattering. The full-sky imager has a fisheye lens for imaging the sky to obtain sky images. Because clouds have different image characteristics from the sky (e.g., different colors of white and blue, and specific shape characteristics of clouds), cloud clusters can be distinguished from the blue sky by analyzing the image features, and then some parameters of the clouds (e.g., cloud thickness, cloud cover) can be accurately calculated based on the image features.

[0051] The photovoltaic-storage collaborative management platform system 100 can perform data statistics based on the first and second operating data, and can generate display data for the graphical user interface (GUI) of the photovoltaic power generation system 210 and the energy storage system 220, which can be provided to the user terminal 400 connected to the communication for the user to view.

[0052] The photovoltaic management module 120 is used to generate a set of photovoltaic management graphical interfaces based on the first operating data for display on the user terminal connected to the photovoltaic-storage collaborative management platform system. The set of photovoltaic management graphical interfaces includes a photovoltaic power plant overview interface, a photovoltaic power plant operation dashboard interface, and an inverter 2112 monitoring interface, etc.

[0053] like Figure 2 The diagram shown illustrates a schematic of a photovoltaic power plant overview interface in one embodiment of this disclosure.

[0054] The photovoltaic power station overview interface is used to display overview information of each photovoltaic power station on an electronic map. For details, please refer to... Figure 2As shown, the electronic map displays the various photovoltaic power stations marked with their corresponding actual geographical locations.

[0055] In some embodiments, the photovoltaic power plant overview interface displays representative icon controls for each photovoltaic power plant on an electronic map. These representative icon controls allow user interaction to display current operational thumbnail information of the represented photovoltaic power plant in an adjacent thumbnail information area, facilitating quick selection and understanding of key information for each photovoltaic power plant. Exemplarily, the representative icon control for a photovoltaic power plant can be drawn as a graphic distinct from surrounding facility icons to facilitate user location. Exemplarily, the user interaction includes, but is not limited to, clicking, hovering, or long-pressing the representative icon control. Exemplarily, the current operational thumbnail information can be displayed in a pop-up window adjacent to the representative icon control. Exemplarily, if photovoltaic power plant A is currently selected, the current operational thumbnail information may include key information about the photovoltaic power plant that the user is interested in, including at least one of the following: daily power generation, current power, and daily revenue. Optionally, the current operational thumbnail information may also include the name / ID of the photovoltaic power plant, total installed capacity, etc. For example, the pop-up window may also provide a jump control for jumping to the photovoltaic power station operation dashboard interface corresponding to the photovoltaic power station, such as text or graphic icons like "View Details>".

[0056] In some embodiments, the information displayed on the photovoltaic power station overview interface may also include at least one of the following key information: the number of photovoltaic power stations, total power station capacity, cumulative power generation, cumulative revenue, current power generation, daily power generation, power generation curve of the past 24 hours, and monthly power generation, so that users can obtain key overview information of the entire photovoltaic system.

[0057] like Figure 3 The diagram shown illustrates a photovoltaic power plant operation dashboard interface in one embodiment of this disclosure.

[0058] The photovoltaic power plant operation dashboard interface is used to display detailed operation information for each photovoltaic power plant. In some embodiments, the information displayed on the photovoltaic power plant operation dashboard interface includes: power generation data and revenue data over a preset time period; and inverter thumbnail cards for each inverter under the photovoltaic power plant.

[0059] In some examples, the photovoltaic power plant operation dashboard interface displays information including, but not limited to, power generation statistics, power generation trends, revenue statistics, and equipment monitoring information. For example, the power generation statistics can be displayed in a power generation statistics card (or form), and may include at least one of the following: daily power generation, monthly power generation, and annual power generation. Exemplarily, the power generation statistics may also include comparison data between the daily, monthly, and annual power generation and the power generation of the same period (e.g., the previous day / month / year), such as an increase of 12% represented as "+12%"; a decrease of 10% represented as "-10%". Exemplarily, the power generation statistics may also include a power generation trend chart for a previously preset period, such as a power generation trend chart for the most recent 30 days, which may be a bar chart, line chart, or curve chart.

[0060] In some examples, the power generation trend can be displayed in a power generation card (or window), which may include at least one of the following: current power generation (i.e., power generation at the current moment), current maximum power generation, etc. Optionally, a power generation trend chart for a previously preset period of time can also be displayed, such as a power generation trend chart for the past 24 hours, which may be a bar chart, line chart, or curve chart, etc.

[0061] In some examples, the revenue statistics can be displayed in a revenue statistics card (or form), and the revenue statistics include at least one of daily revenue, monthly revenue, and annual revenue. For example, the revenue statistics may also include comparison data between daily, monthly, and annual revenue and revenue within the same period (e.g., the previous day / month / year), such as an increase of 12% represented as "+12%"; a decrease of 10% represented as "-10%". For example, the revenue statistics may also include a revenue trend chart for a previously preset period, such as a recent 30-day revenue trend chart, which can be a bar chart, line chart, or curve chart, etc.

[0062] In some examples, the inverter thumbnail cards for each inverter in the photovoltaic power station are used to display some key operating information of the corresponding inverter. For example, the figure shows five inverter thumbnail cards. Of course, there may be more inverters, which are hidden in the figure. Users can use the forward and backward arrows to display the inverter thumbnail cards of other inverters. For example, the information displayed by the inverter thumbnail cards may include at least one of the following: inverter identifier, equipment model, operating status, peak power, rated AC power, real-time power generation, and daily power generation. Each inverter thumbnail card may display a jump control for accessing the corresponding inverter's inverter monitoring interface, such as... Figure 3 The "View Details >" option is located in the inverter's thumbnail.

[0063] like Figure 4The diagram shown illustrates an inverter monitoring interface in one embodiment of this disclosure.

[0064] exist Figure 4 In the interface, the inverter monitoring system displays detailed operating information for the corresponding inverter, including: inverter identifier, manufacturer, equipment model, component peak power, rated AC power, grid type, annual generating hours, power generation efficiency, power generation trend data, current power generation, maximum power generation for the day, DC side detection information, AC side detection information, and at least one of power generation / revenue. As an example, in... Figure 4 The display shows the operating information of inverter 1 in photovoltaic power station A. Both the photovoltaic power station and the inverter can be switched between via drop-down menus. Compared to... Figure 3 Medium inverter abbreviation card, Figure 4 Another inverter thumbnail card displays more information, including manufacturer, equipment model, component peak power, rated AC power, grid type, annual generating hours, and generation efficiency. Additionally, Figure 4 The power generation / revenue of the inverter can be displayed in a format similar to... Figure 3 The presentation format for the power generation / revenue of photovoltaic power plants is consistent. For example, Figure 4 The system can also display cards showing the power generation statistics of inverter 1, including information such as daily power generation, monthly power generation, annual power generation, and a trend chart of power generation over the past 30 days. Figure 4 The display also shows the power generation trend card of Inverter 1, including the current power generation, the maximum power generation of the day, and the power generation trend chart of the past 24 hours. Figure 4 The system also displays a revenue statistics card for Inverter 1, showing information such as daily revenue, monthly revenue, annual revenue, and a revenue trend chart for the most recent 30 days.

[0065] As described above, a jump path is formed between the photovoltaic power station overview interface, the photovoltaic power station dashboard interface, and the inverter monitoring interface. Specifically, the photovoltaic power station overview interface includes a jump control that can be used to jump to the photovoltaic power station dashboard interface to display the operating information of the selected photovoltaic power station, for example... Figure 2 The photovoltaic power station overview interface includes a "View Details >" option. The photovoltaic power station dashboard interface also features a jump control that can be used to jump to the inverter monitoring interface to display the operating information of the selected inverter, for example... Figure 3 The "View Details >" option is located in the inverter's thumbnail.

