Energy management method and system based on intelligent electric energy meter

Abstract

The invention provides an energy management method and system based on an intelligent electric energy meter, and the method comprises the steps: determining the predicted power generation amount of a photovoltaic system in each natural day in a future time period under the condition of no light abandoning according to the historical electric energy data of the intelligent electric energy meter and the service reservation information of a target service site in the future time period; according to the business item information and the power utilization load, determining the predicted basic load electric quantity of the target business site in each natural day under the condition of no charging load of the new energy vehicle in the self-driving vehicle; according to the predicted generating capacity of each natural day, the predicted basic load electric quantity and storable electric quantity of the energy storage system, determining flexible load electric quantity, which can be absorbed by the new energy vehicle, of the photovoltaic system in each natural day; and according to the flexible load electric quantity and the vehicle information of the self-driving vehicle, creating and issuing a charging preferential scheme of the target business site to consume the flexible load electric quantity. The utilization rate and the conversion rate of photovoltaic resources can be improved.

Description

Technical Field

[0001] This application relates to the technical field of energy management for photovoltaic and energy storage in new energy services, and particularly to an energy management method and system based on an intelligent electricity meter. Background Art

[0002] With the wide application of photovoltaic and energy storage systems, business sites such as hotels have gradually started to be equipped with photovoltaic and energy storage energy management systems. By connecting the local photovoltaic and energy storage systems to the power grid, a more stable and cost-effective electricity usage plan can be achieved. Moreover, the electricity generated by the photovoltaic system can directly supply the electrical loads of the business site, or charge the energy storage system of the business site, and then the energy storage system supplies power to the electrical loads to meet the electricity demand of the business site.

[0003] Currently, the use and conversion of the electricity generated by photovoltaic and energy storage systems have become a research hotspot in the field of photovoltaic and energy storage power management. Existing solutions are difficult to fully balance the maximized use of the generated electricity and the benefit conversion of the surplus electricity in photovoltaic and energy storage, thus causing waste of resources and reducing the energy conversion rate. Summary of the Invention

[0004] This application provides an energy management method and system based on an intelligent electricity meter. Aiming at the photovoltaic and energy storage energy management requirements of the target business site in future periods, a creative solution is proposed to utilize the surplus electricity under the condition of no light abandonment in the photovoltaic system based on the flexible load electricity consumption over consecutive natural days. Moreover, the flexible load electricity consumption is specifically deeply integrated with the charging service of new energy vehicles at the target business site. By creating and publishing a charging preferential plan through the charging service system, users can be targeted to quickly and accurately consume the flexible load electricity. On the one hand, the maximized use of the electricity generated under the condition of no light abandonment in the photovoltaic system is achieved, and on the other hand, the precise benefit conversion of the surplus electricity in the photovoltaic system is carried out.

[0005] In the first aspect, this application provides an energy management method based on an intelligent electricity meter, which is applied to the server of the photovoltaic and energy storage energy management system of the target business site. The photovoltaic and energy storage energy management system includes a photovoltaic system, an energy storage system, the server, and electrical loads arranged at the target business site. The method includes: Determine the predicted power generation amount of each natural day in the future period under the condition of no light abandonment in the photovoltaic system according to the historical electricity data of the intelligent electricity meter and the business reservation information of the target business site in the future period. The business reservation information includes business project information and vehicle information of self-driving vehicles; Determine the predicted basic load electricity amount of each natural day at the target business site under the condition of no charging load of new energy vehicles in the self-driving vehicles according to the business project information and the electrical loads; Determine the flexible load power that can be absorbed by the new energy vehicle in the self-driving vehicle for the photovoltaic system on each natural day according to the predicted power generation on each natural day, the predicted basic load power, and the storable power of the energy storage system; Create and publish a charging preferential plan for the target business site according to the flexible load power and the vehicle information of the self-driving vehicle to absorb the flexible load power.

[0006] 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 in a target business site, where The server is configured to execute the steps performed by the server in the first aspect of the embodiments of the present application.

[0007] It can be seen that in the embodiments of the present application, the server determines the predicted power generation on each natural day in the future period under the condition of no light abandonment of the photovoltaic system according to the historical power data of the intelligent electricity meter and the business reservation information of the target business site in the future period. The business reservation information includes business item information and vehicle information of the self-driving vehicle; determines the predicted basic load power on each natural day of the target business site under the condition of no charging load of the new energy vehicle in the self-driving vehicle according to the business item information and the electrical load; determines the flexible load power that can be absorbed by the new energy vehicle in the self-driving vehicle for the photovoltaic system on each natural day according to the predicted power generation on each natural day, the predicted basic load power, and the storable power of the energy storage system; creates and publishes a charging preferential plan for the target business site according to 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 rate and conversion rate, the present application can create and publish a charging preferential plan through the charging business system to attract users to quickly and accurately absorb the flexible load power, realizing the maximum utilization of the power generation under the condition of no light abandonment of the photovoltaic system and the precise benefit conversion of the surplus power of the photovoltaic system, which is beneficial to improving the intelligence, comprehensiveness, and flexibility of the photovoltaic energy storage management system for photovoltaic data processing, and improving the utilization rate and conversion rate of photovoltaic resources. Description of the Drawings

[0008] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0009] Figure 1 It is a system architecture diagram of a photovoltaic energy storage management system provided by an embodiment of the present application; Figure 2 It is a structural block diagram of an electronic device provided by an embodiment of the present application; Figure 3 It is an overall flowchart of an energy management method based on an intelligent electricity meter provided by an embodiment of the present application; Figure 4 It is an electrical system diagram of a photovoltaic power generation grid connection provided by an embodiment of the present application; Figure 5 It is an application scenario diagram of an energy management method based on an intelligent electricity meter provided by an embodiment of the present application. Detailed implementation manners

[0010] In order to enable those skilled in the art to better understand the solutions of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

[0011] The terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally further includes steps or units not listed, or optionally further includes other steps or units inherent to these processes, methods, products or devices.

[0012] Referring to "embodiment" herein means that a specific feature, structure or characteristic described in connection with the embodiment may be included in at least one embodiment of the present application. The phrase appears in various places in the specification and does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art will explicitly and implicitly understand that the embodiments described herein may be combined with other embodiments.

[0013] The "and / or" in the embodiments of the present application describes the association relationship of associated objects and indicates that three relationships may exist. For example, A and / or B may represent the following three situations: A exists alone; A and B exist simultaneously; B exists alone. Among them, A and B may be singular or plural.

[0014] In the embodiments of the present application, the symbol " / " may represent an "or" relationship between the associated objects before and after. In addition, the symbol " / " may also represent a division sign, that is, perform a division operation. For example, A / B may represent A divided by B.

[0015] The "at least one (individual)" or its similar expression in the embodiments of the present application refers to any combination of these items, including any combination of single item (individual) or plural items (individuals), which means one or more, and multiple means two or more. For example, at least one (individual) 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.

[0016] "Equal to" in the embodiments of the present application can be used in combination with "greater than", applicable to the technical solutions adopted when it is greater than, and can also be used in combination with "less than", applicable to the technical solutions adopted when it is less than. When "equal to" is used in combination with "greater than", it is not used in combination with "less than"; when "equal to" is used in combination with "less than", it is not used in combination with "greater than".

