Agricultural light complementary light storage cooperative control strategy system and method

Abstract

The invention relates to an agriculture and light complementary light storage cooperative control strategy system and method, and the system comprises a light storage integrated clustering simulation test debugging platform which is used for carrying out a light storage integrated simulation test according to the Internet of Things strategy information of an Internet of Things light storage cooperative control strategy system, generating a light storage cooperative control strategy of the agriculture and light complementary application scene; the optical storage cooperative control system is used for generating a corresponding cooperative control action for controlling the optical storage system to execute based on the optical storage cooperative control strategy; and the AGC control system is used for performing power generation control according to the data information of the battery energy storage, the direct current charging and discharging pile and the photovoltaic array so as to realize cooperative control of light storage and charging. Therefore, the problems that the economic benefit of a photovoltaic power station is not high, the power of photovoltaic power generation is easy to fluctuate, the power transmitted to an alternating-current power grid continuously changes, the difficulty of peak regulation and frequency modulation of the power grid is high and the like due to the fact that the income loss is large after agricultural and photovoltaic complementary new energy enters a spot market in the related technology are solved.

Description

Technical Field

[0001] This application relates to the technical field of photovoltaic power generation, and particularly relates to a photovoltaic-storage collaborative control strategy system and method for complementary agriculture and photovoltaic. Background Art

[0002] The "complementary agriculture and photovoltaic" project belongs to the agricultural and photovoltaic composite project, which uses the open space and intervals under the photovoltaic array to plant crops, realizes the compound utilization of land, and is designed according to the mode and concept of "generating electricity on the shed, planting under the shed, and complementary agriculture and photovoltaic". It generates electricity on the top and takes into account agricultural production below, making dual use of the land and sharing sunlight.

[0003] In related technologies, complementary agriculture and photovoltaic adopt the combination of agriculture and photovoltaic power generation, aiming to achieve mutual benefit between solar power generation and crop planting by arranging photovoltaic power generation panels in farmland. This method can effectively improve the resource utilization rate of land, promote the development and utilization of renewable energy, and at the same time does not affect the normal growth of crops in farmland.

[0004] However, the income loss of complementary agriculture and photovoltaic new energy in the spot market is relatively large in related technologies, resulting in not very high economic benefits of photovoltaic power stations. Moreover, the power of photovoltaic power generation is prone to fluctuations, resulting in continuous changes in the power transmitted to the AC power grid, making it difficult for the power grid to perform peak shaving and frequency modulation, which urgently needs to be improved. Summary of the Invention

[0005] This application provides a photovoltaic-storage collaborative control strategy system and method for complementary agriculture and photovoltaic to solve problems such as relatively large income loss of complementary agriculture and photovoltaic new energy in the spot market, resulting in not very high economic benefits of photovoltaic power stations, and the power of photovoltaic power generation is prone to fluctuations, resulting in continuous changes in the power transmitted to the AC power grid, making it difficult for the power grid to perform peak shaving and frequency modulation.

[0006] The first aspect of the embodiments of this application provides a photovoltaic-storage collaborative control strategy system for complementary agriculture and photovoltaic, including: an integrated photovoltaic-storage cluster simulation test and commissioning platform, which is used to perform integrated photovoltaic-storage simulation tests according to the Internet of Things strategy information of the Internet of Things photovoltaic-storage collaborative control strategy system, and generate a photovoltaic-storage collaborative control strategy for the application scenario of complementary agriculture and photovoltaic; a photovoltaic-storage collaborative control system, which is used to generate control over the photovoltaic-storage system to perform corresponding collaborative control actions based on the photovoltaic-storage collaborative control strategy; an AGC control system, which is used to perform power generation control according to the data information of battery energy storage, DC charging and discharging piles, and photovoltaic arrays, and realize the collaborative control of photovoltaic-storage charging.

[0007] The above technical solution can utilize the clustered simulation test and commissioning platform for integrated photovoltaics and energy storage to generate the coordinated control strategy for the integrated solar and energy storage application scenario, thereby optimizing the operation of the photovoltaic power station in the spot market; it can utilize the coordinated control system for photovoltaics and energy storage to generate control actions for the energy storage system to perform corresponding coordinated control actions, and through Internet of Things data acquisition and communication transmission technologies, build a digital intelligent operation and maintenance platform for photovoltaics and energy storage, and adopt deep learning methods such as machine learning to develop technologies such as fault diagnosis, power prediction, peak shaving and frequency modulation of the energy storage system, so as to achieve flexible and automatic adjustment of the photovoltaic power station in the spot market; it can utilize the AGC control system to perform power generation control according to the data information of the battery energy storage, DC charging and discharging piles and photovoltaic arrays, realize the coordinated control of photovoltaics, energy storage and charging, ensure the combined operation efficiency of the photovoltaic power station and the energy storage system, and improve the regulation ability during the operation process of the photovoltaic power station.

[0008] Optionally, in an embodiment of the present application, the clustered simulation test and commissioning platform for integrated photovoltaics and energy storage includes: a digital twin simulation system for photovoltaic power stations, which is used to simulate at least one characteristic function of a centralized photovoltaic power generation system, where the characteristic function includes power generation characteristics and power transmission characteristics; a digital twin simulation system for energy storage power stations, which is used to simulate at least one characteristic function of an energy storage grid-connected power generation system; and a joint virtual simulation test platform for photovoltaics and energy storage, which is used to receive the Internet of Things policy information and transmit the Internet of Things policy information to the digital twin simulation system for photovoltaic power stations and the digital twin simulation system for energy storage power stations.

