Photovoltaic control method and device

Abstract

The present invention relates to the field of photovoltaic power generation technology, and discloses a photovoltaic control method and device, comprising: when a local control switch is turned on, determining whether a direct control strategy is received; if a direct control strategy is received, directly executing the direct control strategy; otherwise, selecting and executing the control strategy that should be executed in the current time period according to the priority of the currently received control strategy and its corresponding scheduling schedule. In the present invention, when the local control switch is turned on, the execution mode can be flexibly selected according to whether a direct control strategy is received. If a direct control strategy is received, it is directly executed; otherwise, it is selected and executed according to the priority and scheduling schedule, so that the control mode is diverse and can be flexibly switched according to actual needs, thereby enhancing the adaptability and flexibility of the system, and solving the problem that the photovoltaic inverter monitoring system can only monitor alarms and cannot perform planned control.

Description

Technical Field

[0001] The present invention relates to the technical field of photovoltaic power generation, and in particular to a photovoltaic control method and device. Background Art

[0002] The characteristics of photovoltaic power generation dictate that its output power is significantly affected by external environmental factors, such as solar radiation. For example, under poor lighting conditions, such as cloudy or rainy days, or at different times of the day, solar radiation intensity can vary significantly, causing the output power of photovoltaic power generation systems to exhibit certain fluctuations and uncertainties. This volatility and uncertainty poses a serious challenge to the safe and stable operation of the power grid, potentially causing voltage fluctuations, frequency deviations, and other problems, affecting the normal power supply quality of the grid.

[0003] To address these challenges and improve the reliability and economic efficiency of distributed photovoltaic systems, research on distributed photovoltaic control has important practical significance. By flexibly controlling the operation of photovoltaic systems in real-time scheduling, it is possible to achieve optimal utilization of photovoltaic power generation, effectively improve the efficiency and stability of the system, and reduce the negative impact of photovoltaic power generation on the power grid.

[0004] While some charging pile monitoring systems exist, they suffer from numerous flaws and shortcomings. For one thing, the PV inverter industry has only recently flourished, and different manufacturers have adopted varying standards and communication protocols in their production processes. This leads to compatibility issues between PV inverters and concentrators, hindering effective data collection and analysis, and consequently, the planned control of PV inverters. Furthermore, most current PV inverter monitoring systems only offer monitoring and alarm functions, failing to implement planned control of PV inverters. This can lead to overloads on the power grid, waste energy, and hinder the full performance of PV inverters, compromising stable grid operation and the rational allocation of energy. Summary of the Invention

[0005] In view of this, the present invention provides a photovoltaic control method and device to solve the problem that the photovoltaic inverter monitoring system can only monitor and alarm but cannot perform planned control.

[0006] In a first aspect, the present invention provides a photovoltaic control method, which is applied to a distributed power access unit, which is used to access a distributed power source. The method includes: when a local control switch is turned on, determining whether a direct control strategy is received; if a direct control strategy is received, directly executing the direct control strategy; otherwise, according to the priority of the currently received control strategy and its corresponding scheduling schedule, selecting and executing the control strategy that should be executed in the current period.

[0007] In this invention, when the local control switch is turned on, the execution mode can be flexibly selected based on whether a direct control strategy has been received. If a direct control strategy is received, it is directly executed; otherwise, it is selected according to the priority and scheduling schedule. This makes the control mode diverse and can be flexibly switched according to actual needs, enhancing the adaptability and flexibility of the system. At the same time, it solves the problem that the photovoltaic inverter monitoring system can only monitor alarms but cannot perform planned control.

[0008] In an optional embodiment, the direct control strategy includes: local control parameters of distributed power sources; other control strategies include: local control parameters of distributed power sources and distributed power source control scheduling plan parameters; local control parameters of distributed power sources include local control time periods, and distributed power source control scheduling plan parameters include planned execution dates.