[0017] With the continuous integration of information technology, communication technology, and power technology, the smart grid has become a new direction for the development of the power system. The smart grid emphasizes the comprehensive perception, intelligent decision-making, and optimized control of the power system, and can achieve the efficient transmission, distribution, and utilization of electricity. As an important part of the smart grid, the photovoltaic and energy storage management system can operate in coordination with other links of the smart grid to improve the intelligent level of the grid. In order to achieve the efficient utilization of energy and cost control, it is necessary to conduct refined management of the production, transmission, storage, and consumption of energy. The photovoltaic and energy storage management system can perform real-time monitoring and data analysis on the photovoltaic system, energy storage system, and electrical load through the server, and can achieve the optimized allocation and management of energy, improve energy utilization efficiency, and reduce energy costs.

[0018] Currently, the existing energy management solutions lack the collaborative management of photovoltaic and energy storage, mainly focus on single energy management, and cannot achieve real-time dynamic regulation of the energy system. When facing the uncertainty of photovoltaic power generation and the changes in load demand, they cannot quickly and accurately adjust the energy distribution and operation strategies, and cannot solve the problem that it is difficult to perfectly handle the surplus electricity under the condition of no light abandonment of the photovoltaic system based on the flexible load power consumption for consecutive natural days.

[0019] In view of the above problems, the embodiments of the present application provide an energy management method and system based on an intelligent electricity meter. The embodiments of the present application will be introduced in detail below with reference to the accompanying drawings.

[0020] Please refer to Figure 1 , Figure 1 which is the system architecture diagram of a photovoltaic and energy storage management system provided by the embodiments of the present application. As Figure 1 shown, the system architecture diagram of the photovoltaic and energy storage management system 100 includes a server, a photovoltaic system, an energy storage system, and an electrical load.

[0021] Among them, a photovoltaic system generally includes photovoltaic modules, an inverter, and a combiner box. Specifically, the photovoltaic module is the core component that converts solar energy into electrical energy. It consists of multiple solar panels and converts sunlight energy into direct current electrical energy through the photovoltaic effect; the inverter converts the direct current generated by the photovoltaic module into alternating current to supply power to an AC load or connect to the AC grid. At the same time, it also has the maximum power point tracking (MPPT) function, which can automatically adjust the operating point of the photovoltaic module to make it always operate near the maximum power point, improving the photovoltaic power generation efficiency; the combiner box collects the output currents of multiple photovoltaic module strings and then transports them to the inverter or other devices, facilitating the wiring and management of the system. At the same time, it also has functions such as overcurrent protection and lightning protection to ensure the safe operation of the photovoltaic system.

[0022] Among them, an energy storage system generally includes a battery pack, a battery management system (BMS), and a bidirectional converter. Specifically, the battery pack is the core part of the energy storage system for storing electrical energy. Common battery types include lead-acid batteries, lithium-ion batteries, flow batteries, etc. Different types of batteries have different performance characteristics and application scenarios; the battery management system monitors and manages the battery pack in real time, monitoring parameters such as the voltage, current, temperature, and SOC (state of charge) of the battery to prevent overcharging, over-discharging, overheating, etc. of the battery, ensuring the safe operation of the battery pack. At the same time, it can also perform equalization management on the battery pack to improve the overall performance and service life of the battery pack; the bidirectional converter realizes the bidirectional electrical energy conversion between the battery pack and the grid or other devices. When charging, it converts the alternating current of the grid or photovoltaic system into direct current to charge the battery pack, and when discharging, it converts the direct current of the battery pack into alternating current to supply power to the load or transmit it to the grid.

[0023] Among them, the electrical load includes various electrical equipment, such as industrial production equipment, commercial office equipment, household appliances of residents, etc., which are all devices that need to consume electrical energy and are the electrical energy consumption terminals of the photovoltaic-energy storage energy management system 100. Their electricity consumption demands are diverse and uncertain.

[0024] Furthermore, the photovoltaic-energy storage energy management system 100 may further include an intelligent electricity meter, which can be an intelligent electric meter installed on the AC output side of the photovoltaic system. The intelligent electricity meter is used to count the electricity quantity delivered by the photovoltaic system to the grid and / or the electrical load of the target business site.

[0025] Among them, the server is respectively connected to the photovoltaic system, the energy storage system, the electrical load, and the intelligent electricity meter, and is used for data collection and monitoring, and for data analysis and decision-making. Specifically, the server is used to create and publish a charging preferential plan for the target business site based on the historical electricity data of the intelligent electricity meter, the business reservation information of the target business site in the future period, the electrical load, and the storable current of the energy storage system to absorb the flexible load electricity quantity.

[0026] It can be seen that in this embodiment, the server creatively proposes a solution for the surplus electricity under the condition of no light abandonment of the photovoltaic system based on the flexible load power consumption in the dimension of consecutive natural days for the future time period of the target business site. Moreover, the flexible load power consumption is specifically deeply integrated with the charging service of new energy vehicles at the target business site. By creating and publishing a charging preferential plan through the charging service system, users can be directed to quickly and accurately consume the flexible load power. On the one hand, the maximum utilization of the power generation under the condition of no light abandonment of the photovoltaic system is realized, and on the other hand, the precise benefit conversion of the surplus electricity of the photovoltaic system is achieved.

[0027] Please refer to Figure 2 , Figure 2 which is a structural block diagram of an electronic device provided by an embodiment of the present application for executing the Figure 1 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. Specifically, 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 can be optionally called to complete the corresponding operation. Among them, the electronic device 20 may be a mobile phone terminal, a tablet computer, a laptop computer, and a wearable intelligent device.

[0028] The processor 21 may include one or more processing cores. The processor 21 connects various parts within the entire electronic device 20 using various interfaces and circuits. By running or executing instructions, programs, code sets, or instruction sets stored in the memory 23, and by invoking the data stored in the memory 23, it performs various functions of the electronic device 20 and processes data. Optionally, the processor 21 may be implemented in at least one hardware form of digital signal processing (DSP), field-programmable gate array (FPGA), or programmable logic array (PLA). The processor 21 may integrate a combination of one or several of a central processing unit (CPU), a graphics processing unit (GPU), and a modem, etc. Among them, the CPU mainly processes the operating system, user interface, application programs, etc.; the GPU is responsible for rendering and drawing the display content; the modem is used to process wireless communication. It can be understood that the above-mentioned modem may not be integrated into the processor 21 and may be implemented separately through a communication chip.

[0029] The memory 23 may include random access memory (RAM) and may also include read-only memory (ROM). The memory 23 can be used to store instructions, programs, code, code sets, or instruction sets. The memory 23 may include a program storage area and a data storage area. Among them, the program storage area can store instructions for implementing the operating system, instructions for implementing at least one function (such as touch function, sound playback function, image playback function, etc.), instructions for implementing the above-mentioned various method embodiments, etc. The data storage area can also store the data created during the use of the electronic device 20.

[0030] It can be understood that the electronic device 20 may include more or fewer structural elements than those shown in the above structural block diagram. For example, it may include a power module, physical buttons, a Wi-Fi module, a speaker, a Bluetooth module, sensors, etc., which are not limited herein.