[0066] The energy storage management module is used to generate a set of energy storage management graphical interfaces based on the second operating data for display on the user terminal. The set of energy storage management graphical interfaces includes: an energy storage power station overview interface, an energy storage power station operation dashboard interface, an energy storage power station topology interface, and an energy storage cabinet operation information interface, etc.

[0067] like Figure 5 The diagram shown illustrates an overview interface of an energy storage power station according to one embodiment of this disclosure.

[0068] The energy storage power station overview interface is used to display overview information of each energy storage power station on an electronic map. For details, please refer to... Figure 5 As shown, the electronic map displays the locations of each of the energy storage power stations, corresponding to their actual geographical locations.

[0069] In some embodiments, the energy storage power station overview interface displays representative icon controls for each energy storage power station on an electronic map. These representative icon controls allow user interaction to display current operational thumbnail information for the represented energy storage power station in an adjacent thumbnail information area, facilitating quick selection and understanding of key information for each energy storage power station. In some embodiments, exemplarily, the representative icon control for an energy storage power station can be drawn as a graphic distinct from surrounding facility icons to facilitate user location. Exemplarily, user interaction includes, but is not limited to, clicking, hovering, or long-pressing the representative icon control. Exemplarily, the current operational thumbnail information can be displayed in a pop-up window adjacent to the representative icon control. Exemplarily, if energy storage power station A is currently selected, the current operational thumbnail information may include key information about the energy storage power station of interest to the user, including at least one of the following: daily charge / discharge volume, current remaining power, and daily revenue. Optionally, the current operational thumbnail information may also include the name / ID of the energy storage power station, total installed capacity, etc. For example, the pop-up window may also provide a jump control for jumping to the operation dashboard interface of the energy storage power station corresponding to the energy storage power station, such as text or graphic icons like "View Details>".

[0070] In some embodiments, the information displayed on the energy storage power station overview interface may also include at least one of the following: the number of power stations in the energy storage system, the total capacity of the power stations, the daily charging / discharging amount, the cumulative revenue, the monthly charging / discharging amount and its trend chart, and the monthly revenue and its trend chart, so that users can obtain key overview information of the entire photovoltaic system in a comprehensive manner.

[0071] like Figure 6 The diagram shown illustrates the operation dashboard interface of an energy storage power station in one embodiment of this disclosure.

[0072] The energy storage power station operation dashboard interface is used to display detailed operation information for each energy storage power station. In some embodiments, the information displayed on the energy storage power station operation dashboard interface includes at least one of: charge / discharge statistics, revenue statistics, and charge / discharge power statistics; a thumbnail card for each energy storage cabinet in the energy storage power station; and a jump control for accessing the energy storage power station topology interface; the thumbnail card for each energy storage cabinet includes a jump control that allows user operation to access the energy storage cabinet operation information interface.

[0073] In some examples, the charging / discharging statistics can be displayed in a charging / discharging statistics card (or form), which may include, for example, the charging amount and discharging amount for the current day. Optionally, a trend chart of charging / discharging amounts for a previously preset period can also be displayed, such as a trend chart of charging / discharging amounts for the most recent 30 days, which can be a bar chart, line chart, or curve chart, etc. For example, the charging / discharging statistics may also include comparative data of the charging amount and discharging amount for the current day with the power generation in the same period (e.g., the previous day), such as an increase of 12% indicated as "+12%"; a decrease of 10% indicated as "-10%".

[0074] In some examples, the revenue statistics can be displayed in a revenue statistics card (or form), and the revenue statistics include at least one of daily revenue, monthly revenue, and annual revenue. For example, the revenue statistics may also include comparison data between daily, monthly, and annual revenue and revenue within the same period (e.g., the previous day / month / year), such as an increase of 12% represented as "+12%"; a decrease of 10% represented as "-10%". For example, the revenue statistics may also include a revenue trend chart for a previously preset period, such as a recent 30-day revenue trend chart, which can be a bar chart, line chart, or curve chart, etc.

[0075] In some examples, the operation dashboard interface of the energy storage power station can also display cards showing the charging / discharging power trend. The displayed information includes the current discharge power of the energy storage cabinet, the current charging power, and the charging / discharging power trend chart of the past 24 hours, such as curves, bar charts, etc.

[0076] In some examples, the energy storage power station operation dashboard interface allows switching between energy storage power stations, for example, by selecting other energy storage power stations via a drop-down menu. The energy storage power station operation dashboard interface also displays energy storage cabinet monitoring cards, which contain thumbnail cards for each energy storage cabinet in the currently selected energy storage power station, such as Energy Storage Cabinet 1 and Energy Storage Cabinet 2. Exemplarily, the energy storage cabinet thumbnail cards may display at least one key status information such as equipment model, operating status (e.g., normal, fault), installed capacity, current capacity, current charging power, and current discharging power. In some examples, the jump control for accessing the energy storage power station topology interface in the energy storage power station operation dashboard interface is exemplarily displayed as text or icons such as "Real-time Topology of Energy Storage Station >" in the energy storage cabinet monitoring card. In some examples, the thumbnail cards of the energy storage cabinets include jump controls that allow user operation to access the energy storage power station topology interface, which may be exemplified as text or icons such as "Real-time Topology Map of Energy Storage Station >".

[0077] like Figure 7 The diagram shown illustrates a schematic of the energy storage power station topology interface in one embodiment of this disclosure.

[0078] In some embodiments, the information displayed on the energy storage power station topology interface includes: a topology diagram of the energy storage power station comprising each energy storage cabinet and each energy storage cabinet comprising a battery stack consisting of multiple battery clusters, wherein the battery stack comprises multiple battery clusters connected in parallel; the information displayed for each energy storage cabinet in the topology diagram includes at least one of the following: the rechargeable capacity, dischargeable capacity, cumulative charge capacity, cumulative discharge capacity, current, voltage, power, and remaining capacity of the battery stack in the energy storage cabinet; the information displayed for each battery cluster in the topology diagram includes at least one of the following: charge / discharge statistics, revenue statistics, charge / remaining capacity, health status, maximum voltage, minimum voltage, operating status, charge / discharge status, maximum temperature, and minimum temperature.

[0079] In some examples, an energy storage cabinet contains a battery stack, and a battery stack can contain multiple battery clusters. The battery stacks of each energy storage cabinet are connected in parallel to a busbar. The multiple battery clusters under each battery stack converge to an output line and are connected to the busbar. The energy storage power station topology interface displays icons for each battery cluster and PCS, as well as a topology diagram showing the connection structure to the busbar via connecting lines. Through this topology diagram, users can clearly understand each energy storage cabinet and its corresponding battery stack within the energy storage power station, as well as the connection relationships of the battery clusters contained within the battery stack. The topology diagram also displays the operating information for each battery stack and battery cluster, such as the rechargeable capacity, dischargeable capacity, cumulative charge, cumulative discharge, current, voltage, power, and remaining capacity of the battery stack in the energy storage cabinet. Furthermore, the topology diagram can also display the operating information of battery clusters marked on or adjacent to the battery cluster icon, such as charge / discharge statistics, revenue statistics, charge / remaining capacity, health status, maximum voltage, minimum voltage, operating status, charge / discharge status, maximum temperature, minimum temperature, and so on.

[0080] Optionally, the remaining power can be visually represented by the proportion of different color / grayscale areas in the "battery icon" corresponding to each battery cluster. Optionally, different display parameters can be used in the topology diagram to represent different operating states of battery clusters / pile.