[0009] In the present invention, a clear distinction is made between direct control strategies and other control strategies, and corresponding parameters such as distributed power local control parameters (including local control time period) and distributed power control scheduling schedule parameters (including planned execution date) are defined in detail, which facilitates the system to accurately understand and execute control strategies, thereby improving the accuracy and standardization of control.

[0010] In an optional embodiment, the process of directly executing the direct control strategy includes: forcibly terminating the currently executing control strategy; judging whether the direct control strategy is power load control or power on / off control; if the direct control strategy is power load control, then according to the local control parameters of the distributed power source, the output parameters of the photovoltaic inverter in the distributed power source are set; if the direct control strategy is power on / off control, then according to the local control parameters of the distributed power source, the photovoltaic inverter in the distributed power source is controlled to be turned on or off.

[0011] In the present invention, when the direct control strategy is directly executed, the currently executing control strategy is first forcibly terminated, and then corresponding operations are performed according to the type of direct control strategy (adjusting power load control or power on / off control), such as setting photovoltaic inverter output parameters or controlling power on / off, thereby realizing refined control of distributed power sources and being able to quickly respond to specific control needs.

[0012] In an optional embodiment, the process of selecting and executing the control strategy that should be executed in the current time period includes: determining whether an overload control strategy is received; if an overload control strategy is received, directly executing the overload control strategy, otherwise cyclically querying the currently received control strategies, executing the control strategy with the highest priority and a scheduling time in the current time period, or executing the local control strategy.

[0013] In this invention, if no direct control strategy is received, the system determines whether an overload control strategy has been received. If so, it executes it directly. Otherwise, it loops through and executes the highest-priority control strategy or the local control strategy scheduled within the current time period. This priority control mechanism ensures that important control tasks, such as overload situations, are prioritized in different situations, while also rationally arranging the execution of other control strategies, thereby improving the stability and reliability of system operation.

[0014] In an optional embodiment, the process of executing the control strategy with the highest priority and a scheduling time in the current time period, or executing the local control strategy, includes: if the local control strategy is currently being executed, when at least one planned control strategy is received, the execution of the local control strategy is stopped, and each planned control strategy is polled to see whether the scheduling time is in the current time period; if there is a planned control strategy with a scheduling time in the current time period, the planned control strategy is executed, otherwise the local control strategy continues to be executed.

[0015] In the present invention, when a local control strategy is currently being executed and a planned control strategy is received, the local control strategy can be stopped in an orderly manner and the scheduling time of the planned control strategy can be polled. Whether to execute the planned control strategy is determined based on the scheduling time, thereby ensuring the orderliness of switching between different control strategies and avoiding conflicts and confusion in strategy execution.

[0016] In an optional embodiment, the process of polling whether the scheduling time of each planned control strategy is within the current time period includes: determining whether the execution date in the control schedule of the planned control strategy is the current date; if it is the current date, determining whether the local control time period of the planned control strategy is the current time period.

[0017] In the present invention, when polling the scheduling time of the planned control strategy, whether it is in the current time period is determined by judging the execution date and the local control time period. This precise time judgment can ensure that the control strategy is executed at the appropriate time, further improving the accuracy and effectiveness of the control.

[0018] In an optional embodiment, the photovoltaic control method also includes: using a convolutional neural network to perform deep feature extraction and dimensionality reduction on multidimensional data; mining the temporal dependencies between data through a long short-term memory network and predicting photovoltaic power data; comparing, analyzing and calculating the predicted photovoltaic power data with a pre-set site power threshold to generate a local control strategy.

[0019] This method uses a convolutional neural network to extract deep features and reduce dimensionality from multidimensional data. A long-short-term memory network then mines the temporal dependencies between the data and predicts photovoltaic power. This data is then compared with pre-set site power thresholds for analysis and calculation to generate a local control strategy. This data analysis and strategy generation approach, based on advanced algorithms, fully utilizes data information, improving the accuracy of photovoltaic power predictions and generating more effective local control strategies to optimize photovoltaic system operation.