[0031] Please refer to Figure 3 , Figure 3 which is the overall flowchart of an energy management method based on an intelligent electricity meter provided by an embodiment of this application, and is applied to the Figure 1 server in, as Figure 3 shown, the method includes the following steps: Step S301: Determine the predicted power generation for each natural day in the future period under the condition of no PV curtailment of the PV system according to the historical power data of the intelligent electricity meter and the business reservation information of the target business site in the future period. The business reservation information includes business item information and vehicle information of self-driving vehicles.

[0032] Among them, in the business reservation information of the target business site in the future period, the business item information may involve the electricity consumption characteristics and electricity consumption time arrangements of different businesses. For example, if the reserved business item is a large-scale meeting, the electricity consumption demand for lighting, electronic devices, etc. during the meeting is large and concentrated, which will affect the consumption of the power generated by the PV system. The vehicle information of self-driving vehicles, such as the number of vehicles and whether there is a charging demand, will also affect the electricity load situation. If there are more self-driving vehicles and they need to be charged, then the electricity demand will increase during the charging period. By comprehensively considering this business reservation information, the change of the electricity load in the future period can be more accurately estimated, and then a more reasonable judgment on the demand and consumption of the power generation of the PV system can be made.

[0033] Among them, the historical power data includes basic power data, electrical parameter data, time-related data, and other operation data.

[0034] Specifically, the basic power data includes active power, reactive power, and apparent power. Among them, the active power records the cumulative value of the active electric energy actually consumed or delivered to the power grid by the PV system, and can be used to measure the power generation capacity and actual power generation of the PV system; the reactive power reflects the cumulative value of the reactive electric energy exchanged between the PV system and the power grid, and can be used to evaluate the contribution or demand of the PV system to the reactive power of the power grid; the apparent power is the vector sum of the active power and the reactive power, reflecting the total electric energy transmission volume of the PV system, which helps to comprehensively understand the overall situation of the PV system in power transmission.

[0035] Specifically, the electrical parameter data includes voltage data, current data, and power data. Among them, the voltage data includes the phase voltage and line voltage data output by the PV system, recording the voltage values at different times, which is crucial for judging the operation state and power quality of the PV system; the current data records the phase current and line current output by the PV system. Combining the current data with the voltage data can calculate other important parameters such as power, and at the same time can also reflect the load situation and the magnitude of the power generation of the PV system; the power data includes active power, reactive power, and apparent power. Further, the active power represents the power actually output by the PV system for doing work per unit time, which is an important indicator for measuring the power generation capacity and real-time power generation state of the PV system. The reactive power reflects the reactive power exchanged between the PV system and the power grid per unit time, and is used to evaluate the impact of the PV system on the reactive power balance of the power grid. The apparent power is the vector sum of the active power and the reactive power, reflecting the total power output capacity of the PV system.

[0036] Specifically, the time-related data mainly includes timestamps, which are used to accurately record the acquisition time of each group of electrical energy data and electrical parameter data, usually accurate to seconds or even milliseconds. The timestamp is the key for the data to have timeliness and traceability. Through the timestamp, the data at different times can be accurately sorted and associated, facilitating the analysis of the operation of the photovoltaic system at different times.

[0037] Specifically, other operating data includes power factor and frequency. Among them, the power factor is the ratio of active power to apparent power, which reflects the efficiency of electrical energy utilization of the photovoltaic system and the degree of influence on the power grid. A higher power factor indicates high electrical energy utilization efficiency and little impact on the power grid load; and the frequency records the frequency of the electrical energy output by the photovoltaic system. The frequency data can be used to judge the synchronization and operation stability of the photovoltaic system with the power grid.

[0038] In a possible embodiment, determining the expected power generation of the photovoltaic system on each natural day in the future period under the condition of no light curtailment according to the historical electrical energy data of the intelligent electricity meter and the business reservation information of the target business site in the future period includes: Statistically analyze the historical electrical energy data of the photovoltaic system sampled and created by the intelligent electricity meter to obtain the corresponding relationship between the actual power generation of the photovoltaic system under the condition of no light curtailment and the light conditions; Obtain the weather data of each natural day in the future period of the target business site, and the weather data includes light conditions; Determine the expected power generation of the photovoltaic system on each natural day under the condition of no light curtailment according to the corresponding relationship and the weather data.

[0039] In a possible embodiment, the intelligent electricity meter may be an intelligent electricity meter installed on the AC output side of the photovoltaic system; before statistically analyzing the historical electrical energy data of the photovoltaic system sampled and created by the intelligent electricity meter to obtain the corresponding relationship between the actual power generation of the photovoltaic system under the condition of no light curtailment and the light conditions, the method further includes: Receive the sampling data and timestamps reported by the intelligent electricity meter; Query and obtain the light conditions of the photovoltaic system at the timestamp; Determine the reference light curtailment rate of the photovoltaic system at the timestamp; Create the historical electrical energy data according to the light conditions, the reference light curtailment rate and the sampling data.

[0040] It is understandable that the smart electricity meter is used to count the amount of electricity delivered by the photovoltaic system to the power grid and / or the load of the target business site. By sampling the AC current signal and voltage signal, the smart electricity meter can calculate parameters such as active power and reactive power using digital signal processing technology and report them to the server. After receiving the sampling data, the server queries the weather system or obtains the lighting conditions at the time stamp based on the lighting perception devices deployed on the photovoltaic modules, and finally creates and stores historical electricity data according to the lighting conditions and sampling data.

[0041] Exemplarily, the target business site can be, for example, a hotel, a resort, an integrated amusement park, etc. Taking a certain resort as an example, in the photovoltaic energy storage management system of the resort, the smart electricity meter reports the sampling data every 15 minutes, such as the current, voltage and other data recorded at 9:15 am, as well as the corresponding time stamp, and reports the sampling data and time stamp to the server. Then, the server queries the corresponding lighting conditions according to the time stamp. The source of the lighting conditions can be a professional meteorological data platform or the lighting sensors installed in the resort. For example, it can be queried that at 9:15 am, the light intensity is 800 lux.

[0042] In a possible embodiment, determining the reference light curtailment rate of the photovoltaic system at the time stamp includes: Determining the theoretical output power of the photovoltaic system at the time stamp according to the lighting conditions and the configuration information of the photovoltaic system; Obtaining the sampled output power of the photovoltaic system at the time stamp; Determining the reference light curtailment rate of the photovoltaic system at the time stamp according to the theoretical output power and the sampled output power.

[0043] Among them, the reference light curtailment rate is used to measure the proportion of the electric energy generated by the photovoltaic modules that is discarded due to various factors and cannot be effectively utilized or transmitted to the grid at a specific time stamp.

[0044] In a possible embodiment, determining the theoretical output power of the photovoltaic system at the time stamp according to the lighting conditions and the configuration information of the photovoltaic system includes: Obtaining the maximum power and power temperature coefficient of the photovoltaic modules in the photovoltaic system; and, Obtaining the actual light intensity and standard test light intensity of the photovoltaic system at the time stamp; Determining the temperature difference between the first temperature in the actual working scenario of the photovoltaic module and the second temperature in the standard test scenario; Based on the maximum power, the power temperature coefficient, the actual light intensity, the standard test light intensity, and the temperature difference, considering the series and parallel relationships of the photovoltaic modules, determine the theoretical output power of the photovoltaic system at the time stamp.

