Operation scheduling method of liquefied natural gas receiving station and computer device

Abstract

The invention discloses an operation scheduling method of a liquefied natural gas receiving station and a computer device. The operation scheduling method comprises the following steps: obtaining operation data of a plurality of target key devices of the liquefied natural gas receiving station; according to the operation data, establishing a target electricity charge prediction model by using a target regression algorithm; a target optimization scheduling model adopting a first target function and a target constraint condition is established according to the target electricity charge prediction model, and the first target function is used for minimizing the total electricity charge on the premise that the gasification output load requirement within the target duration is met; according to the target constraint condition, solving the first target function by using a target optimization algorithm to obtain a target operation scheduling scheme within the target duration; and performing operation scheduling on each target key device according to the target operation scheduling scheme. Therefore, the energy consumption and the electric charge can be reduced to the greatest extent on the premise of meeting the gasification output load requirement, and an efficient, energy-saving and economical intelligent scheduling scheme is provided for the actual output operation of the receiving station.

Description

Technical Field

[0001] The present application relates to the field of energy technology, and in particular to an operation scheduling method and a computer device for a liquefied natural gas receiving station. Background Art

[0002] At present, the number of liquefied natural gas (LNG) receiving stations put into operation is increasing. How to optimize the production energy consumption of LNG receiving stations and improve operational efficiency is one of the main problems currently faced and concerned by the receiving stations.

[0003] At present, the external transmission of LNG receiving stations mainly relies on the experience of operators, and the production rhythm is adjusted by staggered electricity use to achieve the purpose of saving equipment electricity costs. However, this peak-shaving method has problems such as low efficiency, high randomness, and high dependence, resulting in high production energy consumption for external transmission operations at receiving stations. Summary of the invention

[0004] An embodiment of the present application provides an operation scheduling method for a liquefied natural gas receiving station. According to target constraints, a target optimization algorithm is used to solve the first objective function of a target optimization scheduling model to obtain a target operation scheduling plan within a target duration, so as to reduce the production energy consumption of the receiving station's external transmission operations.

[0005] In a first aspect, an operation scheduling method for a liquefied natural gas receiving station is provided, comprising: obtaining operation data corresponding to a plurality of target key equipment of the liquefied natural gas receiving station; establishing a target electricity cost prediction model based on the operation data using a target regression algorithm, wherein the target electricity cost prediction model can predict the total electricity cost of each of the target key equipment within a target duration; establishing a target optimization scheduling model using a first objective function and target constraints based on the target electricity cost prediction model, wherein the first objective function is used to minimize the total electricity cost while satisfying the gasification external transmission load requirement within the target duration; solving the first objective function using a target optimization algorithm based on the target constraints to obtain a target operation scheduling plan within the target duration; and scheduling the operation of each of the target key equipment based on the target operation scheduling plan.

[0006] In some embodiments, the target electricity fee prediction model adopts a second objective function, the target duration is one day, and the second objective function is used to determine the total electricity fee based on the power consumption and time-of-use electricity price of each target key equipment in each time period within a day, and the time period includes peak electricity consumption period, low electricity consumption period and level electricity consumption period.

[0007] In some embodiments, the second objective function is specifically:

[0008] Cost=∑C i ;

[0009] Among them, C i =∑E i ·P i , E i =∑u a E a , Cost is the total daily electricity cost, in yuan; C i is the electricity fee for each period, in yuan; P i is the time-of-use electricity price corresponding to each period, in yuan / kWh; E i is the total power consumption corresponding to each of the time periods, in kWh; a represents each of the target key equipment; u a and E a are the corresponding quantity and power consumption of each target key equipment in each period, E a The unit is kWh.

[0010] In some embodiments, the target constraint conditions include the allowed operating flow and power limit of the target key equipment in each time period, the daily total external transmission capacity constraint of the receiving station, and the pipeline pressure constraint.