[0081] like Figure 8 The diagram shown illustrates the operation information interface of the energy storage cabinet in one embodiment of this disclosure.

[0082] The energy storage cabinet operation information interface is used to display the operation information of the energy storage cabinet. Figure 8 The information displayed on the energy storage cabinet operation information interface includes: energy storage cabinet manufacturer, equipment model, battery manufacturer, installation location, rated capacity, real-time power, remaining power, peak shaving and valley filling power curve, daily charging amount, daily discharging amount, cumulative charging amount, cumulative discharging amount, revenue statistics, and at least one of the following: a PCS abbreviated card for monitoring the energy storage converter of the corresponding energy storage cabinet, and an EMS abbreviated card for monitoring the battery stack of the corresponding energy storage cabinet. The PCS abbreviated card and the EMS abbreviated card respectively include jump controls for accessing the energy storage converter monitoring interface and the energy management system monitoring interface.

[0083] In some examples, the energy storage cabinet operation information interface displays a switchable selection of energy storage power stations and energy storage cabinets, for example, through a multi-level drop-down menu.

[0084] In some examples, the energy storage cabinet operation information interface displays thumbnail cards with more information about the energy storage cabinet, including manufacturer, model, battery manufacturer, installation location, rated capacitor, real-time power, SOC, operating status (e.g., "normal"), charging / discharging status (e.g., "discharging"), etc.

[0085] In some examples, the energy storage cabinet's operation information interface displays peak-shaving and valley-filling power cards, including input / selection fields for selectable dates, and recorded data on the charging / discharging behavior of the energy storage cabinet corresponding to peak-shaving and valley-filling. This data can be displayed through a two-dimensional curve graph of charging / discharging action-time. Peak-shaving and valley-filling refers to a charging / discharging strategy based on peak / valley electricity consumption (corresponding to peak / valley time-of-use electricity prices), charging during off-peak hours (i.e., off-peak electricity prices) and discharging during peak hours (i.e., peak electricity prices) to utilize the energy charged during off-peak hours, thereby reducing load and costs.

[0086] In some examples, the energy storage cabinet operation information interface displays charge / discharge cards, which may include an input / selection field for selecting a date, as well as data on the charge / discharge of the energy storage cabinet along the time axis, which can be displayed through a two-dimensional curve of charge / discharge amount versus time.

[0087] In some examples, the revenue statistics can be displayed in a revenue statistics card (or form), and the revenue statistics include at least one of daily revenue, monthly revenue, and annual revenue. For example, the revenue statistics may also include comparison data between daily, monthly, and annual revenue and revenue within the same period (e.g., the previous day / month / year), such as an increase of 12% represented as "+12%"; a decrease of 10% represented as "-10%". For example, the revenue statistics may also include a revenue trend chart for a previously preset period, such as a recent 30-day revenue trend chart, which can be a bar chart, line chart, or curve chart, etc.

[0088] In some examples, the energy storage cabinet's operation information interface also includes a setting card for the energy storage strategy mode, with a switching control for accepting operations to select the operating mode; the operating modes include at least two of the following: automatic mode, manual mode, and proxy mode. Automatic mode means the energy storage cabinet (e.g., EMS) autonomously decides on charging and discharging without manual intervention, automatically executing according to a preset built-in strategy. Proxy mode means the energy storage cabinet relinquishes its scheduling decision-making power, with charging / discharging commands issued by an upper-level remote platform, grid dispatch, virtual power plant, or group energy platform; the local equipment only executes these commands without making autonomous decisions.

[0089] As an example, the PCS thumbnail card can display some key operating information of the corresponding energy storage converter, including at least one of the following: conversion efficiency, battery voltage, temperature, alarm status, and fault status.

[0090] As an example, the EMS thumbnail card can display some key operational information of the battery stack, including at least one of the following: the highest voltage of a single cell, the lowest voltage of a single cell, the highest temperature of a single cell, and the lowest temperature of a single cell.

[0091] As an example, the energy storage cabinet's operation information interface may also display fire protection thumbnail cards for the fire protection system beneath the energy storage cabinet. The information displayed on these fire protection thumbnail cards includes at least one of the following: water immersion, smoke detection, and intrusion. The fire protection thumbnail cards also include jump controls for accessing the fire protection system monitoring interface.

[0092] As an example, the energy storage cabinet operation information interface may also include a temperature control thumbnail information card, which displays information including the temperature and humidity of the energy storage cabinet.

[0093] like Figure 9 The diagram shown illustrates a monitoring interface for an energy storage converter in one embodiment of this disclosure.

[0094] The energy storage converter monitoring interface is used to monitor the operating information of the PCS under the energy storage cabinet. The information displayed on the energy storage converter monitoring interface includes: equipment status, AC side real-time data, and DC side real-time data; the fault status is one of the equipment statuses.

[0095] In some examples, the energy storage converter monitoring interface displays selectable PCS under energy storage power stations and energy storage cabinets, for example, through multi-level drop-down menus.

[0096] In some examples, the device status displayed on the energy storage converter monitoring interface may include one or more of the following: device temperature, operating status (e.g., "stopped"), fault status (e.g., "normal"), and shutdown status (e.g., "shutdown").

[0097] In some examples, the real-time AC side data displayed on the energy storage converter monitoring interface may include one or more of the following: three-phase current, power factor, active power, apparent power, and reactive power; voltages between the three phases (such as AB line, BC line, and CA line); grid frequency; AC active charging amount; AC reactive charging amount; and trend graphs of the above items over time (selectable time period) that can be switched (as shown in the drop-down box), such as line graphs or curve graphs.

[0098] In some examples, the real-time DC-side data displayed on the energy storage converter monitoring interface may include one or more of the following: DC power, DC voltage, DC current, DC charging amount, DC discharging amount, bus voltage, and trend graphs of the above items over time (selectable time periods) that can be switched (as shown in the drop-down box), such as line graphs or curve graphs.

[0099] In some embodiments, the information displayed on the monitoring interface of the energy management system includes at least one of the following: real-time operating status of the battery stack, voltage, current, power, remaining power, health status, dischargeable amount, rechargeable amount, single discharge amount, single charge amount, cumulative discharge amount, cumulative charge amount, minimum temperature of a single cell, maximum temperature of a single cell, minimum voltage of a single cell, maximum voltage of a single cell, minimum voltage of a cluster, maximum voltage of a cluster, maximum remaining power of a cluster, and minimum remaining power of a cluster.

[0100] In some embodiments, the information displayed on the energy management system monitoring interface further includes a jump control for switching to the energy storage battery cluster monitoring interface.

[0101] In some embodiments, the information displayed on the energy storage battery cluster monitoring interface includes: battery cluster operation information, including at least one of the following: number of managed battery cells, real-time operating status, charge / discharge status, number of charging cycles, number of discharging cycles, rechargeable capacity, average temperature of individual cells, maximum temperature of individual cells, minimum temperature of individual cells, average voltage of individual cells, maximum voltage of individual cells, minimum voltage of individual cells, average remaining capacity of individual cells, maximum remaining capacity of individual cells, minimum remaining capacity of individual cells, cumulative charging capacity, cumulative discharging capacity, discharging capacity, current, voltage, power, group negative electrode insulation resistance, group positive electrode insulation resistance, remaining capacity of battery cluster, and battery cluster health status; the allowed range of voltage and temperature consistency values ​​between individual cells; and voltage and temperature data of individual cells, including individual cell voltage, average voltage difference, voltage consistency value, individual cell temperature, average temperature difference, and temperature consistency value.

