Multi-energy collaborative scheduling method and system based on intelligent algorithm

Abstract

The invention discloses a multi-energy collaborative scheduling method and system based on an intelligent algorithm, and relates to the technical field of energy collaborative scheduling, and the method comprises the steps: carrying out the calculation of the energy consumption data of power consumption equipment and the real-time transmission energy data of photovoltaic equipment if the real-time transmission energy of photovoltaic equipment cannot meet the operation demands of the power consumption equipment, and carrying out the calculation of the real-time transmission energy data of the photovoltaic equipment; and selecting an energy compensation scheme of the power consumption equipment. Energy data comparison processing is performed on real-time transmission energy data of photovoltaic equipment and power consumption equipment, whether energy of the photovoltaic equipment can meet requirements of the power consumption equipment or not is determined, if not, data comparison is performed on a task execution time period of a task to be executed and a power consumption peak time period of an area where the power consumption equipment is located, and the task execution time period of the task to be executed and the power consumption peak time period are determined. And determining whether the task executed by the power consumption equipment is in the power consumption peak time period, if not, performing energy compensation on the power consumption equipment through the commercial power grid, and if so, jointly supplying power to the power consumption equipment through the photovoltaic equipment, the commercial power grid and the energy storage equipment to realize real-time optimal power distribution.

Description

Technical Field

[0001] This invention relates to the field of energy collaborative scheduling technology, specifically to a multi-energy collaborative scheduling method and system based on intelligent algorithms. Background Technology

[0002] Photovoltaic (PV) power generation is a technology that directly converts light energy into electrical energy using the photovoltaic effect at semiconductor interfaces. PV power generation mainly consists of three parts: solar panels (modules), controllers, and inverters, with the main components being electronic devices. Solar cells are connected in series and encapsulated for protection to form large-area solar cell modules. Combined with components such as power controllers, this forms a photovoltaic power generation device. PV power generation systems have no moving mechanical parts, produce no pollution or noise, and have a long service life. Although it is less efficient than solar thermal power generation systems, its particularly simple system structure and unique advantage—modular structure—make it suitable for power generation of any scale, from large-scale central power plants to small-scale private residential power supply.

[0003] When photovoltaic (PV) devices supply power to power-consuming equipment, the energy output of PV devices is unstable and may not be able to meet the needs of the power-consuming equipment. Therefore, it is necessary to design an energy dispatch scheme that coordinates the supply of power to power-consuming equipment by PV devices, the mains power grid, and energy storage devices. Summary of the Invention

[0004] To address the aforementioned technical problems, a multi-energy collaborative scheduling method and system based on intelligent algorithms is provided. This technical solution solves the problems mentioned in the background section.

[0005] To achieve the above objectives, the technical solution adopted by the present invention is as follows: A multi-energy cooperative scheduling method based on intelligent algorithms includes: Acquire historical operating data of photovoltaic equipment, perform energy consumption analysis on real-time production capacity data of photovoltaic equipment based on historical operating data of photovoltaic equipment, and obtain real-time energy transmission data of photovoltaic equipment; Based on the real-time energy transmission data of photovoltaic equipment, energy data comparison processing is performed on power-consuming equipment to determine whether the real-time energy transmission of photovoltaic equipment can meet the operating requirements of power-consuming equipment. If the real-time energy transmission of photovoltaic equipment can meet the operating needs of power-consuming equipment, the excess energy generated by the photovoltaic equipment can be stored in energy storage equipment; If the real-time energy transmission of photovoltaic equipment cannot meet the operating requirements of power-consuming equipment, the energy consumption data of power-consuming equipment and the real-time energy transmission data of photovoltaic equipment are calculated and processed to select an energy compensation scheme for power-consuming equipment.

[0006] Preferably, the step of acquiring historical operating data of the photovoltaic equipment, and based on this historical operating data, performing energy consumption analysis on the real-time production capacity data of the photovoltaic equipment to obtain real-time energy transmission data of the photovoltaic equipment specifically includes the following steps: Based on the serial number information of the power-consuming equipment, the database system is used to retrieve and process data to obtain the energy transmission lines of the power-consuming equipment. Based on the identification information of photovoltaic equipment, information extraction and processing are performed on the energy transmission lines of power-consuming equipment to obtain the number information of photovoltaic equipment. Based on the serial number information of photovoltaic equipment, the database system is used to retrieve and process data to obtain historical operating data of photovoltaic equipment. The system acquires real-time production capacity data of photovoltaic (PV) equipment, performs data calculations and processing on historical operating data and real-time production capacity data of PV equipment, and determines the real-time energy transmission data of PV equipment.

