Light storage direct flexible system regulation and control method and device and electronic equipment

Abstract

The invention provides an optical storage direct flexible system regulation and control method and device and electronic equipment, and the method comprises the steps: obtaining historical data inputted for an electrical architecture model; complementing the input historical data based on the neural network prediction model to obtain sample data and inputting the sample data into a simulation system; generating an operation strategy of the electrical system based on the demand strategy, and regulating the operation of the electrical system according to the operation strategy to obtain a simulation operation result; and outputting final system configuration parameters under the condition that the simulation operation result meets a preset economic performance index. According to the optical storage direct flexible system regulation and control method and device and the electronic equipment provided by the embodiment of the invention, the operation is convenient and efficient, and time and energy consumed by strategy optimization can be reduced; high-precision output can be achieved, the operation model is formed by building circuits of all devices, and the step length can be calculated in a user-defined mode; and the energy-saving effect is remarkable, the predicted data is iteratively upgraded through the circuit model, the effect fits the reality, and the electricity saving quantity is remarkable.

Description

Technical Field

[0001] The present invention relates to the field of photovoltaic storage, direct-flexible technology, and in particular to a photovoltaic storage, direct-flexible system control method, device, electronic equipment and computer-readable storage medium. Background Art

[0002] At present, the PV-storage-direct-flexible system uses automation technology to achieve independent closed-loop control of equipment, but there is currently a lack of joint regulation capabilities between the various devices, which limits the applicability and flexibility of the system in practical applications. For example, energy storage devices often use simple charging and discharging strategies, while systems such as central air conditioning rely on traditional PID (proportional-integral-derivative control) feedback control to optimize the energy efficiency of a single device. However, these methods fail to fully utilize the overall advantages of the PV-storage-direct-flexible system. Summary of the invention

[0003] In order to solve the existing technical problems, the embodiments of the present invention provide a control method, device, electronic device and computer-readable storage medium for a photovoltaic storage direct-flexible system.

[0004] In the first aspect, an embodiment of the present invention provides a method for controlling a photovoltaic-storage direct-flexible system, comprising: obtaining historical data input for an electrical architecture model; the historical data comprising historical light intensity data and historical load power usage data; completing the input historical data based on a neural network prediction model to obtain sample data, and inputting the sample data into a simulation system; obtaining a user's demand strategy, generating an electrical system operation strategy based on the demand strategy, and controlling the operation of the electrical system according to the operation strategy to obtain a simulation operation result; when the simulation operation result meets the preset economic performance indicators, outputting final system configuration parameters, and operating the electrical system with the final system configuration parameters as input.

[0005] Optionally, before obtaining historical data for input of the electrical architecture model, the method further includes: constructing the electrical architecture model based on preset system configuration parameters; the preset system configuration parameters include at least photovoltaic parameters, load parameters, energy storage parameters, and electricity price parameters.

[0006] Optionally, the demand strategy includes at least: a new energy consumption priority strategy, a peak shaving and valley filling priority strategy, or a day-ahead economic operation priority strategy.

[0007] Optionally, the priority strategy for new energy consumption includes: when the load is higher than photovoltaic power generation, controlling the discharge of energy storage to reduce the purchase of electricity from the power grid; when the load is less than photovoltaic power generation, controlling the charging of energy storage; the priority strategy for peak shaving and valley filling includes: when electricity prices are low, drawing electricity from the power grid and storing it in energy storage equipment; when electricity prices are peak, drawing electricity from energy storage equipment and replenishing it to power-consuming equipment; the priority strategy for economic operation within the day before includes: coordinating the peak electricity price policy, virtual power plant task release information, photovoltaic power generation information and load power consumption information within a day in advance, and reasonably allocating electricity while ensuring its own stable operation.

[0008] Optionally, the operation of the electrical system is regulated according to the operation strategy, including: regulating the operation of the electrical system by timed changes in the charging and discharging power of the energy storage, the operating power of the AC-DC energy conversion cabinet, the bidirectional charging and discharging power of the automobile V2G charging pile, and / or the power consumption of the air conditioning load.

[0009] Optionally, the economic performance indicator includes: adjustable power related to the reserve capacity height.

[0010] In the second aspect, an embodiment of the present invention further provides a photovoltaic storage direct flexible energy control device, including: a data acquisition module, a data completion module, a strategy generation module and a result operation module; the data acquisition module is used to obtain historical data input for an electrical architecture model; the historical data includes historical light intensity data and historical load power usage data; the data completion module is used to complete the input historical data based on a neural network prediction model to obtain sample data, and input the sample data into a simulation system; the strategy generation module is used to obtain a user's demand strategy, generate an electrical system operation strategy based on the demand strategy, and control the operation of the electrical system according to the operation strategy to obtain a simulation operation result; the result operation module is used to output the final system configuration parameters when the simulation operation result meets the preset economic performance indicators, and operate the electrical system with the final system configuration parameters as input.

