Intelligent energy management method and device for multi-port energy routers for oil fields

Abstract

The embodiments of the present application relate to the technical field of oilfield energy management, and provide an intelligent energy management method and apparatus for a multi-port energy router for oilfields. The method comprises: determining the predicted photovoltaic power generation power of photovoltaic panels and the predicted market clearing price of electricity for each preset time period within a preset future time range; determining the predicted transaction power in each preset time period based on the operating power of the pumping unit, the charge and discharge power of the energy storage system, the predicted photovoltaic power generation power of the photovoltaic panels, and the first, second, third, and fourth conversion efficiencies; determining the predicted minimum operating cost based on the predicted market clearing price and the predicted transaction power; determining the predicted final transaction data for each preset time period based on the predicted minimum operating cost; and generating an initial energy management strategy based on the predicted final transaction data, wherein the strategy defines the amount of power stored in the energy storage system, supplied to the pumping unit, sold, and purchased by the multi-port energy router in each preset time period within the preset future time range.

Description

Technical Field

[0001] The present application relates to the technical field of oilfield energy management, and in particular to an intelligent energy management method, device, system, storage medium and computer program product for a multi-port energy router for oilfields. Background Art

[0002] Guided by the "dual carbon" goals, the energy-intensive oil extraction industry is undergoing a profound transformation towards a green, low-carbon economy. Global oilfield service companies are steadily advancing this transformation, exploring the integration of fossil fuels with new energy sources such as wind, solar, and geothermal energy, and focusing on intelligent regulation. This has become a new trend in the development of future energy systems. The integration of clean energy not only promotes resource conservation and efficient utilization, reduces overexploitation and waste of natural resources, but also effectively reduces exploration and development costs and improves social and economic benefits. However, with the high proportion of new energy integration in oilfields, its random and intermittent nature has created a mismatch with the demand for continuous oil and gas production. This has led to inefficient utilization of new energy, severe resource waste, and even poses a threat to the stability of oilfield power systems.

[0003] Existing approaches to improving oilfield energy efficiency primarily focus on improvements to production and energy conversion equipment, without addressing energy scheduling. Some oilfields that consider energy scheduling only maintain internal energy stability, without considering interactions with other power generators and users, participation in the electricity spot market, or responsiveness to grid demand, resulting in a failure to effectively manage energy. Summary of the Invention

[0004] The purpose of the embodiments of the present application is to provide an intelligent energy management method, device, energy management system, storage medium and computer program product for a multi-port energy router for oil fields, so as to address the technical defects of the prior art in that oil field energy management has not been improved at the energy scheduling level, has not considered interaction with other power generation and consumption entities, has not participated in the electricity spot market, and has not responded to the needs of the power grid, resulting in the inability to effectively manage energy.

[0005] To achieve the above objectives, the present application provides, in a first aspect, an intelligent energy management method for a multi-port energy router for oil fields, the method comprising:

[0006] determining a predicted photovoltaic power generation power of the photovoltaic panel for each predetermined time period within a predetermined future time range, and determining a predicted market clearing price of electricity for each predetermined time period, wherein the photovoltaic panel is used to generate electricity to drive a pumpjack to operate an oil field;

[0007] Determine the predicted transaction power of the multi-port energy router in each preset time period based on the operating power of the pumping unit in each preset time period, the charge and discharge power of the energy storage system in each preset time period, the predicted photovoltaic power generation power of the photovoltaic panel in each preset time period, the first conversion efficiency of the first converter, the second conversion efficiency of the second converter, the third conversion efficiency of the third converter, and the fourth conversion efficiency of the fourth converter, wherein the energy storage system is used to store the power converted by the photovoltaic panel, and the pumping unit, the energy storage system, the photovoltaic panel, and the power market that trades power with the multi-port energy router are connected to the multi-port energy router through the first converter, the second converter, the third converter, and the fourth converter, respectively;

[0008] Determine the predicted minimum operating cost of the multi-port energy router based on the predicted market clearing price and predicted transaction power in each time period;

[0009] determining predicted final transaction data of the multi-port energy router in each preset time period based on the predicted minimum operating cost;

[0010] An initial energy management strategy is generated based on the predicted final transaction data, where the initial energy management strategy defines the amount of electricity stored in the energy storage system, supplied to the pumping units, sold, and purchased by the multi-port energy router in each preset time period within a preset future time range.

[0011] In an embodiment of the present application, the predicted transaction power of the multi-port energy router in each preset time period is determined according to formula (1):

[0012] (1),

[0013] in, is the predicted transaction power of the multi-port energy router in a preset time period t within a preset future time range, is the working power of the pumping unit in the preset time period t, is the charge and discharge power of the energy storage system in the preset time period t, is the predicted photovoltaic power generation power of the photovoltaic panel in the preset time period t, is the fourth conversion efficiency, is the first conversion efficiency, is the second conversion efficiency, is the third conversion efficiency.

[0014] In an embodiment of the present application, the operating power of the oil pump satisfies a first power constraint condition, wherein the first power constraint condition defines that the total operating power of the oil pump within a preset future time range meets the total production demand of the oil field within the preset future time range, and the operating power of the oil pump in each preset time period does not exceed the power threshold of the oil pump.

[0015] In the embodiment of the present application, the first power constraint condition is shown in formula (2):

[0016] (2),

[0017] in, is the total operating power of the pumping unit within the preset future time range, is the total production demand of the oil field within a preset future time range, is the power threshold of the pumping unit, N is the preset future time range, is the working power of the pumping unit in each preset time period.

[0018] In an embodiment of the present application, the charge and discharge power of the energy storage system satisfies a charge and discharge power constraint condition, wherein the charge and discharge power constraint condition defines that the charge and discharge power of the energy storage system in each preset time period within a preset future time range does not exceed a charge and discharge power threshold of the energy storage system; and / or the state of charge of the energy storage system satisfies a first charge constraint condition, wherein the first charge constraint condition defines that the difference between a first charge amount and a second charge amount of the energy storage system is greater than or equal to a first preset difference value and less than or equal to a second preset difference value, and the charge amount of the energy storage system in each preset time period is greater than or equal to a first value and less than or equal to a second value, the first charge amount is the charge amount of the energy storage system corresponding to the end time of the preset future time range, and the second charge amount is the charge amount of the energy storage system corresponding to the start time of the preset future time range.

[0019] In the embodiment of the present application, the first charge constraint condition is shown in formula (3):

[0020] (3),

[0021] in, is the first value, is the second value, is the charge of the energy storage system in a preset time period t within a preset future time range, is the first preset difference, is the second preset difference, is the second charge, is the first charge, is the charge of the energy storage system in the previous preset time period of the preset time period t within the preset future time range, For the preset time interval, is the charging efficiency of the energy storage system, is the discharge efficiency of the energy storage system, is the rated capacity of the energy storage system, N is the preset future time range, and is the actual charging and discharging power of the energy storage system in the preset time period t, is the second conversion efficiency.

[0022] In the embodiment of the present application, the predicted minimum operating cost is determined according to formula (4):

[0023] (4),

[0024] in, To predict the minimum operating cost, is the predicted transaction power of the multi-port energy router in a preset time period t within a preset future time range, is the predicted market clearing price of electricity in the preset time period t, and N is the preset future time range.