[0011] The first objective function is specifically:

[0012] Cost min =min∑C i ;

[0013] The allowed operating flow and power limits of the target key equipment in each of the time periods are specifically as follows:

[0014] E a =f(Q a );

[0015] Q a ≤Q a,max ;

[0016] p a ≤p a,max ;

[0017] The daily total external transmission constraint of the receiving station is expressed as:

[0018] Q total =∑u a Q a ;

[0019] The pipeline pressure constraint is expressed as:

[0020] P min <P i <P max ;

[0021] Among them, Q a , Q a,,maxThey are the delivery volume of each target key equipment in each period and the rated flow of the equipment, in m 3 / h;p a 、p a,max are the operating power and rated power of each target key equipment in each period, in kW; f represents the function of the power consumption and the transmission volume, Q total It is the daily total gasification external transmission task, the unit is m 3 / h; P i , P max and P min They are respectively the pipeline pressure after performing the external transmission task, the maximum pipeline pressure and the minimum pipeline pressure, and the unit is Pa.

[0022] In some embodiments, operation scheduling is performed on each of the target key devices according to the target operation scheduling scheme, including: determining a target sub-scheduling scheme corresponding to each of the time periods according to the target operation scheduling scheme; in each of the time periods, operation scheduling is performed on each of the target key devices according to the target sub-scheduling scheme corresponding to the time period.

[0023] In some embodiments, each of the target sub-scheduling plans includes the amount of gas allocated in each time period, the number of key equipment started and stopped in each time period, the energy consumption of key equipment in each time period, and the optimal electricity cost economic index.

[0024] In some embodiments, the target key equipment includes a seawater pump, a high-pressure pump, and a low-pressure pump, and the operating data includes the total daily gasification output of the receiving station, the flow and power of the seawater pump, the flow and power of the high-pressure pump, and the flow and power of the low-pressure pump.

[0025] In some embodiments, after obtaining the operating data of a plurality of target key equipment of the liquefied natural gas receiving station, the method further includes: preprocessing the operating data, wherein the preprocessing includes removing outliers, filling missing values, and normalizing.

[0026] In a second aspect, a computer device is provided, comprising a processor, a memory, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the operation scheduling method of the liquefied natural gas receiving station as described in the first aspect.

[0027] In a third aspect, a computer-readable storage medium is provided, on which a computer program / instruction is stored, and when the computer program / instruction is executed by a processor, the steps of the operation scheduling method of the liquefied natural gas receiving station as described in the first aspect are implemented.

[0028] By applying the above technical solutions, the operation data of multiple target key equipment of the liquefied natural gas receiving station are obtained; based on the operation data, a target electricity cost prediction model is established using the target regression algorithm, and the target electricity cost prediction model can predict the total electricity cost of each target key equipment within the target time; based on the target electricity cost prediction model, a target optimization scheduling model using the first objective function and target constraint conditions is established, and the first objective function is used to minimize the total electricity cost under the premise of meeting the gasification external transmission load requirements within the target time; based on the target constraint conditions, the first objective function is solved using the target optimization algorithm to obtain the target operation scheduling plan within the target time; and each target key equipment is operated and scheduled according to the target operation scheduling plan. In this way, energy consumption and electricity costs can be minimized while meeting the gasification external transmission load requirements, which is better than manual experience operation, and provides an efficient, energy-saving and economical intelligent scheduling plan for the actual external transmission operation of the receiving station. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the technical solution of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0030] Figure 1 A flowchart of an operation scheduling method for a liquefied natural gas receiving station according to an embodiment of the present application;

[0031] Figure 2 A flowchart of operating and scheduling each target key device in an embodiment of the present application;

[0032] Figure 3 4 is a structural block diagram of a computer device according to an embodiment of the present application. DETAILED DESCRIPTION

[0033] Various aspects and features of the present application are described herein with reference to the accompanying drawings.

[0034] It should be understood that various modifications may be made to the embodiments of the present application. Therefore, the above description should not be considered as limiting, but only as an example of an embodiment. Other modifications within the scope and spirit of the present application will occur to those skilled in the art.

[0035] The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate embodiments of the present application and, together with the general description of the present application given above and the detailed description of the embodiments given below, serve to explain the principles of the present application.

[0036] These and other characteristics of the present application will become apparent from the following description of a preferred form of embodiment given as a non-limiting example with reference to the accompanying drawings.

[0037] It should also be understood that although the present application has been described with reference to some specific examples, those skilled in the art will be able to readily implement many other equivalent forms of the present application.

[0038] The above and other aspects, features and advantages of the present application will become more apparent in view of the following detailed description when taken in conjunction with the accompanying drawings.