[0020] In an optional embodiment, before determining whether an overload control strategy is received, it also includes: determining whether the connected distributed power source is in an island operation mode; if the distributed power source is in an island operation mode, disconnecting the distributed power source from the power grid, otherwise determining whether an overload control strategy is received.

[0021] In the present invention, before determining whether an overload control strategy has been received, it is first determined whether the distributed power source is in an island operation mode. If it is in an island operation mode, the connection with the power grid is disconnected, thereby avoiding potential safety hazards and system failures caused by island operation and improving the safety and reliability of system operation.

[0022] In the second aspect, the present invention provides a photovoltaic control system, including: a master station side, a terminal side and a site side, wherein the master station side is used to obtain the site side data sent by the terminal side; according to various control requirements, a planned control strategy or a direct control strategy is generated according to the site side data, and the planned control strategy or the direct control strategy is sent to the terminal side; the terminal side is used to generate an overload control strategy when the distributed power source is overloaded; the planned control strategy or the direct control strategy or the overload control strategy site side is connected to the distributed power source for executing the photovoltaic control method of the first aspect or any corresponding embodiment thereof.

[0023] The system adopts a layered architecture consisting of a master station, terminal, and site, with clear division of labor among each component. The master station is responsible for acquiring data and generating planned or direct control strategies. The terminal is responsible for generating overload control strategies when the distributed power source is overloaded. The site implements the photovoltaic control method. This layered architecture enables each system module to perform its duties, achieving efficient collaboration and improving the operational efficiency and management capabilities of the entire photovoltaic control system.

[0024] In a third aspect, the present invention provides a computer device comprising: a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the photovoltaic control method of the first aspect or any corresponding embodiment thereof by executing the computer instructions.

[0025] In a fourth aspect, the present invention provides a computer-readable storage medium having computer instructions stored thereon, the computer instructions being used to enable a computer to execute the photovoltaic control method of the first aspect or any corresponding embodiment thereof.

[0026] In a fifth aspect, the present invention provides a computer program product, comprising computer instructions, which are used to enable a computer to execute the photovoltaic control method of the first aspect or any corresponding embodiment thereof. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0028] Figure 1 is a diagram of the composition of a photovoltaic control system according to an embodiment of the present invention;

[0029] Figure 2 This is a flow chart of generating a direct control strategy and a planned control strategy by the master station side according to an embodiment of the present invention;

[0030] Figure 3 is a flow chart of generating an overload control strategy on the terminal side according to an embodiment of the present invention;

[0031] Figure 4 is a flow chart of a photovoltaic control strategy according to an embodiment of the present invention;

[0032] Figure 5 is a flow chart of another photovoltaic control strategy according to an embodiment of the present invention;

[0033] Figure 6 is a flow chart of generating a local control strategy at a site side according to an embodiment of the present invention;

[0034] Figure 7 Schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0035] To make the purpose, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making creative efforts shall fall within the scope of protection of the present invention.

[0036] In this embodiment, a photovoltaic control system is provided. Figure 1 As shown, it includes: master station side, terminal side and site side.

[0037] The master station side is used to obtain the site-side data sent by the terminal side; according to various control requirements, a planned control strategy or a direct control strategy is generated according to the site-side data, and the planned control strategy or the direct control strategy is sent to the terminal side; the terminal side is used to generate an overload control strategy when the distributed power supply is overloaded; the planned control strategy or the direct control strategy or the overload control strategy site side is connected to the distributed power supply to execute the photovoltaic control method of the following embodiments or any corresponding implementation method thereof.

[0038] Specifically, the PV control system consists of three parts: the master station, the terminal, and the site. The master station, the central cloud, is primarily responsible for data analysis and issuing commands such as control and parameters. The terminal collects and manages all site-side equipment within the substation area. The site is responsible for the units being collected and operated.