[0025] In an embodiment of the present application, determining the predicted photovoltaic power generation power of the photovoltaic panel for each preset time period within a preset future time range includes: obtaining meteorological data of the oil field within the preset future time range and historical power generation data of the photovoltaic panel; and determining the predicted photovoltaic power generation power of the photovoltaic panel for each preset time period within the preset future time range based on the meteorological data and the historical power generation data.

[0026] In an embodiment of the present application, determining the predicted market clearing price of electricity in each preset time period includes: obtaining historical trading electricity data, historical meteorological data and current climate data of the oil field; and determining the predicted market clearing price of electricity in each preset time period based on the historical trading electricity data, historical meteorological data and current climate data.

[0027] In an embodiment of the present application, the method further includes: in the process of executing energy management operations according to the initial energy management strategy, obtaining the actual photovoltaic power generation power of the photovoltaic panel in the current time period, the actual charge and discharge power of the energy storage system in the current time period, the actual operating power of the pumping unit in the current time period, and the actual market clearing price of electricity in the next preset time period; determining the actual transaction power difference of the multi-port energy router in the next preset time period based on the actual photovoltaic power generation power, the actual charge and discharge power of the energy storage system, the actual operating power of the pumping unit, the first conversion efficiency, the second conversion efficiency, the third conversion efficiency, the fourth conversion efficiency, and the predicted transaction power; predicting the minimum additional operating cost of the multi-port energy router based on the actual transaction power difference in the next preset time period and the actual market clearing price of electricity; updating the predicted final transaction data of the multi-port energy router in the next preset time period based on the minimum additional operating cost; and adjusting the energy management strategy for the next preset time period according to the updated predicted final transaction data, so that the energy management operation corresponding to the adjusted energy management strategy is performed when the next preset time period is reached.

[0028] In an embodiment of the present application, the actual transaction power difference of the multi-port energy router in the next preset time period is determined according to formula (5):

[0029] (5),

[0030] in, is the actual transaction power difference of the multi-port energy router within the preset time period t, is the actual transaction power of the multi-port energy router within the preset time period t, is the predicted transaction power in the preset time period t, and is the actual working power of the pumping unit in the preset time period t, and is the actual charging and discharging power of the energy storage system in the preset time period t, and is the actual photovoltaic power generation power of the photovoltaic panel in the preset time period t, is the fourth conversion efficiency, is the first conversion efficiency, is the second conversion efficiency, is the third conversion efficiency, is a constant, The next preset time period.

[0031] In an embodiment of the present application, the actual working power of the oil pump satisfies the second power constraint condition, which defines that the total working power of the oil pump within a preset future time range must meet the total production demand of the oil field within the preset future time range, and the actual working power of the oil pump in each preset time period does not exceed the power threshold; wherein, the total working power includes a first working power, a second working power and a third working power, the first working power is the total actual working power of the oil pump within the starting moment of the preset future time range to the current preset time period, the second working power is the predicted working power of the oil pump in the next preset time period, and the third working power is the predicted total working power of the oil pump from the end moment of the next preset time period to the end moment of the preset future time range.

[0032] In an embodiment of the present application, the second power constraint condition is as shown in formula (6):

[0033] (6),

[0034] in, is the first working power, is the second working power, is the third working power, is the total working power, is the power threshold of the pumping unit, It is the actual working power of the pumping unit in each preset time period.

[0035] In an embodiment of the present application, the state of charge of the energy storage system satisfies a second charge constraint condition, wherein the second charge constraint condition defines that the difference between the third charge and the fourth charge of the energy storage system is greater than or equal to the first preset difference and less than or equal to the second preset difference, the third charge is the predicted charge corresponding to the end time of the next preset time period of the energy storage system under the execution of the updated energy management strategy, and the fourth charge is the predicted charge corresponding to the end time of the next preset time period of the energy storage system under the execution of the initial energy management strategy.

[0036] In the embodiment of the present application, the minimum additional operating cost is determined according to formula (7):

[0037] (7),

[0038] in, Minimize additional operating costs, is the actual transaction power difference of the multi-port energy router within the preset time period t, is the actual market clearing price of electricity in the preset time period t, The next preset time period.

[0039] A second aspect of the present application provides an intelligent energy management device for a multi-port energy router for oil fields, comprising:

[0040] a memory configured to store instructions;

[0041] The processor is configured to call the instructions from the memory and implement the above-mentioned intelligent energy management method for the oil field-oriented multi-port energy router when executing the instructions.

[0042] A third aspect of the present application provides a multi-port energy router intelligent energy management system for oil fields, comprising:

[0043] The pumping unit is connected to the multi-port energy router via a first converter;

[0044] An energy storage system, connected to the multi-port energy router via a second converter, for storing the electricity converted by the photovoltaic panels;

[0045] The photovoltaic panel is connected to the multi-port energy router via a third converter and is used to generate electricity to drive a pumping unit to operate the oil field;

[0046] a multi-port energy router connected to the power market via a fourth converter to trade electricity with the power market;

[0047] The above-mentioned multi-port energy router intelligent energy management device for oil fields.

[0048] A fourth aspect of the present application provides a machine-readable storage medium having instructions stored thereon, which, when executed by a processor, configures the processor to execute the above-mentioned intelligent energy management method for a multi-port energy router for oil fields.

[0049] A fifth aspect of the present application provides a computer program product, including a computer program, which, when executed by a controller, implements the above-mentioned intelligent energy management method for a multi-port energy router for oil fields.

[0050] The above technical solution determines the predicted photovoltaic power generation and the predicted market-clearing price of electricity for each preset time period within a preset future time range; determines the predicted transaction volume for each preset time period based on the operating power of the oil pump, the charge and discharge power of the energy storage system, the predicted photovoltaic power generation of the photovoltaic panel, and the first, second, third, and fourth conversion efficiencies within each preset time period; determines the predicted minimum operating cost based on the predicted market-clearing price and the predicted transaction volume; determines the predicted final transaction data for each preset time period based on the predicted minimum operating cost; and generates an initial energy management strategy based on the predicted final transaction data. The strategy defines the amount of electricity that the multi-port energy router stores in the energy storage system, supplies to the oil pump, sells, and buys within each preset time period within the preset future time range. By making improvements at the energy scheduling level, considering and interacting with other power generation and consumption entities, and participating in the electricity spot market and responding to market demand, effective energy management is achieved, effectively improving energy utilization and reducing oilfield operating costs.

[0051] Other features and advantages of the embodiments of the present application will be described in detail in the subsequent detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] The accompanying drawings are used to provide a further understanding of the embodiments of the present application and constitute a part of the specification. Together with the following detailed description, they are used to explain the embodiments of the present application but do not constitute a limitation on the embodiments of the present application. In the accompanying drawings:

[0053] Figure 1 A schematic diagram of an application environment of an intelligent energy management method for a multi-port energy router for oil fields according to an embodiment of the present application is shown;

[0054] Figure 2 The following schematically illustrates a flow chart of an intelligent energy management method for a multi-port energy router for oil fields according to an embodiment of the present application;

[0055] Figure 3 The internal structure diagram of a computer device according to an embodiment of the present application is schematically shown. DETAILED DESCRIPTION

[0056] To make the purpose, technical solutions, and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. It should be understood that the specific implementation methods described herein are only used to illustrate and explain the embodiments of the present application and are not intended to limit the embodiments of the present application. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present application without making creative efforts are within the scope of protection of this application.