[0039] Specific embodiments of the present application are described hereinafter with reference to the accompanying drawings; however, it should be understood that the embodiments applied for are merely examples of the present application, which may be implemented in a variety of ways. Well-known and / or repeated functions and structures are not described in detail to avoid unnecessary or redundant details that obscure the present application. Therefore, the specific structural and functional details applied for herein are not intended to be limiting, but merely serve as a basis and representative basis for the claims to teach those skilled in the art to use the present application in a variety of ways with substantially any suitable detailed structure.

[0040] This specification may use the phrases "in one embodiment," "in another embodiment," "in yet another embodiment," or "in other embodiments," all of which may refer to one or more of the same or different embodiments according to the present application.

[0041] The operation and scheduling method of the liquefied natural gas receiving station of the embodiment of the present application establishes a target electricity fee prediction model based on the operation data of multiple target key equipment, establishes a target optimization scheduling model using a first objective function and target constraints based on the target electricity fee prediction model, and then solves the first objective function based on the target constraints using the target optimization algorithm to obtain a target operation scheduling plan within the target duration, and finally schedules the operation of each target key equipment based on the target operation scheduling plan. In this way, energy consumption and electricity costs can be reduced to the maximum extent under the premise of meeting the gasification transmission load requirements, which is better than manual experience operation and provides an efficient, energy-saving and economical intelligent scheduling plan for the actual transmission operation of the receiving station.

[0042] like Figure 1 As shown, the following steps are included:

[0043] Step S101, obtaining operation data of multiple target key equipment of a liquefied natural gas receiving station.

[0044] In this embodiment, multiple target key equipment is equipment related to the natural gas export of the liquefied natural gas receiving station. The gasification export volume, start and stop conditions, power consumption, operating status, etc. corresponding to the multiple target key equipment in the liquefied natural gas receiving station are monitored to obtain the operating data corresponding to each target key equipment.

[0045] Step S102, based on the operation data, a target electricity cost prediction model is established using a target regression algorithm, and the target electricity cost prediction model can predict the total electricity cost of each target key equipment within a target duration.

[0046] In this embodiment, the target regression algorithm can adopt the traditional Kriging interpolation regression method, or the modern neural network model method, such as the BP neural network model. After obtaining the operation data, the target regression algorithm is used to establish a target electricity fee prediction model based on the operation data. The target electricity fee prediction model can predict the total electricity fee of each target key equipment within the target time, wherein the target time can be, for example, one day, one week, or one month, etc., and those skilled in the art can flexibly set it according to actual needs.

[0047] Step S103, establishing a target optimization scheduling model using a first objective function and target constraints based on the target electricity cost prediction model, wherein the first objective function is used to minimize the total electricity cost while satisfying the gasification transmission load requirement within the target duration.

[0048] In this embodiment, a target optimization scheduling model is established according to the target electricity fee prediction model, and the target operation scheduling plan can be determined based on the target optimization scheduling model. The target optimization scheduling model adopts a first objective function and a target constraint condition. The first objective function is used to minimize the total electricity cost of the target key equipment within the target time length under the premise of meeting the gasification external transmission load requirement within the target time length, wherein the gasification external transmission load requirement within the target time length is the target amount of natural gas transported by the liquefied natural gas receiving station within the target time length.

[0049] Step S104, according to the target constraint conditions, using the target optimization algorithm to solve the first target function to obtain the target operation scheduling plan within the target duration.

[0050] In this embodiment, according to the target constraints, the first objective function is solved using the target optimization algorithm, and the target operation scheduling plan within the target duration is obtained according to the solution result. The target operation scheduling plan can minimize the total electricity cost while meeting the gasification external transmission load requirements within the target duration.

[0051] The target optimization algorithm simulates natural phenomena to find the optimal solution, and has certain adaptability and self-learning properties. At the same time, because random factors are introduced into the algorithm, it has global search capabilities and is less likely to fall into local optimality. Optionally, the target optimization algorithm can adopt any of the algorithms including the geyser algorithm (GEA), particle swarm optimization algorithm (PSO), grey wolf optimization algorithm (GWO) and whale optimization algorithm (WOA).

[0052] Step S105: performing operation scheduling on each of the target key devices according to the target operation scheduling plan.

