Energy management method and system based on smart electric energy meter

Abstract

The present application provides an energy management method and system based on a smart energy meter, including: determining the expected power generation of the photovoltaic system for each natural day in the future period under the condition of no abandoned solar power based on the historical power data of the smart energy meter and the business reservation information of the target business site in the future period; determining the expected basic load power of the target business site for each natural day under the condition of the charging load of new energy vehicles in the absence of self-driving vehicles based on business project information and power load; determining the flexible load power that can be absorbed by new energy vehicles in the photovoltaic system for each natural day based on the expected power generation, expected basic load power, and the storable power of the energy storage system; and creating and publishing a charging discount plan for the target business site based on the flexible load power and vehicle information of the self-driving vehicles to absorb the flexible load power. This application is conducive to improving the utilization and conversion rate of photovoltaic resources.

Description

Technical Field

[0001] The present application relates to the technical field of photovoltaic energy storage management for new energy services, and in particular to an energy management method and system based on a smart electricity meter. Background Art

[0002] With the widespread application of photovoltaic storage systems, business venues such as hotels have gradually begun to be equipped with photovoltaic storage energy management systems. By connecting local photovoltaic storage systems to the power grid, a more stable and cost-effective electricity usage plan can be achieved. The power generated by the photovoltaic system can directly power the electrical loads of the business venue, or charge the energy storage system of the business venue, and then the energy storage system can power the electrical loads to meet the electricity needs of the business venue.

[0003] At present, the use and conversion of power generated by photovoltaic storage systems has become a research hotspot in the field of photovoltaic storage power management. Existing solutions are difficult to fully balance the maximum use of power generation and the efficient conversion of surplus photovoltaic storage power, which in turn causes waste of resources and reduces energy conversion efficiency. Summary of the Invention

[0004] The present application provides an energy management method and system based on a smart electricity meter. Aiming at the photovoltaic energy storage management needs of the target business site in the future period, the application creatively proposes a solution for absorbing the surplus electricity of the photovoltaic system without abandoned light based on flexible load power in the dimension of multiple consecutive natural days. The flexible load power absorption is deeply integrated with the charging business of new energy vehicles in the target business site. The charging business system creates and releases charging preferential plans, which can attract users to absorb the flexible load power quickly and accurately. On the one hand, it realizes the maximum use of the power generation of the photovoltaic system without abandoned light, and on the other hand, it accurately converts the surplus power of the photovoltaic system into benefits.

[0005] In a first aspect, the present application provides an energy management method based on a smart electric energy meter, which is applied to a server of a photovoltaic energy storage management system at a target business site. The photovoltaic energy storage management system includes a photovoltaic system, an energy storage system, the server, and an electric load provided at the target business site. The method includes:

[0006] Determining, based on historical power data of the smart power meter and service reservation information of the target service site in the future time period, an expected power generation of the photovoltaic system on each natural day in the future time period under the condition that no power is abandoned, the service reservation information including service project information and vehicle information of the self-driving vehicle;

[0007] Determine, based on the business project information and the power load, the estimated basic load power of the target business site for each natural day under the condition that there is no charging load of the new energy vehicle among the self-driving vehicles;

[0008] Determining the flexible load power of the photovoltaic system that can be consumed by the new energy vehicle in the self-driving vehicle on each natural day based on the expected power generation on each natural day, the expected basic load power, and the storable power of the energy storage system;

[0009] A preferential charging plan for the target business site is created and published based on the flexible load power and the vehicle information of the self-driving vehicle to absorb the flexible load power.

[0010] In a second aspect, an embodiment of the present application provides a photovoltaic energy storage management system, including a server, a photovoltaic system, an energy storage system, and an electrical load arranged at a target business site, wherein:

[0011] The server is used to execute the steps performed by the server described in the first aspect of the embodiment of the present application.

[0012] It can be seen that in the embodiment of the present application, the server determines the expected power generation of the photovoltaic system on each natural day in the future period under the condition of no abandoned light based on the historical power data of the smart power meter and the business reservation information of the target business site in the future period, and the business reservation information includes business project information and vehicle information of the self-driving vehicle; the expected basic load power of the target business site on each natural day under the condition of no charging load of new energy vehicles in the self-driving vehicle is determined based on the business project information and the power load; the flexible load power that can be absorbed by the new energy vehicles in the self-driving vehicles of the photovoltaic system on each natural day is determined based on the expected power generation, the expected basic load power and the storable power of the energy storage system; and the charging preferential plan of the target business site is created and published based on the flexible load power and the vehicle information of the self-driving vehicle to absorb the flexible load power. In this way, compared with the existing energy management solutions with low energy utilization and conversion rates, this application creates and publishes charging preferential plans through the charging business system, which can attract users to quickly and accurately absorb flexible load electricity, realize the maximum use of the power generation of the photovoltaic system without abandoned light conditions, and accurately convert the surplus power of the photovoltaic system into benefits, which is conducive to improving the intelligence, comprehensiveness and flexibility of the photovoltaic data processing of the photovoltaic storage energy management system, and improving the utilization and conversion rate of photovoltaic resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0014] Figure 1This is a system architecture diagram of a photovoltaic energy storage management system provided by an embodiment of the present application;

[0015] Figure 2 This is a structural block diagram of an electronic device provided in an embodiment of the present application;

[0016] Figure 3 This is an overall flow chart of an energy management method based on a smart energy meter provided in an embodiment of the present application;

[0017] Figure 4 This is an electrical system diagram of a photovoltaic power generation grid-connected provided in an embodiment of the present application;

[0018] Figure 5 This is an application scenario diagram of an energy management method based on a smart electricity meter provided in an embodiment of the present application. DETAILED DESCRIPTION

[0019] In order to enable those skilled in the art to better understand the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0020] The terms "first," "second," and the like in the specification and claims of this application and the accompanying drawings are used to distinguish between different objects, not to describe a particular order. Furthermore, the terms "including," "having," and any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or apparatus comprising a series of steps or elements is not limited to the listed steps or elements but may optionally include steps or elements not listed, or may optionally include other steps or elements inherent to the process, method, product, or apparatus.

[0021] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute an independent or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0022] In the embodiments of this application, "and / or" describes the relationship between associated objects and indicates that three relationships can exist. For example, "A and / or B" can represent the following three situations: A exists alone; A and B exist simultaneously; and B exists alone. A and B can be singular or plural.

[0023] In the embodiments of the present application, the symbol " / " can indicate that the preceding and following objects are in an "or" relationship. In addition, the symbol " / " can also represent a division sign, that is, performing a division operation. For example, A / B can mean A divided by B.

[0024] In the embodiments of the present application, "at least one item" or similar expressions refers to any combination of these items, including any combination of single items or plural items, and refers to one or more, and multiple refers to two or more. For example, at least one item (item) of a, b, or c can represent the following seven situations: a, b, c, a and b, a and c, b and c, a, b, and c. Among them, each of a, b, and c can be an element or a set containing one or more elements.