[0102] Based on the above embodiments, it can be understood that a jump path is formed between the energy storage power station overview interface, the energy storage power station operation dashboard interface, the energy storage power station topology interface, and the energy storage cabinet operation information interface. For example, in the energy storage power station overview interface, by selecting a certain energy storage power station and operating the jump control, one can jump to the energy storage power station operation dashboard interface to display the operation information of the selected energy storage power station. Furthermore, in the energy storage power station operation dashboard interface, one can jump to the energy storage converter monitoring interface to display the operation information of the PCS under the energy storage cabinet of the selected energy storage power station, or jump to the energy storage power station topology interface to display the topology diagram of the selected energy storage power station.

[0103] The prediction strategy module, coupled to the data access module, can perform strategy prediction based on the operating information obtained by the data access module, such as the charging / discharging strategy of an energy storage system.

[0104] In some embodiments, the photovoltaic power generation system and energy storage system can be integrated into a photovoltaic-energy storage system, or belong to the same virtual power plant, private grid, dedicated grid, etc., or have private electricity trading contracts, making the price of electricity transfer between them lower than the price of electricity from the public grid. Therefore, when the photovoltaic power plant's power generation is insufficient (e.g., causing insufficient power supply to its load), the energy storage system can discharge to compensate for the photovoltaic power plant's power generation, effectively reducing costs compared to purchasing electricity from the public grid. Conversely, if the photovoltaic power plant has surplus power generation, it may also send it to the energy storage system for storage.

[0105] The prediction strategy module includes a meteorological fluctuation compensation prediction unit. This unit can be applied to the "power generation and consumption simultaneously" mode of photovoltaic power plants. To avoid fluctuations in photovoltaic power generation caused by meteorological conditions such as cloud cover, and because compensation for power fluctuations through the power grid may be costly due to peak-hour electricity prices, this unit utilizes the energy stored in the energy storage system, charged at lower electricity prices, to compensate for fluctuations in photovoltaic power generation. As a specific process example, the future fluctuations in photovoltaic power generation caused by meteorological changes can be predicted based on accurately detected meteorological data, and the energy storage system can be pre-designed for corresponding future charging / discharging compensation. Therefore, the compensation method in this embodiment can achieve accurate and forward-looking compensation strategy settings. Compared to "closing the barn door after the horse has bolted" compensation after fluctuations have occurred, the compensation method in this embodiment is significantly better at smoothing fluctuations.

[0106] like Figure 10 The diagram illustrates a method for compensating photovoltaic power generation based on weather forecasts in one embodiment of this disclosure.

[0107] The process includes:

[0108] Step S1001: Predict future weather data based on the actual weather data of each photovoltaic power station.

[0109] Step S1002: In response to determining, based on the predicted irradiance data corresponding to the predicted meteorological data, that at least one of the photovoltaic power plants will experience fluctuations in power generation at the future time.

[0110] Step S1003: In response to determining the impact of the fluctuation on the load power supply of the photovoltaic power station, determine the compensation output object at the future time and the predicted power compensation amount of the corresponding power generation deviation of the fluctuation.

[0111] In some embodiments, the compensation output may be an energy storage system, a power grid, or a combination thereof. The predicted power compensation amount may be equal to the power generation deviation amount.

[0112] In some embodiments, the meteorological changes mainly include cloud changes, which may cause varying degrees of shading of the solar photovoltaic array, resulting in changes in illuminance and consequently, changes in power generation. In some embodiments, the predicted meteorological data may include: local sky images captured by a full-sky imager located at the photovoltaic power station, and local irradiance values ​​measured by an irradiance meter located at the photovoltaic power station. The meteorological fluctuation compensation prediction unit can then predict cloud changes and the corresponding changes in local irradiance values ​​based on the local sky images, and calibrate the predicted values ​​with reference to the local irradiance values ​​to obtain accurate fluctuation compensation.

[0113] like Figure 11 The diagram shown illustrates a photovoltaic power generation compensation process based on weather forecasts in another specific embodiment of this disclosure.

[0114] exist Figure 11 The process includes:

[0115] Step S1101: Identify each cloud cluster by extracting image features from the continuous frames of the sky image in the meteorological data, obtain the motion vector data of each cloud cluster by optical flow method, predict the shading time of each cloud cluster arriving at the shading area above the photovoltaic array based on the motion vector data, and determine the predicted amount of shading cloud based on the set of shading cloud clusters in the shading area in the future time.

[0116] In some embodiments, a specific implementation of step S1101 is illustrated by way of example.

[0117] Image feature extraction and segmentation are performed on consecutive frames of sky images to identify individual moving clouds. Specifically, due to the different colors of clouds (e.g., white) and the background color of the sky (e.g., blue), and the specific shapes of cloud edges, individual moving clouds can be identified through image feature extraction and segmentation. Of course, cloud recognition algorithms are not limited to those of all-sky imagers; in other embodiments, cloud recognition models trained based on neural network models can also be used to identify and segment clouds from sky images. Examples include neural network models such as FCN, U-NET, MASK R-CNN, or YOLOv. A training dataset is constructed using sky images labeled with the segmented clouds as training data to train the neural network model. The loss between the prediction results and the labels is calculated, and the model parameters are updated based on the loss until convergence and training is complete.

[0118] In some embodiments, an optical flow algorithm (such as the LK sparse optical flow algorithm) can be used to match the feature points of the same cloud cluster in adjacent frames and solve for the motion vector data of each cloud cluster, as shown in the following formula (1):

[0119]

[0120] in, Let i be the motion vector of the i-th cloud cluster; The pixel displacement of a single cloud cluster in adjacent frames; The time interval between frames sampled for the image.

[0121] Based on the current location of the cloud clusters and the determined locations where they will obstruct the ground-based photovoltaic array, predict the shading time for each cloud cluster to reach the area obstructing the photovoltaic array:

[0122]

[0123] in, Predict the arrival time of occlusion for the i-th cloud cluster; This represents the distance the cloud cluster has moved from its current location to the area shaded by the photovoltaic array.

[0124] In some embodiments, the shading area can be determined and updated with reference to the azimuth information of the sun relative to the photovoltaic panel array. Specifically, an all-sky imager can identify the sun's position and determine its azimuth information by analyzing the image features of the sun (pixels of light spots). See also... Figure 12 As shown, the sun has two astronomical angles: altitude and azimuth. The altitude angle is the angle between the sun's rays and the horizontal plane, while the azimuth angle is the angle within the horizontal plane from true north clockwise to the sun's projection. (See also...) Figure 13 As shown, if each photovoltaic panel array has an angle relative to the horizontal plane, i.e., the array tilt angle β, the final orientation of the sun relative to the photovoltaic panel array can be determined by the solar incidence angle θ. AOI Let θ represent z Let α be the zenith angle and α be the solar altitude angle. At noon, when the sun is perpendicular to the ground, α is close to 90°; at sunrise and sunset: α = 0°; when the sun is below the horizon (at night): α < 0°.

[0125] Solar zenith angle θ z =90°-α, then according to the trigonometric relationship in the figure, the formula for the incident angle can be obtained as follows (3):

[0126] cosθ AOI =cosβcosθ z +sinβsinθ z cos(φ s −φ pv (3)

[0127] Where, φ s The solar azimuth angle is the angle measured in the horizontal plane, starting from true north and rotating clockwise to the line of the sun's projection on the Earth's surface, ranging from 0° to 360°. Specifically, it extends approximately 90° east, 180° south, and 270° west. φ pv This represents the azimuth angle of the photovoltaic array. In the horizontal plane, it is the angle calculated by rotating clockwise from due north to the projection of the photovoltaic panel's normal onto the horizontal plane. For example, if the photovoltaic power station is located due south, then φ... pv 180° is acceptable.