[0007] Preferably, the step of obtaining real-time production capacity data of photovoltaic equipment, and performing data calculation and processing on historical operating data and real-time production capacity data of photovoltaic equipment to determine real-time energy transmission data of photovoltaic equipment specifically includes the following steps: The management interface of the photovoltaic equipment is used to read and process data to obtain real-time production capacity data of the photovoltaic equipment. The historical operating data of photovoltaic equipment is filtered and processed to obtain historical production capacity data and historical energy transmission data of photovoltaic equipment. Based on the same timestamp information, the historical production capacity data and historical energy transmission data of photovoltaic equipment are matched to obtain a set of photovoltaic equipment parameter data; wherein, the data in the photovoltaic equipment parameter data set is represented in the form of (historical production capacity data, historical energy transmission data, and the same timestamp information). The historical production capacity data and historical energy transmission data of each data in the photovoltaic equipment parameter data set are calculated by subtraction to obtain the set of energy conversion loss difference values ​​of photovoltaic equipment. Based on the energy conversion loss difference set of photovoltaic equipment, the real-time production capacity data of photovoltaic equipment is processed to determine the real-time energy transmission data of photovoltaic equipment.

[0008] Preferably, the process of calculating and processing the real-time production capacity data of photovoltaic equipment based on the energy conversion loss difference set of photovoltaic equipment to determine the real-time energy transmission data of photovoltaic equipment specifically includes the following steps: The data in the set of energy conversion loss differences of photovoltaic equipment are counted to obtain the total number of data for energy conversion loss differences. The average energy conversion loss difference of photovoltaic equipment is obtained by averaging the total number of data points of energy conversion loss difference and all data in the set of energy conversion loss difference of photovoltaic equipment. Based on the average energy conversion loss difference of photovoltaic equipment, the real-time production capacity data of photovoltaic equipment is processed by data difference calculation to obtain the real-time energy transmission data of photovoltaic equipment.

[0009] Preferably, the step of comparing the energy data of power-consuming equipment with the real-time energy transmission data of the photovoltaic equipment to determine whether the real-time energy transmission of the photovoltaic equipment can meet the operating requirements of the power-consuming equipment specifically includes the following steps: Acquire historical operating data and pending tasks of power-consuming devices; The historical operating data of power-consuming equipment is retrieved and processed to obtain the energy consumption data of the power-consuming equipment when it is not under any task. The average energy consumption data of power-consuming equipment when it is not under any task is calculated and processed to obtain the average energy consumption data of the power-consuming equipment when it is not under any task. The average energy consumption data of power-consuming equipment when it has no tasks, the pending tasks of power-consuming equipment, and the real-time energy transmission data of photovoltaic equipment are compared and processed to determine whether the real-time energy transmission of photovoltaic equipment can meet the operating needs of power-consuming equipment.

[0010] Preferably, the step of comparing the average energy consumption data of the power-consuming equipment when it has no tasks, the pending tasks of the power-consuming equipment, and the real-time energy transmission data of the photovoltaic equipment to determine whether the real-time energy transmission of the photovoltaic equipment can meet the operating requirements of the power-consuming equipment specifically includes the following steps: The system reads and processes data from pending tasks of power-consuming devices to obtain task execution time and energy requirements. The average execution time and energy required for the task are calculated to obtain the energy required per unit time for the task to be executed. The system assesses and processes the energy required per unit time for performing tasks, the average energy consumption data of power-consuming equipment when it is not performing tasks, and the real-time energy transmission data of photovoltaic equipment. If the sum of the energy required per unit time for the task to be performed and the average energy consumption data of the power-consuming equipment when there is no task is greater than or equal to the real-time energy transmission data of the photovoltaic equipment, the real-time energy transmission of the photovoltaic equipment cannot meet the operating needs of the power-consuming equipment. If the sum of the energy required per unit time for the task to be performed and the average energy consumption data of the power-consuming equipment when there is no task is less than the real-time energy transmission data of the photovoltaic equipment, the real-time energy transmission data of the photovoltaic equipment can meet the operating needs of the power-consuming equipment.

[0011] Preferably, the step of calculating and processing the energy consumption data of the power-consuming equipment and the real-time transmitted energy data of the photovoltaic equipment, and selecting an energy compensation scheme for the power-consuming equipment, specifically includes the following steps: The system reads and processes data from pending tasks of power-consuming devices to obtain the task execution time period. Obtain the peak electricity consumption time periods in the area where power-consuming equipment is located; The data is compared and analyzed between the task execution time period and the peak electricity consumption time period of the area where the power-consuming equipment is located, and an energy compensation scheme for the power-consuming equipment is selected.

[0012] Preferably, the process of comparing and analyzing data between the task execution time period and the peak electricity consumption time period in the area where the power-consuming equipment is located, and selecting an energy compensation scheme for the power-consuming equipment, specifically includes the following steps: The task execution time period and the peak electricity consumption time period of the area where the power-consuming equipment is located are judged and processed. If the task execution time period and the peak electricity consumption time period of the area where the power-consuming equipment is located do not overlap at all, energy compensation for the power-consuming equipment will be provided through the municipal power grid. If the task execution time period of the task to be executed and the peak electricity consumption time period of the area where the power-consuming equipment is located completely or partially overlap, the energy required per unit time of the task to be executed, the average energy consumption data of the power-consuming equipment when there is no task, and the real-time energy transmission data of the photovoltaic equipment are calculated to obtain the energy compensation difference. By comparing and analyzing the energy replenishment difference and the instantaneous output energy of the energy storage equipment, an energy compensation scheme for the power-consuming equipment is determined.