[0025] In the embodiments of this application, "equal to" can be used in conjunction with "greater than" and is applicable to the technical solution adopted when "greater than" is used, and can also be used in conjunction with "less than" and is applicable to the technical solution adopted when "less than" is used. When "equal to" is used in conjunction with "greater than", it should not be used in conjunction with "less than"; when "equal to" is used in conjunction with "less than", it should not be used in conjunction with "greater than".

[0026] With the continuous integration of information technology, communications technology, and power technology, smart grids have become a new direction for the development of power systems. Smart grids emphasize comprehensive perception, intelligent decision-making, and optimized control of the power system, enabling efficient transmission, distribution, and utilization of electricity. As a key component of the smart grid, the photovoltaic energy storage management system can operate in coordination with other smart grid components to enhance the intelligence level of the grid. To achieve efficient energy utilization and cost control, refined management of energy production, transmission, storage, and consumption is necessary. The photovoltaic energy storage management system uses a server to perform real-time monitoring and data analysis of photovoltaic systems, energy storage systems, and power loads, enabling optimized energy allocation and management, improving energy utilization efficiency, and reducing energy costs.

[0027] Currently, existing energy management solutions lack the coordinated management of photovoltaics and energy storage, and are mainly based on single energy management. They are unable to achieve real-time dynamic regulation of the energy system. When faced with the uncertainty of photovoltaic power generation and changes in load demand, they cannot quickly and accurately adjust energy distribution and operation strategies. They are also unable to solve the problem of the difficulty in fully handling surplus power in photovoltaic systems based on flexible load power consumption without curtailment over multiple natural days.

[0028] In response to the above problems, an embodiment of the present application provides an energy management method and system based on a smart electricity meter. The embodiment of the present application is described in detail below with reference to the accompanying drawings.

[0029] See also Figure 1 , Figure 1This is a system architecture diagram of a photovoltaic energy storage management system provided by an embodiment of the present application, such as Figure 1 As shown, the system architecture diagram of the photovoltaic energy storage management system 100 includes a server, a photovoltaic system, an energy storage system and an electrical load.

[0030] A photovoltaic system typically includes photovoltaic modules, inverters, and combiner boxes. Specifically, photovoltaic modules are the core components that convert solar energy into electrical energy. They consist of multiple solar panels and convert sunlight into DC power through the photoelectric effect. The inverter converts the DC power generated by the photovoltaic modules into AC power to power AC loads or connect to the AC grid. It also features maximum power point tracking (MPPT), automatically adjusting the operating point of the photovoltaic modules to keep them operating near their maximum power point, improving photovoltaic power generation efficiency. The combiner box aggregates the output current from multiple photovoltaic module strings and transmits it to the inverter or other equipment, facilitating system wiring and management. It also provides overcurrent protection and lightning protection to ensure the safe operation of the photovoltaic system.

[0031] Energy storage systems typically include battery packs, battery management systems (BMS), and bidirectional converters. Specifically, battery packs are the core component of energy storage systems, used to store electrical energy. Common battery types include lead-acid batteries, lithium-ion batteries, and flow batteries. Different types of batteries have different performance characteristics and applicable scenarios. The battery management system monitors and manages the battery pack in real time, monitoring parameters such as battery voltage, current, temperature, and SOC (state of charge) to prevent overcharging, overdischarge, and overheating, ensuring the safe operation of the battery pack. It also manages the battery pack for balancing and improves its overall performance and service life. The bidirectional converter implements bidirectional power conversion between the battery pack and the power grid or other equipment. During charging, it converts the AC power from the power grid or photovoltaic system into DC power to charge the battery pack. During discharge, it converts the DC power from the battery pack into AC power to power the load or transmit it to the power grid.

[0032] Among them, the power load includes various electrical equipment, such as industrial production equipment, commercial office equipment, residential household appliances and other equipment that need to consume electricity. They are the power consumption terminals of the photovoltaic energy storage management system 100, and their power demand is diverse and uncertain.

[0033] Furthermore, the photovoltaic energy storage management system 100 may also include a smart electricity meter, which may be a smart electricity meter installed on the AC output side of the photovoltaic system. The smart electricity meter is used to count the amount of electricity delivered by the photovoltaic system to the power grid and / or the power load of the target business site.

[0034] Among them, the server is connected to the photovoltaic system, energy storage system, power load and smart electricity meter respectively for data collection and monitoring, as well as for data analysis and decision-making. Specifically, the server is used to create and publish charging preferential plans for the target business site based on the historical electricity data of the smart electricity meter, the business reservation information of the target business site in the future time period, the power load and the storable current of the energy storage system to absorb the flexible load electricity.

[0035] It can be seen that in this embodiment, the server creatively proposes a solution for absorbing the surplus electricity of the photovoltaic system without abandoned light based on flexible load power in the dimension of multiple consecutive natural days, aiming at the photovoltaic energy storage management needs in the future period of the target business site. The flexible load power absorption is deeply integrated with the charging business of new energy vehicles in the target business site. The charging business system creates and publishes charging preferential plans, which can attract users to absorb flexible load power quickly and accurately. On the one hand, it realizes the maximum use of the power generation of the photovoltaic system without abandoned light, and on the other hand, it accurately converts the surplus power of the photovoltaic system into benefits.

[0036] See also Figure 2 , Figure 2 This is a block diagram of an electronic device provided in an embodiment of the present application, for executing Figure 1 The photovoltaic energy storage management system in Figure 2 As shown, the electronic device 20 may include one or more of the following components: a memory 23, a processor 21, a communication bus 30, a communication interface 22, and one or more programs 231. The one or more programs 231 are stored on the memory 23 and are configured to be executed by the processor 21. The one or more programs 231 include instructions for executing any step in the following method embodiments. In a specific implementation, the processor 21 is used to execute any step in the following method embodiments, and when performing data transmission such as sending, the communication interface 22 may be selectively called to complete the corresponding operation. The electronic device 20 may be a mobile phone terminal, a tablet computer, a laptop computer, or a wearable smart device.

[0037] The processor 21 may include one or more processing cores. The processor 21 utilizes various interfaces and circuits to connect the various components within the electronic device 20. It executes instructions, programs, code sets, or instruction sets stored in the memory 23, as well as accesses data stored in the memory 23, to perform various functions and process data within the electronic device 20. Optionally, the processor 21 may be implemented using at least one of the following hardware forms: a digital signal processing (DSP), a field-programmable gate array (FPGA), or a programmable logic array (PLA). The processor 21 may integrate one or a combination of a central processing unit (CPU), a graphics processing unit (GPU), and a modem. The CPU primarily processes the operating system, user interface, and application programs; the GPU is responsible for rendering and drawing display content; and the modem handles wireless communications. It is understood that the modem may not be integrated into the processor 21 and may be implemented separately via a communication chip.

[0038] The memory 23 may include a random access memory (RAM) or a read-only memory (ROM). The memory 23 may be used to store instructions, programs, codes, code sets, or instruction sets. The memory 23 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for implementing at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned various method embodiments, etc. The data storage area may also store data created by the electronic device 20 during use.