[0009] The above technical solution can utilize the digital twin simulation system for photovoltaic power stations to simulate the power generation characteristics of a centralized photovoltaic power generation system, helping to predict and optimize the power generation efficiency; it can utilize the digital twin simulation system for energy storage power stations to simulate the charging and discharging characteristics of an energy storage grid-connected power generation system, helping to optimize the charging and discharging process of the energy storage system, and ensuring that the energy storage system can effectively suppress the power fluctuation of photovoltaic power generation; it can utilize the joint virtual simulation test platform for photovoltaics and energy storage to receive and transmit the Internet of Things policy information, helping to optimize the coordinated control strategy for photovoltaics and energy storage, and ensuring the feasibility and timeliness of the system in actual operation.

[0010] Optionally, in an embodiment of the present application, the clustered simulation test and commissioning platform for integrated photovoltaics and energy storage further includes: a three-dimensional model combined with a digital twin simulation model, which is used to establish the actual application of the three-dimensional model combined with the digital twin simulation to meet the preset conditions with the consistency of on-site production equipment, and evaluate the evaluation information of at least one of the influence, stability and reliability of the coordinated control strategy for photovoltaics and energy storage on the performance of the photovoltaics and energy storage system.

[0011] The above technical solution can use a 3D model combined with a digital twin simulation model to reproduce the main scenarios and production equipment of the PV energy storage station with high precision, ensuring that the simulation model is highly consistent with the actual on-site equipment, so as to facilitate the evaluation of the impact of the PV energy storage collaborative control strategy on system performance, stability and reliability, and help select the optimal control strategy.

[0012] Optionally, in an embodiment of the present application, the PV energy storage collaborative control system includes: a battery energy storage system for suppressing the power fluctuation of the PV power generation of the PV power station; a PV energy storage operation and maintenance platform for generating at least one operation and maintenance strategy of fault diagnosis, power prediction, peak shaving and frequency modulation of the PV energy storage system to execute the collaborative control action.

[0013] The above technical solution can deeply integrate advanced Internet of Things technology with the traditional PV power generation industry based on the battery energy storage system and the PV energy storage operation and maintenance platform, and suppress the power fluctuation of PV power generation by adding an energy storage system to the PV power station.

[0014] Optionally, in an embodiment of the present application, the AGC control system includes: a battery energy management system layer for collecting the data information; a cloud platform server for generating corresponding control instructions according to the data information; a PV inverter for adjusting the power factor based on a reactive power compensation strategy while generating active power; a converter system layer for converting the DC power generated by the PV into AC power, connecting to the power grid, and receiving the control instructions based on the battery energy management system layer to perform collaborative control of PV energy storage charging.

[0015] The above technical solution can use the battery energy management system layer to collect data information, so as to comprehensively master the operation status of the PV energy storage system; can use the cloud platform server to generate corresponding control instructions according to the data information to achieve remote monitoring and control; can use the PV inverter to adjust the power factor based on a reactive power compensation strategy while generating active power to improve the stability of the power grid; can use the converter system layer to convert the DC power generated by the PV into AC power and connect to the power grid, ensuring that the PV power generation system can be seamlessly connected to the power grid and realizing stable power transmission.

[0016] An embodiment of the second aspect of the present application provides a method for the PV energy storage collaborative control strategy of agricultural-light complementary, including the following steps: performing a PV energy storage integrated simulation test according to the Internet of Things strategy information of the Internet of Things PV energy storage collaborative control strategy system to generate a PV energy storage collaborative control strategy for the agricultural-light complementary application scenario; generating control to make the PV energy storage system execute corresponding collaborative control actions based on the PV energy storage collaborative control strategy; performing power generation control according to the data information of the battery energy storage, DC charging and discharging piles and PV arrays to achieve collaborative control of PV energy storage charging.

[0017] Optionally, in an embodiment of the present application, the integrated photovoltaic and energy storage simulation test is performed according to the Internet of Things (IoT) policy information of the IoT photovoltaic and energy storage collaborative control strategy system to generate a photovoltaic and energy storage collaborative control strategy for an agricultural and photovoltaic complementary application scenario, including: simulating at least one characteristic function of a centralized power station photovoltaic power generation system, where the characteristic function includes a power generation characteristic and a power transmission characteristic; simulating at least one characteristic function of an energy storage grid-connected power generation system; receiving the IoT policy information, and transmitting the IoT policy information to the digital twin simulation system of the photovoltaic power station and the digital twin simulation system of the energy storage power station.

[0018] Optionally, in an embodiment of the present application, the integrated photovoltaic and energy storage simulation test is performed according to the IoT policy information of the IoT photovoltaic and energy storage collaborative control strategy system to generate a photovoltaic and energy storage collaborative control strategy for an agricultural and photovoltaic complementary application scenario, further including: a three-dimensional model paired with a digital twin simulation model, used to establish the actual application of the three-dimensional model paired with the digital twin simulation, so that the consistency with the on-site production equipment meets the preset conditions, and evaluate the evaluation information of at least one of the influence, stability, and reliability of the photovoltaic and energy storage collaborative control strategy on the performance of the photovoltaic and energy storage system.