[0057] It should be noted that if the embodiments of the present application involve directional indications (such as up, down, left, right, front, back, etc.), such directional indications are only used to explain the relative position relationship, movement status, etc. between the various components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly.

[0058] In addition, if there are descriptions involving "first" and "second" in the embodiments of the present application, the descriptions of "first" and "second" are only for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of such features. In addition, the technical solutions between the various embodiments can be combined with each other, but they must be based on the ability of ordinary technicians in this field to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such a combination of technical solutions does not exist and is not within the scope of protection required by this application.

[0059] The intelligent energy management method for multi-port energy routers for oil fields provided in this application can be applied to Figure 1 In the application environment shown in the figure, Figure 1 As shown, a multi-port energy router intelligent energy management system for oil fields is provided, which may include:

[0060] The pumping unit is connected to the multi-port energy router via a first converter;

[0061] An energy storage system, connected to the multi-port energy router via a second converter, for storing the electricity converted by the photovoltaic panels;

[0062] The photovoltaic panel is connected to the multi-port energy router via a third converter and is used to generate electricity to drive a pumping unit to operate the oil field;

[0063] The multi-port energy router is connected to the power market through the fourth converter to trade electricity with the power market.

[0064] In this embodiment, it should be noted that the pumping unit, energy storage system, photovoltaic panel, and electricity market are connected to the multi-port energy router via a first converter, a second converter, a third converter, and a fourth converter, respectively. The first converter may be a DC / AC converter, and the second and third converters may be DC / DC converters. A DC / AC converter is an electronic device that converts direct current (DC) to alternating current (AC), also known as an inverter. The fourth converter may be a bidirectional DC / AC converter, a power electronic device capable of bidirectional conversion between direct current (DC) and alternating current (AC). Photovoltaic panels convert light energy into electrical energy to generate electricity. The generated electricity is converted by a third converter and then distributed by a multi-port energy router. For example, the electricity can be transmitted to the first converter for conversion by the first converter to drive a pumping unit to operate the oil field. At the same time, the electricity can be transmitted to the second converter for conversion by the second converter and then stored in the energy storage system. Alternatively, the electricity can be transmitted to the fourth converter for conversion by the fourth converter and then supplied to the electricity market. The electricity market can also supply electricity to the fourth converter for conversion by the fourth converter and then supply to the multi-port energy router, which then distributes it to the energy storage system and / or the pumping unit. It should be noted that the electricity market can refer to power generation and consumption entities such as power grids.

[0065] Figure 2 The following schematically shows a flow chart of an intelligent energy management method for a multi-port energy router for oil fields according to an embodiment of the present application. Figure 2 As shown, an embodiment of the present application provides an intelligent energy management method for a multi-port energy router for oil fields, which may include the following steps:

[0066] Step 101, determining a predicted photovoltaic power generation power of a photovoltaic panel for each preset time period within a preset future time range, and determining a predicted market clearing price of electricity for each preset time period, wherein the photovoltaic panel is used to generate electricity to drive a pump jack to operate an oil field.

[0067] In the embodiments of the present application, it should be noted that the preset future time range can be set to different time scales based on actual needs, including but not limited to one day, one week, one month, and other time scales. Each preset time period can be set based on actual needs, including but not limited to two hours. A photovoltaic panel can refer to a power generation device that converts light energy into electrical energy. It is composed of photovoltaic cells made of semiconductor materials (such as silicon) and its core principle is the photovoltaic effect. In this technical solution, photovoltaic panels serve as the power generation entity. After generating electricity, the electricity can be distributed by a multi-port energy router to drive pumping units to operate in the oil field. The market clearing price can refer to the price formed when the market supply and demand reach a balance at a specific price level. In the electricity market, this means that at a certain electricity price level, the supply and demand sides of the power system reach an agreement, and supply and demand are equal, thus achieving market supply and demand balance. Therefore, in this technical solution, taking the preset future time range as one day and each preset time period as two hours as an example, the processor can first predict the photovoltaic power generation power of the photovoltaic panel for every two hours in the future day. At the same time, the processor can predict the predicted market clearing price of electricity corresponding to every 2 hours in the next day.

[0068] In an embodiment of the present application, determining the predicted photovoltaic power generation power of the photovoltaic panel for each preset time period within a preset future time range includes: obtaining meteorological data of the oil field within the preset future time range and historical power generation data of the photovoltaic panel; and determining the predicted photovoltaic power generation power of the photovoltaic panel for each preset time period within the preset future time range based on the meteorological data and the historical power generation data.

[0069] In this embodiment, it should be noted that meteorological data may refer to meteorological data such as temperature, humidity, and light intensity. The processor may predict the predicted photovoltaic power generation of the photovoltaic panel for each preset time period within the preset future time range based on the meteorological data of the oil field within the preset future time range and the historical power generation data of the photovoltaic panel. Specifically, taking the preset future time range as the next day and each preset time period as 2 hours as an example, the processor may obtain the temperature, humidity, and light intensity of the oil field for the next day, and further predict the predicted photovoltaic power generation of the photovoltaic panel for each 2-hour period within the next day based on the temperature, humidity, and light intensity of the oil field for the next day and the historical power generation data of the photovoltaic panel. The historical power generation data of the photovoltaic panel may be selected and called according to actual needs.

[0070] In an embodiment of the present application, determining the predicted market-clearing price of electricity in each preset time period includes: obtaining historical trading electricity data, historical meteorological data, and current climate data of the oil field; and determining the predicted market-clearing price of electricity in each preset time period based on the historical trading electricity data, historical meteorological data, and current climate data.

[0071] In this embodiment, it should be noted that historical meteorological data may refer to historical meteorological data such as temperature, humidity, and light intensity, and current climate data may refer to the current season. The processor may predict the predicted market-clearing price for electricity for each preset time period within a preset future time range based on the oilfield's historical transaction power data, temperature, humidity, and light intensity, as well as the current season. Specifically, taking the preset future time range as one day and each preset time period as two hours, the processor may obtain the oilfield's historical transaction power data, temperature, humidity, and light intensity, as well as the current season, to predict the predicted market-clearing price for each two-hour period within the next day. It should be noted that socioeconomic activities and the type of the current workday (e.g., workday or weekend) may also be used as predictive factors to predict the predicted market-clearing price for each preset time period.

[0072] Step 102: Determine the predicted transaction power of the multi-port energy router in each preset time period based on the operating power of the pumping unit in each preset time period, the charge and discharge power of the energy storage system in each preset time period, the predicted photovoltaic power generation power in each preset time period, the first conversion efficiency of the first converter, the second conversion efficiency of the second converter, the third conversion efficiency of the third converter, and the fourth conversion efficiency of the fourth converter, wherein the energy storage system is used to store the power converted by the photovoltaic panels, and the pumping unit, the energy storage system, the photovoltaic panels, and the power market that trades power with the multi-port energy router are connected to the multi-port energy router via the first converter, the second converter, the third converter, and the fourth converter, respectively.