[0128] Let β, θ z =90°-α、φ s φ pv Substituting the values ​​into the equation above and calculating the right side of the equation, then finding the inverse cosine, we can obtain θ. AOI The horizontal deflection angle Δφ = φ relative to the sun relative to the photovoltaic panel is Δφ = φ s −φ pv Both parameters are used together as the orientation information of the sun relative to the photovoltaic panel array.

[0129] Since the distance between the all-sky imager and the photovoltaic array is known or negligible, the azimuth information of the sun relative to the photovoltaic array can be approximately obtained.

[0130] In other embodiments, a solar tracker can be installed, integrating a GPS positioning module and a photoelectric sun-finding sensor. On one hand, the sun's position is calculated using an astronomical model based on the station's latitude, longitude, and time; on the other hand, the photoelectric sun-finding sensor measures the sun's direction in a closed-loop correction to determine altitude and azimuth, outputting high-precision sun position information. Then, θ is calculated by substituting this information into the above formula. AOI This, together with Δφ, forms the aforementioned orientation information.

[0131] Furthermore, after determining the orientation of the sun relative to the photovoltaic array, it is possible to identify the shading areas at different altitudes that will block solar radiation from reaching the photovoltaic array, corresponding to clouds at different altitudes. In some embodiments, only the shading areas at lower altitudes can be considered; the lower the altitude, the closer the clouds are to the ground, the larger the shadow area, and the stronger the impact on photovoltaic output.

[0132] In some embodiments, real-time wind direction changes obtained from meteorological data can also be considered to predict changes in the movement direction of cloud clusters and update the movement distance in real time.

[0133] Additionally, the method for calculating cloud cover is illustrated by example. In some examples, this can be achieved by filtering all instances that meet the occlusion time condition, i.e., future times. The cloud clusters located exactly above the photovoltaic array in the shading area constitute the future shading cloud cluster set. For example, the predicted shading cloud amount at future times can be calculated based on the total pixel area of ​​all cloud clusters in this set, as shown in the following equation (4):

[0134]

[0135] in, This represents the predicted amount of cloud cover at a future time. The value can be normalized to 0~1, where 0 represents no cloud cover and 1 represents complete cloud cover. This represents the total number of pixels in all cloud clusters within the future occlusion cloud cluster set. This indicates the total number of pixels in the sky image.

[0136] Step S1102: Based on the gray values ​​of clouds in the sky image, calculate the predicted average cloud thickness of the set of occluded clouds located in the occlusion area at future time using a cloud thickness optical mapping model that has been pre-calibrated to represent the mapping relationship between gray values ​​and cloud thickness values.

[0137] In some embodiments, the grayscale value and cloud thickness value can be obtained through actual measurement. For example, a laser altimeter emits a laser pulse vertically into the sky, and the distance is calculated by receiving the time difference of the backscattered signals from the cloud layers. The device first measures the cloud base height. If the laser penetrates the first layer of cloud and continues to be scattered by the upper layer, multiple echoes can be identified to obtain the cloud top height. The difference between the two is the cloud thickness. The grayscale value can be obtained through optical imaging. By fitting, regressing, or pre-establishing a model and then identifying parameters from multiple sets of measured cloud thickness and grayscale values ​​for different clouds, the mapping relationship between cloud thickness and grayscale values ​​can be determined.

[0138] As an example, the cloud thickness (optically calculated thickness) of the i-th cloud can be solved by calculating the average gray value of each cloud in the sky image and using a pre-calibrated cloud thickness optical mapping model. For example, the linear model shown in equation (5) can be used:

[0139]

[0140] in, The value is the thickness of the i-th cloud cluster, and it is greater than 1. The thicker the cloud cluster, the larger the value. Let be the average gray value of the i-th cloud patch image. a and b are the model coefficients obtained from the measured values, respectively.

[0141] The cloud clusters obtained according to equation (5) Calculate the average cloud thickness of the cloud cluster located in the shading region at a future time. As shown in equation (6):

[0142]

[0143] Step S1103: Obtain the local irradiance attenuation coefficient based on the ratio of the currently collected local irradiance value to the clear sky reference irradiance value.

[0144] The clear-sky reference irradiance value is obtained based on the local irradiance value collected by the irradiometer under a clear-sky reference weather scenario.

[0145] The clear-sky baseline irradiance value is obtained by actual measurement and calibration of the irradiance instrument under local cloudless clear-sky conditions. Combined with the local irradiance value collected in real time by the irradiance instrument, the real-time local irradiance attenuation coefficient is calculated as shown in equation (7):

[0146]

[0147] in, This is the local irradiance attenuation coefficient, with a value ranging from 0 to 1; This represents the local irradiance value currently collected by the irradiation instrument. The reference irradiance values ​​for clear sky were collected and calibrated by the irradiance instrument under local cloudless and clear weather conditions.

[0148] Step S1104: Based on the predicted average cloud thickness and predicted cloud amount of the set of obscuring clouds at the future time, and the local irradiance attenuation coefficient, predict the predicted local irradiance value at the future time.

[0149] It is worth noting that the future time should not be too far from the current time to avoid significant weather changes that could affect the accuracy of the forecast. Preferably, the future time can be within the range of 5-10 minutes, 10-15 minutes, or 15-20 minutes from the current time.

[0150] Understandably, irradiance intensity is negatively correlated with cloud thickness and the amount of obstructing cloud cover, but positively correlated with the irradiance attenuation coefficient. Furthermore, when sunlight passes through clouds, water vapor and droplets scatter and absorb photons, and the radiation intensity decreases exponentially with the optical thickness of the medium (i.e., the cloud). Therefore, the predicted average cloud thickness can be calculated based on the future obstructing cloud clusters. Predicting cloud cover Local irradiance attenuation coefficient Using the radiative transfer attenuation model based on the above positive and negative correlations, i.e., the following equation (8), the predicted local irradiance value for future times is calculated. :

[0151] (8)

[0152] It is worth noting that Equation (8) is only an example of a radiative transfer attenuation model, and can be varied in other embodiments, and is not limited thereto. For example, It can be segmented according to the season. For example, The power k can be increased, and k is determined by inversion based on actual data.

[0153] In other embodiments, the radiative transfer attenuation model can also be implemented using a machine learning model. The machine learning model is trained using average cloud thickness, cloud cover, local irradiance attenuation coefficient, and corresponding measured local irradiance values ​​as training data until training is complete. Optionally, the machine learning model can be implemented as a neural network model, such as a CNN, a Physical Information Neural Network (PINN), etc.

[0154] Step S1105: Based on the update of the predicted local irradiance value, obtain the time-varying data of the corresponding predicted power generation.

[0155] Specifically, there is a known conversion relationship between irradiance and power generation, which is related to the total area of ​​the photovoltaic array and the photoelectric conversion efficiency. Specifically, it is shown in equation (9) below:

[0156]

[0157] in, The total area of ​​the photovoltaic panel array. This represents the photoelectric conversion efficiency of the photovoltaic array.

[0158] Furthermore, according to different This allows us to obtain the time axis. The time series data is used as the time-varying data for the predicted power generation.

[0159] Step S1106: In response to the time-varying data of the predicted power generation determining that the fluctuation condition is met, determine the predicted power compensation amount corresponding to the power generation deviation of the energy storage system during fluctuation.