[0019] Optionally, in an embodiment of the present application, generating a control for the photovoltaic and energy storage system to perform corresponding collaborative control actions based on the photovoltaic and energy storage collaborative control strategy includes: suppressing the power fluctuation of the photovoltaic power generation in the photovoltaic power station; generating at least one operation and maintenance strategy among fault diagnosis, power prediction, peak shaving, and frequency modulation of the photovoltaic and energy storage system to execute the collaborative control actions.

[0020] Optionally, in an embodiment of the present application, performing power generation control according to the data information of the battery energy storage, DC charging and discharging pile, and photovoltaic array to achieve the collaborative control of photovoltaic, energy storage, and charging includes: collecting the data information; generating corresponding control instructions according to the data information; adjusting the power factor based on the reactive power compensation strategy while generating active power; converting the direct current generated by the photovoltaic into alternating current, connecting it to the power grid, and receiving the control instructions based on the battery energy management system layer to perform the collaborative control of photovoltaic, energy storage, and charging.

[0021] An embodiment of the third aspect of the present application provides an electronic device, including: a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor executes the program to implement the photovoltaic and energy storage collaborative control strategy method for agricultural and photovoltaic complementarity as described in the above embodiment.

[0022] An embodiment of the fourth aspect of the present application provides a computer-readable storage medium, where the computer-readable storage medium stores a computer program, and when the program is executed by a processor, it implements the photovoltaic and energy storage collaborative control strategy method for agricultural and photovoltaic complementarity as above.

[0023] The fifth aspect of the present application provides a computer program product. The computer program product stores a computer program, which when executed by a processor, implements the above-mentioned photovoltaic-storage collaborative control strategy method for complementary agriculture and photovoltaic power generation.

[0024] The embodiments of the present application utilize Internet of Things data collection and communication transmission technologies. By constructing a digital intelligent photovoltaic-storage operation and maintenance platform and adopting deep learning methods such as machine learning, technologies such as fault diagnosis, power prediction, peak shaving, and frequency modulation of the photovoltaic-storage system are developed, enabling flexible and automatic adjustment of photovoltaic power stations in the spot market and enhancing the regulation ability during the operation of photovoltaic power stations. Thus, the problems in the related technologies are solved, such as significant revenue losses after complementary agriculture and new energy enter the spot market, resulting in relatively low economic benefits of photovoltaic power stations, and the power of photovoltaic power generation is prone to fluctuations, leading to continuous changes in the power transmitted to the AC power grid, making it difficult for the power grid to perform peak shaving and frequency modulation.

[0025] Additional aspects and advantages of the present application will be partially given in the following description, partially become apparent from the following description, or be understood through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] The above and / or additional aspects and advantages of the present application will become apparent and understandable from the following description of the embodiments in conjunction with the drawings, where:

[0027] Figure 1 FIG. is a schematic structural diagram of a photovoltaic-storage collaborative control strategy system for complementary agriculture and photovoltaic power generation according to an embodiment of the present application;

[0028] Figure 2 FIG. is a flowchart of a photovoltaic-storage collaborative control strategy method for complementary agriculture and photovoltaic power generation according to an embodiment of the present application;

[0029] Figure 3 FIG. is a schematic structural diagram of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0030] Embodiments of the present application will be described in detail below. Examples of the embodiments are shown in the drawings, where the same or similar reference numerals represent the same or similar elements or elements with the same or similar functions throughout. The embodiments described below with reference to the drawings are exemplary and are intended to explain the present application and should not be construed as limiting the present application.

[0031] The following describes the photovoltaic-storage collaborative control strategy system and method of the embodiment of the present application with reference to the accompanying drawings. In view of the problems in the related art mentioned in the above background technology that the income loss of the agro-photovoltaic complementary new energy is relatively large after entering the spot market, resulting in not very high economic benefits of the photovoltaic power station. In addition, the power of photovoltaic power generation is prone to fluctuations, resulting in continuous changes in the power transmitted to the AC power grid, making it difficult for the power grid to perform peak shaving and frequency modulation. The present application provides a photovoltaic-storage collaborative control strategy system and method. In this system, the Internet of Things data acquisition and communication transmission technology can be used to develop technologies such as fault diagnosis, power prediction, peak shaving and frequency modulation of the photovoltaic-storage system by constructing a digital intelligent photovoltaic-storage operation and maintenance platform and adopting deep learning methods such as machine learning, so as to realize the flexible and automatic adjustment of the photovoltaic power station in the spot market and improve the control ability during the operation of the photovoltaic power station. Thus, the problems in the related art that the income loss of the agro-photovoltaic complementary new energy is relatively large after entering the spot market, resulting in not very high economic benefits of the photovoltaic power station. In addition, the power of photovoltaic power generation is prone to fluctuations, resulting in continuous changes in the power transmitted to the AC power grid, making it difficult for the power grid to perform peak shaving and frequency modulation are solved.

[0032] Specifically, Figure 1 FIG. is a schematic structural diagram of a photovoltaic-storage collaborative control strategy system provided by an embodiment of the present application.

[0033] As Figure 1 shown, the photovoltaic-storage collaborative control strategy system 10 includes: an integrated photovoltaic-storage cluster simulation test and commissioning platform 100, a photovoltaic-storage collaborative control system 200, and an AGC control system 300.