[0039] It is understandable that the electronic device 20 may include more or fewer structural elements than those in the above structural block diagram, for example, a power module, physical buttons, a Wi-Fi module, a speaker, a Bluetooth module, a sensor, etc., which are not limited here.

[0040] See also Figure 3 , Figure 3 This is an overall flow chart of an energy management method based on a smart energy meter provided in an embodiment of the present application, which is applied to Figure 1 Servers in Figure 3 As shown, the method includes the following steps:

[0041] Step S301, based on the historical electricity data of the smart electricity meter and the business reservation information of the target business site in the future time period, determine the expected power generation of the photovoltaic system on each natural day in the future time period under the condition of no abandoned light, and the business reservation information includes business project information and vehicle information of the self-driving vehicle.

[0042] Among them, the business reservation information for the target business venue in the future time period may include business project information related to the electricity consumption characteristics and electricity consumption time arrangements of different businesses. For example, if the scheduled business project is a large-scale conference, the electricity demand for lighting, electronic equipment, etc. during the meeting will be large and concentrated, which will affect the absorption of photovoltaic system power generation. Vehicle information of self-driving vehicles, such as the number of vehicles and whether they have charging needs, will also affect the power load. If there are many self-driving vehicles that need to be charged, the demand for electricity will increase during the charging period. By comprehensively considering this business reservation information, the changes in power load in the future time period can be more accurately estimated, and then a more reasonable judgment can be made on the demand and absorption of photovoltaic system power generation.

[0043] Among them, historical power data includes basic power data, power parameter data, time-related data and other operating data.

[0044] Specifically, basic power data includes active energy, reactive energy, and apparent energy. Active energy records the cumulative value of active energy actually consumed by the PV system or delivered to the grid, and can be used to measure the PV system's power generation capacity and actual power generation. Reactive energy reflects the cumulative value of reactive energy exchanged between the PV system and the grid, and can be used to assess the PV system's contribution to or demand for reactive power on the grid. Apparent energy is the vector sum of active energy and reactive energy, reflecting the total energy transmission capacity of the PV system and helping to fully understand the overall situation of the PV system in power transmission.

[0045] Specifically, electrical parameter data includes voltage data, current data, and power data. Voltage data includes the phase and line voltage data output by the photovoltaic system, recording voltage values ​​at different times and crucial for determining the operating status and power quality of the photovoltaic system. Current data records the phase and line currents output by the photovoltaic system. Combining current data with voltage data can calculate other important parameters such as power, and also reflect the load conditions and power generation of the photovoltaic system. Power data includes active power, reactive power, and apparent power. Active power represents the actual power output of the photovoltaic system for work per unit time, and is an important indicator for measuring the photovoltaic system's power generation capacity and real-time power generation status. Reactive power reflects the reactive power exchanged between the photovoltaic system and the power grid per unit time, and is used to assess the impact of the photovoltaic system on the reactive power balance of the power grid. Apparent power is the vector sum of active power and reactive power, reflecting the total power output capacity of the photovoltaic system.

[0046] Specifically, time-related data primarily includes timestamps, which accurately record the time each set of power and electrical parameter data was collected, typically down to the second or even millisecond. Timestamps are key to ensuring data's temporal sequence and traceability. They enable accurate sequencing and correlation of data at different moments, facilitating analysis of PV system operation over time.

[0047] Specifically, other operational data includes power factor and frequency. Power factor is the ratio of active power to apparent power, reflecting the efficiency of the PV system's energy utilization and its impact on the grid. A higher power factor indicates high energy utilization efficiency and minimal impact on the grid load. Frequency, on the other hand, records the frequency of the PV system's output power. Frequency data can be used to determine the synchronization between the PV system and the grid and its operational stability.

[0048] In a possible embodiment, determining the expected power generation of the photovoltaic system on each natural day in the future period under the condition that there is no abandoned light, based on the historical power data of the smart power meter and the service reservation information of the target service site in the future period, includes:

[0049] Collecting and analyzing historical electric energy data of the photovoltaic system sampled and created by the smart electric energy meter to obtain a corresponding relationship between the actual power generation of the photovoltaic system under no abandoned light conditions and the lighting conditions;

[0050] Obtaining weather data for each natural day of the target business site in a future period, the weather data including lighting conditions;

[0051] The expected power generation of the photovoltaic system on each natural day under the condition that there is no abandoned light is determined based on the corresponding relationship and the weather data.

[0052] In a possible embodiment, the smart energy meter may be a smart energy meter installed on the AC output side of the photovoltaic system; before collecting and analyzing the historical energy data of the photovoltaic system sampled and created by the smart energy meter to obtain the corresponding relationship between the actual power generation of the photovoltaic system under the condition of no abandoned solar power and the illumination conditions, the method further includes:

[0053] Receiving sampling data and timestamp reported by the smart electric energy meter;

[0054] Query and obtain the lighting condition of the photovoltaic system at the timestamp;

[0055] Determining a reference abandonment rate of the photovoltaic system at the timestamp;

[0056] The historical electric energy data is created according to the lighting condition, the reference abandoned light rate and the sampling data.

[0057] As you can understand, smart energy meters are used to measure the amount of electricity delivered by the photovoltaic system to the grid and / or the load at the target business site. By sampling AC current and voltage signals and using digital signal processing techniques, smart meters can calculate parameters such as active and reactive energy and report them to a server. After receiving the sampled data, the server queries the weather system or uses light sensors installed on the photovoltaic panels to obtain timestamps of lighting conditions. Finally, the server creates and stores historical energy data based on the lighting conditions and the sampled data.

[0058] For example, the target business venue can be a hotel, a resort, an integrated amusement park, etc. For example, in a resort's solar energy storage management system, the smart energy meter reports sampled data every 15 minutes, such as the current, voltage, and other data recorded at 9:15 a.m., along with the corresponding timestamp. The sampled data and timestamp are then reported to the server, which then queries the corresponding lighting conditions based on the timestamp. The lighting conditions can be sourced from a professional meteorological data platform or from light sensors installed within the resort. For example, the server can query that the light intensity at 9:15 a.m. is 800 lux.

[0059] In a possible embodiment, determining a reference abandonment rate of the photovoltaic system at the timestamp includes:

[0060] determining a theoretical output power of the photovoltaic system at the timestamp according to the illumination condition and the configuration information of the photovoltaic system;

[0061] Obtaining a sampled output power of the photovoltaic system at the timestamp;

[0062] A reference abandonment rate of the photovoltaic system at the timestamp is determined according to the theoretical output power and the sampled output power.

[0063] Among them, the reference abandonment rate is used to measure the proportion of electricity generated by photovoltaic components in a photovoltaic system at a specific time stamp that cannot be effectively utilized or transmitted to the grid due to various factors and is discarded.