[0045] Specifically, an embodiment of the present application provides a calculation method for the reference curtailment rate, that is, by calculating based on the theoretical and sampled output powers. Among them, the theoretical output power of the photovoltaic system at a certain time stamp is the power that the photovoltaic system should be able to output under this light condition. At the same time, through devices such as smart electricity meters, the actual sampled output power of the photovoltaic system at this time stamp can be obtained. The reference curtailment rate can be determined according to the theoretical output power and the sampled output power, and the calculation formula is as follows: Reference curtailment rate = 。

[0046] Among them, the calculation formula for the theoretical output power of the photovoltaic system is as follows: ; Among them, is the theoretical output power of the photovoltaic system under specific light conditions, is the maximum power of the photovoltaic module, is the actual light intensity under specific light conditions, is the standard test light intensity under standard test conditions, is the power temperature coefficient of the photovoltaic module, is the temperature difference between the actual working temperature of the photovoltaic module and the standard test temperature.

[0047] Among them, the maximum power can generally be obtained from the technical parameter table of the photovoltaic module; the actual light intensity under specific light conditions can be obtained through local meteorological data or by using professional light intensity measurement equipment; the standard test light intensity usually takes a value of 1000W / ; the power temperature coefficient is generally between -0.3% / °C and -0.5% / °C, and can also be obtained from the component technical parameter table; the standard test temperature of the photovoltaic module is usually 25°C.

[0048] Furthermore, it is also necessary to consider the influence of the series and parallel relationships of the photovoltaic modules on the theoretical output power of the photovoltaic system at this time stamp. If the photovoltaic system is composed of multiple photovoltaic modules in series and parallel, first calculate the total series resistance and parallel resistance and other parameters according to the circuit principles of series and parallel, and then calculate in combination with the above basic formula. For example, the number of series-connected components is , and the number of parallel-connected components is , then the calculation formula for the theoretical output power of the photovoltaic system is as follows: ; Among them, is the theoretical output power of the photovoltaic system in the case of series and parallel connection of photovoltaic modules, is the number of series-connected photovoltaic modules, is the number of parallel-connected photovoltaic modules.

[0049] Furthermore, for an actual photovoltaic system, the system efficiency needs to be considered, including factors such as inverter efficiency, line loss, dust shading, etc. Generally, the system efficiency is between 75% - 90%. At this time, the calculation formula for the theoretical output power of the photovoltaic system is as follows: ; Among them, is the theoretical output power of the photovoltaic system considering the photovoltaic system efficiency, is the photovoltaic system efficiency.

[0050] Exemplarily, the maximum power of the photovoltaic system is 300W, and the power temperature coefficient is -0.4% / °C. At a certain moment, the actual light intensity is 800W / , and the actual working temperature is 35°C. Then, the temperature difference between the actual working temperature and the standard test temperature = 35 - 25 = 10°C. Then, the theoretical output power of the photovoltaic system under specific light conditions can be obtained = 300× ×(1 - 0.4%×10) = 220.8W. Furthermore, assuming that the photovoltaic system includes 10 series-connected photovoltaic modules and 5 groups of such series circuits in parallel, and the photovoltaic system efficiency is 85%, then = 10×5×220.8 = 11040W, = 11040×85% = 9384W.

[0051] Exemplarily, if the actual sampled output power of the photovoltaic system is 7500W, then the reference curtailment rate can be obtained = ×100% = 20%.

[0052] In a possible embodiment, determining the reference curtailment rate of the photovoltaic system at the timestamp includes: Obtaining the operation log of the photovoltaic system generated according to the status data reported by the anti-islanding protection meter of the photovoltaic system, where the status data includes the reverse current status flag reported by the anti-islanding protection meter, the first output power before the reverse current occurs in the photovoltaic system, and the second output power after the reverse current occurs in the photovoltaic system; Determining the reference curtailment rate of the photovoltaic system at the timestamp according to the first output power and the second output power.

[0053] It can be seen that the embodiment of the present application provides another calculation method for the reference curtailment rate, that is, it is determined by comparing the difference in output power before and after reverse power flow occurs. Among them, the anti-reverse power meter can detect the reverse power flow phenomenon of the photovoltaic system to the power grid. When reverse power flow occurs, it means that the power generation of the photovoltaic system may exceed the local load demand. The server adjusts the output power of the photovoltaic system according to the data reported by the anti-reverse power meter. The power generation reduced due to this adjustment can to a certain extent reflect the curtailment situation. By analyzing the changes in these data in the operation log, the power adjustment information caused by the anti-reverse power control can be obtained, so as to conduct a certain analysis and calculation of the curtailment situation.

[0054] Furthermore, the operation log recorded by the server usually contains the detailed status data reported by the anti-reverse power meter, such as the power sampling signals at different times, the time and power magnitude when reverse power flow occurs, etc. These data are traceable and have a certain degree of integrity, providing a relatively reliable data basis for analyzing the curtailment rate. By sorting and calculating these data, the power change situation of the photovoltaic system under the anti-reverse power control can be understood, and then the curtailment rate can be estimated.

[0055] It can be understood that the first output power before the reverse power flow of the photovoltaic system represents the power generation capacity and output level of the photovoltaic system when there is no reverse power flow. And the second output power after the reverse power flow of the photovoltaic system. Usually due to the action of the anti-reverse power mechanism, this power will decrease, reflecting the actual output situation of the photovoltaic system after taking anti-reverse power measures. By comparing the difference in output power before and after reverse power flow occurs, the power generation power loss caused by the anti-reverse power measures can be determined, and then the reference curtailment rate can be calculated to measure the proportion of photovoltaic electric energy not effectively utilized due to anti-reverse power factors at this time stamp.

[0056] Exemplarily, in the photovoltaic system of a resort, at the time stamp of 10:00 am, the operation log reported by the anti-reverse power meter shows the reverse power flow status flag, and the flag is "yes", that is, reverse power flow of electric energy occurs at this moment; and it shows that before the reverse power flow occurs, the first output power of the photovoltaic system = 200 kW, which indicates that the power generation output of the photovoltaic system can reach 200 kW when not restricted by anti-reverse power; and it shows that after the reverse power flow occurs, the second output power of the photovoltaic system = 150 kW. This is because the anti-reverse power device is started to adjust the output of the photovoltaic system, resulting in a decrease in the output power. Then the reference curtailment rate can be calculated = × 100% = × 100% = 25%.

[0057] In a possible embodiment, the method of statistically analyzing the historical power data of the photovoltaic system sampled and created by the smart electricity meter to obtain the correspondence between the actual power generation of the photovoltaic system under non-light curtailment conditions and the light conditions includes: Obtain a preset light condition classification table; Classify the historical power data according to the light condition classification table to obtain multiple historical power data sets corresponding to various types of light conditions; According to the reference light curtailment rate, perform data screening on each historical power data set to obtain the historical power data after screening out the sampling data with light curtailment; Perform denoising and mean processing on the parameter values of the screened historical power data to obtain the actual power generation; Create the correspondence between the actual power generation of the photovoltaic system under non-light curtailment conditions and the light conditions.

[0058] Among them, the light condition classification table can refer to the parameter intervals divided according to the typical light condition types of the weather system.

[0059] Among them, the denoising of the parameter values of the screened historical power data includes outlier identification and outlier removal.