[0073] In the embodiments of the present application, it should be noted that Figure 1As shown, the pumping unit, energy storage system, photovoltaic panel, and electricity market are connected to the multi-port energy router via a first converter, a second converter, a third converter, and a fourth converter, respectively. The first converter may be a DC / AC converter, the second converter and the third converter may be DC / DC converters, and the fourth converter may be a bidirectional DC / AC converter. After predicting the predicted photovoltaic power generation of the photovoltaic panel and the predicted market clearing price of electricity for each preset time period within a preset future time range, the processor may further calculate the predicted transaction power of the multi-port energy router in each preset time period based on the predicted photovoltaic power generation of the photovoltaic panel, the operating power of the pumping unit, the charge and discharge power of the energy storage system, the first conversion efficiency of the first converter, the second conversion efficiency of the second converter, the third conversion efficiency of the third converter, and the fourth conversion efficiency of the fourth converter. Specifically, taking the preset future time range as the future day and each preset time period as 2 hours as an example, the processor can calculate the predicted trading power of the multi-port energy router every 2 hours in the future day based on the predicted photovoltaic power generation power of the photovoltaic panels every 2 hours in the future day, the working power of the oil pump, the charging and discharging power of the energy storage system, the first conversion efficiency of the first converter, the second conversion efficiency of the second converter, the third conversion efficiency of the third converter, and the fourth conversion efficiency of the fourth converter.

[0074] In the embodiment of the present application, the predicted transaction power of the multi-port energy router in each preset time period is determined according to formula (1):

[0075] (1),

[0076] in, is the predicted transaction power of the multi-port energy router in a preset time period t within a preset future time range, is the working power of the pumping unit in the preset time period t, is the charge and discharge power of the energy storage system in the preset time period t, is the predicted photovoltaic power generation power of the photovoltaic panel in the preset time period t, is the fourth conversion efficiency, is the first conversion efficiency, is the second conversion efficiency, is the third conversion efficiency.

[0077] In this embodiment, it should be noted that the operating power of the pumping unit and the charge and discharge power of the energy storage system can be set according to the specification information and requirements, and the first conversion efficiency, the second conversion efficiency, the third conversion efficiency and the fourth conversion efficiency can be determined according to the specification information of the corresponding converter. When it is positive, it means that the multi-port energy router buys electricity from the power market. When is a negative value, it means that the multi-port energy router sells electricity to the power market. When it is a positive value, it means that the energy storage system is currently charging, that is, the electricity converted by the photovoltaic panel can be stored. When it is a negative value, it indicates that the energy storage system is currently discharging, that is, the stored electricity can be supplied to the pumping unit to drive the pumping unit to operate the oil field, and / or the stored electricity can be supplied to the multi-port energy router to be traded to the electricity market through the multi-port energy router. According to the above formula (1), the processor can calculate the predicted transaction electricity of the multi-port energy router for each preset time period within the preset future time range.

[0078] In an embodiment of the present application, the operating power of the oil pump satisfies a first power constraint condition, wherein the first power constraint condition defines that the total operating power of the oil pump within a preset future time range meets the total production demand of the oil field within the preset future time range, and the operating power of the oil pump in each preset time period does not exceed the power threshold of the oil pump.

[0079] In this embodiment, it should be noted that due to the limitation of the operating power of the pumping unit and in order to meet the production demand of the oil field the next day, a first power constraint condition of the operating power of the pumping unit is set. Therefore, the pumping unit should meet the second power constraint condition. Specifically, the first power constraint condition defines that the total operating power of the pumping unit within a preset future time range meets the total production demand of the oil field within the preset future time range, and the operating power of the pumping unit in each preset time period does not exceed the power threshold of the pumping unit. Taking the preset future time range as the next day and each preset time period as 2 hours as an example, the total operating power of the pumping unit in the next day should meet the total production demand of the oil field in the next day. At the same time, the operating power of the pumping unit in every 2 hours in the next day should be less than or equal to the power threshold of the pumping unit, that is, the rated maximum power.

[0080] In the embodiment of the present application, the first power constraint condition is as shown in formula (2):

[0081] (2),

[0082] in, is the total operating power of the pumping unit within the preset future time range, is the total production demand of the oil field within a preset future time range, is the power threshold of the pumping unit, N is the preset future time range, is the working power of the pumping unit in each preset time period.

[0083] In this embodiment, it should be noted that the operating power of the pumping unit should satisfy the first power constraint condition set by the above formula (2).

[0084] In an embodiment of the present application, the charge and discharge power of the energy storage system satisfies a charge and discharge power constraint condition, wherein the charge and discharge power constraint condition defines that the charge and discharge power of the energy storage system in each preset time period within a preset future time range does not exceed a charge and discharge power threshold of the energy storage system; and / or the state of charge of the energy storage system satisfies a first charge constraint condition, wherein the first charge constraint condition defines that the difference between a first charge amount and a second charge amount of the energy storage system is greater than or equal to a first preset difference amount and less than or equal to a second preset difference amount, and the charge amount of the energy storage system in each preset time period is greater than or equal to a first value amount and less than or equal to a second value amount, the first charge amount is the charge amount corresponding to the energy storage system at the end time of the preset future time range, and the second charge amount is the charge amount corresponding to the energy storage system at the start time of the preset future time range.

[0085] In this embodiment, it should be noted that due to the port power limitation of the multi-port energy router, the energy storage system's charge and discharge power constraint is set. Therefore, the energy storage system must meet the charge and discharge power constraint. Specifically, the charge and discharge power constraint defines that the charge and discharge power of the energy storage system in each preset time period within a preset future time range does not exceed the charge and discharge power threshold of the energy storage system. Specifically, it can be shown as the following formula:

[0086]

[0087] in, is the maximum discharge power, is the maximum charging power, It is the charge and discharge power of the energy storage system in each preset time period within a preset future time range.

[0088] It should be noted that to ensure the recycling of the energy storage system and prevent it from overcharging or over-discharging, a first charge constraint condition is set for the energy storage system. Therefore, the charge state of the energy storage system satisfies the first charge constraint condition. Specifically, the first charge constraint condition defines that the difference between the first and second charges of the energy storage system is greater than or equal to the first preset difference and less than or equal to the second preset difference, and the charge of the energy storage system in each preset time period is greater than or equal to the first value and less than or equal to the second value. The first charge is the charge of the energy storage system at the end time of the preset future time range, and the second charge is the charge of the energy storage system at the start time of the preset future time range. Specifically, taking the preset future time range as one day in the future and each preset time period as two hours as an example, the difference between the charge of the energy storage system at the end time and the start time of the future day should be greater than or equal to the first preset difference and less than or equal to the second preset difference. At the same time, the charge of the energy storage system every two hours in the future day should be greater than or equal to the first value and less than or equal to the second value. Among them, the preset difference, the first value and the second value can be set according to needs. For example, the preset difference can include but is not limited to being set to 10%, the first value can include but is not limited to being set to 5%, and the second value can include but is not limited to being set to 95%.