[0039] In some optional embodiments, such as Figure 1 As shown, the master station side includes: a procurement platform and a user photovoltaic monitoring master station, wherein the procurement platform is connected to the terminal side; the user photovoltaic monitoring master station is connected to the site side.

[0040] Alternatively, as Figure 1 As shown, the terminal side includes: a concentrator, wherein the first end of the concentrator transmits data with the user platform through a wireless network, and the second end of the concentrator transmits data with the site side through HPLC combined with HRF.

[0041] Alternatively, as Figure 1 As shown, the site side includes: a smart meter, a photovoltaic circuit breaker, a photovoltaic inverter, an interface adapter and a distributed power access unit, wherein the smart meter transmits data to the second end of the concentrator and the first end of the distributed power access unit respectively through HPLC combined with HRF; the first end of the photovoltaic circuit breaker is connected to the smart meter, the second end of the photovoltaic circuit breaker is connected to the second end of the distributed power access unit, and the third end of the photovoltaic circuit breaker is connected to the DC side of the photovoltaic inverter; the AC side of the photovoltaic inverter is connected to the first end of the interface adapter; the second end of the interface adapter is connected to the user photovoltaic detection master station through a wireless network; the third end of the distributed power access unit is connected to the third end of the interface adapter, and the fourth end of the distributed power access unit is used to access the distributed power supply.

[0042] Specifically, refer to Figure 1Smart meters and distributed generation access units (DGAUs) are installed at property boundary points. This downstream network, representing a single site, provides information on grid load and PV inverters. The concentrator uses HPLC+HRF to collect and monitor site-side data and forwards it to the upstream master station via 4G. The master station stores and analyzes the relevant monitoring data and issues a distributed generation control and scheduling plan. Finally, the DGAU supports automatic adjustment. Based on historical data such as temperature, humidity, solar irradiance, wind speed, wind direction, and PV power, a convolutional neural network-long short-term memory (CNN-LSTM) prediction model generates a local control plan. Based on the control and scheduling plan issued by the upstream collector and the master station, as well as its own generation, the DGAU controls the active and reactive power parameters of downstream PV inverters in different time periods, improving the grid's carrying capacity and addressing the issue of limited distributed PV access.

[0043] In an optional implementation, the master station side is used to obtain the site side data sent by the terminal side; according to various control requirements, it generates a planned control strategy or a direct control strategy based on the site side data, and sends the planned control strategy or the direct control strategy to the terminal side. The specific process is as follows Figure 2 shown.

[0044] Specifically, the master station saves and counts the site segment data sent by the concentrator, and independently generates control strategies according to control requirements such as grid peak regulation, substation management, and user management. By sending data to the distributed power access unit, regional-level scheduling control is achieved.

[0045] Optionally, the planned control strategy includes: distributed power local control strategy parameters and distributed power control schedule parameters; the direct control strategy includes: distributed power load parameters.

[0046] Specifically, if the planned control strategy is used, the following settings are required: local control parameters for the distributed generation (DGs), including control type, priority, startup status, local control switch, and local control period. Also required are the DG control schedule, including the plan source, execution date, control period, control method, and control value. If the direct control strategy is used, the DG load control parameters, including the control method and control value, must be set.

[0047] In an optional implementation, the terminal side is used to collect data from the site side and send it to the master side; obtain the planned control strategy or direct control strategy sent by the master side, and send the planned control strategy or direct control strategy to the site side. Figure 3 shown.

[0048] Specifically, the concentrator regularly collects and stores data from downlink site equipment via the HPLC+HRF channel. Depending on the master station configuration, the concentrator actively reports or passively collects data, forwarding it to the upstream user acquisition platform via 4G. When detecting reverse overload or forward overload, the concentrator automatically generates a control strategy and sends it to the distributed power access unit, enabling dispatch control at the substation level. Furthermore, if data is lost or zero, data re-copying is performed.