[0011] In a third aspect, an embodiment of the present invention provides an electronic device, including a processor and a memory, wherein the memory stores a computer program, and the processor executes the computer program stored in the memory. When the computer program is executed by the processor, the method for controlling the photovoltaic storage direct-flexible system described in the first aspect is implemented.

[0012] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the method for controlling the photovoltaic storage direct-flexible system described in the first aspect above is implemented.

[0013] In a fifth aspect, the present application also provides a computer program product, including a computer program. When the computer program is executed, it can implement the method for controlling the photovoltaic storage direct-flexible system described in the first aspect or any possible design method of the first aspect.

[0014] The control method, device, electronic device and computer-readable storage medium of the photovoltaic storage direct-flexible system provided by the embodiment of the present invention can respond to the regulation signal of the power grid and realize multi-objective collaborative optimization control by establishing an accurate electrical architecture model. This comprehensive control method not only improves the overall energy efficiency of the system, but also enhances the adaptability to power grid fluctuations, thereby significantly expanding the application scope and flexibility of the photovoltaic storage direct-flexible system. In addition, the embodiment of the present invention can predict the long-term operation data of modules such as photovoltaic loads through a neural network model, and iteratively optimize a distribution system operation scheduling strategy that maximizes the user's target requirements by running, verifying and iteratively optimizing on an actual simulation platform. In addition, the operation of the embodiment of the present invention is convenient and efficient, which can help greatly reduce the time and energy consumed by strategy optimization; it can also achieve high-precision output. The operation model is constructed by circuits of various devices, and the calculation step size can be customized (for example, the minimum step size of the system operation, and the millisecond-level operation data changes can be viewed); the energy-saving effect of the embodiment of the present invention is significant, and the predicted data is iteratively upgraded through the circuit model, the effect is in line with reality, and the power saving is significant. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the background technology, the drawings required for use in the embodiments of the present invention or the background technology will be described below.

[0016] Figure 1 A flow chart of a method for controlling a photovoltaic storage direct-flexible system provided by an embodiment of the present invention is shown; Figure 2 The operating model diagram of the electrical system in the control method of the photovoltaic storage direct-flexible system provided in the embodiment of the present invention is shown; Figure 3 The basic process of regulating the photovoltaic storage direct-flexible system provided by the embodiment of the present invention is shown; Figure 4 A schematic diagram showing the system operation status under the new energy consumption priority strategy in the photovoltaic storage direct flexible energy control method provided in an embodiment of the present invention is shown; Figure 5 A schematic diagram showing the system operation status under the peak shaving and valley filling priority strategy in the photovoltaic storage direct flexible energy control method provided in an embodiment of the present invention is shown; Figure 6 A schematic diagram showing the system operation status under the economic operation priority strategy within the day before in the photovoltaic storage direct flexible energy control method provided by an embodiment of the present invention is shown; Figure 7It shows the line operation voltage diagram of the pcs (ac dc energy conversion cabinet) equipment; Figure 8 The iterative optimization process in the photovoltaic storage direct flexible energy control method provided in the embodiment of the present invention is shown; Fig. 9 A schematic diagram of the structure of a photovoltaic storage direct-flexible system control device provided by an embodiment of the present invention is shown; Fig.10 A schematic diagram of the structure of an electronic device for executing a control method for a solar-storage direct-flexible system provided by an embodiment of the present invention is shown.

[0017] Reference numerals: 1- Photovoltaic subsystem, 2- AC / DC energy conversion module, 3- Charging pile subsystem, 4- Energy storage subsystem, 5- Various load subsystems. DETAILED DESCRIPTION

[0018] The embodiments of the present invention are described below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0019] Figure 1 FIG. 1 is a flow chart showing a method for controlling a solar-storage direct-flexible system provided by an embodiment of the present invention. Figure 1 As shown, the method includes the following steps 101-104.

[0020] Step 101: Acquire historical data input to an electrical architecture model; the historical data includes historical light intensity data and historical load power usage data.