[0013] Preferably, the step of comparing and analyzing the energy replenishment difference and the instantaneous output energy of the energy storage device to determine the energy compensation scheme for the power-consuming equipment specifically includes the following steps: When the task execution time period of the task to be executed completely overlaps with the peak electricity consumption time period of the area where the power-consuming equipment is located, the energy replenishment difference and the instantaneous output energy of the energy storage equipment are judged and processed. If the energy replenishment difference is less than or equal to the instantaneous output energy of the energy storage device, the energy storage device will compensate the power-consuming equipment for energy. If the energy replenishment difference is greater than the instantaneous output energy of the energy storage device, the energy storage device and the mains power grid will work together to compensate the power-consuming equipment for energy. When the task execution time period of the task to be executed does not completely overlap with the peak electricity consumption time period of the area where the power-consuming equipment is located; During the period when the task execution time and the peak electricity consumption time in the area where the power-consuming equipment is located overlap, if the energy replenishment difference is less than or equal to the instantaneous output energy of the energy storage device, the energy storage device will compensate the power-consuming equipment for energy; if the energy replenishment difference is greater than the instantaneous output energy of the energy storage device, the energy storage device and the mains power grid will jointly compensate the power-consuming equipment for energy. When the task execution time period does not coincide with the peak electricity consumption time period in the area where the power-consuming equipment is located, energy compensation for the power-consuming equipment is provided through the municipal power grid.

[0014] Furthermore, a multi-energy cooperative scheduling system based on intelligent algorithms is proposed to implement the aforementioned multi-energy cooperative scheduling method based on intelligent algorithms, including: The collaborative scheduling terminal is used to control the data transmission and information interaction between various modules. The collaborative scheduling terminal is used to control the various modules to compare and process the real-time transmitted energy data of photovoltaic equipment and the energy consumption data of power-consuming equipment, and select the energy compensation scheme of power-consuming equipment. A database system is used to store historical operating data of energy transmission lines and photovoltaic equipment for power-consuming equipment; The real-time energy transmission calculation module performs data calculation and processing on the real-time production capacity data of the photovoltaic equipment based on the average energy conversion loss difference of the photovoltaic equipment, and obtains the real-time energy transmission data of the photovoltaic equipment. The data comparison module is used to judge and process the energy required per unit time for the task to be executed, the average energy consumption data of the power-consuming equipment when there is no task, and the real-time energy transmission data of the photovoltaic equipment, and to determine whether the real-time energy transmission of the photovoltaic equipment can meet the operating needs of the power-consuming equipment. The scheme selection module is used to calculate and process the energy consumption data of the power-consuming equipment and the real-time energy transmission data of the photovoltaic equipment, and select the energy compensation scheme for the power-consuming equipment.

[0015] Compared with existing technologies, this invention provides a multi-energy collaborative scheduling method and system based on intelligent algorithms, which has the following beneficial effects: This invention first compares the real-time energy data transmitted by the photovoltaic equipment with the energy data of the power-consuming equipment to determine whether the energy of the photovoltaic equipment can meet the needs of the power-consuming equipment. If not, it compares the data of the task execution time period to be performed with the peak electricity consumption time period of the area where the power-consuming equipment is located to determine whether the power-consuming equipment is performing the task during the peak electricity consumption time period. If not, it compensates the power-consuming equipment with energy through the mains power grid. If it is, it provides power to the power-consuming equipment through the photovoltaic equipment, the mains power grid and energy storage equipment, thereby achieving real-time optimal power allocation. Attached Figure Description

[0016] Figure 1 This is a flowchart illustrating steps S100-S400 in a multi-energy collaborative scheduling method based on intelligent algorithms proposed in this invention. Figure 2 This is a structural block diagram of a multi-energy collaborative scheduling system based on intelligent algorithms proposed in this invention. Detailed Implementation

[0017] The following description is intended to disclose the invention and enable those skilled in the art to implement it. The preferred embodiments described below are merely examples, and other obvious variations will occur to those skilled in the art.