[0064] In a possible embodiment, determining the theoretical output power of the photovoltaic system at the timestamp according to the illumination condition and the configuration information of the photovoltaic system includes:

[0065] Obtaining the maximum power and power temperature coefficient of the photovoltaic components in the photovoltaic system; and

[0066] Obtaining the actual light intensity of the photovoltaic system at the timestamp and the standard test light intensity;

[0067] Determining a temperature difference between a first temperature of the photovoltaic assembly in an actual operating scenario and a second temperature in a standard test scenario;

[0068] The theoretical output power of the photovoltaic system at the timestamp is determined based on the maximum power, the power temperature coefficient, the actual light intensity, the standard test light intensity, and the temperature difference, taking into account the series-parallel relationship of the photovoltaic components.

[0069] Specifically, the embodiment of the present application provides a method for calculating the reference abandonment rate, which is calculated based on theoretical and sampled output power. The theoretical output power of the photovoltaic system at a certain timestamp is the power that the photovoltaic system should be able to output under the lighting conditions. At the same time, the actual sampled output power of the photovoltaic system at the timestamp can be obtained through devices such as smart electricity meters. The reference abandonment rate can be determined based on the theoretical output power and the sampled output power. The calculation formula is as follows:

[0070] Reference abandoned light rate = .

[0071] The calculation formula for the theoretical output power of the photovoltaic system is as follows: ;

[0072] in, is the theoretical output power of the photovoltaic system under specific lighting conditions, is the maximum power of the photovoltaic module, is the actual light intensity under specific lighting conditions, is the standard test light intensity under standard test conditions, is the power temperature coefficient of the photovoltaic module, It is the temperature difference between the actual operating temperature of the photovoltaic module and the standard test temperature.

[0073] Among them, the maximum power Generally available from the technical parameter table of the photovoltaic module; actual light intensity under specific lighting conditions Can be obtained through local meteorological data or using professional light intensity measurement equipment; standard test light intensity Usually the value is 1000W / ;Power temperature coefficient It is generally between -0.3% / ℃ and -0.5% / ℃, and can also be obtained from the component technical parameter table; the standard test temperature for photovoltaic modules is usually 25℃.

[0074] Furthermore, we need to consider the impact of the series and parallel relationship of photovoltaic modules on the theoretical output power of the photovoltaic system at that time stamp. If the photovoltaic system consists of multiple photovoltaic modules connected in series and in parallel, first calculate the total series resistance and parallel resistance and other parameters based on the circuit principles of series and parallel connection, and then calculate them based on the above basic formula. For example, the number of modules in series is , the number of components in parallel is , then the theoretical output power calculation formula of the photovoltaic system is as follows: ;

[0075] in, is the theoretical output power of the photovoltaic system when photovoltaic modules are connected in series and parallel, is the number of PV modules connected in series, is the number of PV panels connected in parallel.

[0076] Furthermore, the actual photovoltaic system also needs to consider the system efficiency , including factors such as inverter efficiency, line loss, and dust shielding. Generally, the system efficiency is between 75% and 90%. At this time, the theoretical output power of the photovoltaic system is calculated as follows: ;

[0077] in, is the theoretical output power of the photovoltaic system considering the efficiency of the photovoltaic system, is the efficiency of the photovoltaic system.

[0078] For example, the maximum power of the photovoltaic system is 300W, the power temperature coefficient is -0.4% / °C, and the actual light intensity at a certain moment is 800W / , the actual working temperature is 35℃, then the temperature difference between the actual working temperature and the standard test temperature can be obtained =35-25=10℃, then we can get the theoretical output power of the photovoltaic system under specific lighting conditions. =300× × (1-0.4% × 10) = 220.8 W. Further, assuming that the photovoltaic system includes 10 photovoltaic modules connected in series and 5 sets of such series circuits in parallel, and the photovoltaic system efficiency is 85%, we can get =10×5×220.8=11040W, =11040×85%=9384W.

[0079] For example, if the actual sampling output power of the photovoltaic system is 7500W, the reference abandoned light rate can be obtained = ×100%=20%.

[0080] In a possible embodiment, determining a reference abandonment rate of the photovoltaic system at the timestamp includes:

[0081] Obtaining an operation log of the photovoltaic system generated based on status data reported by the backflow prevention table of the photovoltaic system, the status data including a backflow status indicator reported by the backflow prevention table, a first output power of the photovoltaic system before the backflow occurs, and a second output power of the photovoltaic system after the backflow occurs;

[0082] A reference abandonment rate of the photovoltaic system at the timestamp is determined according to the first output power and the second output power.

[0083] It can be seen that the embodiment of the present application provides another calculation method for the reference abandonment rate, which is determined by comparing the difference in output power before and after the reverse flow occurs. Among them, the anti-backflow meter can detect the reverse flow phenomenon from the photovoltaic system to the power grid. When a reverse flow occurs, it means that the photovoltaic system may have a power generation capacity that exceeds the local load demand. The server adjusts the output power of the photovoltaic system according to the data reported by the anti-backflow meter. This part of the power generation reduced due to the adjustment can reflect the abandonment situation to a certain extent. By analyzing the changes in these data in the operation log, the power adjustment information caused by the anti-backflow control can be obtained, so as to perform certain analysis and calculations on the abandonment situation.

[0084] Furthermore, the server's operation logs typically include detailed status data reported by the backflow prevention meter, such as power sampling signals at different times, the time and power level of backflow, and so on. This data is traceable and relatively complete, providing a reliable basis for analyzing the curtailment rate. By organizing and calculating this data, we can understand the power changes of the PV system under backflow prevention control and thus estimate the curtailment rate.

[0085] It is understood that the first output power of the PV system before the reverse flow occurs represents the power generation capacity and output level of the PV system when the reverse flow does not occur. The second output power of the PV system after the reverse flow occurs is usually reduced due to the anti-reverse flow mechanism, reflecting the actual output of the PV system after the anti-reverse flow measures are implemented. By comparing the output power difference before and after the reverse flow occurs, the power loss caused by the anti-reverse flow measures can be determined, and then the reference curtailment rate can be calculated to measure the proportion of PV power that is not effectively utilized due to the anti-reverse flow factors at that time stamp.

[0086] For example, in the photovoltaic system of the resort, at the time stamp of 10:00 am, the operation log reported by the anti-backflow meter shows the reverse flow status mark, and the mark is "yes", that is, the power reverse flow occurred at this moment; and it shows that before the reverse flow occurred, the first output power of the photovoltaic system =200kW, which means that when there is no reverse flow restriction, the power generation output of the photovoltaic system can reach 200kW; and it shows that after reverse flow occurs, the second output power of the photovoltaic system =150kW, this is because the anti-backflow device is activated, which adjusts the output of the photovoltaic system, resulting in a decrease in output power, and then the reference abandoned light rate can be calculated = ×100%= ×100%=25%.

[0087] In a possible embodiment, the counting and analyzing of historical electric energy data of the photovoltaic system sampled and created by the smart electric energy meter to obtain a correspondence between actual power generation of the photovoltaic system under no abandoned light conditions and illumination conditions includes:

[0088] Get the preset lighting condition classification table;

[0089] Classify the historical electric energy data according to the lighting condition classification table to obtain multiple historical electric energy data sets corresponding to multiple types of lighting conditions;

[0090] Filter each of the historical power data sets according to the reference curtailment rate to obtain historical power data after removing sampled data with curtailment.