[0034] The integrated photovoltaic-storage cluster simulation test and commissioning platform 100 is used to perform an integrated photovoltaic-storage simulation test according to the Internet of Things strategy information of the Internet of Things photovoltaic-storage collaborative control strategy system, and generate a photovoltaic-storage collaborative control strategy for the agro-photovoltaic complementary application scenario.

[0035] It can be understood that the integrated photovoltaic-storage simulation test in the embodiment of the present application can be a simulation test of the combined operation of the photovoltaic power generation system and the energy storage system; the agro-photovoltaic complementary application scenario can refer to an application mode in which photovoltaic panels are installed above agricultural land to generate solar power without affecting the growth of crops; the photovoltaic-storage collaborative control strategy can refer to rules and algorithms for optimizing the combined operation of the photovoltaic power station and the energy storage system. For example, when the power generation power of a photovoltaic power station fluctuates greatly on a certain day, resulting in an increase in the difficulty of peak shaving and frequency modulation of the power grid, the photovoltaic-storage collaborative control strategy can monitor the fluctuation of the photovoltaic power generation power, identify the time period with large power fluctuations for optimized operation, and ensure that the power fluctuations can be effectively handled during actual operation.

[0036] Among them, the embodiments of the present application can utilize the integrated photovoltaic and energy storage cluster simulation test and debugging platform 100 to conduct integrated photovoltaic and energy storage simulation tests according to the Internet of Things policy information of the Internet of Things photovoltaics and energy storage collaborative control strategy system, so as to generate the photovoltaics and energy storage collaborative control strategy for the agricultural-photovoltaic complementary application scenario, thereby optimizing the joint operation of the photovoltaic power station and the energy storage system, and further improving the stability, economic benefits and renewable energy utilization rate of the power system.

[0037] The integrated photovoltaic and energy storage cluster simulation test and debugging platform 100 in the embodiments of the present application builds a high-precision simulation model through research and development to simulate the characteristics of each system of the photovoltaic power station and the energy storage power station on the user side, forming an integrated photovoltaic and energy storage cluster simulation test and debugging system. After the system is built, using the system as a platform and the external Internet of Things policy information as input, a high-precision integrated photovoltaic and energy storage cluster simulation test and debugging platform 100 is formed to test whether the characteristics such as the feasibility and timeliness of the photovoltaics and energy storage collaborative control strategy system are met.

[0038] Optionally, in an embodiment of the present application, the integrated photovoltaic and energy storage cluster simulation test and debugging platform 100 includes: a digital twin simulation system for a photovoltaic power station, which is used to simulate at least one characteristic function of a centralized photovoltaic power generation system, where the characteristic function includes power generation characteristics and power transmission characteristics; a digital twin simulation system for an energy storage power station, which is used to simulate at least one characteristic function of an energy storage grid-connected power generation system; and an integrated photovoltaic and energy storage joint virtual simulation test platform, which is used to receive Internet of Things policy information and transmit the Internet of Things policy information to the digital twin simulation system for the photovoltaic power station and the digital twin simulation system for the energy storage power station.

[0039] It can be understood that the digital twin simulation system for the photovoltaic power station in the embodiments of the present application includes, but is not limited to, simulation mathematical models such as photovoltaic modules, photovoltaic inverters, photovoltaic box transformers, and collector lines; the digital twin simulation system for the energy storage power station in the embodiments of the present application includes, but is not limited to, simulation mathematical models such as energy storage battery cores, PCS (Power Conversion System, energy storage converter), and integrated energy storage step-up converter bins; the integrated photovoltaic and energy storage joint virtual simulation test platform in the embodiments of the present application is used to test the optimal strategy in the photovoltaics and energy storage collaborative control strategy system in the integrated photovoltaic and energy storage joint virtual simulation test platform. For example, test and verify the photovoltaics and energy storage collaborative control strategy in a virtual environment, and quickly screen out the most suitable strategy through simulation optimization to improve the operation efficiency and economic benefits of the photovoltaics and energy storage system.

[0040] In the actual implementation process, the embodiments of the present application can use the digital twin simulation system of the photovoltaic power station to simulate functions such as the power generation characteristics and power transmission characteristics of the centralized power station photovoltaic power generation system, and use the digital twin simulation system of the energy storage power station to simulate the charge and discharge characteristics, energy management system, and power control of the energy storage grid-connected power generation system, so as to realize the function of simulating the charge and discharge process and power transmission of the energy storage system. The embodiments of the present application use the optical storage joint virtual simulation test platform to receive the Internet of Things policy information and transmit the Internet of Things policy information to the digital twin simulation system of the photovoltaic power station and the digital twin simulation system of the energy storage power station. For example, the optical storage joint virtual simulation test platform is used to receive the data transmission information of the external Internet of Things optical storage collaborative control strategy system and transmit the data transmission information of the external Internet of Things optical storage collaborative control strategy system to the digital twin simulation system of the photovoltaic power station and the digital twin simulation system of the energy storage power station, so as to further realize the flexible automatic adjustment of the photovoltaic power station in the spot market.