[0049] Optionally, the terminal side monitors whether there is a forward overload or a reverse heavy overload on the site side based on the site side data; when there is a forward overload or a reverse heavy overload on the site side, a control strategy is automatically generated and the planned control strategy is sent to the site side.

[0050] Specifically, the concentrator does not necessarily generate a regulation strategy. Only when the data collected by the distributed power source meets the preset parameters in the concentrator, a strategy is immediately generated and a local control strategy is issued. For example, the regulation type is set to forward overload, the priority is 1, the startup state is started, and the distributed power source regulation scheduling plan parameters, the plan source is set to the concentrator, the photovoltaic regulation execution date is set to the current day, the photovoltaic output regulation period is the concentrator's default current period, and the regulation data is a variety of data.

[0051] In this embodiment, a photovoltaic control method is provided. The method is applied to a distributed power access unit, that is, applied to a site side. The distributed power access unit is used to access a distributed power source, such as Figure 4 As shown, the method includes:

[0052] Step S1: When the local control switch is turned on, determine whether a direct control strategy is received;

[0053] Step S2: If a direct control strategy is received, the direct control strategy is directly executed; otherwise, the control strategy to be executed in the current period is selected and executed according to the priority of the currently received control strategy and its corresponding scheduling schedule.

[0054] Specifically, the site side may receive a direct control strategy or a planned control strategy sent by the master station side, or the site side may also receive an overload control strategy sent by the terminal side. At the same time, the site side can also generate its own local control strategy. Among the above control strategies, the direct control strategy has the highest priority. Therefore, when a direct control strategy is received, the site side directly stops the currently executed control strategy and immediately executes the direct control strategy.

[0055] Specifically, if the site side does not receive a direct control strategy, then according to the priorities of the currently received control strategies, a control strategy with the highest priority and an execution time within the current time period is selected.

[0056] In some optional embodiments, the direct control strategy includes: local control parameters of distributed power sources; other control strategies include: local control parameters of distributed power sources and distributed power source control scheduling plan parameters; local control parameters of distributed power sources include local control time periods, and distributed power source control scheduling plan parameters include planned execution dates.

[0057] Optionally, the local control parameters of the distributed power supply are shown in Table 1, the parameters of the distributed power supply regulation and scheduling plan table are shown in Table 2, and the distributed power supply parameters are shown in Table 3.

[0058] Table 1

[0059]

[0060] Table 2

[0061]

[0062] Table 3

[0063]

[0064] In some optional embodiments, reference Figure 5 , the process of directly executing the direct control strategy includes:

[0065] Forcefully terminate the currently executing control strategy; determine whether the direct control strategy is power load regulation control or power on / off control; if the direct control strategy is power load regulation control, set the output parameters of the photovoltaic inverter in the distributed power source according to the local control parameters of the distributed power source; if the direct control strategy is power on / off control, control the photovoltaic inverter in the distributed power source to be turned on or off according to the local control parameters of the distributed power source.

[0066] In some optional implementations, the process of selecting and executing the control strategy to be executed in the current period includes:

[0067] Determine whether an overload control policy has been received; if an overload control policy has been received, execute the overload control policy directly; otherwise, loop through the currently received control policies, execute the control policy with the highest priority and a scheduling time in the current time period, or execute the local control policy.

[0068] Specifically, the terminal side will regularly collect data from the downlink site-end equipment for storage. According to the configuration of the master station side, it will actively report or passively collect the data and forward it to the upper-level user acquisition platform via 4G. When it detects reverse heavy overload or forward overload, it will automatically generate an overload control strategy. At the same time, the overload control strategy has a higher priority than the local control strategy generated by the site side and the planned control strategy generated by the master station side.

[0069] In some optional implementations, executing the control strategy with the highest priority and a scheduling time within the current time period, or executing the local control strategy, includes:

[0070] If the local control policy is currently being executed, when at least one planned control policy is received, the execution of the local control policy will be stopped, and the scheduling time of each planned control policy will be polled to see if it is within the current time period; if there is a planned control policy with a scheduling time within the current time period, the planned control policy will be executed, otherwise the local control policy will continue to be executed.