[0091] Performing parameter denoising and averaging processing on the filtered historical electric energy data to obtain the actual power generation;

[0092] A correspondence between the actual power generation of the photovoltaic system under the condition of no abandoned light and the lighting conditions is established.

[0093] The lighting condition classification table may divide parameter intervals by referring to typical lighting condition types of the weather system.

[0094] The denoising of parameter values ​​of the filtered historical electric energy data includes identifying abnormal values ​​and removing abnormal values.

[0095] In a possible embodiment, filtering each historical power data set according to the reference curtailment rate to obtain historical power data after removing sampled data with curtailment includes:

[0096] Obtaining a reference curtailment rate corresponding to each piece of historical power data in each historical power data set;

[0097] Determine whether the reference curtailment rate corresponding to each piece of historical power data in each historical power data set is greater than a preset threshold;

[0098] The historical power data with a reference abandonment rate greater than the preset threshold is removed from the corresponding historical power data set to obtain the historical power data after the sampling data with abandonment is screened out.

[0099] For example, the lighting condition classification table may include lighting intensity intervals and their corresponding lighting intensity levels. For example, 0-200 lux is considered weak light, 201-500 lux is considered medium light, 501-800 lux is considered strong light, and 801 lux and above is considered strong light. The server reads electricity data recorded every 15 minutes over the past month, including multiple similar records such as "2025-01-09:15, light intensity 300 lux, power generation 10 kWh." The server then classifies each record into different lighting intensity intervals and levels. For each data item in each historical electricity data set, the server determines whether its corresponding reference curtailment rate exceeds a set threshold, such as 5%. For example, if the reference curtailment rate for a data record is 8%, if it exceeds 5%, the data is considered to have curtailed power and is removed from the corresponding historical electricity data set.

[0100] Furthermore, the parameter values ​​of the filtered historical electric energy data are denoised and averaged to obtain the actual power generation. Then, the corresponding relationship between the actual power generation of the photovoltaic system under the condition of no abandoned light and the lighting conditions can be obtained. For example: weak light - the actual power generation is an average of 3 degrees; medium light - the actual power generation is an average of 10 degrees; relatively strong light - the actual power generation is an average of 18 degrees; strong light - the actual power generation is an average of 25 degrees.

[0101] It can be seen that in this embodiment, by comprehensively considering historical power generation data, future business electricity demand and other factors, the expected power generation of the photovoltaic system on each natural day in the future period can be predicted more accurately. Compared with the prediction based solely on the relationship between historical sunlight and power generation, the changes in power load in actual business scenarios are taken into account, making the prediction results more in line with the actual situation, which helps to reasonably arrange the operation and maintenance of the photovoltaic system, prepare necessary maintenance resources and equipment in advance, reduce energy waste or insufficient supply caused by inaccurate power generation predictions, and improve the overall operation efficiency and reliability of the photovoltaic energy storage management system.

[0102] Step S302 : determining the estimated basic load power of each natural day at the target business site without the charging load of the new energy vehicle among the self-driving vehicles based on the business project information and the power load.

[0103] Specifically, different business projects have different electricity consumption characteristics and needs. Their basic electricity load can be determined based on the type, scale and operating hours of the business project. For example, the business hours of a large supermarket are usually from 9 am to 10 pm. During this period, the lighting system, refrigeration equipment, cash register system, etc. will continue to use electricity. The basic electricity load of the supermarket business can be calculated based on the power and operating time of these devices.

[0104] Specifically, in addition to the electrical equipment of the business project itself, the power load may also include some other basic power facilities, such as the building's public area lighting and ventilation system. Although these power loads are not directly related to the business project, they are also necessary for the normal operation of the target business site. For example, the power loads of the office building's public area lighting and elevator operation are relatively fixed and need to be included in the calculation of the expected basic load electricity.

[0105] It's understandable that by combining business project information and power load data, the estimated base load electricity consumption for each calendar day at the target business site, assuming no new energy vehicle charging loads, can be calculated. This requires detailed statistics and calculations of the power consumption and operating hours of various types of electrical equipment. The estimated base load electricity consumption for each calendar day can then be calculated by summing up the power consumption of all stores within a shopping mall, as well as the power consumption of public area lighting and air conditioning equipment. This can yield the estimated base load electricity consumption for the mall, assuming no new energy vehicle charging.

[0106] Step S303, based on the expected power generation of each natural day, the expected basic load power and the storable power of the energy storage system, determine the flexible load power of the photovoltaic system that can be consumed by the new energy vehicle in the self-driving vehicle on each natural day.

[0107] In a possible embodiment, determining the flexible load power of the photovoltaic system that can be consumed by the new energy vehicle in the self-driving vehicle on each natural day based on the expected power generation on each natural day, the expected base load power, and the storable power of the energy storage system includes:

[0108] Determining a minimum guaranteed power capacity for each natural day of the energy storage system without requiring grid power during the future period based on the estimated power generation for each natural day, the estimated base load power, and the storable power;

[0109] The flexible load power of the photovoltaic system that can be absorbed by the new energy vehicle in the self-driving vehicle on each natural day is determined based on the expected power generation, the expected basic load power and the minimum guaranteed power.

[0110] It is understandable that on the first day of the future period, the power generation of the photovoltaic system and the original storage capacity of the energy storage system can meet the expected basic load power demand of the day, that is, the city power will not be called on on the first day.

[0111] Among them, the flexible load power consumed by new energy vehicles can be calculated by the following formula:

[0112] Flexible load power = expected power generation - expected base load power - minimum guaranteed power.

[0113] In a possible embodiment, before determining the minimum guaranteed power capacity of each natural day for the energy storage system in the future period without requiring grid power based on the estimated power generation for each natural day, the estimated base load power, and the storable power, the method further includes:

[0114] Determining the total expected power generation in the future period based on the expected power generation for each natural day;

[0115] Determine the total expected base load electricity for the future period based on the expected base load electricity for each natural day;

[0116] It is detected that the total projected power generation is greater than the total projected base load power.

[0117] For example, the future time period may be the next week. Based on historical data and weather forecasts, the resort's photovoltaic system is expected to generate 1000 kWh, 1200 kWh, 1100 kWh, 1300 kWh, 1200 kWh, 1000 kWh, and 900 kWh of power per day from Monday to Sunday, respectively. The total expected power generation for this week is 1000+1200+1100+1300+1200+1000+900=7700 kWh. In addition, the resort's expected base load power (including lighting, equipment operation, etc.) is 800 kWh, 900 kWh, 850 kWh, 1000 kWh, 950 kWh, 800 kWh, and 750 kWh per day from Monday to Sunday, respectively. The total expected base load power is 800+900+850+1000+950+800+750=6050 kWh.

[0118] Furthermore, by comparing the total expected power generation of 7,700 kWh with the total expected base load power of 6,050 kWh, it was found that the total expected power generation was greater than the total expected base load power, which means that the photovoltaic system theoretically has excess power available for other uses.