[0089] In the embodiment of the present application, the first charge constraint condition is shown in formula (3):

[0090] (3),

[0091] in, is the first value, is the second value, is the charge of the energy storage system in a preset time period t within a preset future time range, is the first preset difference, is the second preset difference, is the second charge, is the first charge, is the charge of the energy storage system in the previous preset time period of the preset time period t within the preset future time range, For the preset time interval, is the charging efficiency of the energy storage system, is the discharge efficiency of the energy storage system, is the rated capacity of the energy storage system, N is the preset future time range, and is the actual charging and discharging power of the energy storage system in the preset time period t, is the second conversion efficiency.

[0092] In this embodiment, it should be noted that the charge of the energy storage system should satisfy the first charge constraint condition set by the above formula (3). It is a preset time interval, which can be set according to actual needs, for example, including but not limited to being set to 15 minutes.

[0093] Step 103 : determining the predicted minimum operating cost of the multi-port energy router based on the predicted market clearing price and the predicted transaction power in each time period.

[0094] In an embodiment of the present application, it should be noted that after obtaining the predicted market clearing price of electricity in each preset time period within a preset future time range and the predicted trading electricity of the multi-port energy router, the processor can further calculate the predicted minimum operating cost of the multi-port energy router based on the predicted market clearing price and predicted trading electricity in each time period.

[0095] In the embodiment of the present application, the predicted minimum operating cost is determined according to formula (4):

[0096] (4),

[0097] in, To predict the minimum operating cost, is the predicted transaction power of the multi-port energy router in a preset time period t within a preset future time range, is the predicted market clearing price of electricity in the preset time period t, and N is the preset future time range.

[0098] In this embodiment, it should be noted that when When it is positive, it means that the multi-port energy router buys electricity from the power market. When is negative, it means that the multi-port energy router sells electricity to the power market. When it is a negative value, it means that the predicted minimum operating cost is lower. When it is a positive value, it means that the predicted minimum operating cost is higher. This technical solution aims to minimize the predicted minimum operating cost, so it should be The smaller the value.

[0099] Step 104 : Determine predicted final transaction data of the multi-port energy router in each preset time period based on the predicted minimum operating cost.

[0100] In the embodiment of the present application, it should be noted that after calculating the predicted minimum operating cost of the multi-port energy router, with the goal of minimizing the predicted minimum operating cost, the predicted final transaction data of the multi-port energy router in each preset time period can be further determined based on the predicted minimum operating cost.

[0101] Step 105: Generate an initial energy management strategy based on the predicted final transaction data, where the initial energy management strategy defines the amount of electricity stored in the energy storage system, the amount of electricity supplied to the pumping units, the amount of electricity sold, and the amount of electricity purchased by the multi-port energy router in each preset time period within a preset future time range.

[0102] In the embodiments of the present application, it should be noted that, after obtaining the predicted final transaction data for the multi-port energy router within each preset time period, the processor may further generate an initial energy management strategy based on the predicted final transaction data, i.e., define the amount of electricity that the multi-port energy router should store in the energy storage system, supply to the oil pumping units, sell to, and purchase from the energy storage system, within each preset time period within a preset future time range. Specifically, taking the preset future time range as one day and each preset time period as two hours as an example, the generated initial energy management strategy may define the amount of electricity that the multi-port energy router should store in the energy storage system, supply to the oil pumping units, sell to the electricity market, and purchase from the electricity market every two hours within the next day.

[0103] The above technical solution determines the predicted photovoltaic power generation and the predicted market-clearing price of electricity for each preset time period within a preset future time range; determines the predicted transaction volume for each preset time period based on the operating power of the oil pump, the charge and discharge power of the energy storage system, the predicted photovoltaic power generation of the photovoltaic panel, and the first, second, third, and fourth conversion efficiencies within each preset time period; determines the predicted minimum operating cost based on the predicted market-clearing price and the predicted transaction volume; determines the predicted final transaction data for each preset time period based on the predicted minimum operating cost; and generates an initial energy management strategy based on the predicted final transaction data. The strategy defines the amount of electricity that the multi-port energy router stores in the energy storage system, supplies to the oil pump, sells, and buys within each preset time period within the preset future time range. By making improvements at the energy scheduling level, considering and interacting with other power generation and consumption entities, and participating in the electricity spot market and responding to market demand, effective energy management is achieved, effectively improving energy utilization and reducing oilfield operating costs.

[0104] In an embodiment of the present application, the method further includes: in the process of executing energy management operations according to the initial energy management strategy, obtaining the actual photovoltaic power generation power of the photovoltaic panel in the current time period, the actual charge and discharge power of the energy storage system in the current time period, the actual operating power of the pumping unit in the current time period, and the actual market clearing price of electricity in the next preset time period; determining the actual transaction power difference of the multi-port energy router in the next preset time period based on the actual photovoltaic power generation power, the actual charge and discharge power of the energy storage system, the actual operating power of the pumping unit, the first conversion efficiency, the second conversion efficiency, the third conversion efficiency, the fourth conversion efficiency, and the predicted transaction power; predicting the minimum additional operating cost of the multi-port energy router based on the actual transaction power difference in the next preset time period and the actual market clearing price of electricity; updating the predicted final transaction data of the multi-port energy router in the next preset time period based on the minimum additional operating cost; and adjusting the energy management strategy for the next preset time period according to the updated predicted final transaction data, so that the energy management operation corresponding to the adjusted energy management strategy is performed when the next preset time period is reached.

[0105] In the embodiment of the present application, it should be noted that, in the process of executing energy management operations according to the initial energy management strategy, the processor can obtain the actual photovoltaic power generation power of the photovoltaic panels, the actual charging and discharging power of the energy storage system, and the actual working power of the oil pump in the current time period according to the actual cloud operation situation, and can also obtain the actual market clearing price of electricity in the next preset time period. Specifically, the electricity market usually performs rolling clearing at shorter time intervals, rolling clearing information such as the price and output curve of electricity in the future time period. For example, the price and output curve of electricity in the next 2 hours can be rolled cleared in a cycle of 15 minutes. Therefore, the actual market clearing price of electricity in the next preset time period can be obtained by reading the rolling price.

[0106] Furthermore, the processor can calculate the actual transaction power difference of the multi-port energy router within the next preset time period based on the acquired actual photovoltaic power generation power, the actual charge and discharge power of the energy storage system, the actual operating power of the oil pumping unit, the first conversion efficiency, the second conversion efficiency, the third conversion efficiency, the fourth conversion efficiency, and the predicted transaction power. Specifically, taking the preset time period of 2 hours as an example, the processor can calculate the actual transaction power difference of the multi-port energy router within the next 2 hours based on the actual photovoltaic power generation power of the current photovoltaic panel, the actual charge and discharge power of the energy storage system, the actual operating power of the oil pumping unit, the first conversion efficiency, the second conversion efficiency, the third conversion efficiency, and the fourth conversion efficiency.