[0160] In some embodiments, the fluctuation condition can be set to a period of time. If the change exceeds a preset threshold n times (n is an integer that can be set according to requirements), then a fluctuation event is determined. Alternatively, it can be based on... A fluctuation event is identified when the rate of change of the change exceeds a preset threshold.

[0161] In some embodiments, the power generation deviation can be set according to actual power supply needs, such as using the required power supply P of the load as a standard. P can be determined based on the load's nominal power, peak power, or actual power during normal operation. Corresponding power generation deviation ,if A negative value indicates a deficiency. This is insufficient to satisfy P. The predicted power compensation amount can be equal to the power generation deviation amount.

[0162] In some embodiments, since the upper limit of the regulation capacity range that the grid dispatching side may reserve free of charge for smoothing short-term small power fluctuations of photovoltaic power, which can be called "grid-free compensation power", the "grid-free compensation power" of the grid can be used first when compensating according to the predicted power compensation amount.

[0163] Therefore, in the corresponding example, the compensation strategy described in step S1106 for determining the predicted power compensation amount obtained from the energy storage system and / or the power grid at the future time can be implemented as follows: determining whether the predicted power compensation amount is within the power grid's cost-free compensation power range; if so, the power grid independently compensates for the predicted power compensation amount. If not, the power grid compensates with the maximum cost-free compensation power, and the energy storage system discharges to replenish the predicted power compensation amount. For example, suppose the power grid's cost-free compensation power threshold is... The power generation deviation is First, determine and The size relationship, if If the power generation deviation falls within the grid's cost-free compensation threshold, it will be entirely compensated by the grid's cost-free compensation power, while the predicted power compensation from the energy storage system will be less. =0. If the power generation deviation exceeds the grid's costless compensation threshold, i.e. If the power grid cannot absorb excess fluctuations free of charge, then it is necessary to coordinate with energy storage systems to jointly compensate, thereby obtaining the predicted power compensation amount from the energy storage systems. .

[0164] In other embodiments, considering that the grid's costless compensation power may be slower than that of the local energy storage system in real-world scenarios, the choice can be made to prioritize the use of the local energy storage system for compensation based on the actual severity of cloud obstruction. The severity of cloud obstruction can be determined based on the cloud distribution type. The cloud distribution type includes a first type of continuous cloud clusters and a second type of scattered cloud clusters. The cloud distribution type in the future can be obtained from the predicted location distribution of cloud clusters within the obstruction area in the future.

[0165] Therefore, as an example, step S1106 can also be implemented as follows: determining the cloud distribution type based on the distribution of the shading cloud cluster set, including: in response to the cloud distribution type being a first type, preferentially compensating the real-time power generation deviation by the energy storage system according to the predicted power compensation amount. Alternatively, in response to the cloud distribution type being a second type, preferentially compensating the real-time power generation deviation by the power grid according to the predicted power compensation amount. If the predicted power compensation amount exceeds the power grid's cost-free compensation power threshold, then the power grid compensates with the maximum cost-free compensation power, and the energy storage system discharges to make up to the predicted power compensation amount.

[0166] For example, by predicting the distribution of cloud clusters in the future, we can determine whether the cloud distribution is continuous or scattered. If the clouds are continuous, it indicates severe shading and a large deviation in power generation. To quickly compensate for this large deviation, we can prioritize using energy storage systems for discharge compensation. Alternatively, if the clouds are scattered, it indicates less severe shading and a smaller deviation in power generation, in which case we can utilize the grid's cost-free compensation power.

[0167] Step S1107: Determine a compensation strategy for obtaining the predicted power compensation amount from the energy storage system and / or the power grid at the future time.

[0168] In some embodiments, the compensation strategy may include a strategy for obtaining power from the grid, and / or a discharge strategy for the energy storage system, etc.

[0169] In some embodiments, the method for determining the corresponding compensation discharge strategy for the energy storage system based on the fluctuations in the predicted meteorological impact of photovoltaic power generation in the "power generation and consumption" mode can be implemented as a strategy independent of the "peak shaving and valley filling" strategy, and also embedded in the "automatic mode". Alternatively, in other embodiments, the method for implementing the compensation charging / discharging strategy can also be implemented in combination with the "peak shaving and valley filling" strategy. For example, when discharging during the "peak" period, the discharge amount is adjusted based on the original discharge benchmark and combined with the predicted power compensation amount, and also embedded in the "automatic mode". For example, the "peak shaving and valley filling with photovoltaic compensation" strategy can coexist with the original "peak shaving and valley filling" strategy.

[0170] It should be noted that the compensation strategy in this method embodiment is a "predictive compensation" strategy based on the "predicted" photovoltaic power generation fluctuations caused by the predicted cloud shading situation in the future, in order to smooth the power supply of photovoltaic load as accurately as possible when the future time arrives.

[0171] In some embodiments, when compensation via an energy storage system is required, a group of alternative energy storage stations located close to each load that requires power generation from photovoltaic power and causes power fluctuations can be identified along the power supply path. This is used to determine the predicted power compensation amount. In this process, the required sub-predicted power compensation amount for each load can be determined separately, and one or more target energy storage stations that can bear the sub-predicted power compensation amount in the future can be selected from a group of alternative energy storage stations corresponding to each load. The charging / discharging strategies of the target energy storage stations in the future can then be set accordingly. This process continues until each load is determined.

[0172] In some embodiments, the charging / discharging strategy of each target energy storage power station can also be displayed in at least one of the energy storage power station operation dashboard interface, energy storage power station topology interface, etc., to prompt the user.

[0173] The photovoltaic management graphical interface and energy storage management graphical interface in the above embodiments can be unified into a single photovoltaic-energy storage collaborative management platform system interface for selection and navigation, thereby improving management efficiency. Additionally, data of managed objects (source, grid, load) can be added to the photovoltaic-energy storage collaborative management platform system and displayed on the interface, such as various electricity loads and charging piles.

[0174] It should be specifically noted that the flowchart representations of the embodiments described above in this disclosure can be understood as representing a module, segment, or portion of code comprising one or more executable instructions configured to implement a specific logical function or process. Furthermore, the scope of the preferred embodiments of this disclosure includes other implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved.

[0175] For example, Figure 10 , Figure 11 The order of the steps in the method embodiments may vary in specific scenarios and is not limited to the above representation.

[0176] like Figure 14 The diagram shown illustrates the structure of a computer device according to an embodiment of the present disclosure.

[0177] The computer device 1400 can be implemented in servers / server groups, etc.

[0178] The computer device 1400 includes a bus 1401, a processor 1402, and a memory 1403. The processor 1402 and the memory 1403 can communicate via the bus 1401. The memory 1403 can store computer programs or instructions. The processor 1402 implements the method flow or function of the previous embodiments by running the computer program or instructions in the memory 1403, for example... Figure 10 , Figure 11 .

[0179] Bus 1401 can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of representation, although only one thick line is used in the diagram, this does not indicate that there is only one bus or one type of bus.

[0180] In some embodiments, processor 1402 may be implemented as a central processing unit (CPU), microprocessor unit (MCU), system on chip (System on Chip), or field-programmable array (FPGA). Memory 1403 may include volatile memory for temporary data storage during program execution, such as random access memory (RAM).

[0181] The memory 1403 may also include non-volatile memory for data storage, such as read-only memory (ROM), flash memory, hard disk drive (HDD), or solid-state disk (SSD).