[0119] It is understandable that if it is detected that the total expected power generation is not greater than the total expected basic load power, it is necessary to call on the mains power to meet the basic power demand of the target business site. In this case, the power generation of the photovoltaic system can be fully used, that is, there is no flexible load power as the surplus power of the photovoltaic system. Therefore, the system does not need to create an additional charging discount plan, and can carry out the charging business of new energy vehicles according to the conventional charging plan.

[0120] In a possible embodiment, the determining of the minimum guaranteed power of each natural day for the energy storage system without requiring grid power in the future period based on the estimated power generation of each natural day, the estimated base load power, and the storable power includes:

[0121] Determining the storable surplus electricity of the photovoltaic system on each natural day based on the estimated power generation on each natural day, the estimated base load power, and the storable power, wherein the storable surplus electricity includes a positive state and a negative state, wherein the positive state indicates that the photovoltaic system has a positive surplus in the estimated power generation on the current natural day, and the negative state indicates that the photovoltaic system has no positive surplus in the estimated power generation on the current natural day and the minimum power that the energy storage system needs to store before the current natural day in order to meet the power demand on the current natural day;

[0122] Based on the storable remaining electricity of each natural day, the minimum guaranteed electricity of each natural day in the future period without calling on the power of the grid is obtained by reasoning day by day according to the order of multiple natural days in the future period from the back to the front.

[0123] The minimum guaranteed power level refers to the minimum amount of energy that the energy storage system must store each calendar day, under specific conditions, to ensure it meets future electricity demand without requiring additional power from the grid. If the PV system's projected power generation for a given day exceeds the projected baseload power, a positive difference indicates excess power can be stored in the energy storage system. A negative difference indicates that the projected power generation for that day will not meet the projected baseload power, and the energy storage system will need to store a certain amount of power before that day to make up for the shortfall. This amount is the daily storable surplus power and serves as the basis for determining the minimum guaranteed power level.

[0124] Specifically, when determining the minimum guaranteed energy level, the system must reason through the future calendar days one by one, starting from the last day. For example, first determine the minimum guaranteed energy level for the last day. If the remaining storable energy on the last day is positive, the minimum guaranteed energy level is the remaining storable energy level. Next, consider the previous day. If the remaining storable energy on the previous day is less than the minimum guaranteed energy level for the next day, the minimum guaranteed energy level for the previous day is the minimum guaranteed energy level for the next day minus the remaining storable energy level. This process continues in this order, ensuring that the energy storage system's stored energy can meet subsequent power demand each day without relying on grid power.

[0125] For example, suppose a hotel's photovoltaic energy storage management system requires priority use of the photovoltaic system's unwasted power generation and minimizes the use of mains electricity. If the hotel's business reservation information for the next three days is known, the weather conditions can be learned from the weather forecast system, the energy storage system can store 600 kWh of electricity, and the initial power state of the energy storage system on the first day is 0, the expected power generation from the first to the third day is 800 kWh, 550 kWh, and 300 kWh respectively, and the expected base load power from the first to the third day is 500 kWh, 500 kWh, and 400 kWh respectively. Then, the total power generation of the photovoltaic system is 1650 kWh, and the total expected base load power is 1400 kWh. Based on the fact that 1650 is greater than 1400, it is determined that there is no need to borrow mains electricity, and balance can be achieved based on the charging and discharging capacity of the energy storage system.

[0126] Furthermore, on the first day, the hotel's photovoltaic storage system's power generation minus the base load power generation is 800-500=300 kWh, and the energy storage system can store 300 kWh of surplus power. On the second day, the hotel's photovoltaic storage system's power generation minus the base load power generation is 550-500=50 kWh, and there is no need to borrow city power. The energy storage system can store 50 kWh of surplus power. On the third day, the hotel's photovoltaic storage system's power generation minus the base load power generation is 300-400=-100 kWh of surplus power, and the surplus power that can be stored is -100 kWh. Therefore, it is analyzed that the minimum daily power consumption of the energy storage system without calling on the grid power in three natural days is 50 kWh, 50 kWh, and 0 kWh. Correspondingly, the flexible load power that can be absorbed by the new energy vehicles of the photovoltaic system on each natural day is 250 kWh, 0 kWh, and 0 kWh.

[0127] It can be seen that in this embodiment, by calculating the minimum guaranteed power and flexible load power, it is possible to clearly determine how much power the energy storage system needs to store to guarantee the basic load, and how much surplus power the photovoltaic system has available for new energy vehicles to consume. This achieves a reasonable distribution of energy between the basic load, energy storage, and new energy vehicle charging, allowing the electricity generated by the photovoltaic system to be more fully utilized, reducing the waste of electricity, and reducing the interaction with the power grid, alleviating the burden on the power grid, and also reducing electricity costs to a certain extent.

[0128] Step S304 : creating and publishing a preferential charging plan for the target business site based on the flexible load power and the vehicle information of the self-driving vehicle to absorb the flexible load power.

[0129] For example, the target business site is a large shopping mall equipped with a photovoltaic system and an energy storage system, and customers often drive new energy vehicles to shop. Among them, the vehicle information of self-driving vehicles may include 10 cars A with a battery capacity of 60kWh and 8 cars B with a battery capacity of 76.9kWh. The currently determined flexible load power is 500kWh per day. Furthermore, taking car A as an example, if its average remaining power is 30%, the power required for each car is approximately 60×(1-30%)=42kWh, and then the 10 cars A require a total of 420kWh of power. Similarly, the power required for 8 cars B can be obtained.

[0130] Furthermore, based on the flexible load power and vehicle charging demand, charging preferential plans for target business sites can be created and released, including discounts based on charging volume, time-based discounts, and member-only discounts.

[0131] Specifically, there are discounts based on charging volume. For example, when a customer's charging volume reaches 20kWh or above, they can enjoy a discount of 0.5 yuan per kilowatt-hour; and if the customer's charging volume reaches a certain proportion of the flexible load power allocation (such as 80%), they will be given a certain amount of additional points, which can be exchanged for goods or services in the mall.

[0132] Specifically, time-of-day discounts can be implemented by factoring in the PV system's power generation characteristics and the mall's operating hours, offering different discounts for different charging periods. For example, if the mall's operating hours are 10:00 AM to 10:00 PM, charging during the 12:00 PM to 4:00 PM period, when the PV system is generating sufficient power, can offer a 20% discount. During other periods, the discounts are relatively smaller. This can encourage car owners to charge when PV power generation is sufficient, better accommodating flexible load power.

[0133] Specifically, exclusive member discounts could include additional charging discounts for mall members. For example, Silver Card members can enjoy a 0.3 RMB discount per kilowatt-hour, while Gold Card members can enjoy a 0.5 RMB discount and double their points. This approach not only attracts more members to the mall but also promotes the charging of new energy vehicles and improves the efficiency of flexible load power consumption.