[0053] In this embodiment, the operation of each target key equipment is scheduled according to the target operation scheduling plan to minimize the gasification transmission energy consumption and electricity costs.

[0054] The operation and scheduling method of the liquefied natural gas receiving station of the embodiment of the present application obtains the operation data of multiple target key equipment of the liquefied natural gas receiving station; based on the operation data, a target electricity cost prediction model is established using a target regression algorithm, and the target electricity cost prediction model can predict the total electricity cost of each target key equipment within the target time; based on the target electricity cost prediction model, a target optimization scheduling model using a first objective function and a target constraint condition is established, and the first objective function is used to minimize the total electricity cost under the premise of meeting the gasification external transmission load requirements within the target time; based on the target constraint conditions, the first objective function is solved using a target optimization algorithm to obtain a target operation scheduling plan within the target time; and each target key equipment is operated and scheduled according to the target operation scheduling plan. In this way, energy consumption and electricity costs can be minimized to the maximum extent under the premise of meeting the gasification external transmission load requirements, which is better than manual experience operation, and provides an efficient, energy-saving, and economical intelligent scheduling plan for the actual external transmission operation of the receiving station.

[0055] In some embodiments of the present application, the target electricity fee prediction model adopts a second objective function, the target duration is one day, and the second objective function is used to determine the total electricity fee based on the power consumption and time-of-use electricity price of each target key equipment in each time period within a day, and the time period includes peak electricity consumption period, low electricity consumption period and level electricity consumption period.

[0056] In this embodiment, the target duration is one day, that is, from 0:00 to 24:00. Each time period in a day includes a peak power consumption period, a low power consumption period, and a flat power consumption period. The time-of-use electricity prices corresponding to each time period are different. The target electricity fee prediction model adopts a second objective function. The second objective function is used to determine the total electricity fee according to the power consumption and time-of-use electricity prices of each target key equipment in each time period in a day. Since the time-of-use electricity prices corresponding to each time period are taken into account, the target electricity fee prediction model can more accurately predict the total daily electricity fee, thereby improving the accuracy of the target electricity fee prediction model.

[0057] In some embodiments of the present application, the second objective function is specifically:

[0058] Cost=∑C i ;

[0059] Among them, C i =∑E i ·P i , E i =∑u aE a , Cost is the total daily electricity cost, in yuan; C i is the electricity fee for each period, in yuan; P i is the time-of-use electricity price corresponding to each period, in yuan / kWh; E i is the total power consumption corresponding to each of the time periods, in kWh; a represents each of the target key equipment; u a and E a are the corresponding quantity and power consumption of each target key equipment in each period, E a The unit is kWh.

[0060] In this embodiment, the total power consumption corresponding to each time period is determined by the corresponding quantity and power consumption of each target key equipment in each time period, the electricity fee for each time period is determined according to the total power consumption corresponding to each time period and the time-of-use electricity price corresponding to each time period, and the total daily electricity fee is determined according to the sum of the electricity fees for each time period, thereby achieving more accurate determination of the total daily electricity fee.

[0061] In some embodiments of the present application, the target constraint conditions include the allowed operating flow and power limit of the target key equipment in each time period, the daily total external transmission capacity constraint of the receiving station, and the pipeline pressure constraint.

[0062] The first objective function is specifically:

[0063] Cost min =min∑C i ;

[0064] The allowed operating flow and power limits of the target key equipment in each of the time periods are specifically as follows:

[0065] E a =f(Q a );

[0066] Q a ≤Q a,max ;

[0067] p a ≤p a,max ;

[0068] The daily total external transmission constraint of the receiving station is expressed as:

[0069] Q total =∑u a Q a ;

[0070] The pipeline pressure constraint is expressed as:

[0071] P min <P i <P max ;

[0072] Among them, Q a , Q a,,max They are the delivery volume of each target key equipment in each period and the rated flow of the equipment, in m 3 / h;p a 、p a,max are the operating power and rated power of each target key equipment in each period, in kW; f represents the function of the power consumption and the transmission volume, Q total It is the daily total gasification external transmission task, the unit is m 3 / h; P i , P max and P min They are respectively the pipeline pressure after performing the external transmission task, the maximum pipeline pressure and the minimum pipeline pressure, and the unit is Pa.