[0018] Reference Figure 1 As shown, a multi-energy cooperative scheduling method based on intelligent algorithms includes: S100. Obtain historical operating data of photovoltaic equipment. Based on the historical operating data of photovoltaic equipment, perform energy consumption analysis and processing on the real-time production capacity data of photovoltaic equipment to obtain real-time energy transmission data of photovoltaic equipment. S200: Based on the real-time energy transmission data of photovoltaic equipment, perform energy data comparison processing on power-consuming equipment to determine whether the real-time energy transmission of photovoltaic equipment can meet the operating requirements of power-consuming equipment. S300. If the real-time energy transmission of the photovoltaic equipment can meet the operating requirements of the power-consuming equipment, the excess energy generated by the photovoltaic equipment shall be stored in the energy storage equipment. S400. If the real-time energy transmission of the photovoltaic equipment cannot meet the operating requirements of the power-consuming equipment, calculate and process the energy consumption data of the power-consuming equipment and the real-time energy transmission data of the photovoltaic equipment, and select an energy compensation scheme for the power-consuming equipment. Those skilled in the art will understand that the electricity generated by photovoltaic equipment is affected by the weather. If the weather is good, the photovoltaic equipment will generate more energy, which may be able to meet the needs of the power-consuming equipment. If the photovoltaic equipment generates less energy, it may not be able to meet the needs of the power-consuming equipment, and external energy is needed to compensate for the power-consuming equipment. Therefore, in order to achieve real-time optimal power allocation, energy calculations are performed on the photovoltaic equipment, the mains power grid, and the energy storage equipment to determine a suitable energy allocation scheme for the power-consuming equipment. Example 1

[0019] Step S100: Obtain historical operating data of photovoltaic equipment. Based on the historical operating data of photovoltaic equipment, perform energy consumption analysis and processing on the real-time production capacity data of photovoltaic equipment to obtain real-time energy transmission data of photovoltaic equipment. This specifically includes the following steps: S101. Based on the serial number information of the power-consuming equipment, perform data retrieval processing on the database system to obtain the energy transmission line of the power-consuming equipment. S102. Based on the identification information of photovoltaic equipment, perform information extraction and processing on the energy transmission lines of power-consuming equipment to obtain the number information of photovoltaic equipment; S103. Based on the serial number information of the photovoltaic equipment, perform data retrieval processing on the database system to obtain the historical operating data of the photovoltaic equipment; S104. Obtain real-time production capacity data of photovoltaic equipment, perform data calculation and processing on historical operating data and real-time production capacity data of photovoltaic equipment, and determine real-time energy transmission data of photovoltaic equipment. Specifically, step S104, obtaining real-time production capacity data of photovoltaic equipment, involves data calculation and processing of historical operating data and real-time production capacity data of photovoltaic equipment to determine the real-time energy transmission data of photovoltaic equipment, including the following steps: S1041. Read and process data from the management interface of the photovoltaic equipment to obtain real-time production capacity data of the photovoltaic equipment; S1042. Perform data filtering and processing on the historical operating data of photovoltaic equipment to obtain historical production capacity data and historical energy transmission data of photovoltaic equipment. S1043. Based on the same timestamp information, perform data matching processing on the historical production capacity data and historical energy transmission data of the photovoltaic equipment to obtain a photovoltaic equipment parameter data set; wherein, the data in the photovoltaic equipment parameter data set is represented in the form of (historical production capacity data, historical energy transmission data, and the same timestamp information). S1044. Perform difference calculation on the historical production capacity data and historical energy transmission data of each data in the photovoltaic equipment parameter data set to obtain the energy conversion loss difference set of the photovoltaic equipment. S1045. Based on the energy conversion loss difference set of photovoltaic equipment, perform data calculation and processing on the real-time production capacity data of photovoltaic equipment to determine the real-time energy transmission data of photovoltaic equipment. It is understandable that photovoltaic equipment converts solar energy into electrical energy. However, some losses will occur during the conversion process, and the losses may vary each time. However, these losses will also be concentrated within a certain range. Therefore, by averaging the losses in each conversion process, an average loss value is obtained. This average loss value is the closest to the loss pattern. Therefore, by using the average loss value, real-time energy transmission data of photovoltaic equipment with small errors can be obtained. It is worth noting that the time information of the data here refers to the minimum data acquisition time. Specifically, step S1045, which involves performing data calculation and processing on the real-time capacity data of photovoltaic equipment based on the energy conversion loss difference set of photovoltaic equipment, to determine the real-time energy transmission data of photovoltaic equipment, includes the following steps: S10451. Count the data in the set of energy conversion loss difference of photovoltaic equipment to obtain the total number of data of energy conversion loss difference; S10452. Perform average calculation on the total number of data points of energy conversion loss difference and all data in the set of energy conversion loss difference of photovoltaic equipment to obtain the average energy conversion loss difference of photovoltaic equipment. S10453. Based on the average energy conversion loss difference of photovoltaic equipment, perform data difference calculation on the real-time production capacity data of photovoltaic equipment to obtain the real-time energy transmission data of photovoltaic equipment. In this embodiment, to avoid situations where the energy of the photovoltaic equipment does not meet the needs of the power-consuming equipment and requires temporary energy allocation, the solar energy collected by the photovoltaic equipment is first converted and calculated to obtain the real-time energy transmission data of the photovoltaic equipment. Then, the real-time energy transmission data of the photovoltaic equipment is compared with the energy consumption demand of the power-consuming equipment to determine in advance whether the energy of the photovoltaic equipment can meet the needs of the power-consuming equipment. If not, an energy compensation scheme is designed in advance to ensure that the power-consuming equipment can operate normally. Example 2