[0134] It can be seen that in this embodiment, in response to the photovoltaic energy storage management needs of the target business site in the future period, a solution is creatively proposed to absorb the surplus electricity of the photovoltaic system without abandoned light conditions based on flexible load power in the dimension of multiple consecutive natural days, and the flexible load power absorption is deeply integrated with the charging business of new energy vehicles in the target business site. The creation and release of charging preferential plans through the charging business system can attract users to quickly and accurately absorb flexible load power. On the one hand, it realizes the maximum use of the power generation of the photovoltaic system without abandoned light conditions, and on the other hand, it carries out accurate benefit conversion of the surplus electricity of the photovoltaic system, which is conducive to improving the intelligence, comprehensiveness and flexibility of the photovoltaic data processing of the photovoltaic energy storage energy management system, and improving the utilization rate and conversion rate of photovoltaic resources.

[0135] See also Figure 4 , Figure 4 This is an electrical system diagram of a photovoltaic power generation grid-connected provided by an embodiment of the present application, such as Figure 4 As shown, the electrical system includes a power grid, a 35kV high-voltage bus, a high-voltage transformer, a high-voltage backflow prevention device, a 10kV high-voltage bus, a low-voltage transformer, a first load, a second load, a 400V low-voltage bus, a third load, a grid connection point, an energy storage system, a smart electricity meter and a photovoltaic system.

[0136] Among them, the power grid is connected to the system through a 35kV high-voltage bus and is transformed by a high-voltage transformer. The high-voltage transformer can be a 35 / 10kV transformer, which can convert 35kV voltage into 10kV, realizing the initial voltage reduction transmission of high-voltage electric energy; then, the 10kV electric energy after the voltage reduction by the high-voltage transformer is collected on the 10kV high-voltage bus, and then further reduced by a low-voltage transformer. The low-voltage transformer can be a 10 / 0.4kV transformer, which can convert 10kV voltage into 400V, realizing the final voltage reduction transmission of high-voltage electric energy, and connected to the 400V low-voltage bus to supply power to various loads, such as the first load and the second load; further, the 400V low-voltage bus is connected to a third load, a photovoltaic system, an energy storage device, etc., which is a key node for terminal power distribution and energy interaction.

[0137] Among them, the high-voltage backflow prevention device is located between the high-voltage transformer and the input side of the 10kV bus voltage. It is used to prevent the electric energy generated by the photovoltaic system from flowing back into the power grid, ensuring that the flow of electric energy on the 10kV high-voltage bus side meets the requirements, and ensuring the stability of the power grid and the effective absorption of electric energy.

[0138] Among them, the photovoltaic system is connected to the 400V low-voltage bus grid connection point, and the electricity it generates is preferentially used by the third load. The excess electricity can be stored or connected to the grid; the smart electricity meter is located between the photovoltaic system and the grid connection point, and is used to measure the amount of electricity transmitted by the photovoltaic system to the grid or load, providing data support for energy management and billing; the energy storage system is connected to the 400V low-voltage bus, and can store electricity when there is excess photovoltaic power, such as releasing electricity for use by the third load at night or when there is insufficient light, reducing dependence on the grid, and can coordinate with the photovoltaic system, load and backflow prevention device to optimize energy utilization efficiency.

[0139] It can be seen that the photovoltaic energy storage management system in this application selects a high-voltage backflow prevention solution, and the high-voltage backflow prevention device is arranged on the incoming line side of the 10kV high-voltage bus, which can enable more loads under the 10kV high-voltage bus to absorb photovoltaic power generation, maximize the absorption of power generation, and increase power generation revenue. In addition, it is understandable that this application does not select a low-voltage backflow prevention solution because when the third load under the 400V low-voltage bus cannot absorb the power generation of the photovoltaic system, the upward flow of power in the circuit where the low-voltage transformer is located will immediately activate the backflow prevention function, reduce photovoltaic power generation, and the first load and the second load under the same section of the 10kV high-voltage bus will not be able to use photovoltaic power, resulting in the phenomenon of "unnecessary abandonment of light".

[0140] It is understood that in the photovoltaic energy storage management technology solutions mentioned in this application, backflow prevention technology is a key component in ensuring efficient utilization of photovoltaic power, avoiding curtailment, and ensuring stable system operation. The installation of a high-voltage backflow prevention device helps optimize the design of the entire photovoltaic energy storage management system, improve energy utilization efficiency, reduce curtailment, and ensure the stable operation of the power grid and photovoltaic system.

[0141] See also Figure 5 , Figure 5 This is an application scenario diagram of an energy management method based on a smart electric energy meter provided in an embodiment of the present application, such as Figure 5 As shown, the application scenario diagram includes a power grid 501 , a photovoltaic system 502 , an energy storage system 503 , a smart energy meter 504 , an electrical load 505 and a server 506 .

[0142] The power grid 501 is directly connected to the energy storage system 503 and the power load 505. The power grid 501 can directly supply the generated electricity to the power load 505. When the power grid is at a low load and the electricity price is low, the energy storage system 503 can absorb the electricity from the power grid 501 to charge and store the electricity. When the power grid is at a peak load or the photovoltaic system 502 is insufficiently generating electricity and the power load 505 is in high demand, the energy storage system 503 can supply power to the power grid 501.

[0143] The photovoltaic system 502 is connected to the energy storage system 503 and the electrical load 505 via a smart energy meter 504. When the power generated by the photovoltaic system 502 exceeds the power consumption of the electrical load 505, the excess power is transferred to the energy storage system 503 for storage, enabling the flow of power from the photovoltaic system 502 to the energy storage system 503. Furthermore, when the power generation of the photovoltaic system 502 is insufficient or the power load 505 has a high demand, the energy storage system 503 releases the stored power to supply the power load 505, enabling the transmission of power from the energy storage system 503 to the power load 505.

[0144] Among them, the server 506 is connected to the photovoltaic system 502, the energy storage system 503, the smart electricity meter 504 and the power load 505 respectively, and is used to collect and obtain relevant electricity data, such as the power generation, light intensity, and component temperature of the photovoltaic system 502, the battery power, charge and discharge status, voltage and current of the energy storage system 503, and the power and electricity consumption of the power load 504; and the server 506 is also used to create and publish charging preferential plans for the target business site based on the historical electricity data of the smart electricity meter 504, the business reservation information of the target business site in the future time period, and the storable current of the power load 504 and the energy storage system 503 to absorb the flexible load electricity.

[0145] It can be seen that in this embodiment, the server creatively proposes a solution for absorbing the surplus electricity of the photovoltaic system without abandoned light based on flexible load power in the dimension of multiple consecutive natural days, aiming at the photovoltaic energy storage management needs in the future period of the target business site. The flexible load power absorption is deeply integrated with the charging business of new energy vehicles in the target business site. The charging business system creates and publishes charging preferential plans, which can attract users to absorb flexible load power quickly and accurately. On the one hand, it realizes the maximum use of the power generation of the photovoltaic system without abandoned light, and on the other hand, it accurately converts the surplus power of the photovoltaic system into benefits.