[0073] In this embodiment, the objective constraints of the first objective function include the allowable operating flow and power limit of the target key equipment in each time period, the daily total external transmission constraint of the receiving station, and the pipeline pressure constraint. Specifically, for the allowable operating flow and power limit of the target key equipment in each time period, it is necessary to make the transmission volume of each target key equipment in each time period not greater than the corresponding equipment rated flow, and the operating power of each target key equipment in each time period not greater than the corresponding equipment rated power. For the daily total external transmission constraint of the receiving station, it is necessary to make the sum of the transmission volume of each target key equipment in each time period equal to the daily total gasification external transmission task. For the pipeline pressure constraint, it is necessary to make the pipeline pressure after executing the external transmission task greater than the minimum pipeline pressure and less than the maximum pipeline pressure.

[0074] Through a variety of target constraints, the target optimization scheduling model can determine the optimal target operation scheduling plan under the premise of meeting the target constraints, thus ensuring the reliability of the target optimization scheduling model.

[0075] In some embodiments of the present application, the operation of each of the target key devices is scheduled according to the target operation scheduling scheme, such as Figure 2 As shown, the following steps are included:

[0076] Step S1051, determining the target sub-scheduling scheme corresponding to each of the time periods according to the target operation scheduling scheme.

[0077] In this embodiment, since each time period within the target duration includes a peak power consumption period, a valley power consumption period, and an even power consumption period, the target sub-scheduling plan corresponding to the peak power consumption period, the valley power consumption period, and the even power consumption period is determined according to the target operation scheduling plan.

[0078] Step S1052: In each of the time periods, operation scheduling is performed on each of the target key devices according to the target sub-scheduling plan corresponding to the time period.

[0079] In this embodiment, during peak power consumption periods, each target key device is operated and scheduled according to the target sub-scheduling scheme corresponding to the peak power consumption period; during valley power consumption periods, each target key device is operated and scheduled according to the target sub-scheduling scheme corresponding to the valley power consumption period; during level power consumption periods, each target key device is operated and scheduled according to the target sub-scheduling scheme corresponding to the level power consumption period.

[0080] By performing operation scheduling for each target key device according to the target sub-scheduling plan corresponding to the time period, the operation scheduling of each target key device is made more in line with the actual operation scheduling needs of each time period, thereby improving the operation scheduling accuracy of each target key device.

[0081] In some embodiments of the present application, each of the target sub-scheduling plans includes the gas volume allocated in each time period, the number of key equipment started and stopped in each time period, the energy consumption of key equipment in each time period, and the optimal electricity cost economic index.

[0082] By allocating gas volume in each time period, the number of key equipment starts and stops in each time period, the energy consumption of key equipment in each time period, and the optimal electricity cost economic indicators, the operation scheduling of each target key equipment can be achieved more accurately.

[0083] In some embodiments of the present application, the target key equipment includes a seawater pump, a high-pressure pump, and a low-pressure pump, and the operating data includes the total daily gasification output of the receiving station, the flow and power of the seawater pump, the flow and power of the high-pressure pump, and the flow and power of the low-pressure pump.

[0084] In this embodiment, natural gas needs to be cooled and condensed in the receiving station. The seawater pump extracts seawater and transports it to the cooling system, using the low temperature characteristics of seawater to remove the heat generated by natural gas during compression and liquefaction, ensuring that the temperature and pressure of natural gas are within a suitable range, and ensuring the safety and stability of the process. In addition, in the event of a fire or other emergency, the seawater pump can quickly provide a large amount of seawater for fire fighting and emergency cooling of key equipment to prevent the expansion of the accident and damage to the equipment.

[0085] In the process of natural gas transportation, in order to overcome pipeline resistance and achieve long-distance transportation, natural gas needs to be pressurized to a higher pressure. High-pressure pumps can provide sufficient pressure to allow natural gas to enter the transmission pipeline at a higher pressure, ensuring that natural gas can be stably and efficiently transported to various user terminals or storage facilities. In addition, in the natural gas liquefaction process, high-pressure pumps are one of the key equipment. It compresses the pre-treated natural gas to a high-pressure state, making it easier to liquefy natural gas at low temperatures. The high-pressure natural gas exchanges heat with the low-temperature refrigerant in the heat exchanger and is cooled below its critical temperature, thereby achieving liquefaction for easy storage and transportation.