[0020] Step S200: Based on the real-time energy transmission data of the photovoltaic equipment, perform energy data comparison processing on the power-consuming equipment to determine whether the real-time energy transmission of the photovoltaic equipment can meet the operating requirements of the power-consuming equipment. This specifically includes the following steps: S201. Obtain historical operating data and pending tasks of power-consuming equipment; S202. Retrieve and process the historical operating data of the power-consuming equipment to obtain the energy consumption data of the power-consuming equipment when it is not under any task. S203. Perform average calculation on the energy consumption data of power-consuming equipment when it is not under any task to obtain the average energy consumption data of power-consuming equipment when it is not under any task. S204. Compare the average energy consumption data of the power-consuming equipment when there is no task, the pending tasks of the power-consuming equipment and the real-time energy transmission data of the photovoltaic equipment to determine whether the real-time energy transmission of the photovoltaic equipment can meet the operating needs of the power-consuming equipment. Specifically, step S204, which involves comparing the average energy consumption data of the power-consuming equipment when it has no tasks, the pending tasks of the power-consuming equipment, and the real-time energy transmission data of the photovoltaic equipment to determine whether the real-time energy transmission of the photovoltaic equipment can meet the operating requirements of the power-consuming equipment, includes the following steps: S2041. Read and process data for tasks to be executed by power-consuming equipment to obtain task execution time and energy required for the task. S2042. Calculate the average of the task execution time and the energy required by the task to obtain the energy required per unit time for the task to be executed. S2043. The energy required per unit time for the task to be performed, the average energy consumption data of the power-consuming equipment when there is no task, and the real-time energy transmission data of the photovoltaic equipment are judged and processed. S2044. If the sum of the energy required per unit time for the task to be performed and the average energy consumption data of the power-consuming equipment when there is no task is greater than or equal to the real-time energy transmission data of the photovoltaic equipment, the real-time energy transmission of the photovoltaic equipment cannot meet the operating requirements of the power-consuming equipment. S2045. If the sum of the energy required per unit time for the task to be performed and the average energy consumption data of the power-consuming equipment when there is no task is less than the real-time energy transmission data of the photovoltaic equipment, the real-time energy transmission of the photovoltaic equipment can meet the operating needs of the power-consuming equipment. In this embodiment, the energy demand of the power-consuming equipment is divided into two types: one is the energy consumption data when the power-consuming equipment has no task, and the other is the energy consumption data when performing a task. Therefore, when the power-consuming equipment needs to perform a task, it is necessary to judge the energy required per unit time of the task to be performed, the average energy consumption data of the power-consuming equipment when it has no task, and the real-time energy transmission data of the photovoltaic equipment to determine whether the real-time energy transmission data of the photovoltaic equipment can meet the needs of the power-consuming equipment. If it cannot meet the needs, energy compensation is required for the power-consuming equipment to ensure its normal operation. Example 3

[0021] Step S400: Calculate and process the energy consumption data of the power-consuming equipment and the real-time energy transmission data of the photovoltaic equipment, and select an energy compensation scheme for the power-consuming equipment. This specifically includes the following steps: S401. Read and process the data of the tasks to be executed by the power-consuming equipment to obtain the task execution time period of the tasks to be executed. S402. Obtain the peak electricity consumption time period in the area where the power-consuming equipment is located; S403. Compare and analyze the data of the task execution time period and the peak electricity consumption time period of the area where the power-consuming equipment is located, and select an energy compensation scheme for the power-consuming equipment.