[0107] Furthermore, after calculating the actual transaction power difference within the next preset time period, the processor can predict the minimum additional operating cost of the multi-port energy router based on the calculated actual transaction power difference and the actual market clearing price of the electricity obtained. The additional operating cost can refer to the real-time changes of the multi-port energy router and the costs such as the loss of the converter. After calculating the additional minimum operating cost of the multi-port energy router, with the goal of minimizing the additional minimum operating cost, the predicted final transaction data of the multi-port energy router within the next preset time period can be further determined based on the additional minimum operating cost, and the energy management strategy for the next preset time period can be adjusted according to the updated predicted final transaction data, so that the energy management operation corresponding to the adjusted energy management strategy is executed when the next preset time period is reached. In this way, the energy management strategy for the future preset time period is optimized according to the changes in the real-time electricity market, the transaction power is adjusted in real time, and the energy utilization rate is effectively improved and the operating cost is effectively reduced.

[0108] In the embodiment of the present application, the actual transaction power difference of the multi-port energy router in the next preset time period is determined according to formula (5):

[0109] (5),

[0110] in, is the actual transaction power difference of the multi-port energy router within the preset time period t, is the actual transaction power of the multi-port energy router within the preset time period t, is the predicted transaction power in the preset time period t, and is the actual working power of the pumping unit in the preset time period t, and is the actual charging and discharging power of the energy storage system in the preset time period t, and is the actual photovoltaic power generation power of the photovoltaic panel in the preset time period t, is the fourth conversion efficiency, is the first conversion efficiency, is the second conversion efficiency, is the third conversion efficiency, is a constant, The next preset time period.

[0111] In the embodiment of the present application, it should be noted that the processor can calculate the actual transaction power difference of the multi-port energy router in the next preset time period based on the actual photovoltaic power generation power, the actual charge and discharge power of the energy storage system, the actual working power of the oil pump, the first conversion efficiency, the second conversion efficiency, the third conversion efficiency, the fourth conversion efficiency and the predicted transaction power. Specifically, the processor can first calculate the actual transaction power of the multi-port energy router in the next preset time period based on the above formula (5) based on the actual photovoltaic power generation power, the actual charge and discharge power of the energy storage system, the actual working power of the oil pump, the first conversion efficiency, the second conversion efficiency, the third conversion efficiency and the fourth conversion efficiency. Wherein, when When it is positive, it means that the multi-port energy router buys electricity from the power market. When it is a negative value, it means that the multi-port energy router sells electricity to the power market. Then, according to the above formula (5), based on the difference between the calculated actual transaction power of the multi-port energy router in the next preset time period and the predicted transaction power in each preset time period, the actual transaction power difference of the multi-port energy router in the next preset time period is calculated. Specifically, taking the preset time period of 2 hours as an example, the actual transaction power of the multi-port energy router in the next 2 hours can be calculated according to the above formula (5). According to the difference between the actual transaction power in the next 2 hours and the predicted transaction power, the actual transaction power difference of the multi-port energy router in the next 2 hours can be obtained.

[0112] It should be noted that when When it is positive, the energy storage system is charged, and vice versa.

[0113] In an embodiment of the present application, the actual working power of the oil pump satisfies the second power constraint condition, which defines that the total working power of the oil pump within a preset future time range must meet the total production demand of the oil field within the preset future time range, and the actual working power of the oil pump in each preset time period does not exceed the power threshold; wherein, the total working power includes a first working power, a second working power and a third working power, the first working power is the total actual working power of the oil pump within the starting moment of the preset future time range to the current preset time period, the second working power is the predicted working power of the oil pump in the next preset time period, and the third working power is the predicted total working power of the oil pump from the end moment of the next preset time period to the end moment of the preset future time range.

[0114] In the embodiment of the present application, it should be noted that, since a second power constraint condition for the operating power of the oil pump is set in order to meet the current total production demand of the oil field, the oil pump should meet the second power constraint condition. Specifically, the second power constraint condition defines that the total operating power of the oil pump within a preset future time range must meet the total production demand of the oil field within a preset future time range, and the operating power of the oil pump in each preset time period does not exceed the power threshold of the oil pump. Among them, the total operating power should include a first operating power, a second operating power and a third operating power. The first operating power is the total actual operating power of the oil pump within the preset future time range to the current preset time period, the second operating power is the predicted operating power of the oil pump in the next preset time period, and the third operating power is the predicted total operating power of the oil pump from the end moment of the next preset time period to the end moment of the preset future time range. Specifically, taking the current time range as the current day and each preset time period as 2 hours as an example, the total operating power of the pumping unit during the current day should meet the total production demand of the oil field during the current day. At the same time, the operating power of the pumping unit in every 2 hours of the current day should be less than or equal to the power threshold of the pumping unit, that is, the rated maximum power. The total operating power should include a first operating power, a second operating power, and a third operating power. The first operating power is the total actual operating power of the pumping unit from the start of the current day to the current 2 hours. The second operating power is the predicted operating power of the pumping unit in the next 2 hours. The third operating power is the predicted total operating power of the pumping unit from the end of the next 2 hours to the end of the current day.

[0115] In the embodiment of the present application, the second power constraint condition is as shown in formula (6):

[0116] (6),

[0117] in, is the first working power, is the second working power, is the third working power, is the total working power, is the power threshold of the pumping unit, It is the actual working power of the pumping unit in each preset time period.

[0118] In the embodiment of the present application, it should be noted that the operating power of the pumping unit should satisfy the second power constraint condition set by the above formula (6).

[0119] In an embodiment of the present application, the state of charge of the energy storage system satisfies a second charge constraint condition, wherein the second charge constraint condition defines that the difference between the third charge and the fourth charge of the energy storage system is greater than or equal to the first preset difference and less than or equal to the second preset difference, the third charge is the predicted charge corresponding to the end time of the next preset time period of the energy storage system under the execution of the updated energy management strategy, and the fourth charge is the predicted charge corresponding to the end time of the next preset time period of the energy storage system under the execution of the initial energy management strategy.

[0120] In the embodiment of the present application, it should be noted that, in order to coordinate the current global energy management strategy and the real-time local energy management strategy, a second charge constraint condition is set for the energy storage system. Therefore, the charge state of the energy storage system satisfies the second charge constraint condition. Specifically, the second charge constraint condition defines that the difference between the third charge and the fourth charge of the energy storage system is greater than or equal to the first preset difference and less than or equal to the second preset difference. The third charge is the predicted charge of the energy storage system at the end of the next preset time period under the updated energy management strategy, and the fourth charge is the predicted charge of the energy storage system at the end of the next preset time period under the initial energy management strategy. Specifically, taking the current time range as one day and each preset time period as two hours, the difference between the predicted charge of the energy storage system at the end of the next two hours under the updated energy management strategy on the current day, i.e., the third charge, and the predicted charge of the energy storage system at the end of the next two hours under the initial energy management strategy, i.e., the fourth charge, should be greater than or equal to the first preset difference and less than or equal to the second preset difference. The preset difference can be set according to actual needs, for example, including but not limited to setting the preset difference to 10%. Specifically, it can be shown as the following formula:

[0121]

[0122] in, is the fourth charge, is the third charge.