[0021] Specifically, the electrical architecture model is a model that can reflect the power consumption of each subsystem based on electrical control. Figure 2 As shown, Figure 2 The operating model diagram of the electrical system shows the overall structure of the electrical architecture model. Figure 2 As shown, the electrical architecture model may include: a photovoltaic subsystem 1, an AC-DC energy conversion module 2, a charging pile subsystem 3, an energy storage subsystem 4 and various load subsystems 5. Among them, the photovoltaic subsystem 1 can simulate and display the photovoltaic power generation curve; the AC-DC energy conversion module 2 is used to connect to the power grid, which can be set to the expected value, and can also choose to operate in a constant power mode or a stable voltage mode according to project requirements. In an embodiment of the present invention, the user is required to input historical data into the electrical architecture model. The historical data includes: historical light intensity data and historical load power usage data. By obtaining these two types of historical data, the operation strategy of the electrical system is adjusted.

[0022] Step 102: Completing the input historical data based on the neural network prediction model to obtain sample data, and inputting the sample data into the simulation system.

[0023] Since the amount of historical data input by the user obtained in the above step 101 is small and the accuracy is not high, it is impossible to run the test in the simulation system by directly using the input historical data. Therefore, the embodiment of the present invention can use a neural network prediction model, such as LSTM (Long Short Term Memory), etc., to predict and supplement the existing historical data, so as to obtain the prediction data for a long time in the future, that is, sample data, and input the sample data into the simulation system. Among them, the simulation system is different from other data models. It is an electrical basic model, and each module has its corresponding circuit to play a verification test function.

[0024] Step 103: Obtain the user's demand strategy, generate an operation strategy for the electrical system based on the demand strategy, and regulate the operation of the electrical system according to the operation strategy to obtain a simulation operation result.

[0025] Specifically, the system can guide the user to input his actual demand strategy in the form of inquiry, so as to obtain the user's demand strategy. Optionally, the demand strategy can at least include: a new energy consumption priority strategy, a peak shaving and valley filling priority strategy, or a day-ahead economic operation priority strategy. The embodiment of the present invention can generate at least one electrical system operation strategy for a longer period of time based on any of the above demand strategies input by the user. In other words, the embodiment of the present invention can generate an operation strategy of the electrical system for the purpose of the demand strategy input by the user, so as to achieve the user's final demand through the operation strategy. It can be understood that the process of regulating the operation of the electrical system according to the operation strategy is actually a simulation process. After the operation is completed (that is, after the simulation is completed), the simulation operation result will be obtained. The simulation operation result in the embodiment of the present invention can be the data generated by the simulation operation after a period of time, for example, the adjustable power generated after a day of simulation operation, the adjustable power is obtained by subtracting the actual measured power in the simulation circuit from the required power, and the required power can be a load adjustable power curve, a pcs adjustable power curve, an energy storage adjustable power curve, etc.

[0026] Step 104: When the simulation operation result meets the preset economic performance index, the final system configuration parameters are output, and the final system configuration parameters are used as the input of the electrical system for operation.

[0027] The condition for judging whether the optimal state is reached in the embodiment of the present invention is: when the simulation operation result can meet the preset economic performance index, it indicates that the operation of the electrical architecture model (such as the electrical system) is optimal, and the corresponding system configuration parameters are also optimal parameters, which can be output as the final system configuration parameters. Subsequently, the final system configuration parameters can be directly used to set the electrical architecture model, so that the electrical architecture model can operate based on the final system configuration parameters and the operation strategy.

[0028] The control method of the photovoltaic storage direct-flexible system provided by the embodiment of the present invention can respond to the regulation signal of the power grid and realize multi-objective collaborative optimization control by establishing an accurate electrical architecture model. This comprehensive control method not only improves the overall energy efficiency of the system, but also enhances the adaptability to power grid fluctuations, thereby significantly expanding the application scope and flexibility of the photovoltaic storage direct-flexible system. In addition, the embodiment of the present invention can predict the long-term operation data of modules such as photovoltaic loads through a neural network model, and iteratively optimize a distribution system operation scheduling strategy that maximizes the user's target requirements by running, verifying, and iteratively optimizing on an actual simulation platform. In addition, the operation of the embodiment of the present invention is convenient and efficient, which can help greatly reduce the time and energy consumed by strategy optimization; it can also achieve high-precision output. This operation model is built by circuits of various devices, and the calculation step size can be customized (for example, the minimum step size of the system operation, and the millisecond-level operation data changes can be viewed); the energy-saving effect of the embodiment of the present invention is significant, and the predicted data is iteratively upgraded through the circuit model, the effect is in line with reality, and the power saving is significant.