[0022] Step S403, which involves comparing and analyzing data between the task execution time period and the peak electricity consumption time period in the area where the power-consuming equipment is located, and selecting an energy compensation scheme for the power-consuming equipment, specifically includes the following steps: S4031. Determine and process the task execution time period and the peak electricity consumption time period of the area where the power-consuming equipment is located; S4033. If the task execution time period of the task to be executed does not overlap with the peak electricity consumption time period of the area where the power-consuming equipment is located, energy compensation for the power-consuming equipment shall be provided through the municipal power grid. S4033. If the task execution time period of the task to be executed and the peak electricity consumption time period of the area where the power-consuming equipment is located completely or partially overlap, the energy required per unit time of the task to be executed, the average energy consumption data of the power-consuming equipment when there is no task, and the real-time energy transmission data of the photovoltaic equipment are calculated to obtain the energy compensation difference. S4034. Compare and analyze the energy replenishment difference and the instantaneous output energy of the energy storage equipment to determine the energy compensation scheme for the power-consuming equipment. Specifically, step S4034, which involves comparing and analyzing the energy replenishment difference and the instantaneous output energy of the energy storage device to determine the energy compensation scheme for the power-consuming equipment, includes the following steps: S40341. When the task execution time period of the task to be executed completely overlaps with the peak electricity consumption time period of the area where the power-consuming equipment is located, the energy replenishment difference and the instantaneous output energy of the energy storage equipment shall be judged and processed. S40342. If the energy replenishment difference is less than or equal to the instantaneous output energy of the energy storage device, the energy storage device shall compensate the power-consuming equipment for energy. S40343. If the energy replenishment difference is greater than the instantaneous output energy of the energy storage device, the energy storage device and the mains power grid shall work together to compensate the power-consuming equipment for energy consumption. S40344. When the task execution time period of the task to be executed does not completely overlap with the peak electricity consumption time period of the area where the power-consuming equipment is located; S40345. During the period when the task execution time of the task to be executed coincides with the peak electricity consumption time in the area where the power-consuming equipment is located, if the energy replenishment difference is less than or equal to the instantaneous output energy of the energy storage device, the energy storage device will compensate the power-consuming equipment for energy; if the energy replenishment difference is greater than the instantaneous output energy of the energy storage device, the energy storage device and the mains power grid will jointly compensate the power-consuming equipment for energy. S40346. When the task execution time period of the task to be executed does not coincide with the peak electricity consumption time period of the area where the power-consuming equipment is located, energy compensation shall be provided to the power-consuming equipment through the municipal power grid. In this embodiment, when the energy of the photovoltaic equipment cannot meet the needs of the power-consuming equipment, external energy is required to compensate for the power consumption. This can be achieved using energy storage devices or the mains power grid. However, energy storage devices may experience energy shortages, and if the mains power grid compensates for the power consumption during peak electricity consumption periods, it will increase the operating costs of the power consumption. Therefore, the task execution time period is first compared with the peak electricity consumption time period in the area where the power consumption equipment is located. If they do not overlap, the power grid will be used to fully compensate for the power consumption, while reserving the energy from the energy storage device. If they completely overlap, it is first determined whether the energy storage device can fully meet the needs of the power consumption. If it can, the energy storage device will be used to compensate for the power consumption. If it cannot, the portion that the energy storage device cannot meet will be compensated by the mains power grid, minimizing the use of the mains power grid and reducing the operating costs of the power consumption.

[0023] Reference Figure 2 As shown, a multi-energy collaborative scheduling system based on intelligent algorithms is used to implement the multi-energy collaborative scheduling method based on intelligent algorithms as described above, including: The collaborative scheduling terminal is used to control the data transmission and information interaction between various modules. The collaborative scheduling terminal is used to control the various modules to compare and process the real-time transmitted energy data of photovoltaic equipment and the energy consumption data of power-consuming equipment, and select the energy compensation scheme of power-consuming equipment. A database system is used to store historical operating data of energy transmission lines and photovoltaic equipment for power-consuming equipment; The real-time energy transmission calculation module performs data calculation and processing on the real-time production capacity data of the photovoltaic equipment based on the average energy conversion loss difference of the photovoltaic equipment, and obtains the real-time energy transmission data of the photovoltaic equipment. The data comparison module is used to judge and process the energy required per unit time for the task to be executed, the average energy consumption data of the power-consuming equipment when there is no task, and the real-time energy transmission data of the photovoltaic equipment, and to determine whether the real-time energy transmission of the photovoltaic equipment can meet the operating needs of the power-consuming equipment. The scheme selection module is used to calculate and process the energy consumption data of the power-consuming equipment and the real-time energy transmission data of the photovoltaic equipment, and select the energy compensation scheme for the power-consuming equipment.

[0024] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the claimed invention. The scope of protection claimed by the appended claims and their equivalents is defined.

Claims

1. A multi-energy collaborative scheduling method based on intelligent algorithms, characterized in that, include: Acquire historical operating data of photovoltaic equipment, perform energy consumption analysis on real-time production capacity data of photovoltaic equipment based on historical operating data of photovoltaic equipment, and obtain real-time energy transmission data of photovoltaic equipment; Based on the real-time energy transmission data of photovoltaic equipment, energy data comparison processing is performed on power-consuming equipment to determine whether the real-time energy transmission of photovoltaic equipment can meet the operating requirements of power-consuming equipment. If the real-time energy transmission of photovoltaic equipment can meet the operating needs of power-consuming equipment, the excess energy generated by the photovoltaic equipment can be stored in energy storage equipment; If the real-time energy transmission of photovoltaic equipment cannot meet the operating requirements of power-consuming equipment, the energy consumption data of power-consuming equipment and the real-time energy transmission data of photovoltaic equipment are calculated and processed to select an energy compensation scheme for power-consuming equipment.