[0182] In some embodiments, the computer device 1400 may further include a communicator 1404. The communicator 1404 is used for communication with external devices. In specific examples, the communicator 1404 may include one or more wired and / or wireless communication circuit modules. For example, the communicator 1404 may include one or more of, such as a wired network card, a USB module, a serial interface module, etc. The wireless communication protocols followed by the wireless communication module include, for example, Nearfield communication (NFC) technology, Infrared (IR) technology, Global System for Mobile Communications (GSM), General Packet Radio Service (GPRS), Code Division Multiple Access (CDMA), Wideband Code Division Multiple Access (WCDMA), Time-Division Code Division Multiple Access (TD-SCDMA), Long Term Evolution (LTE), Bluetooth (BT), Global Navigation Satellite System (GNSS), etc.

[0183] This disclosure also provides a computer-readable storage medium storing a computer program or instructions, which, when run, implement the method flow or function of any of the previous embodiments.

[0184] That is, the method steps in the above embodiments are implemented as software or computer code that can be stored in a recording medium (such as CD ROM, RAM, floppy disk, hard disk or magneto-optical disk), or implemented as computer code that is originally stored in a remote recording medium or a non-transitory machine-readable medium and will be stored in a local recording medium after being downloaded via a network, so that the method represented herein can be stored in such software processing on a recording medium using a general-purpose computer, a special processor or programmable or special hardware (such as ASIC or FPGA).

[0185] This disclosure may also provide a computer program product, comprising one or more computer programs or instructions, which, when run, perform all or part of the processes or functions described in this disclosure. The computer program product includes one or more computer programs or instructions.

[0186] Computer programs or instructions can be stored in a readable storage medium or transferred from one readable storage medium to another. For example, the computer program or instructions can be transferred from one website, computer, server, or data center to another website, computer, server, or data center via wired or wireless means. The readable storage medium can be any available medium capable of access, or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium, such as a floppy disk, hard disk, or magnetic tape; an optical medium, such as a digital video optical disc; or a semiconductor medium, such as a solid-state drive. The computer-readable storage medium can be a volatile or non-volatile storage medium, or it can include both volatile and non-volatile types of storage media.

[0187] In summary, this disclosure relates to the field of new energy technology and provides a photovoltaic-storage collaborative management platform system. The system includes: a data access module; a photovoltaic management module forming a set of photovoltaic management graphical interfaces, including: a photovoltaic power station overview interface with jump paths, a photovoltaic power station operation dashboard interface, and an inverter monitoring interface; and an energy storage management module forming a set of energy storage management graphical interfaces, including: an energy storage power station overview interface with jump paths, an energy storage power station operation dashboard interface, an energy storage power station topology interface, and an energy storage cabinet operation information interface. The prediction strategy module includes a meteorological fluctuation compensation prediction unit, which, in response to determining that at least one of the photovoltaic power stations will experience power generation fluctuations in the future time based on predicted irradiance data corresponding to predicted meteorological data, determines the predicted power compensation amount based on the fluctuation deviation. This achieves visualized management of all information in the photovoltaic-storage system and predicts and compensates for photovoltaic power generation fluctuations based on locally measured meteorological data, thereby improving system stability.

[0188] The above embodiments are merely illustrative of the principles and effects of this disclosure and are not intended to limit this disclosure. Any person skilled in the art can modify or alter the above embodiments without departing from the spirit and scope of this disclosure. Therefore, all equivalent modifications or alterations made by those skilled in the art without departing from the spirit and technical concept disclosed in this disclosure should still be covered by the protection scope of this disclosure.

Claims

1. A photovoltaic-storage collaborative management platform system, characterized in that, This system is used for managing a photovoltaic (PV) power generation system and an energy storage system. The PV power generation system includes various PV power plants, each PV power plant including a PV panel array and an inverter. The energy storage system includes various energy storage power plants. Each energy storage power plant includes one or more energy storage cabinets, each energy storage cabinet containing a battery stack composed of multiple battery clusters. The PV-energy storage collaborative management platform system includes: The data access module is used to collect and update the first operating data of the photovoltaic power generation system, the second operating data of the energy storage system, and the meteorological data of the distribution area of ​​the photovoltaic power generation system; The photovoltaic management module is used to generate a set of photovoltaic management graphical interfaces based on the first operating data for display on user terminals connected to the photovoltaic-storage collaborative management platform system. These interfaces include: a photovoltaic power station overview interface for displaying an overview of each photovoltaic power station on an electronic map; a photovoltaic power station operation dashboard interface for displaying the operating information of each photovoltaic power station; and an inverter monitoring interface for displaying the operating information of the inverters in the photovoltaic power stations. A jump path is formed between the photovoltaic power station overview interface, the photovoltaic power station dashboard interface, and the inverter monitoring interface. The energy storage management module is used to generate a set of energy storage management graphical interfaces based on the second operating data for display on the user terminal. These interfaces include: an energy storage power station overview interface for displaying an overview of each energy storage power station on an electronic map; an energy storage power station operation dashboard interface for displaying the operating information of each energy storage power station; an energy storage power station topology interface for displaying the topology information of each energy storage cabinet in the energy storage power station; and an energy storage cabinet operation information interface for displaying the operating information of the energy storage cabinets. A jump path is formed between the energy storage power station overview interface, the energy storage power station operation dashboard interface, the energy storage power station topology interface, and the energy storage cabinet operation information interface. The prediction strategy module, coupled to the data access module, includes: a meteorological fluctuation compensation prediction unit, used to predict future meteorological data based on the actual meteorological data of each photovoltaic power station; in response to determining, based on the predicted irradiance data corresponding to the predicted meteorological data, that at least one of the photovoltaic power stations experiences fluctuations in power generation in the future time; and in response to determining that the fluctuations affect the load power supply of the photovoltaic power station, determining the compensation output object in the future time and the predicted power compensation amount of the corresponding power generation deviation of the fluctuations.

2. The photovoltaic-storage collaborative management platform system according to claim 1, characterized in that, The photovoltaic power station overview interface displays representative icon controls for each photovoltaic power station on an electronic map. These representative icon controls allow user interaction to display the current operating thumbnail information of the represented photovoltaic power station in an adjacent thumbnail information area. The current operating thumbnail information includes at least one of the following: the photovoltaic power station's daily power generation, current power, and daily revenue.

3. The photovoltaic-storage collaborative management platform system according to claim 1, characterized in that, The photovoltaic power station operation dashboard displays information including: power generation data and revenue data for a preset time period; and inverter thumbnail cards for each inverter in the photovoltaic power station. The inverter thumbnail cards display some key operating information of the inverter, including at least one of the following: inverter identifier, equipment model, operating status, peak power, rated AC power, real-time power generation, and daily power generation.

4. The photovoltaic-storage collaborative management platform system according to claim 3, characterized in that, Each inverter thumbnail also includes a jump control for accessing the inverter monitoring interface for the corresponding inverter; the inverter monitoring interface displays detailed operating information for the corresponding inverter, including at least one of the following: inverter identifier, manufacturer, equipment model, component peak power, rated AC power, grid type, annual power generation hours, power generation efficiency, power generation trend data, current power generation, maximum power generation of the day, DC side detection information, AC side detection information, and power generation / revenue.

5. The photovoltaic-storage collaborative management platform system according to claim 1, characterized in that, The overview interface of the energy storage power station displays representative icon controls for each energy storage power station on an electronic map. The representative icon controls allow user operation to display the current operation thumbnail information of the represented energy storage power station in an adjacent thumbnail information area. The current operation thumbnail information of the energy storage power station includes at least one of the following: the energy storage power station's daily charge / discharge amount, current power, and daily revenue.