[0029] Optionally, before the above step 101 "obtaining historical data for input of the electrical architecture model", the method further includes: constructing an electrical architecture model based on preset system configuration parameters. The preset system configuration parameters are configurations preset by the user according to actual needs, and may at least include: photovoltaic parameters (such as photovoltaic panel parameters), load parameters (such as parameters of each connected load), energy storage parameters, and electricity price parameters. In addition, the embodiment of the present invention can also input PCS (AC / DC energy conversion cabinet) parameters, demand-side response parameters, etc. When the above preset system configuration parameters are input into the system, the following will be automatically configured: Figure 2 The electrical architecture model can be constructed by running the model diagram shown in the figure. Figure 3 As shown, Figure 3 The basic process of regulating the solar-storage direct-flexible system is shown.

[0030] Optionally, in the demand strategy input by the user, the new energy consumption priority strategy includes: when the load is higher than photovoltaic power generation, controlling the energy storage discharge to reduce the purchase of electricity from the grid; when the load is less than photovoltaic power generation, controlling the energy storage charging.

[0031] Specifically, Figure 4 As shown, Figure 4 The schematic diagram of the system operation under the new energy consumption priority strategy is shown. Among them, line a represents the photovoltaic power generation, line b represents the daily operation curve of the photovoltaic system, and line c represents the curve after the operation strategy. This strategy aims to use energy storage to recover the surplus photovoltaic power generation as much as possible, thereby realizing the role of new energy consumption and maximizing the use of photovoltaics.

[0032] Secondly, if Figure 5As shown, Figure 5 The figure shows the schematic diagram of the system operation under the peak-shaving and valley-filling priority strategy. Specifically, line a shows the daily power consumption curve, while line b shows the data curve after the strategy is executed. That is, the peak-shaving and valley-filling priority strategy will take electricity from the grid and store it in the energy storage device during the low electricity price period; during the peak electricity price period, it will take electricity from the energy storage device and supplement it to the power consumption equipment, thereby achieving peak-shaving and valley-filling.

[0033] In addition, if Figure 6 As shown, Figure 6 The diagram shows the system operation status under the economic operation priority strategy of the day before. Among them, line a is the daily operation curve, line b is the curve after the operation strategy, and line c is the energy storage curve, that is, the economic operation priority strategy of the day before will coordinate the peak electricity price policy within a day in advance (storing in energy storage when the electricity price is low, and extracting from energy storage when the electricity price is high), virtual power plant task release information, photovoltaic power generation information and load power consumption information, etc., and reasonably distribute electricity while ensuring its own stable operation to meet the principle of economic maximization.

[0034] Optionally, in the above step 103, "regulating the operation of the electrical system according to the operation strategy" includes: regulating the operation of the electrical system by timed changes in the charging and discharging power of the energy storage, the operating power of the AC-DC energy conversion cabinet, the bidirectional charging and discharging power of the automobile V2G charging pile, and / or the power consumption of the air conditioning load.

[0035] In other words, the embodiment of the present invention can regulate the operation of the system by changing one or more parameters such as the charging and discharging power of the energy storage every 15 minutes, the operating power of the PCS (AC / DC energy conversion cabinet - grid-connected cabinet), the bidirectional charging and discharging power of the automobile V2G charging pile, and the power consumption of the air-conditioning load, thereby generating data for more time, i.e., the simulation operation results.

[0036] Optionally, the economic performance index may include actual adjustable power. The adjustable power is obtained by subtracting the actual measured power in the simulation circuit from the required power. The required power may be, for example, a load adjustable power curve, a PCS adjustable power curve, an energy storage adjustable power curve, etc.

[0037] Specifically, for the PV-storage direct-flexible system, sufficient spare capacity buffer is required, that is, the capacity of the battery and the power that can be reduced or increased by the load, that is, the spare capacity buffer can be used to respond to demand side response, realize peak shaving and valley filling, and absorb photovoltaic power. Therefore, the embodiment of the present invention can set the adjustable power that is highly related to the spare capacity as an economic performance indicator.

[0038] It should be noted that when judging the simulation operation results based on the economic performance index, it can be judged whether the simulation operation results meet the economic performance index. If not, it will be iteratively optimized to update the system configuration parameters required for operation and continue the simulation until the economic performance index is met. In addition to generating the operation strategy, the embodiment of the present invention can also generate a timeline-based view of the operating conditions of all devices in the system within a set time, such as Figure 7 As shown, Figure 7 The line operating voltage diagram of the PCS (AC / DC energy conversion cabinet) equipment is shown, in which the three colors represent the three voltages of the three phases of the three-phase AC power. The blue curve can be represented as phase A, the red curve can be represented as phase B, and the green curve can be represented as phase C.

[0039] See also Figure 8 As shown, Figure 8 What is shown is the iterative optimization process. When the error of the actual operating power change curve of the system is too large, it means that the economic performance indicators of the demand strategy are not met at the electrical system operation level. Therefore, it is necessary to analyze and read the power consumption of each module, increase or decrease the operating power of each module through the algorithm, and iterate the simulation until the final configuration is generated after the indicators are met.