2. The multi-energy collaborative scheduling method based on intelligent algorithms according to claim 1, characterized in that, The process of acquiring historical operating data of photovoltaic equipment, and then performing energy consumption analysis on the real-time production capacity data of the photovoltaic equipment based on this historical operating data to obtain real-time energy transmission data of the photovoltaic equipment, specifically includes the following steps: Based on the serial number information of the power-consuming equipment, the database system is used to retrieve and process data to obtain the energy transmission lines of the power-consuming equipment. Based on the identification information of photovoltaic equipment, information extraction and processing are performed on the energy transmission lines of power-consuming equipment to obtain the number information of photovoltaic equipment. Based on the serial number information of photovoltaic equipment, the database system is used to retrieve and process data to obtain historical operating data of photovoltaic equipment. The system acquires real-time production capacity data of photovoltaic (PV) equipment, performs data calculations and processing on historical operating data and real-time production capacity data of PV equipment, and determines the real-time energy transmission data of PV equipment.

3. The multi-energy collaborative scheduling method based on intelligent algorithms according to claim 2, characterized in that, The process of obtaining real-time production capacity data of photovoltaic equipment, and performing data calculations and processing on historical operating data and real-time production capacity data of photovoltaic equipment to determine real-time energy transmission data of photovoltaic equipment, specifically includes the following steps: The management interface of the photovoltaic equipment is used to read and process data to obtain real-time production capacity data of the photovoltaic equipment. The historical operating data of photovoltaic equipment is filtered and processed to obtain historical production capacity data and historical energy transmission data of photovoltaic equipment. Based on the same timestamp information, the historical production capacity data and historical energy transmission data of photovoltaic equipment are matched to obtain a set of photovoltaic equipment parameter data; wherein, the data in the photovoltaic equipment parameter data set is represented in the form of (historical production capacity data, historical energy transmission data, and the same timestamp information). The historical production capacity data and historical energy transmission data of each data in the photovoltaic equipment parameter data set are calculated by subtraction to obtain the set of energy conversion loss difference values ​​of photovoltaic equipment. Based on the energy conversion loss difference set of photovoltaic equipment, the real-time production capacity data of photovoltaic equipment is processed to determine the real-time energy transmission data of photovoltaic equipment.

4. The multi-energy cooperative scheduling method based on intelligent algorithms according to claim 3, characterized in that, The process of calculating and processing the real-time production capacity data of photovoltaic equipment based on the energy conversion loss difference set of photovoltaic equipment to determine the real-time energy transmission data of photovoltaic equipment specifically includes the following steps: The data in the set of energy conversion loss differences of photovoltaic equipment are counted to obtain the total number of data for energy conversion loss differences. The average energy conversion loss difference of the photovoltaic equipment is obtained by averaging the total number of data points of energy conversion loss difference and all data in the set of energy conversion loss difference of photovoltaic equipment. Based on the average energy conversion loss difference of photovoltaic equipment, the real-time production capacity data of photovoltaic equipment is processed by data difference calculation to obtain the real-time energy transmission data of photovoltaic equipment.

5. The multi-energy cooperative scheduling method based on intelligent algorithms according to claim 4, characterized in that, The process of comparing energy data of power-consuming equipment with real-time energy transmission data from photovoltaic devices to determine whether the real-time energy transmission from photovoltaic devices can meet the operational needs of power-consuming equipment includes the following steps: Acquire historical operating data and pending tasks of power-consuming devices; The historical operating data of power-consuming equipment is retrieved and processed to obtain the energy consumption data of the power-consuming equipment when it is not under any task. The average energy consumption data of power-consuming equipment when it is not under any task is calculated and processed to obtain the average energy consumption data of the power-consuming equipment when it is not under any task. The average energy consumption data of power-consuming equipment when it has no tasks, the pending tasks of power-consuming equipment, and the real-time energy transmission data of photovoltaic equipment are compared and processed to determine whether the real-time energy transmission of photovoltaic equipment can meet the operating needs of power-consuming equipment.

6. The multi-energy cooperative scheduling method based on intelligent algorithms according to claim 5, characterized in that, The process of comparing the average energy consumption data of power-consuming equipment when it has no tasks, the pending tasks of power-consuming equipment, and the real-time energy transmission data of photovoltaic equipment to determine whether the real-time energy transmission of photovoltaic equipment can meet the operating requirements of power-consuming equipment includes the following steps: The system reads and processes data from pending tasks of power-consuming devices to obtain task execution time and energy requirements. The average execution time and energy required for the task are calculated to obtain the energy required per unit time for the task to be executed. The system assesses and processes the energy required per unit time for performing tasks, the average energy consumption data of power-consuming equipment when it is not performing tasks, and the real-time energy transmission data of photovoltaic equipment. If the sum of the energy required per unit time for the task to be performed and the average energy consumption data of the power-consuming equipment when there is no task is greater than or equal to the real-time energy transmission data of the photovoltaic equipment, the real-time energy transmission of the photovoltaic equipment cannot meet the operating needs of the power-consuming equipment. If the sum of the energy required per unit time for the task to be performed and the average energy consumption data of the power-consuming equipment when there is no task is less than the real-time energy transmission data of the photovoltaic equipment, the real-time energy transmission data of the photovoltaic equipment can meet the operating needs of the power-consuming equipment.