[0123] In the embodiment of the present application, the minimum additional operating cost is determined according to formula (7):

[0124] (7),

[0125] in, Minimum additional operating costs, is the actual transaction power difference of the multi-port energy router within the preset time period t, is the actual market clearing price of electricity in the preset time period t, The next preset time period.

[0126] In the embodiment of the present application, it should be noted that after calculating the actual transaction power difference of the multi-port energy router in the next preset time period, the processor can further calculate the minimum additional operating cost of the multi-port energy router in the next preset time period based on the actual transaction power difference and the actual market clearing price according to the above formula (7). Specifically, taking the preset time period of 2 hours as an example, since the rolling price can be obtained at intervals of 15 minutes to obtain the market clearing price of electricity in the next 2 hours. Therefore, the next 2 hours can be divided into 8 intervals at intervals of 15 minutes, that is, it can be set The value of is 7. The processor can calculate the minimum additional operating cost of the multi-port energy router in the next 2 hours according to the above formula (7).

[0127] This technical solution, by formulating an initial energy management strategy for the future time scale, makes improvements at the energy scheduling level, considers and interacts with other power generation and consumption entities, and simultaneously participates in the electricity spot market and responds to market demand. It optimizes the initial energy management strategy according to market changes, thus achieving effective energy management, effectively improving energy utilization and reducing oilfield operating costs.

[0128] The embodiment of the present application provides a multi-port energy router intelligent energy management device for oil fields, comprising:

[0129] a memory configured to store instructions;

[0130] The processor is configured to call the instructions from the memory and implement the above-mentioned intelligent energy management method for the oil field-oriented multi-port energy router when executing the instructions.

[0131] An embodiment of the present application provides a machine-readable storage medium having instructions stored thereon. When the instructions are executed by a processor, the processor is configured to execute the above-mentioned intelligent energy management method for a multi-port energy router for oil fields.

[0132] An embodiment of the present application provides a computer program product, including a computer program, which, when executed by a controller, implements the above-mentioned intelligent energy management method for a multi-port energy router for oil fields.

[0133] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 3As shown. The computer device includes a processor A01, a network interface A02, a memory (not shown in the figure) and a database (not shown in the figure) connected via a system bus. Among them, the processor A01 of the computer device is used to provide computing and control capabilities. The memory of the computer device includes an internal memory A03 and a non-volatile storage medium A04. The non-volatile storage medium A04 stores an operating system B01, a computer program B02 and a database (not shown in the figure). The internal memory A03 provides an environment for the operation of the operating system B01 and the computer program B02 in the non-volatile storage medium A04. The database of the computer device is used to store data of an intelligent energy management method for a multi-port energy router for oil fields. The network interface A02 of the computer device is used to communicate with an external terminal through a network connection. When the computer program B02 is executed by the processor A01, it implements an intelligent energy management method for a multi-port energy router for oil fields.

[0134] Those skilled in the art will understand that Figure 3 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0135] An embodiment of the present application provides a device, which includes a processor, a memory, and a program stored in the memory and executable on the processor. When the processor executes the program, the steps of the intelligent energy management method for a multi-port energy router for oil fields are implemented.

[0136] The present application also provides a computer program product, which, when executed on a data processing device, is suitable for executing the program steps of the method for initializing the intelligent energy management of a multi-port energy router for oil fields.

[0137] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0138] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0139] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0140] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0141] In a typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0142] Memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.

[0143] Computer-readable media includes permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. The information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices, or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory computer-readable media (transitory media), such as modulated data signals and carrier waves.

[0144] It should also be noted that the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, commodity, or apparatus that includes a series of elements includes not only those elements but also other elements not explicitly listed, or includes elements inherent to such process, method, commodity, or apparatus. In the absence of further limitations, an element defined by the phrase "comprises a..." does not exclude the presence of other identical elements in the process, method, commodity, or apparatus that includes the element.

[0145] The above are merely embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various modifications and variations. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application should be included within the scope of the claims of the present application.

Claims

1. An intelligent energy management method for a multi-port energy router for oil fields, characterized in that: The method comprises: determining a predicted photovoltaic power generation power of the photovoltaic panel for each predetermined time period within a predetermined future time range, and determining a predicted market clearing price of electricity for each predetermined time period, wherein the photovoltaic panel is used to generate electricity to drive a pump jack to operate an oil field; Determine the predicted transaction power of the multi-port energy router in each preset time period according to the working power of the pumping unit in each preset time period, the charge and discharge power of the energy storage system in each preset time period, the predicted photovoltaic power generation power of the photovoltaic panel in each preset time period, the first conversion efficiency of the first converter, the second conversion efficiency of the second converter, the third conversion efficiency of the third converter, and the fourth conversion efficiency of the fourth converter, wherein the energy storage system is used to store the power converted by the photovoltaic panel, and the pumping unit, the energy storage system, the photovoltaic panel, and the power market that trades power with the multi-port energy router are connected to the multi-port energy router through the first converter, the second converter, the third converter, and the fourth converter, respectively; Determining a predicted minimum operating cost of the multi-port energy router based on the predicted market clearing price and the predicted transaction power in each time period; determining predicted final transaction data of the multi-port energy router in each preset time period based on the predicted minimum operating cost; generating an initial energy management strategy based on the predicted final transaction data, wherein the initial energy management strategy defines the amount of electricity stored in the energy storage system, the amount of electricity supplied to the pumping unit, the amount of electricity sold, and the amount of electricity purchased by the multi-port energy router in each preset time period within the preset future time range; The method determines the predicted transaction power of the multi-port energy router in each preset time period according to formula (1): （1）, in, is the predicted transaction power of the multi-port energy router in the preset time period t within the preset future time range, is the working power of the pumping unit in the preset time period t, is the charge and discharge power of the energy storage system in the preset time period t, is the predicted photovoltaic power generation of the photovoltaic panel in the preset time period t, is the fourth conversion efficiency, is the first conversion efficiency, is the second conversion efficiency, is the third conversion efficiency; The operating power of the oil pumping unit satisfies a first power constraint condition, wherein the first power constraint condition defines that the total operating power of the oil pumping unit within the preset future time range satisfies the total production demand of the oil field within the preset future time range, and the operating power of the oil pumping unit in each preset time period does not exceed a power threshold value of the oil pumping unit; The first power constraint condition is shown in formula (2): （2）, in, is the total operating power of the pumping unit within the preset future time range, is the total production demand of the oil field within a preset future time range, is the power threshold of the pumping unit, N is the preset future time range, is the working power of the pumping unit in each preset time period; The method determines the predicted minimum operating cost according to formula (4): （4）, in, To predict the minimum operating cost, is the predicted transaction power of the multi-port energy router in the preset time period t within the preset future time range, is the predicted market clearing price of electricity in the preset time period t, and N is the preset future time range.