[0040] The above describes in detail the photovoltaic storage direct-flexible energy system control method provided in an embodiment of the present invention. The method can also be implemented by a corresponding device. The following describes in detail the photovoltaic storage direct-flexible energy control device provided in an embodiment of the present invention.

[0041] Fig. 9 FIG. 1 is a schematic diagram showing the structure of a photovoltaic storage direct flexible energy control device provided by an embodiment of the present invention. Fig. 9 As shown, the photovoltaic storage direct flexible energy control device includes a processor. The processor includes: a data acquisition module 91, a data completion module 92, a strategy generation module 93 and a result operation module 94.

[0042] The data acquisition module 91 is used to acquire historical data inputted into the electrical architecture model; the historical data includes historical light intensity data and historical load power usage data.

[0043] The data completion module 92 is used to complete the input historical data based on the neural network prediction model to obtain sample data, and input the sample data into the simulation system.

[0044] The strategy generation module 93 is used to obtain the user's demand strategy, generate an operation strategy of the electrical system based on the demand strategy, and regulate the operation of the electrical system according to the operation strategy to obtain a simulation operation result.

[0045] The result operation module 94 is used to output the final system configuration parameters when the simulation operation result meets the preset economic performance index, and operate the electrical system with the final system configuration parameters as the input.

[0046] Optionally, before obtaining historical data for inputting the electrical architecture model, it also includes: constructing the electrical architecture model based on preset system configuration parameters; the preset system configuration parameters at least include photovoltaic parameters, load parameters, energy storage parameters, and electricity price parameters.

[0047] Optionally, the demand strategy includes at least: a new energy consumption priority strategy, a peak shaving and valley filling priority strategy, or a day-ahead economic operation priority strategy.

[0048] Optionally, the priority strategy for new energy consumption includes: when the load is higher than photovoltaic power generation, controlling the discharge of energy storage to reduce the purchase of electricity from the power grid; when the load is less than photovoltaic power generation, controlling the charging of energy storage; the priority strategy for peak shaving and valley filling includes: when electricity prices are low, drawing electricity from the power grid and storing it in energy storage equipment; when electricity prices are peak, drawing electricity from energy storage equipment and replenishing it to power-consuming equipment; the priority strategy for economic operation within the day before includes: coordinating the peak electricity price policy, virtual power plant task release information, photovoltaic power generation information and load power consumption information within a day in advance, and reasonably allocating electricity while ensuring its own stable operation.

[0049] Optionally, the policy generation module 93 includes: a policy execution unit.

[0050] The strategy execution unit is used to regulate the operation of the electrical system by timed changes in the charging and discharging power of the energy storage, the operating power of the AC-DC energy conversion cabinet, the bidirectional charging and discharging power of the automobile V2G charging pile, and / or the power used by the air conditioning load.

[0051] Optionally, the economic performance indicator includes: adjustable power related to the reserve capacity height.

[0052] The device provided in the embodiment of the present invention can respond to the regulation signal of the power grid and realize multi-objective collaborative optimization control by establishing an accurate electrical architecture model. This comprehensive control device not only improves the overall energy efficiency of the system, but also enhances the adaptability to power grid fluctuations, thereby significantly expanding the application scope and flexibility of the photovoltaic storage direct and flexible system. In addition, the embodiment of the present invention can predict the long-term operation data of modules such as photovoltaic loads through a neural network model, and iteratively optimize a distribution system operation scheduling strategy that maximizes the user's target requirements by running, verifying, and iteratively optimizing on an actual simulation platform. In addition, the embodiment of the present invention is convenient and efficient to operate, which can help greatly reduce the time and energy consumed by strategy optimization; it can also achieve high-precision output. This operation model is built by circuits of various devices, and the calculation step size can be customized (for example, the minimum step size of the system operation, and the millisecond-level operation data changes can be viewed); the embodiment of the present invention has a significant energy-saving effect, and the predicted data is iteratively upgraded through the circuit model, the effect is in line with reality, and the power saving is significant.

[0053] It should be noted that the photovoltaic storage direct and flexible energy control device provided in the above embodiment only uses the division of the above functional modules as an example to implement the corresponding functions. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the photovoltaic storage direct and flexible energy control device provided in the above embodiment and the photovoltaic storage direct and flexible system control method embodiment belong to the same concept. The specific implementation process is detailed in the method embodiment and will not be repeated here.