[0060] In a possible embodiment, the step of performing data screening on each historical power data set according to the reference light curtailment rate to obtain the historical power data after screening out the sampling data with light curtailment includes: Obtain the reference light curtailment rate corresponding to each piece of historical power data in each historical power data set; Judge whether the reference light curtailment rate corresponding to each piece of historical power data in each historical power data set is greater than a preset threshold; Remove the historical power data with a reference light curtailment rate greater than the preset threshold from the corresponding historical power data set to obtain the historical power data after screening out the sampling data with light curtailment.

[0061] Exemplarily, the light condition classification table may include light intensity ranges and their corresponding light intensity levels. For example, light with an intensity of 0 - 200 lux is weak light, light with an intensity of 201 - 500 lux is medium light, light with an intensity of 501 - 800 lux is relatively strong light, and light with an intensity of 801 lux and above is strong light. The server reads the electrical energy data recorded every 15 minutes in the past month, which contains multiple similar records such as "2025-01–01-09:15, light intensity 300 lux, power generation 10 degrees", and then classifies this record into different light intensity ranges and light intensity levels. For each piece of data in each historical electrical energy dataset, it is determined whether the corresponding reference curtailment rate is greater than a set threshold, such as 5%. Suppose the reference curtailment rate corresponding to a certain data record is 8%, which is greater than 5%, then it is considered that there is a curtailment situation for this data, and this data is removed from the corresponding historical electrical energy dataset.

[0062] Furthermore, after performing denoising and mean value processing on the parameter values of the filtered historical electrical energy data to obtain the actual power generation, the corresponding relationship between the actual power generation of the photovoltaic system under no curtailment conditions and the light conditions can be obtained. For example: weak light - the average actual power generation is 3 degrees; medium light - the average actual power generation is 10 degrees; relatively strong light - the average actual power generation is 18 degrees; strong light - the average actual power generation is 25 degrees.

[0063] It can be seen that in this embodiment, by comprehensively considering various factors such as historical power generation data and future business electricity demand, the predicted power generation of the photovoltaic system for each natural day in the future period can be predicted more accurately. Compared with predicting solely based on the historical light and power generation relationship, the changes in the electricity load in the actual business scenario are considered, making the prediction result more in line with the actual situation, which helps to reasonably arrange the operation and maintenance work of the photovoltaic system, prepare necessary maintenance resources and equipment in advance, reduce energy waste or insufficient supply problems caused by inaccurate power generation prediction, and improve the overall operation efficiency and reliability of the photovoltaic and energy storage management system.

[0064] Step S302, determine the predicted basic load power for each natural day of the target business site under the condition of no charging load of new energy vehicles in the self-driving vehicles according to the business project information and the electricity load.

[0065] Specifically, different business projects have different electricity consumption characteristics and requirements. The basic electricity load can be determined according to the type, scale, and operating time of the business project. For example, the business hours of a large supermarket are usually from 9 am to 10 pm. During this period, lighting systems, refrigeration equipment, cash register systems, etc. will all consume electricity continuously. The basic electricity load of the supermarket business can be calculated based on the power and operating time of these devices.

[0066] Specifically, in addition to the electrical equipment of the business project itself, the electrical load may also include some other basic electrical facilities, such as the lighting and ventilation systems in the public areas of the building. Although these electrical 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 electrical loads for the lighting in the public areas of an office building and the operation of elevators are relatively fixed and need to be included in the calculation of the estimated basic load power consumption.

[0067] It can be understood that by integrating the business project information and the electrical load situation, the estimated basic load power consumption of the target business site for each natural day under the condition of no new energy vehicle charging load can be calculated. This requires detailed statistics and calculations of the power and operation time of various electrical equipment, and then adding up the various electrical loads to obtain the estimated basic load power consumption for each natural day. For example, by adding up the electrical loads of all stores in a shopping mall, the electrical loads of equipment such as public area lighting and air conditioners, the estimated basic load power consumption of the shopping mall without new energy vehicle charging can be obtained.

[0068] Step S303: Determine the flexible load power consumption that can be consumed by the new energy vehicle in the self-driving vehicle from the photovoltaic system for each natural day according to the estimated power generation for each natural day, the estimated basic load power consumption, and the storable power of the energy storage system.

[0069] In a possible embodiment, the determining the flexible load power consumption that can be consumed by the new energy vehicle in the self-driving vehicle from the photovoltaic system for each natural day according to the estimated power generation for each natural day, the estimated basic load power consumption, and the storable power of the energy storage system includes: Determine the minimum guaranteed power of the energy storage system for each natural day when the power grid power is not required to be adjusted in the future period according to the estimated power generation for each natural day, the estimated basic load power consumption, and the storable power; Determine the flexible load power consumption that can be consumed by the new energy vehicle in the self-driving vehicle from the photovoltaic system for each natural day according to the estimated power generation, the estimated basic load power consumption, and the minimum guaranteed power.

[0070] It can be understood that on the first day of the future period, the power generation of the photovoltaic system and the original stored power of the energy storage system can meet the demand for the estimated basic load power consumption on that day, that is, the mains power will not be called on the first day.

[0071] Among them, the flexible load power consumption consumed by the new energy vehicle can be calculated by the following formula: Flexible load power consumption = Estimated power generation - Estimated basic load power consumption - Minimum guaranteed power.

[0072] In a possible embodiment, before determining the minimum guaranteed power of each natural day for which the energy storage system does not need to draw power from the power grid during the future period according to the predicted power generation of each natural day, the predicted basic load power, and the storable power, the method further includes: Determine the total predicted power generation of the future period according to the predicted power generation of each natural day; Determine the total predicted basic load power of the future period according to the predicted basic load power of each natural day; It is detected that the total predicted power generation is greater than the total predicted basic load power.

[0073] Exemplarily, the future period may be the next week. The resort's photovoltaic system predicts the daily power generation from Monday to Sunday to be 1000 kWh, 1200 kWh, 1100 kWh, 1300 kWh, 1200 kWh, 1000 kWh, and 900 kWh respectively based on historical data and weather forecasts. Then the total predicted power generation for this week is 1000 + 1200 + 1100 + 1300 + 1200 + 1000 + 900 = 7700 kWh; and the predicted basic load power of the resort (including lighting, equipment operation, etc.) is 800 kWh, 900 kWh, 850 kWh, 1000 kWh, 950 kWh, 800 kWh, and 750 kWh respectively from Monday to Sunday. Then the total predicted basic load power is 800 + 900 + 850 + 1000 + 950 + 800 + 750 = 6050 kWh.

[0074] Furthermore, by comparing the total predicted power generation of 7700 kWh and the total predicted basic load power of 6050 kWh, it is found that the total predicted power generation is greater than the total predicted basic load power, indicating that theoretically there is excess power available for other uses in the photovoltaic system.

[0075] It can be understood that if it is detected that the total predicted power generation is not greater than the total predicted basic load power, then it is necessary to draw power from the mains to meet the basic electricity demand of the target business site. In this case, the power generation of the photovoltaic system can be fully utilized, 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 preferential plan, and the charging business of new energy vehicles can be carried out according to the conventional charging plan.