[0041] The embodiments of the present application can use the digital twin simulation system of the photovoltaic power station to simulate the power generation characteristics of the centralized power station photovoltaic power generation system to help predict and optimize the power generation efficiency; can use the digital twin simulation system of the energy storage power station to simulate the charge and discharge characteristics of the energy storage grid-connected power generation system to help optimize the charge and discharge process of the energy storage system to ensure that the energy storage system can effectively suppress the power fluctuation of photovoltaic power generation; can use the optical storage joint virtual simulation test platform to receive and transmit the Internet of Things policy information to help optimize the optical storage collaborative control strategy to ensure the feasibility and timeliness of the system in actual operation.

[0042] Optionally, in an embodiment of the present application, the integrated optical storage cluster simulation test and debugging platform 100 further includes: a three-dimensional model paired with a digital twin simulation model, which is used to establish the actual application of the three-dimensional model paired with the digital twin simulation to meet the preset conditions with the consistency of the on-site production equipment, and evaluate the evaluation information of the optical storage collaborative control strategy on at least one of the performance, stability, and reliability of the optical storage system.

[0043] It can be understood that the three-dimensional model paired with the digital twin simulation model in the embodiments of the present application can conduct in-depth research on the simulation model and provide an important theoretical support and simulation verification platform for the design and optimization of the optical storage digital intelligent management and control system.

[0044] In the actual implementation process, the three-dimensional model paired with the digital twin simulation model in the embodiments of the present application reproduces the main scenarios and production equipment of the optical storage power station with high precision by establishing the actual application of the three-dimensional model paired with the digital twin simulation, so as to achieve high-precision consistency with the on-site production equipment, and is applicable to evaluating the impact of different control strategies on the performance of the optical storage system, as well as evaluating the stability and reliability of the system. By evaluating the impact of the optical storage collaborative control strategy on the system performance, stability, and reliability, it helps to select the optimal control strategy.

[0045] The photovoltaic and energy storage collaborative control system 200 is used to generate control over the photovoltaic and energy storage system to perform corresponding collaborative control actions based on the photovoltaic and energy storage collaborative control strategy.

[0046] It can be understood that the photovoltaic and energy storage collaborative control system 200 in the embodiments of the present application can be an integrated control system, aiming to coordinate the operations between the photovoltaic power station and the energy storage system to achieve optimal energy management, power regulation, and grid support; the collaborative control actions in the embodiments of the present application can be specific operation instructions generated according to the photovoltaic and energy storage collaborative control strategy, and are actions used to adjust the operating states of the photovoltaic power station and the energy storage system.

[0047] Among them, the embodiments of the present application can utilize the photovoltaic and energy storage collaborative control system 200 to generate control over the photovoltaic and energy storage system to perform corresponding collaborative control actions based on the photovoltaic and energy storage collaborative control strategy. For example, the embodiments of the present application utilize the photovoltaic and energy storage collaborative control system 200 to formulate the photovoltaic and energy storage collaborative control strategy by collecting real-time data and prediction results, and dynamically adjust its charge and discharge rate according to the changes in the actual power generation and grid demand, so as to smooth the output power curve and ensure that the grid side receives a stable power supply, thereby performing corresponding collaborative control actions.

[0048] The photovoltaic and energy storage collaborative control system 200 in the embodiments of the present application can achieve flexible and automatic regulation of the photovoltaic power station in the spot market by integrating a variety of advanced technologies, significantly improving the regulation ability during the operation of the photovoltaic power station.

[0049] Optionally, in an embodiment of the present application, the photovoltaic and energy storage collaborative control system 200 includes: a battery energy storage system for suppressing the power fluctuation of the photovoltaic power generation of the photovoltaic power station; a photovoltaic and energy storage operation and maintenance platform for generating at least one operation and maintenance strategy among fault diagnosis, power prediction, peak shaving, and frequency modulation of the photovoltaic and energy storage system to perform collaborative control actions.

[0050] It can be understood that the photovoltaic and energy storage collaborative control system 200 in the embodiments of the present application can be composed of a battery energy storage system and a digital intelligent photovoltaic and energy storage operation and maintenance platform.

[0051] During the actual execution process, the embodiments of the present application can utilize the battery energy storage system to suppress the power fluctuation of the photovoltaic power generation of the photovoltaic power station, and utilize Internet of Things data acquisition and communication transmission technologies, and adopt deep learning methods such as machine learning to develop the photovoltaic and energy storage operation and maintenance platform to generate operation and maintenance strategies such as fault diagnosis, power prediction, peak shaving, and frequency modulation of the photovoltaic and energy storage system to perform collaborative control actions, so as to achieve flexible and automatic regulation of the photovoltaic power station in the spot market and improve the regulation ability during the operation of the photovoltaic power station.

[0052] The embodiments of the present application deeply integrate advanced Internet of Things technologies with the traditional photovoltaic power generation industry, and add an energy storage system to the photovoltaic power station to suppress the power fluctuation of the photovoltaic power generation.

[0053] An AGC control system 300 is used to perform power generation control based on the data information of battery energy storage, DC charging and discharging piles, and photovoltaic arrays, so as to realize the coordinated control of photovoltaic energy storage and charging.

[0054] Among them, in the embodiment of the present application, the AGC control (Automatic Generation Control) system 300 can perform power generation control according to the data information of battery energy storage, DC charging and discharging piles, and photovoltaic arrays, so as to realize the coordinated control of photovoltaic energy storage and charging, and provide support for solving the problems of large revenue losses after new energy enters the spot market and the easy fluctuation of the power generation of photovoltaic power generation.