[0054] According to one aspect of the present application, an embodiment of the present invention further provides a computer program product, the computer program product comprising a computer program, the computer program comprising a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication part. When the computer program is executed by a processor, the control method of the PV-storage direct-flexible system provided in the embodiment of the present application is executed.

[0055] In addition, an embodiment of the present invention also provides an electronic device, including a bus, a transceiver, a memory, a processor, and a computer program stored in the memory and run on the processor. The transceiver, the memory and the processor are respectively connected via a bus. When the computer program is executed by the processor, each process of the above-mentioned optical storage direct-flexible system control method embodiment is implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0056] For details, see Fig.10 As shown, the electronic device includes a bus 1110 , a processor 1120 , a transceiver 1130 , a bus interface 1140 , a memory 1150 , and a user interface 1160 .

[0057] In an embodiment of the present invention, the electronic device also includes: a computer program stored in the memory 1150 and executable on the processor 1120, and when the computer program is executed by the processor 1120, each process of the above-mentioned embodiment of the method for controlling the photovoltaic storage direct-flexible system is implemented.

[0058] The transceiver 1130 is configured to receive and send data under the control of the processor 1120 .

[0059] In an embodiment of the present invention, a bus architecture (represented by bus 1110 ) may include any number of interconnected buses and bridges, and bus 1110 connects various circuits including one or more processors represented by processor 1120 and a memory represented by memory 1150 .

[0060] Bus 1110 represents one or more of any of several types of bus structures, including a memory bus and memory controller, a peripheral bus, an Accelerate Graphical Port (AGP), a processor, or a local bus using any of a variety of bus architectures. By way of example and not limitation, such architectures include: Industry Standard Architecture (ISA) bus, Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA) bus, Video Electronics Standards Association (VESA), Peripheral Component Interconnect (PCI) bus.

[0061] The processor 1120 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method embodiment may be completed by an integrated logic circuit of hardware in the processor or an instruction in the form of software. The above processors include: a general processor, a central processing unit (CPU), a network processor (NP), a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), a complex programmable logic device (CPLD), a programmable logic array (PLA), a microcontroller unit (MCU) or other programmable logic devices, discrete gates, transistor logic devices, discrete hardware components. The methods, steps and logic block diagrams disclosed in the embodiments of the present invention may be implemented or executed. For example, the processor may be a single-core processor or a multi-core processor, and the processor may be integrated into a single chip or located on multiple different chips.

[0062] Processor 1120 can be a microprocessor or any conventional processor. The method steps disclosed in the embodiment of the present invention can be directly executed by a hardware decoding processor, or by a combination of hardware and software modules in the decoding processor. The software module can be located in a readable storage medium known in the art, such as a random access memory (RAM), a flash memory (FlashMemory), a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), a register, etc. The readable storage medium is located in the memory, and the processor reads the information in the memory and completes the steps of the above method in combination with its hardware.

[0063] The bus 1110 may also connect various other circuits such as peripheral devices, voltage regulators or power management circuits, and the bus interface 1140 provides an interface between the bus 1110 and the transceiver 1130, which are well known in the art. Therefore, the embodiments of the present invention will not be further described.

[0064] The transceiver 1130 may be one element or multiple elements, such as multiple receivers and transmitters, and provides a unit for communicating with various other devices on a transmission medium. For example, the transceiver 1130 receives external data from other devices, and the transceiver 1130 is used to send data processed by the processor 1120 to other devices. Depending on the nature of the computer system, a user interface 1160 may also be provided, such as a touch screen, a physical keyboard, a display, a mouse, a speaker, a microphone, a trackball, a joystick, and a stylus.

[0065] It should be understood that in an embodiment of the present invention, the memory 1150 may further include a memory remotely arranged relative to the processor 1120, and these remotely arranged memories may be connected to the server through a network. One or more parts of the above-mentioned network may be an ad hoc network, an intranet, an extranet, a virtual private network (VPN), a local area network (LAN), a wireless local area network (WLAN), a wide area network (WAN), a wireless wide area network (WWAN), a metropolitan area network (MAN), the Internet, a public switched telephone network (PSTN), a plain old telephone service network (POTS), a cellular telephone network, a wireless network, a wireless fidelity (Wi-Fi) network, and a combination of two or more of the above-mentioned networks. For example, the cellular telephone network and the wireless network can be a Global System for Mobile Communications (GSM) system, a Code Division Multiple Access (CDMA) system, a Worldwide Interoperability for Microwave Access (WiMAX) system, a General Packet Radio Service (GPRS) system, a Wideband Code Division Multiple Access (WCDMA) system, a Long Term Evolution (LTE) system, a LTE Frequency Division Duplex (FDD) system, a LTE Time Division Duplex (TDD) system, an Advanced Long Term Evolution (LTE-A) system, a Universal Mobile Telecommunications (UMTS) system, an Enhanced Mobile Broadband (eMBB) system, a Massive Machine Type of Communication (mMTC) system, an Ultra Reliable Low Latency Communications (uRLLC) system, etc.