[0086] At the entrance of the natural gas receiving station, the natural gas pressure from the pipeline or transport ship may be low. The low-pressure pump is used to initially pressurize the natural gas so that it can meet the pressure requirements of subsequent process treatment in the receiving station, such as filtration, separation and other operations. In addition, in some process links of the receiving station, such as natural gas regasification and pressure regulation, the natural gas needs to be circulated and transported between different equipment and pipelines. The low-pressure pump can provide the necessary power for these process cycles to ensure the stable flow and uniform distribution of natural gas in the system. When the natural gas is unloaded from the transport ship to the storage facility of the receiving station, the low-pressure pump can also help transport the natural gas on the ship to the pipeline and storage tank of the receiving station. When transferring natural gas between different storage facilities, the low-pressure pump can also be used to adjust the pressure and flow of natural gas to achieve smooth transfer.

[0087] By taking seawater pumps, high-pressure pumps and low-pressure pumps as target key equipment, and using the daily total gasification output of the receiving station and the flow and power of seawater pumps, high-pressure pumps and low-pressure pumps as operating data, the operating data is made more consistent with the actual situation of the liquefied natural gas receiving station, thereby improving the accuracy of the operating data.

[0088] In some embodiments of the present application, after obtaining the operating data of multiple target key equipment of the liquefied natural gas receiving station, the method further includes:

[0089] The running data is preprocessed, and the preprocessing includes removing outliers, filling missing values ​​and normalizing.

[0090] In this embodiment, the operating data may include some redundant data, abnormal values, missing data, etc. By preprocessing the operating data, the accuracy of the operating data is further improved, thereby improving the accuracy of the target electricity fee prediction model.

[0091] The present application also provides a computer device, such as Figure 3 As shown, it includes a processor, a memory and a computer program stored in the memory, and the processor executes the computer program to implement the steps of the operation scheduling method of the liquefied natural gas receiving station as described in each embodiment of the present application.

[0092] The computer device in the embodiment of the present application may be a terminal, or may be other devices other than a terminal. Exemplarily, the computer device may be a mobile phone, a tablet computer, a laptop computer, a PDA, an in-vehicle electronic device, a mobile Internet device (MID), an augmented reality (AR) / virtual reality (VR) device, a robot, a wearable device, an ultra-mobile personal computer (UMPC), a netbook or a personal digital assistant (PDA), etc. It may also be a server, a network attached storage (NAS), a personal computer (PC), a television (TV), a teller machine or a self-service machine, etc., which is not specifically limited in the embodiment of the present disclosure.

[0093] The memory may include a RAM (Random Access Memory) or a non-volatile memory, such as at least one disk memory. Optionally, the memory may also be at least one storage device located away from the aforementioned processor.

[0094] The above-mentioned processor can be a general-purpose processor, including CPU, NP (Network Processor), etc.; it can also be DSP (Digital Signal Processing), ASIC (Application Specific Integrated Circuit), FPGA (Field Programmable Gate Array) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0095] In another embodiment provided in the present application, a computer-readable storage medium is also provided, on which a computer program / instruction is stored. When the computer program / instruction is executed by a processor, the steps of the operation scheduling method of the liquefied natural gas receiving station as described in the various embodiments of the present application are implemented.

[0096] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from a website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, server or data center. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more available media integration. The available medium can be a magnetic medium, (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state hard disk), etc.

[0097] The above embodiments are only exemplary embodiments of the present application and are not intended to limit the present application. The protection scope of the present application is defined by the claims. Those skilled in the art may make various modifications or equivalent substitutions to the present application within the essence and protection scope of the present application, and such modifications or equivalent substitutions shall also be deemed to fall within the protection scope of the present application.

Claims

1. A method for operating and scheduling a liquefied natural gas receiving station, characterized in that: include: Obtain the operating data corresponding to multiple target key equipment of the LNG receiving station; According to the operation data, a target electricity fee prediction model is established by using a target regression algorithm, wherein the target electricity fee prediction model can predict the total electricity fee of each target key equipment within a target time period; Establishing a target optimization scheduling model using a first objective function and a target constraint condition according to the target electricity fee prediction model, wherein the first objective function is used to minimize the total electricity fee under the premise of satisfying the gasification external transmission load requirement within the target time; According to the target constraint conditions, the first target function is solved by using the target optimization algorithm to obtain the target operation scheduling plan within the target duration; The operation of each of the target key devices is scheduled according to the target operation scheduling plan.