6. The photovoltaic-storage collaborative management platform system according to claim 1, characterized in that, The information displayed on the energy storage power station operation dashboard interface includes at least one of the following: charging / discharging statistics, revenue statistics, and charging / discharging power statistics; a thumbnail card for each energy storage cabinet in the energy storage power station; and a jump control for accessing the energy storage power station topology interface. The thumbnail card for each energy storage cabinet includes a jump control that allows user operation to access the energy storage cabinet operation information interface. And / or, the energy storage power station topology interface includes: a topology diagram of the energy storage power station and its constituent energy storage cabinets, and a battery stack composed of multiple battery clusters in each energy storage cabinet, wherein the battery stack includes multiple battery clusters connected in parallel; the display information corresponding to each energy storage cabinet in the topology diagram includes at least one of the following: the rechargeable capacity, dischargeable capacity, cumulative charge capacity, cumulative discharge capacity, current, voltage, power, and remaining capacity of the battery stack in the energy storage cabinet; the display information of each battery cluster in the topology diagram includes at least one of the following: charge / discharge statistics, revenue statistics, charge / remaining capacity, health status, maximum voltage, minimum voltage, operating status, charge / discharge status, maximum temperature, and minimum temperature; And / or, the information displayed on the energy storage cabinet operation information interface includes: energy storage cabinet manufacturer, equipment model, battery manufacturer, installation location, rated capacity, real-time power, remaining power, peak shaving and valley filling power curve, daily charging amount, daily discharging amount, cumulative charging amount, cumulative discharging amount, revenue statistics, PCS abbreviated card for monitoring the energy storage converter of the corresponding energy storage cabinet, and EMS abbreviated card for monitoring the battery stack of the corresponding energy storage cabinet; wherein, the PCS abbreviated card and the EMS abbreviated card respectively include jump controls for jumping to the energy storage converter monitoring interface and the energy management system monitoring interface; The PCS thumbnail displays some key operating information of the corresponding energy storage converter, including at least one of the following: conversion efficiency, battery voltage, temperature, alarm status, and fault status; the information displayed on the energy storage converter monitoring interface includes: equipment status, AC side real-time data, and DC side real-time data; the fault status is one of the equipment statuses. The EMS abbreviated card displays some key operating information of the battery stack, including at least one of the following: the highest voltage of a single cell, the lowest voltage of a single cell, the highest temperature of a single cell, and the lowest temperature of a single cell; the information displayed on the energy management system monitoring interface includes at least one of the following: the real-time operating status of the battery stack, voltage, current, power, remaining power, health status, dischargeable capacity, rechargeable capacity, single discharge capacity, single charge capacity, cumulative discharge capacity, cumulative charge capacity, minimum temperature of a single cell, maximum temperature of a single cell, minimum voltage of a single cell, maximum voltage of a single cell, minimum cluster voltage, maximum cluster voltage, maximum remaining power of a cluster, and minimum remaining power of a cluster.

7. The photovoltaic-storage collaborative management platform system according to claim 6, characterized in that, The information displayed on the energy management system monitoring interface also includes: a jump control for accessing the energy storage battery cluster monitoring interface; the information displayed on the energy storage battery cluster monitoring interface includes: battery cluster operating information, including at least one of the following: number of managed battery cells, real-time operating status, charge / discharge status, number of charging cycles, number of discharging cycles, rechargeable capacity, average temperature of individual cells, maximum temperature of individual cells, minimum temperature of individual cells, average voltage of individual cells, maximum voltage of individual cells, minimum voltage of individual cells, average remaining capacity of individual cells, maximum remaining capacity of individual cells, minimum remaining capacity of individual cells, cumulative charging capacity, cumulative discharging capacity, discharging capacity, current, voltage, power, group negative electrode insulation resistance, group positive electrode insulation resistance, remaining capacity of battery cluster, and battery cluster health status; the allowed range of voltage and temperature consistency values ​​between individual cells; and voltage and temperature data of individual cells, including individual cell voltage, average voltage difference, voltage consistency value, individual cell temperature, average temperature difference, and temperature consistency value.

8. The photovoltaic-storage collaborative management platform system according to claim 1, characterized in that, The meteorological data includes: local sky images captured by a full-sky imager located at the photovoltaic power station, and local irradiance values ​​measured by an irradiance meter located at the photovoltaic power station; the meteorological fluctuation compensation prediction unit is used to execute the following processes, including: Image features extracted from consecutive frames of sky images in meteorological data are used to identify each cloud cluster, and motion vector data of each cloud cluster is obtained by optical flow method. Based on the motion vector data, the shading time of each cloud cluster arriving at the shading area above the photovoltaic array is predicted, and the predicted amount of shading cloud is determined based on the set of shading cloud clusters in the shading area in the future. Based on the gray values ​​of clouds in sky images, the predicted average cloud thickness of the set of occluded clouds located in the occlusion area at future time is calculated using a cloud thickness optical mapping model that has been pre-calibrated to represent the mapping relationship between gray values ​​and cloud thickness values. The local irradiance attenuation coefficient is obtained based on the ratio of the currently collected local irradiance value to the clear-sky reference irradiance value; wherein, the clear-sky reference irradiance value is obtained based on the local irradiance value collected by the irradiance instrument under a clear-sky reference weather scenario. Based on the predicted average cloud thickness and predicted cloud amount of the occult cloud cluster at the future time, and the local irradiance attenuation coefficient, the predicted local irradiance value at the future time is predicted. The time-varying data of the corresponding predicted power generation are obtained based on the update of the predicted local irradiance value; In response to the time-varying data of the predicted power generation, it is determined that the fluctuation condition is met, and the predicted power compensation amount corresponding to the power generation deviation of the energy storage system during the fluctuation is determined. Determine a compensation strategy for obtaining the predicted power compensation amount from the energy storage system and / or the power grid at the future time.

9. The photovoltaic-storage collaborative management platform system according to claim 8, characterized in that, The compensation strategy for determining the predicted power compensation amount from the energy storage system and / or the power grid at the future time includes one of the following: 1) Determine whether the predicted power compensation amount is within the power grid's cost-free compensation power range; if so, the power grid shall independently compensate the predicted power compensation amount; if not, the power grid shall compensate with the maximum cost-free compensation power, and the energy storage system shall discharge to make up to the predicted power compensation amount. 2) Determine the cloud distribution type based on the distribution of the occult cloud clusters, including the first type of continuous cloud clusters and the second type of scattered cloud clusters; In response to the cloud distribution type being Type I, the energy storage system is prioritized to compensate for the real-time power generation deviation according to the predicted power compensation amount. In response to the cloud distribution type being type 2, the real-time power generation deviation is compensated by the power grid according to the predicted power compensation amount. If the predicted power compensation amount exceeds the power grid's cost-free compensation power range, the power grid will compensate with the maximum cost-free compensation power, and the energy storage system will discharge to make up to the predicted power compensation amount.

10. The photovoltaic-storage collaborative management platform system according to claim 6, characterized in that, The energy storage cabinet operation information interface also includes a setting card for the energy storage strategy mode of the energy storage cabinet, and has a switching control for accepting operations to select the operation mode; the operation mode includes at least two of the following: automatic mode, manual mode and agent mode; And / or, the information displayed on the energy storage cabinet operation information interface also includes: a fire protection thumbnail card for the fire protection system under the energy storage cabinet, wherein the information displayed on the fire protection thumbnail card includes at least one of water immersion, smoke detection, and intrusion; the fire protection thumbnail card also includes a jump control for jumping to the fire protection system monitoring interface; And / or, the energy storage cabinet operation information interface also includes a temperature control thumbnail information card, which displays information including the temperature and humidity information of the energy storage cabinet.

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