[0066] It should be understood that the memory 1150 in the embodiment of the present invention may be a volatile memory or a non-volatile memory, or may include both a volatile memory and a non-volatile memory. Among them, the non-volatile memory includes: 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.

[0067] Volatile memory includes: Random Access Memory (RAM), which is used as an external cache. By way of example but not limitation, many forms of RAM are available, such as: Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM) and Direct Rambus RAM (DRRAM). The memory 1150 of the electronic device described in the embodiment of the present invention includes but is not limited to the above and any other suitable types of memory.

[0068] In the embodiment of the present invention, the memory 1150 stores the following elements of the operating system 1151 and the application program 1152: executable modules, data structures, or subsets thereof, or extended sets thereof.

[0069] Specifically, the operating system 1151 includes various system programs, such as a framework layer, a core library layer, a driver layer, etc., which are used to implement various basic services and process hardware-based tasks. The application 1152 includes various applications, such as a media player (Media Player) and a browser (Browser), which are used to implement various application services. The program for implementing the method of the embodiment of the present invention may be included in the application 1152. The application 1152 includes applets, objects, components, logic, data structures, and other computer system executable instructions that perform specific tasks or implement specific abstract data types.

[0070] In addition, an embodiment of the present invention also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the various processes of the above-mentioned embodiment of the photovoltaic storage direct-flexible system control method are implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0071] Computer readable storage media include: permanent and non-permanent, removable and non-removable media, which are tangible devices that can retain and store instructions for use by instruction execution devices. Computer readable storage media include: electronic storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, and any suitable combination of the above. Computer readable storage media include: phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), non-volatile random access memory (NVRAM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassette storage, magnetic tape disk storage or other magnetic storage devices, memory sticks, mechanical encoding devices (such as punched cards or raised structures in grooves with instructions recorded thereon) or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined in the embodiments of the present invention, computer-readable storage media do not include temporary signals themselves, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (such as light pulses passing through fiber optic cables), or electrical signals transmitted through wires.

[0072] In the several embodiments provided in the present application, it should be understood that the disclosed devices, electronic devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, or it can be an electrical, mechanical or other form of connection.

[0073] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, and may be located in one location or distributed on multiple network units. Some or all of the units may be selected according to actual needs to solve the problem to be solved by the embodiments of the present invention.

[0074] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0075] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiment of the present invention is essentially or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including several instructions for a computer device (including: a personal computer, a server, a data center or other network equipment) to perform all or part of the steps of the method described in each embodiment of the present invention. The above-mentioned storage medium includes various media that can store program codes as listed above.

[0076] In the description of the embodiments of the present invention, those skilled in the art should know that the embodiments of the present invention can be implemented as methods, devices, electronic devices and computer-readable storage media. Therefore, the embodiments of the present invention can be specifically implemented in the following forms: complete hardware, complete software (including firmware, resident software, microcode, etc.), a combination of hardware and software. In addition, in some embodiments, the embodiments of the present invention can also be implemented in the form of a computer program product in one or more computer-readable storage media, and the computer-readable storage medium contains computer program code.

[0077] The above-mentioned computer-readable storage medium may adopt any combination of one or more computer-readable storage media. Computer-readable storage media include: electrical, magnetic, optical, electromagnetic, infrared or semiconductor systems, devices or devices, or any combination of the above. More specific examples of computer-readable storage media include: portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM), flash memories, optical fibers, compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices or any combination of the above. In an embodiment of the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, device, or device.

[0078] The computer program code contained in the above-mentioned computer-readable storage medium can be transmitted by any appropriate medium, including: wireless, wire, optical cable, radio frequency (RF) or any suitable combination thereof.

[0079] The computer program code for performing the operation of the embodiment of the present invention can be written in assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-related instructions, microcode, firmware instructions, state setting data, integrated circuit configuration data, or in one or more programming languages ​​or a combination thereof, wherein the programming language includes an object-oriented programming language, such as Java, Smalltalk, C++, and also includes a conventional procedural programming language, such as C language or a similar programming language. The computer program code can be executed completely on the user's computer, partially on the user's computer, as an independent software package, partially on the user's computer, partially on a remote computer, and completely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer or to an external computer through any type of network, including a local area network (LAN) or a wide area network (WAN).