7. The multi-energy collaborative scheduling method based on intelligent algorithms according to claim 1, characterized in that, The process of calculating and processing the energy consumption data of power-consuming equipment and the real-time energy transmission data of photovoltaic equipment, and selecting an energy compensation scheme for power-consuming equipment, specifically includes the following steps: The system reads and processes data from pending tasks of power-consuming devices to obtain the task execution time period. Obtain the peak electricity consumption time periods in the area where power-consuming equipment is located; The data is compared and analyzed between the task execution time period and the peak electricity consumption time period of the area where the power-consuming equipment is located, and an energy compensation scheme for the power-consuming equipment is selected.

8. A multi-energy cooperative scheduling method based on intelligent algorithms according to claim 7, characterized in that, The process of comparing and analyzing data between the task execution time period and the peak electricity consumption time period in the area where the power-consuming equipment is located, and selecting an energy compensation scheme for the power-consuming equipment, specifically includes the following steps: The task execution time period and the peak electricity consumption time period of the area where the power-consuming equipment is located are judged and processed. If the task execution time period and the peak electricity consumption time period of the area where the power-consuming equipment is located do not overlap at all, energy compensation for the power-consuming equipment will be provided through the municipal power grid. If the task execution time period of the task to be executed and the peak electricity consumption time period of the area where the power-consuming equipment is located completely or partially overlap, the energy required per unit time of the task to be executed, the average energy consumption data of the power-consuming equipment when there is no task, and the real-time energy transmission data of the photovoltaic equipment are calculated to obtain the energy compensation difference. By comparing and analyzing the energy replenishment difference and the instantaneous output energy of the energy storage equipment, an energy compensation scheme for the power-consuming equipment is determined.

9. A multi-energy collaborative scheduling method based on intelligent algorithms according to claim 8, characterized in that, The process of comparing and analyzing the energy replenishment difference and the instantaneous output energy of the energy storage device to determine the energy compensation scheme for the power-consuming equipment includes the following steps: When the task execution time period of the task to be executed completely overlaps with the peak electricity consumption time period of the area where the power-consuming equipment is located, the energy replenishment difference and the instantaneous output energy of the energy storage equipment are judged and processed. If the energy replenishment difference is less than or equal to the instantaneous output energy of the energy storage device, the energy storage device will compensate the power-consuming equipment for energy. If the energy replenishment difference is greater than the instantaneous output energy of the energy storage device, the energy storage device and the mains power grid will work together to compensate the power-consuming equipment for energy. When the task execution time period of the task to be executed does not completely overlap with the peak electricity consumption time period of the area where the power-consuming equipment is located; During the period when the task execution time and the peak electricity consumption time in the area where the power-consuming equipment is located overlap, if the energy replenishment difference is less than or equal to the instantaneous output energy of the energy storage device, the energy storage device will compensate the power-consuming equipment for energy; if the energy replenishment difference is greater than the instantaneous output energy of the energy storage device, the energy storage device and the mains power grid will jointly compensate the power-consuming equipment for energy. When the task execution time period does not coincide with the peak electricity consumption time period in the area where the power-consuming equipment is located, energy compensation for the power-consuming equipment is provided through the municipal power grid.

10. A multi-energy collaborative scheduling system based on intelligent algorithms, used to implement the multi-energy collaborative scheduling method based on intelligent algorithms as described in any one of claims 1-9, characterized in that, include: The collaborative scheduling terminal is used to control the data transmission and information interaction between various modules. The collaborative scheduling terminal is used to control the various modules to compare and process the real-time transmitted energy data of photovoltaic equipment and the energy consumption data of power-consuming equipment, and select the energy compensation scheme of power-consuming equipment. A database system is used to store historical operating data of energy transmission lines and photovoltaic equipment for power-consuming equipment; The real-time energy transmission calculation module performs data calculation and processing on the real-time production capacity data of the photovoltaic equipment based on the average energy conversion loss difference of the photovoltaic equipment, and obtains the real-time energy transmission data of the photovoltaic equipment. The data comparison module is used to judge and process the energy required per unit time for the task to be executed, the average energy consumption data of the power-consuming equipment when there is no task, and the real-time energy transmission data of the photovoltaic equipment, and to determine whether the real-time energy transmission of the photovoltaic equipment can meet the operating needs of the power-consuming equipment. The scheme selection module is used to calculate and process the energy consumption data of the power-consuming equipment and the real-time energy transmission data of the photovoltaic equipment, and select the energy compensation scheme for the power-consuming equipment.

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