[0071] Optionally, the process of polling whether the scheduling time of each planned control strategy is within the current time period includes: determining whether the execution date in the control schedule of the planned control strategy is the current date; if it is the current date, determining whether the local control time period of the planned control strategy is the current time period.

[0072] Specifically, when the local control switch is turned on, the distributed power access unit will determine whether to turn on the local control strategy based on the local control time period. When it is within the time period, it will poll the control plan unit in the smart meter and first select the strategy unit with the highest priority. According to the distributed power control scheduling schedule corresponding to the strategy unit, the plan execution date and time period are determined. If the current time is within the time period of the schedule, it will be executed directly. If the current time is not within the time period of the schedule, the next strategy unit will be polled and the corresponding judgment will be repeated.

[0073] For example, assume that the control policies received by a distributed power access unit include a planned control policy, a direct control policy, and a local control policy. The direct control policy has a higher priority than the planned control policy, which in turn has a higher priority than the local control policy. A smart meter includes three policy units, one for each control policy. The distributed power access unit polls these three policy units sequentially according to the control policy priority. Specifically, it first selects the policy unit storing the direct control policy and determines whether the scheduled execution date and time period for the direct control policy are the current time. If so, the direct control policy is immediately executed. Otherwise, the policy unit storing the direct control policy is polled until the start time of the next local control policy is reached.

[0074] In some optional embodiments, the photovoltaic control method further includes:

[0075] Convolutional neural networks are used to perform deep feature extraction and dimensionality reduction on multidimensional data. Long-short-term memory networks are used to mine the temporal dependencies between data and predict photovoltaic power data. The predicted photovoltaic power data is compared, analyzed, and calculated with pre-set site power thresholds to generate a local control strategy.

[0076] Specifically, if Figure 6 As shown, the distributed generation access unit uses a CNN-LSTM model to predict photovoltaic power daily, combining raw historical data. This involves using a CNN to extract features such as temperature, humidity, solar radiation intensity, wind speed, wind direction, and photovoltaic power to achieve dimensionality reduction. An LSTM network then mines dependencies to achieve accurate power prediction. Finally, the predicted photovoltaic power is compared with internally set site-measured photovoltaic power thresholds to generate a control schedule, enabling site-level self-management.

[0077] In some optional embodiments, before determining whether an overload control strategy is received, it also includes: determining whether the connected distributed power source is in an island operation mode; if the distributed power source is in an island operation mode, disconnecting the distributed power source from the power grid, otherwise determining whether an overload control strategy is received.

[0078] Specifically, refer to Figure 5 When the distributed generation access unit detects that the property boundary point is in an island situation, it will autonomously generate an island protection tripping operation to protect the power grid.

[0079] In some optional implementations, the specific flow chart of the photovoltaic control method of this embodiment is as follows: Figure 5 As shown, the specific process is as follows:

[0080] (1) The distributed power access unit first determines whether it has received the distributed power parameters in the direct control strategy. If not, it enters the local control related judgment; if received, it forcibly terminates the currently executed local control strategy and executes the direct control strategy.

[0081] The process of executing the direct control strategy includes: For DG parameter information, determining whether it is a power load or a power on / off state. If it is a power on / off state, the DG is turned on / off, and the PV inverter is directly operated based on the power on / off state. If it is a load state, the DG load is controlled, and the PV inverter output parameters are set based on the control method and adjustment value.

[0082] (2) Determine whether the local control switch is turned on. If not, end the process. If it is turned on, continue to determine whether the local control period is within the time limit. If not, end the process. If yes, proceed to the next step.

[0083] (3) Determine whether the property boundary point is in an isolated island. If it is in an isolated island, perform valve section change related operations; if it is not in an isolated island, determine whether it is in forward overload or reverse overload.