[0076] In a possible embodiment, determining the minimum guaranteed power of each natural day for which the energy storage system does not need to draw power from the power grid during the future period according to the predicted power generation of each natural day, the predicted basic load power, and the storable power, includes Determine the storable surplus power of the PV system on each natural day based on the predicted power generation of each natural day, the predicted base load power, and the storable power. The storable surplus power includes a positive state and a negative state. The positive state indicates that there is a positive surplus in the predicted power generation of the PV system on the current natural day, and the negative state indicates that there is no positive surplus in the predicted power generation of the PV system on the current natural day, and the minimum power that the energy storage system needs to store before the current natural day to meet the power consumption demand of the current natural day; According to the storable surplus power of each natural day, infer the minimum guaranteed power of each natural day when the energy storage system does not need to draw power from the power grid during the future period, one natural day by one natural day in the reverse order of the multiple natural days in the future period.

[0077] Among them, the minimum guaranteed power refers to the minimum amount of power that the energy storage system must store every natural day under specific conditions to ensure that it can meet the power consumption demand and does not need to obtain additional power from the power grid in the future. If the predicted power generation of a certain natural day of the PV system is greater than the predicted base load power, the difference is positive, indicating that there is surplus power that can be stored in the energy storage system; if the difference is negative, it means that the predicted power generation on that day cannot meet the predicted base load power, and the energy storage system needs to store a certain amount of power before that day to make up for the gap. This amount of power is the storable surplus power of that day, which is the basic data for determining the minimum guaranteed power.

[0078] Specifically, when determining the minimum guaranteed power, it is necessary to reason one by one in the reverse order of multiple natural days in the future period. For example, first determine the minimum guaranteed power of the last day. If the storable surplus power of the last day is positive, its minimum guaranteed power is the storable surplus power; then look at the previous day. If the storable surplus power of the previous day is less than the minimum guaranteed power of the next day, then the minimum guaranteed power of the previous day is the minimum guaranteed power of the next day minus the storable surplus power of the previous day, and so on, to ensure that the power stored by the energy storage system every day can meet the subsequent power consumption demand and does not rely on power grid power supply.

[0079] Exemplarily, assume that the energy management system of a hotel requires giving priority to using the power generation of the PV system without light curtailment and minimizing the use of municipal power. If the business reservation information of the hotel within the next three days is known, the weather conditions can be obtained from the weather forecasting system, and the energy storage system can store 600 degrees of power, and the initial power state of the energy storage system on the first day is 0, the predicted power generations from the first day to the third day are 800 degrees, 550 degrees, and 300 degrees respectively, and the predicted base load powers from the first day to the third day are 500 degrees, 500 degrees, and 400 degrees respectively. Then the total power generation of the PV system is 1650 degrees, and the total predicted base load power is 1400 degrees. Furthermore, it is determined that there is no need to borrow municipal power based on 1650 being greater than 1400, and balance can be achieved based on the charge and discharge capacity of the energy storage system.

[0080] Further, on the first day, the remaining power generation of the hotel's PV energy storage system minus the base load power is 800 - 500 = 300 kWh, which can be stored in the energy storage system, that is, the remaining power that can be stored is 300 kWh; on the second day, the remaining power generation of the hotel's PV energy storage system minus the base load power is 550 - 500 = 50 kWh, there is no need to borrow grid power, and the energy storage system can store it, that is, the remaining power that can be stored is 50 kWh; on the third day, the remaining power generation of the hotel's PV energy storage system minus the base load power is 300 - 400 = -100 kWh, that is, the remaining power that can be stored is -100 kWh; therefore, it is analyzed that the daily minimum guaranteed power of the energy storage system without adjusting the grid power in three natural days is 50 kWh, 50 kWh, and 0 kWh. Correspondingly, the flexible load power that the PV system can be consumed by the new energy vehicle in each natural day is 250 kWh, 0 kWh, and 0 kWh.

[0081] It can be seen that in this embodiment, by calculating the minimum guaranteed power and the flexible load power, it is possible to clarify how much power the energy storage system needs to store to guarantee the base load, and how much remaining power of the PV system is available for the new energy vehicle to consume, realizing the reasonable distribution of energy among the base load, energy storage, and new energy vehicle charging, making the electric energy generated by the PV system more fully utilized, reducing the waste of electric energy, and reducing the interaction with the grid, reducing the burden on the grid, and also reducing the electricity cost to a certain extent.

[0082] Step S304, create and publish a charging preferential plan for the target business site according to the flexible load power and the vehicle information of the self-driving vehicle to consume the flexible load power.

[0083] Exemplarily, the target business site is a large shopping mall, which is equipped with a PV system and an energy storage system, and there are often customers driving new energy vehicles to shop. Among them, the vehicle information of the self-driving vehicle can include 10 vehicle A with a battery capacity of 60 kWh and 8 vehicle B with a battery capacity of 76.9 kWh. The currently determined flexible load power is 500 kWh per day. Further, taking vehicle A as an example, if its average remaining power is 30%, then the power that each vehicle needs to supplement is about 60×(1 - 30%) = 42 kWh, and then 10 vehicle A in total need 420 kWh of power. Similarly, the power required by 8 vehicle B can be obtained.

[0084] Further, creating and publishing a charging preferential plan for the target business site according to the flexible load power and the vehicle charging demand can include preferential based on the charging amount, time period preferential, and member exclusive preferential.

[0085] Specifically, there are preferential offers based on the charging amount. For example, when the customer's charging amount reaches 20 kWh or more, a discount of 0.5 yuan per kWh is enjoyed. Also, if the customer's charging amount reaches a certain proportion (such as 80%) of the flexible load power distribution, a certain amount of points will be given as a bonus, and the points can be exchanged for goods or services in the mall.

[0086] Specifically, the time period preferential offers can be based on the power generation characteristics of the photovoltaic system and the operating hours of the mall. Different charging time periods are divided and different preferential offers are given. For example, the mall's business hours are from 10:00 to 22:00. During the time period from 12:00 to 16:00, the photovoltaic system has sufficient power generation, and at this time, a 20% discount can be enjoyed when charging; while in other time periods, the charging preferential intensity is relatively small. This can guide vehicle owners to charge when the photovoltaic power generation is sufficient, and better absorb the flexible load power.

[0087] Specifically, the exclusive member preferential offers can be additional charging preferential offers for the mall's members. For example, silver card members can enjoy a discount of 0.3 yuan per kWh when charging, while gold card members can enjoy a discount of 0.5 yuan per kWh, and the points are doubled. In this way, not only can more members be attracted to consume in the mall, but also the charging of new energy vehicles can be promoted, and the absorption efficiency of the flexible load power can be improved.

[0088] It can be seen that in this embodiment, aiming at the optical storage energy management requirements of the target business site in the future time period, a creative solution is proposed to utilize the surplus power of the photovoltaic system without light curtailment based on the flexible load power absorption in the dimension of continuous multiple natural days. And the flexible load power absorption is specifically deeply integrated with the charging business of new energy vehicles in the target business site. By creating and releasing a charging preferential plan through the charging business system, users can be targeted to quickly and accurately absorb the flexible load power. On the one hand, the maximum utilization of the power generation amount under the condition of no light curtailment of the photovoltaic system is realized, and on the other hand, the precise benefit conversion of the surplus power of the photovoltaic system is carried out, which is beneficial to improving the intelligence, comprehensiveness and flexibility of the optical storage energy management system for photovoltaic data processing, and improving the utilization rate and conversion rate of photovoltaic resources.