[0055] Optionally, in an embodiment of the present application, the AGC control system 300 includes: a battery energy management system layer for collecting data information; a cloud platform server for generating corresponding control instructions according to the data information; a photovoltaic inverter for adjusting the power factor based on a reactive power compensation strategy while generating active power; and a converter system layer for converting the direct current generated by the photovoltaic into alternating current, connecting to the power grid, and receiving control instructions based on the battery energy management system layer to perform the coordinated control of photovoltaic energy storage and charging.

[0056] It can be understood that the AGC control system 300 in the embodiment of the present application can be composed of a battery energy management system layer, a cloud platform server, an intelligent photovoltaic inverter, and a converter system layer.

[0057] In the actual execution process, in the embodiment of the present application, the battery energy management system layer can be used as the total control center, responsible for collecting and processing the data information of battery energy storage, DC charging and discharging piles, and photovoltaic arrays, and transmitting it to the cloud platform server through an intermediate communication device, and then issuing it after receiving the control instructions of the cloud platform server. The cloud platform server serves as a data concentration and processing center, receives the data information from the battery energy management system layer, and performs intelligent analysis and control instruction issuing according to the data to realize remote monitoring and control. The intelligent photovoltaic inverter in the embodiment of the present application has an intelligent reactive power compensation function, can adjust the power factor intelligently while generating active power, generate a part of reactive power for intelligent reactive power compensation, save the cost of reactive power compensation devices, reduce the power consumption of the no-load loss of reactive power compensation devices, and improve the stability of the power grid. The converter system layer in the embodiment of the present application is responsible for converting the direct current generated by the photovoltaic into alternating current, connecting to the power grid, and receiving control instructions based on the battery energy management system layer to perform the coordinated control of photovoltaic energy storage and charging, ensuring that the photovoltaic power generation system can be seamlessly connected to the power grid and realizing the stable transmission of electric energy.

[0058] The photovoltaic-storage collaborative control strategy system for complementary agricultural and photovoltaic applications proposed according to the embodiments of the present application utilizes Internet of Things data acquisition and communication transmission technologies. By constructing a digital intelligent photovoltaic-storage operation and maintenance platform and adopting deep learning methods such as machine learning, technologies such as fault diagnosis, power prediction, peak shaving, and frequency modulation of the photovoltaic-storage system are developed to achieve flexible and automatic regulation of photovoltaic power stations in the spot market and improve the regulation ability during the operation process of photovoltaic power stations. Thus, the problems in the related technologies are solved, including that the income loss of complementary agricultural and photovoltaic new energy in the spot market is relatively large, resulting in not very high economic benefits of photovoltaic power stations, and the power of photovoltaic power generation is prone to fluctuations, leading to continuous changes in the power transmitted to the AC power grid, making it difficult to perform peak shaving and frequency modulation of the power grid.

[0059] Next, a method for photovoltaic-storage collaborative control strategy for complementary agricultural and photovoltaic applications proposed according to the embodiments of the present application will be described with reference to the accompanying drawings.

[0060] Figure 2 It is a flowchart of the method for photovoltaic-storage collaborative control strategy for complementary agricultural and photovoltaic applications according to the embodiments of the present application.

[0061] As Figure 2 shown, the method for photovoltaic-storage collaborative control strategy for complementary agricultural and photovoltaic applications includes the following steps:

[0062] In step S201, a photovoltaic-storage integrated simulation test is performed according to the Internet of Things strategy information of the Internet of Things photovoltaic-storage collaborative control strategy system to generate a photovoltaic-storage collaborative control strategy for the complementary agricultural and photovoltaic application scenario.

[0063] In step S202, based on the photovoltaic-storage collaborative control strategy, a control is generated to make the photovoltaic-storage system execute corresponding collaborative control actions.

[0064] In step S203, power generation control is performed according to the data information of battery energy storage, DC charging and discharging piles, and photovoltaic arrays to achieve collaborative control of photovoltaic-storage charging.

[0065] Optionally, in an embodiment of the present application, performing a photovoltaic-storage integrated simulation test according to the Internet of Things strategy information of the Internet of Things photovoltaic-storage collaborative control strategy system to generate a photovoltaic-storage collaborative control strategy for the complementary agricultural and photovoltaic application scenario includes: simulating at least one characteristic function of a centralized power station photovoltaic power generation system, where the characteristic function includes power generation characteristics and power transmission characteristics; simulating at least one characteristic function of an energy storage grid-connected power generation system; receiving the Internet of Things strategy information and transmitting the Internet of Things strategy information to the digital twin simulation system of the photovoltaic power station and the digital twin simulation system of the energy storage power station.

[0066] Optionally, in an embodiment of the present application, an integrated simulation test of photovoltaic and energy storage is performed according to the Internet of Things policy information of the Internet of Things-based photovoltaic and energy storage collaborative control strategy system to generate a photovoltaic and energy storage collaborative control strategy for the agricultural and photovoltaic complementary application scenario, further including: a three-dimensional model combined with a digital twin simulation model for establishing the actual application of the three-dimensional model combined with the digital twin simulation to meet the preset conditions with the consistency of on-site production equipment, and evaluating the evaluation information of the photovoltaic and energy storage collaborative control strategy on at least one of the influence, stability, and reliability of the photovoltaic and energy storage system performance.