[0146] In addition, an embodiment of the present application also provides a computer storage medium, which stores a computer program that can be loaded and executed by a processor such as the above-mentioned energy management method based on a smart electricity meter. The computer-readable storage medium includes, for example: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and other media that can store program codes.

[0147] It should be noted that for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that this application is not limited by the order of the actions described, because according to this application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by this application.

[0148] In the several embodiments provided in this application, it should be understood that the disclosed methods, devices, and systems can be implemented in other ways. For example, the device embodiments described above are merely schematic; for example, the division of the units is merely a logical function division, and there may be other division methods in actual implementation; for example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces, indirect coupling or communication connection of devices or units, which may be electrical, mechanical, or other forms.

[0149] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0150] In addition, the functional units in various embodiments of the present invention may be integrated into a single processing unit, each unit may be physically included separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or hardware plus software functional units.

[0151] The above-mentioned integrated unit implemented as a software functional unit can be stored in a computer-readable storage medium. The software functional unit is stored in a storage medium and includes instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) to perform some of the steps of the method described in various embodiments of the present invention. The aforementioned storage medium includes a USB flash drive, a mobile hard drive, a magnetic disk, an optical disk, a volatile memory, or a non-volatile memory. The non-volatile memory can be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic random access memory (DRAM), synchronous DRAM (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link DRAM (SLDRAM), and direct RAM bus random access memory (DRRAM), among other media that can store program code.

[0152] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0153] The above is a detailed introduction to the embodiments of the present application. Specific examples are used herein to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method and core idea of ​​the present application. At the same time, for those skilled in the art, according to the idea of ​​the present application, there may be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

[0154] Although the present application discloses the above, the present application is not limited thereto. Any person skilled in the art may readily conceive of variations or substitutions, and may make various changes and modifications, including combinations of the above-mentioned functions and implementation steps, including software and hardware implementations, without departing from the spirit and scope of the present application, and all are within the scope of protection of the present application.

Claims

1. An energy management method based on a smart electric energy meter, characterized in that: A server of a photovoltaic energy storage management system applied to a target business site, the photovoltaic energy storage management system comprising a photovoltaic system, an energy storage system, the server, and an electrical load provided at the target business site, the method comprising: Get the preset lighting condition classification table; Classifying the historical electric energy data of the smart electric energy meter according to the lighting condition classification table to obtain multiple historical electric energy data sets corresponding to multiple types of lighting conditions; Filter each historical power data set based on the reference curtailment rate to obtain historical power data after removing sampled data with curtailment. Performing parameter denoising and averaging processing on the filtered historical electric energy data to obtain actual power generation; Creating a correspondence between the actual power generation of the photovoltaic system under the condition of no abandoned light and the lighting conditions; Acquiring weather data for each natural day of the target business site within the future time period based on the business reservation information of the target business site within the future time period, wherein the weather data includes lighting conditions, and the business reservation information includes business item information and vehicle information of the self-driving vehicle; Determine, based on the corresponding relationship and the weather data, the expected power generation of the photovoltaic system on each natural day under the condition that no power is abandoned; Determine, based on the business project information and the power load, the estimated basic load power of the target business site for each natural day under the condition that there is no charging load of the new energy vehicle among the self-driving vehicles; Determining the flexible load power of the photovoltaic system that can be consumed by the new energy vehicle in the self-driving vehicle on each natural day based on the expected power generation on each natural day, the expected basic load power, and the storable power of the energy storage system; A preferential charging plan for the target business site is created and published based on the flexible load power and the vehicle information of the self-driving vehicle to absorb the flexible load power.

2. The method according to claim 1, characterized in that The determining, based on the estimated power generation on each natural day, the estimated base load power, and the storable power of the energy storage system, the flexible load power of the photovoltaic system that can be consumed by the new energy vehicle in the self-driving vehicle on each natural day, includes: Determining a minimum guaranteed power capacity for each natural day of the energy storage system without requiring grid power during the future period based on the estimated power generation for each natural day, the estimated base load power, and the storable power; The flexible load power of the photovoltaic system that can be absorbed by the new energy vehicle in the self-driving vehicle on each natural day is determined based on the expected power generation, the expected basic load power and the minimum guaranteed power.

3. The method according to claim 2, characterized in that Before determining the minimum guaranteed power capacity of each natural day for the energy storage system in the future period without requiring grid power based on the estimated power generation, the estimated base load power, and the storable power, the method further includes: Determining the total expected power generation in the future period based on the expected power generation for each natural day; Determine the total expected base load electricity for the future period based on the expected base load electricity for each natural day; It is detected that the total projected power generation is greater than the total projected base load power.

4. The method according to claim 3, characterized in that The method of determining the minimum guaranteed power of each natural day for the energy storage system in the future period without requiring grid power based on the estimated power generation, the estimated base load power, and the storable power, includes: Determining the storable surplus electricity of the photovoltaic system on each natural day based on the estimated power generation on each natural day, the estimated base load power, and the storable power, wherein the storable surplus electricity includes a positive state and a negative state, wherein the positive state indicates that the photovoltaic system has a positive surplus in the estimated power generation on the current natural day, and the negative state indicates that the photovoltaic system has no positive surplus in the estimated power generation on the current natural day and the minimum power that the energy storage system needs to store before the current natural day in order to meet the power demand on the current natural day; Based on the storable remaining electricity of each natural day, the minimum guaranteed electricity of each natural day in the future period without calling on the power of the grid is obtained by reasoning day by day according to the order of multiple natural days in the future period from the back to the front.

5. The method according to claim 4, characterized in that The smart electric energy meter is a smart electric energy meter installed on the AC output side of the photovoltaic system; before obtaining the preset lighting condition classification table, the method further includes: Receiving sampling data and timestamp reported by the smart electric energy meter; Query and obtain the lighting condition of the photovoltaic system at the timestamp; Determining a reference abandonment rate of the photovoltaic system at the timestamp; The historical electric energy data is created according to the lighting condition, the reference abandoned light rate and the sampling data.

6. The method according to claim 5, characterized in that Determining a reference abandonment rate of the photovoltaic system at the timestamp includes: determining a theoretical output power of the photovoltaic system at the timestamp according to the illumination condition and the configuration information of the photovoltaic system; Obtaining a sampled output power of the photovoltaic system at the timestamp; A reference abandonment rate of the photovoltaic system at the timestamp is determined according to the theoretical output power and the sampled output power.

7. The method according to claim 5, characterized in that Determining a reference abandonment rate of the photovoltaic system at the timestamp includes: Obtaining an operation log of the photovoltaic system generated based on status data reported by the backflow prevention table of the photovoltaic system, the status data including a backflow status indicator reported by the backflow prevention table, a first output power of the photovoltaic system before the backflow occurs, and a second output power of the photovoltaic system after the backflow occurs; A reference abandonment rate of the photovoltaic system at the timestamp is determined according to the first output power and the second output power.

8. A solar energy storage management system, characterized in that: Including servers, photovoltaic systems, energy storage systems, and power loads installed at the target business site, among which, The server is used to execute the steps executed by the server in any one of the methods according to claims 1-7.

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