[0089] Please refer to Figure 4 , Figure 4 which is an electrical system diagram of photovoltaic power generation grid connection provided by the embodiment of the present application. As Figure 4 shown, the electrical system includes a power grid, a 35 kV high-voltage bus, a high-voltage transformer, a high-voltage anti-backflow device, a 10 kV high-voltage bus, a low-voltage transformer, a first load, a second load, a 400 V low-voltage bus, a third load, a grid connection point, an energy storage system, an intelligent electric energy meter, and a photovoltaic system.

[0090] Among them, the power grid is connected to the system through a 35 kV high-voltage busbar and undergoes voltage transformation operations through a high-voltage transformer. The high-voltage transformer can be a 35 / 10 kV transformer, which can convert 35 kV voltage into 10 kV to achieve the preliminary step-down transmission of high-voltage electrical energy. Furthermore, the 10 kV electrical energy stepped down by the high-voltage transformer is collected on the 10 kV high-voltage busbar and further stepped down by a low-voltage transformer. The low-voltage transformer can be a 10 / 0.4 kV transformer, which can convert 10 kV voltage into 400 V to achieve the final step-down transmission of high-voltage electrical energy and connect to the 400 V low-voltage busbar to supply power to various loads, such as the first load and the second load. Further, a third load, a photovoltaic system, an energy storage device, etc. are connected under the 400 V low-voltage busbar, which is a key node for terminal electrical energy distribution and energy interaction.

[0091] Among them, the high-voltage anti-backflow device is located between the high-voltage transformer and the input side of the 10 kV busbar voltage, and is used to prevent the electrical energy generated by the photovoltaic system from flowing back to the power grid, ensuring that the electrical energy flow on the 10 kV high-voltage busbar side meets the requirements and guaranteeing the stability of the power grid and the effective consumption of electrical energy.

[0092] Among them, the photovoltaic system is connected at the 400 V low-voltage busbar connection point. The electrical energy it generates is preferentially used by the third load, and the excess electrical energy can be stored or grid-connected. The intelligent electricity meter is located between the photovoltaic system and the connection point and is used to measure the electricity quantity delivered by the photovoltaic system to the power grid or load, providing data support for energy management and billing. The energy storage system is connected to the 400 V low-voltage busbar, can store electrical energy when the photovoltaic power is excessive, and release electrical energy for the third load to use, such as at night or when the light is insufficient, reducing the dependence on the power grid and being able to cooperate with the photovoltaic system, load, and anti-backflow device to optimize the electrical energy utilization efficiency.

[0093] It can be seen that in the photovoltaic and energy storage energy management system of this application, the high-voltage anti-backflow scheme is selected, and the high-voltage anti-backflow device is arranged on the incoming line side of the 10 kV high-voltage busbar, which can enable more loads under the 10 kV high-voltage busbar to consume the photovoltaic power generation, ensure the consumption of the power generation to the greatest extent, and improve the power generation revenue. In addition, it can be understood that the low-voltage anti-backflow scheme is not selected in this application because when the third load under the 400 V low-voltage busbar cannot consume the photovoltaic power generation of the photovoltaic system, the anti-backflow function will be immediately activated when the electricity quantity goes up in the loop where the low-voltage transformer is located, reducing the photovoltaic power generation, and the first load and the second load under the same 10 kV high-voltage busbar will not be able to use the photovoltaic power, resulting in the phenomenon of "unnecessary light abandonment".

[0094] It can be understood that in the photovoltaic and energy storage energy management technical solution mentioned in this application, the anti-backflow technology is an important link to ensure the efficient utilization of photovoltaic power, avoid light abandonment, and ensure the stable operation of the system. Through the setting of the high-voltage anti-backflow device, it helps to optimize the design of the entire photovoltaic and energy storage energy management system, improve the energy utilization efficiency, reduce the light abandonment phenomenon, and ensure the stable operation of the power grid and the photovoltaic system.

[0095] Please refer to Figure 5 , Figure 5 which is an application scenario diagram of an energy management method based on an intelligent electricity meter provided by an embodiment of the present application. As Figure 5 shown, the application scenario diagram includes a power grid 501, a photovoltaic system 502, an energy storage system 503, an intelligent electricity meter 504, an electrical load 505, and a server 506.

[0096] Among them, the power grid 501 is directly connected to the energy storage system 503 and the electrical load 505 respectively. The power grid 501 can directly supply the generated electric energy for the electrical load 505 to use; and, when the power grid load is low and the electricity price is low, the energy storage system 503 can absorb electric energy from the power grid 501 for charging and store the electric energy; when the power grid load is high or the power generation of the photovoltaic system 502 is insufficient and the demand of the electrical load 505 is large, the energy storage system 503 can supply power to the power grid 501.

[0097] Among them, the photovoltaic system 502 is connected to the energy storage system 503 and the electrical load 505 respectively through the intelligent electricity meter 504. When the power generation of the photovoltaic system 502 is greater than the power consumption of the electrical load 505, the excess electric energy will be transmitted to the energy storage system 503 for storage, realizing the flow of electric energy from the photovoltaic system 502 to the energy storage system 503; and, when the power generation of the photovoltaic system 502 is insufficient or the demand of the electrical load 505 is large, the energy storage system 503 releases the stored electric energy to supply power to the electrical load 505, realizing the transmission of electric energy from the energy storage system 503 to the electrical load 505.

[0098] Among them, the server 506 is connected to the photovoltaic system 502, the energy storage system 503, the intelligent electricity meter 504, and the electrical load 505 respectively, and is used to collect and obtain relevant electric energy data, such as collecting 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 power consumption of the electrical load 504, etc.; and, the server 506 is also used to create and publish a charging preferential plan for the target business site to consume flexible load power according to the historical electric energy data of the intelligent electricity meter 504, the business reservation information of the target business site in the future period, the storable current of the electrical load 504 and the energy storage system 503.

[0099] It can be seen that in this embodiment, for the future-period energy management requirements of the target business site, the server creatively proposes a solution for the surplus power under the condition of no light curtailment of the photovoltaic system based on the flexible load power consumption in the dimension of consecutive natural days. Moreover, the flexible load power consumption is specifically deeply integrated with the charging service of new energy vehicles at the target business site. By creating and publishing a charging preferential plan through the charging service system, users can be directed to quickly and accurately consume the flexible load power. On the one hand, the maximum utilization of the power generation under the condition of no light curtailment of the photovoltaic system is achieved, and on the other hand, the precise benefit conversion of the surplus power of the photovoltaic system is realized.

[0100] 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 for the energy management method based on an intelligent electricity meter as described above. Such a computer-readable storage medium includes, for example: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disc.

[0101] It should be noted that for the foregoing method embodiments, for the sake of simple description, they are all expressed as a series of action combinations. However, those skilled in the art should know that the present application is not limited by the described action sequence, because according to the present application, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to the present application.

[0102] In several embodiments provided by the present 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 illustrative; for example, the division of the units is only a logical function division, and there can be other division methods in actual implementation; for example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed mutual coupling or direct coupling or communication connection can be through some interfaces, and the indirect coupling or communication connection of the device or unit can be in an electrical, mechanical, or other form.

[0103] The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they can be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0104] In addition, in each embodiment of the present invention, the functional units can be integrated into one processing unit, or each unit can be physically separate, or two or more units can be integrated into one unit. The above integrated unit can be implemented in the form of hardware, or in the form of a hardware plus software functional unit.