[0067] Optionally, in an embodiment of the present application, based on the photovoltaic and energy storage collaborative control strategy, a control is generated to make the photovoltaic and energy storage system execute corresponding collaborative control actions, including: suppressing the power fluctuation of photovoltaic power generation in a photovoltaic power station; generating at least one operation and maintenance strategy among fault diagnosis, power prediction, peak shaving, and frequency modulation of the photovoltaic and energy storage system to execute the collaborative control actions.

[0068] Optionally, in an embodiment of the present application, power generation control is performed according to the data information of battery energy storage, DC charging and discharging piles, and photovoltaic arrays to achieve the collaborative control of photovoltaic, energy storage, and charging, including: collecting data information; generating corresponding control instructions according to the data information; adjusting the power factor based on the reactive power compensation strategy while generating active power; converting the direct current generated by the photovoltaic into alternating current, connecting it to the power grid, and receiving control instructions based on the battery energy management system layer to perform the collaborative control of photovoltaic, energy storage, and charging.

[0069] It should be noted that the foregoing explanation of the embodiment of the photovoltaic and energy storage collaborative control strategy system for agricultural and photovoltaic complementarity also applies to the photovoltaic and energy storage collaborative control strategy method for agricultural and photovoltaic complementarity in this embodiment, and will not be elaborated here.

[0070] According to the photovoltaic and energy storage collaborative control strategy method proposed in the embodiment of the present application, by using Internet of Things data collection and communication transmission technologies, through constructing a digital intelligent photovoltaic and energy storage operation and maintenance platform, and adopting deep learning methods such as machine learning, technologies such as fault diagnosis, power prediction, peak shaving, and frequency modulation of the photovoltaic and energy storage system are developed to achieve flexible and automatic adjustment of the photovoltaic power station in the spot market and improve the regulation ability during the operation process of the photovoltaic power station. Thus, the problems in the related technologies are solved, such as the large loss of income after the new energy of agricultural and photovoltaic complementarity enters the spot market, resulting in not very high economic benefits of the photovoltaic power station. In addition, the power of photovoltaic power generation is prone to fluctuations, resulting in continuous changes in the power transmitted to the AC power grid, making it difficult for the power grid to perform peak shaving and frequency modulation.

[0071] Figure 3 The structural schematic diagram of the electronic device provided by the embodiment of the present application. The electronic device may include:

[0072] A memory 301, a processor 302, and a computer program stored on the memory 301 and executable on the processor 302.

[0073] When the processor 302 executes the program, it implements the photovoltaic - energy - storage collaborative control strategy method for complementary agricultural and photovoltaic applications provided in the above - mentioned embodiments.

[0074] Furthermore, the electronic device further includes:

[0075] A communication interface 303, which is used for communication between the memory 301 and the processor 302.

[0076] A memory 301, which is used to store computer programs that can run on the processor 302.

[0077] The memory 301 may include a high - speed RAM memory, and may also include non - volatile memory, such as at least one disk memory.

[0078] If the memory 301, the processor 302, and the communication interface 303 are independently implemented, the communication interface 303, the memory 301, and the processor 302 can be interconnected through a bus and complete communication with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For the sake of representation, Figure 3 only a thick line is used to represent it in the figure, but it does not mean that there is only one bus or one type of bus.

[0079] Optionally, in a specific implementation, if the memory 301, the processor 302, and the communication interface 303 are integrated on a chip, the memory 301, the processor 302, and the communication interface 303 can complete communication with each other through an internal interface.

[0080] The processor 302 may be a Central Processing Unit (CPU), or an Application Specific Integrated Circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application.

[0081] This embodiment also provides a computer - readable storage medium, on which a computer program is stored. When the program is executed by a processor, it implements the above - mentioned photovoltaic - energy - storage collaborative control strategy method for complementary agricultural and photovoltaic applications.

[0082] The embodiment of the present application also provides a computer program product, on which a computer program is stored. When the program is executed by a processor, it implements the above-mentioned photovoltaic-storage collaborative control strategy method for complementary use of agriculture and light.

[0083] In the description of this specification, the description with reference to terms such as "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in any one or N embodiments or examples in a suitable manner. In addition, without contradiction, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0084] In addition, the terms "first" and "second" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include at least one of the features. In the description of the present application, the meaning of "N" is at least two, such as two, three, etc., unless otherwise specifically defined.

[0085] Any process or method description in the flowchart or described in other ways herein can be understood as representing a module, segment, or part of code including one or N executable instructions for implementing a customized logic function or process. The scope of the preferred embodiment of the present application includes additional implementations, where the functions can be executed in a manner that is not shown or discussed in order, including in a substantially simultaneous manner according to the functions involved or in the reverse order, which should be understood by those skilled in the art to which the embodiments of the present application belong.

[0086] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a definite sequence list of executable instructions for implementing logical functions, and can be specifically implemented in any computer-readable medium for use by an instruction execution system, apparatus, or device (such as a computer-based system, a system including a processor, or other systems that can fetch and execute instructions from the instruction execution system, apparatus, or device), or in conjunction with these instruction execution systems, apparatuses, or devices. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by or in conjunction with an instruction execution system, apparatus, or device. More specific examples (non-exhaustive list) of computer-readable media include the following: an electrical connection portion (electronic device) having one or N wirings, a portable computer diskette (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically by optically scanning the paper or other media, followed by editing, interpretation, or otherwise processing as appropriate, and then stored in a computer memory.