[0080] The embodiments of the present invention describe the provided methods, devices, and electronic devices through flowcharts and / or block diagrams.

[0081] It should be understood that each box in the flowchart and / or block diagram and the combination of boxes in the flowchart and / or block diagram can be implemented by computer-readable program instructions. These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer or other programmable data processing device to produce a machine, and these computer-readable program instructions are executed by a computer or other programmable data processing device to produce a device that implements the functions / operations specified by the boxes in the flowchart and / or block diagram.

[0082] These computer-readable program instructions may also be stored in a computer-readable storage medium that enables a computer or other programmable data processing device to work in a specific manner. In this way, the instructions stored in the computer-readable storage medium produce an instruction device product including functions / operations specified in the blocks in the flowchart and / or block diagram.

[0083] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device, so that a series of operational steps are performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby enabling the instructions executed on the computer or other programmable data processing apparatus to provide a process for implementing the functions / operations specified in the blocks in the flowchart and / or block diagram.

[0084] The above is only a specific implementation of the embodiment of the present invention, but the protection scope of the embodiment of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the embodiment of the present invention, which should be included in the protection scope of the embodiment of the present invention. Therefore, the protection scope of the embodiment of the present invention should be based on the protection scope of the claims.

Claims

1. A control method for a solar-storage direct-flexible system, characterized in that: include: Acquire historical data for input of the electrical architecture model; the historical data includes historical light intensity data and historical load power usage data; Completing the input historical data based on the neural network prediction model to obtain sample data, and inputting the sample data into the simulation system; Acquire the user's demand strategy, generate an operation strategy of the electrical system based on the demand strategy, and regulate the operation of the electrical system according to the operation strategy to obtain a simulation operation result; When the simulation operation result meets the preset economic performance index, the final system configuration parameters are output, and the electrical system is operated with the final system configuration parameters as input.

2. The method according to claim 1, characterized in that: Before obtaining the historical data for inputting the electrical architecture model, the method further includes: The electrical architecture model is constructed based on preset system configuration parameters; the preset system configuration parameters at least include photovoltaic parameters, load parameters, energy storage parameters, and electricity price parameters.

3. The method according to claim 1, characterized in that: The demand strategy includes at least: a new energy consumption priority strategy, a peak shaving and valley filling priority strategy or a day-ahead economic operation priority strategy.

4. The method according to claim 3, characterized in that The priority strategies for new energy consumption include: When the load is higher than photovoltaic power generation, control the energy storage discharge to reduce the purchase of electricity from the grid; When the load is less than the photovoltaic power generation, the energy storage charging is controlled; The peak shaving and valley filling priority strategy includes: When electricity prices are low, electricity is drawn from the grid and stored in energy storage devices; During peak electricity prices, electricity is taken from the energy storage device and added to the power-consuming equipment; The economic operation priority strategies for the day before include: Coordinate the peak electricity price policy, virtual power plant task release information, photovoltaic power generation information and load power consumption information within a day in advance, and reasonably allocate electricity while ensuring its own stable operation.

5. The method according to claim 1, characterized in that The step of regulating the operation of the electrical system according to the operation strategy includes: The operation of the electrical system is regulated by periodically changing the charging and discharging power of the energy storage, the operating power of the AC-DC energy conversion cabinet, the bidirectional charging and discharging power of the automobile V2G charging pile, and / or the power used by the air conditioning load.

6. The method according to claim 1, characterized in that The economic performance indicators include: adjustable power that is highly related to the reserve capacity.

7. A solar energy storage direct and flexible energy control device, characterized in that: include: Data acquisition module, data completion module, strategy generation module and result operation module; The data acquisition module is used to acquire historical data input for the electrical architecture model; the historical data includes historical light intensity data and historical load power usage data; The data completion module is used to complete the input historical data based on the neural network prediction model to obtain sample data, and input the sample data into the simulation system; The strategy generation module is used to obtain the user's demand strategy, generate an operation strategy of the electrical system based on the demand strategy, and regulate the operation of the electrical system according to the operation strategy to obtain a simulation operation result; The result operation module is used to output final system configuration parameters when the simulation operation result meets the preset economic performance index, and operate the electrical system with the final system configuration parameters as input.

8. An electronic device comprising a processor and a memory, wherein the memory stores a computer program, characterized in that: The processor executes the computer program stored in the memory to implement the steps in the control method of the photovoltaic storage direct-flexible system as described in any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps in the control method of a PV-storage direct-flexible system as described in any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, which, when executed, can implement the steps in the control method of a solar-storage direct-flexible system as claimed in any one of claims 1 to 6.

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