2. The intelligent energy management method for a multi-port energy router for oil fields according to claim 1 is characterized in that: The charge and discharge power of the energy storage system satisfies a charge and discharge power constraint condition, wherein the charge and discharge power constraint condition defines that the charge and discharge power of the energy storage system in each preset time period within the preset future time range does not exceed a charge and discharge power threshold of the energy storage system; And / or the state of charge of the energy storage system satisfies a first charge constraint condition, wherein the first charge constraint condition defines that the difference between the first charge and the second charge of the energy storage system is greater than or equal to a first preset difference and less than or equal to a second preset difference, and the charge of the energy storage system in each preset time period is greater than or equal to a first value and less than or equal to a second value, the first charge is the charge of the energy storage system corresponding to the end time of the preset future time range, and the second charge is the charge of the energy storage system corresponding to the start time of the preset future time range.

3. The intelligent energy management method for a multi-port energy router for oil fields according to claim 2 is characterized in that: The first charge constraint condition is shown in formula (3): （3）, in, is the first value, is the second value, is the charge of the energy storage system in a preset time period t within a preset future time range, is the first preset difference, is the second preset difference, is the second charge, is the first charge, is the charge of the energy storage system in the previous preset time period of the preset time period t within the preset future time range, For the preset time interval, is the charging efficiency of the energy storage system, is the discharge efficiency of the energy storage system, is the rated capacity of the energy storage system, N is the preset future time range, and is the actual charging and discharging power of the energy storage system in the preset time period t, is the second conversion efficiency.

4. The intelligent energy management method for a multi-port energy router for oil fields according to claim 1 is characterized in that: Determining the predicted photovoltaic power generation of the photovoltaic panel for each preset time period within a preset future time range includes: Obtaining meteorological data of the oil field within a preset future time range and historical power generation data of the photovoltaic panels; The predicted photovoltaic power generation power of the photovoltaic panel in each preset time period within the preset future time range is determined according to the meteorological data and the historical power generation data.

5. The intelligent energy management method for a multi-port energy router for oil fields according to claim 1 is characterized in that: Determining the predicted market clearing price of electricity in each of the preset time periods includes: Obtaining historical transaction electricity data, historical meteorological data, and current climate data for the oil field; The predicted market clearing price of electricity in each preset time period is determined based on the historical transaction power data, the historical meteorological data and the current climate data.

6. The intelligent energy management method for a multi-port energy router for oil fields according to claim 1 is characterized in that: The method further comprises: During the execution of energy management operations according to the initial energy management strategy, the actual photovoltaic power generation of the photovoltaic panel in the current time period, the actual charge and discharge power of the energy storage system in the current time period, the actual operating power of the pumping unit in the current time period, and the actual market clearing price of electricity in the next preset time period are obtained; Determine the actual transaction power difference of the multi-port energy router within the next preset time period based on the actual photovoltaic power generation power, the actual charge and discharge power of the energy storage system, the actual working power of the oil pumping unit, the first conversion efficiency, the second conversion efficiency, the third conversion efficiency, the fourth conversion efficiency, and the predicted transaction power; Predicting the minimum additional operating cost of the multi-port energy router based on the difference in actual transaction power within the next preset time period and the actual market clearing price of electricity; updating the predicted final transaction data of the multi-port energy router within the next preset time period based on the minimum additional operating cost; The energy management strategy for the next preset time period is adjusted according to the updated predicted final transaction data, so that the energy management operation corresponding to the adjusted energy management strategy is performed when the next preset time period is reached.

7. The intelligent energy management method for a multi-port energy router for oil fields according to claim 6 is characterized in that: The actual transaction power difference of the multi-port energy router in the next preset time period is determined according to formula (5): （5）, in, is the actual transaction power difference of the multi-port energy router within the preset time period t, is the actual transaction power of the multi-port energy router within the preset time period t, is the predicted transaction power in the preset time period t, and is the actual working power of the pumping unit in the preset time period t, and is the actual charging and discharging power of the energy storage system in the preset time period t, and is the actual photovoltaic power generation power of the photovoltaic panel in the preset time period t, is the fourth conversion efficiency, is the first conversion efficiency, is the second conversion efficiency, is the third conversion efficiency, is a constant, The next preset time period.

8. The intelligent energy management method for a multi-port energy router for oil fields according to claim 7 is characterized in that: The actual operating power of the pumping unit satisfies a second power constraint condition, wherein the second power constraint condition defines that the total operating power of the pumping unit within the preset future time range must meet the total production demand of the oil field within the preset future time range, and the actual operating power of the pumping unit in each preset time period does not exceed a power threshold; Among them, the total working power includes a first working power, a second working power and a third working power. The first working power is the total actual working power of the oil pump from the starting moment of the preset future time range to the current preset time period. The second working power is the predicted working power of the oil pump in the next preset time period. The third working power is the predicted total working power of the oil pump from the end moment of the next preset time period to the end moment of the preset future time range.

9. The intelligent energy management method for a multi-port energy router for oil fields according to claim 8, characterized in that: The second power constraint condition is shown in formula (6): （6）, in, is the first working power, is the second operating power, is the third operating power, is the total operating power, is the power threshold of the pumping unit, It is the actual working power of the pumping unit in each preset time period.

10. The intelligent energy management method for a multi-port energy router for oil fields according to claim 8, characterized in that: The state of charge of the energy storage system satisfies a second charge constraint condition, wherein the second charge constraint condition defines that the difference between the third charge and the fourth charge of the energy storage system is greater than or equal to the first preset difference and less than or equal to the second preset difference. The third charge is the predicted charge of the energy storage system at the end of the next preset time period under the updated energy management strategy, and the fourth charge is the predicted charge of the energy storage system at the end of the next preset time period under the initial energy management strategy.

11. The intelligent energy management method for a multi-port energy router for oil fields according to claim 6, characterized in that: The minimum additional operating cost is determined according to formula (7): （7）, in, Minimize additional operating costs, is the actual transaction power difference of the multi-port energy router within the preset time period t, is the actual market clearing price of electricity in the preset time period t, The next preset time period.

12. An intelligent energy management device for a multi-port energy router for oil fields, characterized in that: include: a memory configured to store instructions; The processor is configured to call the instructions from the memory and implement the intelligent energy management method of the multi-port energy router for oil fields according to any one of claims 1 to 11 when executing the instructions.

13. A multi-port energy router intelligent energy management system for oil fields, characterized by: include: The pumping unit is connected to the multi-port energy router via a first converter; an energy storage system connected to the multi-port energy router via a second converter, and configured to store the electricity converted by the photovoltaic panel; The photovoltaic panel is connected to the multi-port energy router via a third converter, and is used to generate electricity to drive the pumping unit to operate the oil field; The multi-port energy router is connected to the power market via a fourth converter to trade electricity with the power market; The multi-port energy router intelligent energy management device for oil fields according to claim 12.

14. A machine-readable storage medium having instructions stored thereon, characterized in that: When the instruction is executed by a processor, the processor is configured to execute the intelligent energy management method for a multi-port energy router for oil fields according to any one of claims 1 to 11.

15. A computer program product, characterized in that The invention comprises a computer program, which, when executed by a controller, implements the intelligent energy management method of a multi-port energy router for oil fields according to any one of claims 1 to 11.

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