[0084] If the system is in the forward overload or reverse heavy load state, the concentrator will issue an overload control strategy, which has a lower priority than island protection and preemption control. The concentrator will control the photovoltaic inverter based on the forward overload or reverse heavy load strategy and the target distributed power supply control and scheduling schedule.

[0085] (4) If it is not in the forward overload or reverse overload state, the distributed power supply control scheduling plan table of each control strategy received is cyclically queried to determine whether it is in the planned execution day. If not, the cycle is completed and exited; if it is, the photovoltaic processing time period table is cyclically queried to determine whether it is in the time period. If not, the cycle is completed and exited. If it is, the photovoltaic inverter is controlled according to the control data table.

[0086] The embodiment of the present invention also provides a computer device having the above Figure 1 The photovoltaic control system shown.

[0087] See also Figure 7 , Figure 7 is a structural diagram of a computer device provided by an optional embodiment of the present invention, such as Figure 7 As shown, the computer device includes: one or more processors 10, memory 20, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. Various components utilize different buses to communicate with each other and can be installed on a common mainboard or installed in other ways as needed. The processor can process the instructions executed in the computer device, including instructions stored in the memory or on the memory to display the graphical information of the GUI on an external input / output device (such as, a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Equally, multiple computer devices can be connected, and each device provides part of the necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). Figure 7 A processor 10 is taken as an example.

[0088] The processor 10 may be a central processing unit, a network processor, or a combination thereof. The processor 10 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit, a programmable logic device, or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general purpose array logic, or any combination thereof.

[0089] The memory 20 stores instructions that can be executed by at least one processor 10, so as to enable at least one processor 10 to execute the method shown in the above embodiment.

[0090] The memory 20 may include a program storage area and a data storage area, wherein the program storage area may store an operating system and application programs required for at least one function; the data storage area may store data created based on the use of the computer device, etc. In addition, the memory 20 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some optional embodiments, the memory 20 may optionally include a memory remotely located relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0091] The memory 20 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk or a solid-state drive; the memory 20 may also include a combination of the above types of memory.

[0092] The computer device further includes an input device 30 and an output device 40. The processor 10, the memory 20, the input device 30 and the output device 40 may be connected via a bus or other means. Figure 7 The bus connection is taken as an example.

[0093] The input device 30 can receive input digital or character information and generate key signal input related to user settings and function control of the computer device. Examples include a touch screen, keypad, mouse, trackpad, touchpad, pointing stick, one or more mouse buttons, trackball, joystick, etc. The output device 40 may include a display device, auxiliary lighting devices (e.g., LEDs), and tactile feedback devices (e.g., vibration motors). Such display devices include, but are not limited to, liquid crystal displays, light emitting diodes, monitors, and plasma displays. In some optional embodiments, the display device may be a touch screen.

[0094] The embodiment of the present invention also provides a computer-readable storage medium. The above-mentioned method according to the embodiment of the present invention can be implemented in hardware, firmware, or implemented as a computer code that can be recorded in a storage medium, or implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and downloaded through a network and will be stored in a local storage medium, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state drive, etc.; further, the storage medium can also include a combination of the above-mentioned types of memory. It can be understood that a computer, a processor, a microprocessor controller or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor or hardware, the method shown in the above embodiment is implemented.

[0095] A portion of the present invention may be applied as a computer program product, such as a computer program instruction, which, when executed by a computer, can call or provide the method and / or technical solution according to the present invention through the operation of the computer. Those skilled in the art should understand that the form in which the computer program instruction exists in a computer-readable medium includes, but is not limited to, a source file, an executable file, an installation package file, etc. Accordingly, the way in which the computer program instruction is executed by the computer includes, but is not limited to: the computer directly executes the instruction, or the computer compiles the instruction and then executes the corresponding compiled program, or the computer reads and executes the instruction, or the computer reads and installs the instruction and then executes the corresponding installed program. Here, the computer-readable medium may be any available computer-readable storage medium or communication medium that can be accessed by the computer.