[0087] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware, or a combination thereof. In the above-described embodiments, the N steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or a combination of the following techniques well known in the art can be used: discrete logic circuits having logic gate circuits for implementing logical functions on data signals, application specific integrated circuits having appropriate combinational logic gate circuits, programmable gate arrays (PGAs), field programmable gate arrays (FPGAs), and the like.

[0088] Those of ordinary skill in the art of this technology can understand that all or part of the steps carried by the method of the above embodiments can be completed by a program instructing relevant hardware, and the program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiments.

[0089] In addition, each functional unit in various embodiments of the present application may be integrated into one processing module, may exist physically alone for each unit, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. When the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0090] The above-mentioned storage medium may be a read-only memory, a magnetic disk, an optical disc, etc. Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present application. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present application.

Claims

1. A photovoltaic storage coordinated control strategy system for agricultural photovoltaic complementarity, characterized in that: include: The clustered simulation test and debugging platform for photovoltaic and storage integration is used to conduct photovoltaic and storage integration simulation tests based on the IoT strategy information of the IoT photovoltaic and storage collaborative control strategy system, and generate photovoltaic and storage collaborative control strategies for agricultural photovoltaic complementary application scenarios; A photovoltaic-storage collaborative control system, used to control the photovoltaic-storage system to perform corresponding collaborative control actions based on the photovoltaic-storage collaborative control strategy; The AGC control system is used to control power generation based on data information from battery energy storage, DC charging and discharging piles, and photovoltaic arrays, thereby achieving coordinated control of photovoltaic storage and charging.

2. The system according to claim 1, characterized in that The clustered simulation test and debugging platform for integrated photovoltaic and storage systems includes: A photovoltaic station digital twin simulation system, used to simulate at least one characteristic function of a centralized photovoltaic power generation system, wherein the characteristic function includes power generation characteristics and power transmission characteristics; A digital twin simulation system for energy storage stations, used to simulate at least one characteristic function of an energy storage grid-connected power generation system; The photovoltaic and energy storage joint virtual simulation test platform is used to receive the Internet of Things strategy information and transmit the Internet of Things strategy information to the photovoltaic station digital twin simulation system and the energy storage station digital twin simulation system.

3. The system according to claim 2, characterized in that The photovoltaic and storage integrated cluster simulation test and debugging platform also includes: The three-dimensional model is combined with the digital twin simulation model to establish the three-dimensional model and the digital twin simulation practical application to meet the preset conditions for consistency with the on-site production equipment, and to evaluate the evaluation information of the photovoltaic storage collaborative control strategy on the performance of the photovoltaic storage system in at least one of the impact, stability and reliability.

4. The system according to claim 1, characterized in that The photovoltaic energy storage coordinated control system comprises: The power storage system is used to smooth out the power fluctuations of photovoltaic power generation in photovoltaic power stations; The photovoltaic storage operation and maintenance platform is used to generate at least one operation and maintenance strategy of fault diagnosis, power prediction, peak load and frequency regulation of the photovoltaic storage system to execute the collaborative control action.

5. The system according to claim 1, characterized in that The AGC control system comprises: A battery energy management system layer, used to collect the data information; A cloud platform server, used to generate corresponding control instructions according to the data information; Photovoltaic inverters are used to adjust the power factor based on reactive power compensation strategies while generating active power; The inverter system layer is used to convert the direct current generated by photovoltaics into alternating current, connect it to the power grid, and receive the control instructions based on the battery energy management system layer to perform coordinated control of light storage and charging.

6. A photovoltaic-storage coordinated control strategy method for agricultural photovoltaic complementarity, characterized in that: The following steps are involved: Based on the IoT strategy information of the IoT photovoltaic storage collaborative control strategy system, a photovoltaic storage integration simulation test was conducted to generate a photovoltaic storage collaborative control strategy for the agricultural photovoltaic complementary application scenario; Based on the photovoltaic-storage collaborative control strategy, a control photovoltaic-storage system is generated to perform corresponding collaborative control actions; Power generation is controlled based on data information from battery energy storage, DC charging and discharging piles, and photovoltaic arrays to achieve coordinated control of light storage and charging.

7. The method according to claim 6, characterized in that The photovoltaic-storage integration simulation test is performed according to the Internet of Things strategy information of the Internet of Things photovoltaic-storage collaborative control strategy system to generate a photovoltaic-storage collaborative control strategy for the agricultural photovoltaic complementary application scenario, including: Simulating at least one characteristic function of a centralized photovoltaic power generation system, wherein the characteristic function includes power generation characteristics and power transmission characteristics; Simulating at least one characteristic function of an energy storage grid-connected power generation system; Receive the Internet of Things strategy information, and transmit the Internet of Things strategy information to the photovoltaic station digital twin simulation system and the energy storage station digital twin simulation system.

8. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the photovoltaic-storage coordinated control strategy method for agricultural-photovoltaic complementarity as described in any one of claims 6 to 7.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: The program is executed by a processor to implement the photovoltaic-storage coordinated control strategy method for agricultural-photovoltaic complementarity as described in any one of claims 6-7.

10. A computer program product, comprising a computer program, characterized in that The computer program is executed to implement the photovoltaic-storage coordinated control strategy method for agricultural-photovoltaic complementarity as described in any one of claims 6-7.

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