[0105] The above integrated unit implemented in the form of a software functional unit can be stored in a computer-readable storage medium. The above software functional unit stored in a storage medium includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute some steps of the methods described in each embodiment of the present invention. The foregoing storage medium includes: USB flash drive, mobile hard disk, magnetic disk, optical disk, volatile memory or non-volatile memory. Among them, 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 a flash memory. The volatile memory can be a random access memory (RAM), which is used as an external cache. By way of example but not limitation, many forms of random access memory (RAM) are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), and direct rambus random access memory (DRRAM), etc., all of which are various media that can store program code.

[0106] In the above embodiments, the descriptions of each embodiment have their own emphases. For the parts not detailed in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0107] The above has introduced the embodiments of the present application in detail. Specific examples are used herein to elaborate on the principles and implementation manners of the present application. The description of the above embodiments is only used to help understand the method and its core idea of the present application; at the same time, for those of ordinary skill in the art, according to the idea of the present application, there will be changes in the specific implementation manners and application scopes. In summary, the content of this specification should not be construed as a limitation to the present application.

[0108] Although the present application is disclosed as above, the present application is not limited thereto. Any person skilled in the art can easily think of changes or substitutions without departing from the spirit and scope of the present application, and can make various changes and modifications, including the combination of the above different functions and implementation steps, including software and hardware implementation manners, which are all within the protection scope of the present application.

Claims

1. An energy management method based on an intelligent electricity meter, characterized in that, A server of a photovoltaic and energy storage power management system applied to a target business site. The photovoltaic and energy storage power management system includes a photovoltaic system, an energy storage system, the server, and an electrical load arranged in the target business site. The method includes: Determine the expected power generation of the photovoltaic system on each natural day in the future period under the condition of no light abandonment according to the historical power data of the intelligent electricity meter and the business reservation information of the target business site in the future period. The business reservation information includes business project information and vehicle information of self-driving vehicles. Determine the expected basic load power on each natural day of the target business site under the condition of no charging load of new energy vehicles in the self-driving vehicles according to the business project information and the electrical load. Determine the flexible load power that can be consumed by new energy vehicles in the self-driving vehicles of the photovoltaic system on each natural day according to the expected power generation on each natural day, the expected basic load power, and the storable power of the energy storage system. Create and publish a charging preferential plan for the target business site according to the flexible load power and the vehicle information of the self-driving vehicles to consume the flexible load power.

2. The method according to claim 1, characterized in that The step of determining the flexible load power that can be consumed by new energy vehicles in the self-driving vehicles of the photovoltaic system on each natural day according to the expected power generation on each natural day, the expected basic load power, and the storable power of the energy storage system includes: Determine the minimum guaranteed power of the energy storage system on each natural day in the future period without using grid power according to the expected power generation on each natural day, the expected basic load power, and the storable power. Determine the flexible load power that can be consumed by new energy vehicles in the self-driving vehicles of the photovoltaic system on each natural day according to the expected power generation, the expected basic load power, and the minimum guaranteed power.

3. The method according to claim 2, wherein Before the step of determining the minimum guaranteed power of the energy storage system on each natural day in the future period without using grid power according to the expected power generation on each natural day, the expected basic load power, and the storable power, the method further includes: Determine the total expected power generation in the future period according to the expected power generation on each natural day. Determine the total expected basic load power in the future period according to the expected basic load power on each natural day. Detect that the total expected power generation is greater than the total expected basic load power.

4. The method according to claim 3, characterized in that, The step of determining the minimum guaranteed power of the energy storage system on each natural day in the future period without using grid power according to the expected power generation on each natural day, the expected basic load power, and the storable power includes Determine the storable surplus power of the PV system on each natural day according to the predicted power generation amount of each natural day, the predicted base load power amount, and the storable power amount. The storable surplus power includes a positive state and a negative state. The positive state indicates that there is a positive surplus in the predicted power generation amount of the PV system on the current natural day, and the negative state indicates that there is no positive surplus in the predicted power generation amount of the PV system on the current natural day, and the minimum power amount that the energy storage system needs to store before the current natural day to meet the electricity demand of the current natural day; According to the storable surplus power of each natural day, infer the minimum guaranteed power amount of each natural day when the energy storage system does not need to draw power from the power grid during the future period, one natural day at a time in the reverse order of the multiple natural days in the future period.

5. The method according to claim 1, wherein The determination of the predicted power generation amount of the PV system on each natural day during the future period without light curtailment according to the historical power data of the smart electricity meter and the business reservation information of the target business site during the future period includes: Statistically analyze the historical power data of the PV system sampled and created by the smart electricity meter to obtain the corresponding relationship between the actual power generation amount of the PV system without light curtailment and the light condition; Obtain the weather data of each natural day during the future period of the target business site, where the weather data includes light conditions; Determine the predicted power generation amount of the PV system on each natural day without light curtailment according to the corresponding relationship and the weather data.

6. The method according to claim 5, characterized in that, The smart electricity meter is a smart meter installed on the AC output side of the PV system; before statistically analyzing the historical power data of the PV system sampled and created by the smart electricity meter to obtain the corresponding relationship between the actual power generation amount of the PV system without light curtailment and the light condition, the method further includes: Receive the sampled data and time stamp reported by the smart electricity meter; Query and obtain the light condition of the PV system at the time stamp; Determine the reference light curtailment rate of the PV system at the time stamp; Create the historical power data according to the light condition, the reference light curtailment rate, and the sampled data.

7. The method according to claim 6, wherein The determination of the reference light curtailment rate of the PV system at the time stamp includes: Determine the theoretical output power of the PV system at the time stamp according to the light condition and the configuration information of the PV system; Obtain the sampled output power of the PV system at the time stamp; Determine the reference light curtailment rate of the PV system at the time stamp according to the theoretical output power and the sampled output power.

8. The method according to claim 6, characterized in that The determination of the reference light curtailment rate of the PV system at the time stamp includes: Obtain the operation log of the PV system generated according to the status data reported by the anti-counterflow meter of the PV system. The status data includes the reverse flow status flag reported by the anti-counterflow meter, the first output power before the reverse flow of the PV system, and the second output power after the reverse flow of the PV system; Determine the reference curtailment rate of the photovoltaic system at the timestamp according to the first output power and the second output power.

9. The method according to any one of claims 6-8, characterized in that, Statistically analyze the historical power data of the photovoltaic system sampled and created by the smart electricity meter to obtain the corresponding relationship between the actual power generation of the photovoltaic system and the lighting conditions under the condition of no curtailment, including: Obtain a preset lighting condition classification table; Classify the historical power data according to the lighting condition classification table to obtain multiple historical power data sets corresponding to multiple types of lighting conditions; Perform data screening on each historical power data set according to the reference curtailment rate to obtain the historical power data after screening out the sampled data with curtailment; Perform denoising and mean processing on the parameter values of the screened historical power data to obtain the actual power generation; Create the corresponding relationship between the actual power generation of the photovoltaic system and the lighting conditions under the condition of no curtailment.

10. A photovoltaic and energy storage energy management system, characterized in that, It includes a server, a photovoltaic system, an energy storage system, and an electrical load arranged in a target business site, where The server is used to execute the steps performed by the server in any one of the methods of claims 1-9.

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