2. The operation and scheduling method of a liquefied natural gas receiving station according to claim 1, characterized in that: The target electricity fee prediction model adopts a second objective function, the target duration is one day, and the second objective function is used to determine the total electricity fee based on the power consumption and time-of-use electricity price of each target key equipment in each time period within a day. The time period includes peak electricity consumption period, low electricity consumption period and level electricity consumption period.

3. The operation and scheduling method of a liquefied natural gas receiving station according to claim 2, characterized in that: The second objective function is specifically: Cost=∑C i ; Among them, C i =∑E i ·P i , E i =∑u a E a , Cost is the total daily electricity cost, in yuan; C i is the electricity fee for each period, in yuan; P i is the time-of-use electricity price corresponding to each period, in yuan / kWh; E i is the total power consumption corresponding to each of the time periods, in kWh; a represents each of the target key equipment; u a and E a are the corresponding quantity and power consumption of each target key equipment in each period, E a The unit is kWh.

4. The operation and scheduling method of a liquefied natural gas receiving station according to claim 3, characterized in that: The target constraints include the allowed operating flow and power limit of the target key equipment in each time period, the daily total external transmission capacity constraint of the receiving station, and the pipeline pressure constraint. The first objective function is specifically: Cost min =min∑C i ; The allowed operating flow and power limits of the target key equipment in each of the time periods are specifically as follows: E a =f(Q a ); Q a ≤Q a,max ; p a ≤p a,max ; The daily total external transmission constraint of the receiving station is expressed as: Q total =∑u a Q a ; The pipeline pressure constraint is expressed as: P min <P i <P max ; Among them, Q a , Q a,,max They are the delivery volume of each target key equipment in each period and the rated flow of the equipment, in m 3 / h;p a 、p a,max are the operating power and rated power of each target key equipment in each period, in kW; f represents the function of the power consumption and the transmission volume, Q total It is the daily total gasification external transmission task, the unit is m 3 / h; P i , P max and P min They are respectively the pipeline pressure after performing the external transmission task, the maximum pipeline pressure and the minimum pipeline pressure, and the unit is Pa.

5. The operation and scheduling method of a liquefied natural gas receiving station according to claim 2, characterized in that: The operation of each of the target key devices is scheduled according to the target operation scheduling plan, including: Determine the target sub-scheduling plan corresponding to each of the time periods according to the target operation scheduling plan; In each of the time periods, operation scheduling is performed on each of the target key devices according to the target sub-scheduling plan corresponding to the time period.

6. The operation and scheduling method of a liquefied natural gas receiving station according to claim 5, characterized in that: Each of the target sub-scheduling plans includes the gas volume allocated in each time period, the number of key equipment started and stopped in each time period, the energy consumption of key equipment in each time period, and the optimal electricity cost economic index.

7. The operation and scheduling method of a liquefied natural gas receiving station according to claim 1, characterized in that: The target key equipment includes a seawater pump, a high-pressure pump, and a low-pressure pump, and the operating data includes the total daily gasification output of the receiving station, the flow and power of the seawater pump, the flow and power of the high-pressure pump, and the flow and power of the low-pressure pump.

8. The operation and scheduling method of a liquefied natural gas receiving station according to claim 1, characterized in that: After obtaining the operating data of multiple target key equipment of the LNG receiving terminal, it also includes: The running data is preprocessed, and the preprocessing includes removing outliers, filling missing values ​​and normalizing.

9. A computer device comprising a processor, a memory and a computer program stored in the memory, characterized in that: The processor executes the computer program to implement the steps of the operation scheduling method of the liquefied natural gas receiving station according to any one of claims 1-8.

10. A computer-readable storage medium having a computer program / instruction stored thereon, characterized in that: When the computer program / instructions are executed by a processor, the steps of the operation scheduling method for a liquefied natural gas receiving station as described in any one of claims 1 to 8 are implemented.

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