[0096] Although the embodiments of the present invention have been described with reference to the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present invention. Such modifications and variations are all within the scope defined by the appended claims.

Claims

1. A photovoltaic control method, characterized in that: The method is applied to a distributed power supply access unit, which is used to access a distributed power supply. The method includes: When the local control switch is turned on, it is determined whether a direct control strategy is received; If a direct control strategy is received, the direct control strategy is directly executed; otherwise, the control strategy to be executed in the current period is selected and executed according to the priority of the currently received control strategy and its corresponding scheduling schedule; Direct control strategies include: distributed power local control parameters; other control strategies include: distributed power local control parameters and distributed power control scheduling table parameters; the distributed power local control parameters include the local control time period, and the distributed power control scheduling table parameters include the planned execution date; The process of selecting and executing the control strategy to be executed in the current time period includes: determining whether an overload control strategy has been received; if the overload control strategy has been received, directly executing the overload control strategy; otherwise, cyclically querying the currently received control strategies, executing the control strategy with the highest priority and a scheduling time within the current time period, or executing the local control strategy; The process of executing the control strategy with the highest priority and whose scheduling time is in the current time period, or executing the local control strategy, includes: if the local control strategy is currently being executed, when at least one planned control strategy is received, stopping the execution of the local control strategy, and polling whether the scheduling time of each planned control strategy is in the current time period; if there is a planned control strategy with a scheduling time in the current time period, executing the planned control strategy, otherwise continuing to execute the local control strategy; Before determining whether an overload control strategy is received, it also includes: determining whether the connected distributed power source is in an island operation mode; if the distributed power source is in an island operation mode, disconnecting the distributed power source from the power grid, otherwise determining whether an overload control strategy is received.

2. The photovoltaic control method according to claim 1, characterized in that: The process of directly executing the direct control strategy includes: Forcefully terminate the currently executing control strategy; Determining whether the direct control strategy is power load control or power on / off control; If the direct control strategy is to adjust the power load control, then the output parameters of the photovoltaic inverter in the distributed power supply are set according to the local control parameters of the distributed power supply; If the direct control strategy is on / off control, the photovoltaic inverter in the distributed power source is controlled to be turned on or off according to the local control parameters of the distributed power source.

3. The photovoltaic control method according to claim 1, characterized in that: The process of polling whether the scheduling time of each planning control policy is within the current time period includes: Determine whether the execution date in the control plan table of the planned control strategy is the current date; If it is the current date, determine whether the local control time period of the planning and control strategy is the current time period.

4. The photovoltaic control method according to claim 1, characterized in that: Also includes: Use convolutional neural networks to perform deep feature extraction and dimensionality reduction on multidimensional data; Mining the temporal dependencies between data and predicting photovoltaic power data through long short-term memory networks; The predicted photovoltaic power data is compared, analyzed and calculated with the pre-set site power threshold to generate a local control strategy.

5. A photovoltaic control system, characterized in that: include: Master side, terminal side and site side, among which, The master station side is used to obtain the site side data sent by the terminal side; generate a planned control strategy or a direct control strategy based on the site side data according to various control requirements, and send the planned control strategy or the direct control strategy to the terminal side; The terminal side is used to generate an overload control strategy when the distributed power supply is overloaded; and send the planned control strategy, direct control strategy or overload control strategy to the site side; The site side is connected to the distributed power supply and is used to execute the photovoltaic control method according to any one of claims 1 to 4.

6. A computer device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the photovoltaic control method according to any one of claims 1 to 4 by executing the computer instructions.

7. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the photovoltaic control method according to any one of claims 1 to 4.

8. A computer program product, characterized in that The method comprises computer instructions for causing a computer to execute the photovoltaic control method according to any one of claims 1 to 4.

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