LNG receiving station inventory optimization platform and optimization method based on Internet of Things
By optimizing LNG receiving station inventory management through IoT technology, the problems of decentralization and insufficient monitoring in traditional inventory management are solved, precise inventory balance and supply chain stability are achieved, and downstream market demand and operational benefits are met.
Patent Information
- Application Number
- CN202510783697.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-06-12
- Publication Date
- 2025-09-23
AI Technical Summary
The inventory management of traditional LNG receiving stations is decentralized and lacks monitoring, resulting in insufficient inventory information collection and management, which cannot effectively avoid inventory shortages or surpluses, affecting the stability of the supply chain and operational efficiency.
An IoT-based LNG receiving station inventory optimization platform is used to obtain basic data, perform data preprocessing, optimize inventory, and provide feedback, combining predictive and unexpected factors to adjust inventory and ensure inventory balance at the receiving station.
It achieves a precise balance of LNG receiving station inventory, avoids inventory shortages or surpluses, ensures the stability and operational efficiency of the supply chain, and takes into account the balance of interests of all investors.
Smart Images
Figure CN120688977A_ABST
Abstract
Description
Technical Field
[0001] The present invention belongs to the field of computer intelligent control technology, and in particular relates to an LNG receiving station inventory optimization platform and optimization method based on the Internet of Things. Background Art
[0002] With rising global energy consumption and growing awareness of environmental protection, liquefied natural gas (LNG), as a clean and efficient form of energy, is becoming increasingly prominent and occupying a crucial position in the global energy mix. The widespread use of LNG not only helps reduce greenhouse gas emissions but also provides flexibility and stability in energy supply. In this context, LNG receiving terminals have become an indispensable link in the entire LNG supply chain, playing a crucial role in ensuring its smooth operation. Inventory management at LNG receiving terminals, in particular, is directly linked to the stable operation of the supply chain.
[0003] LNG receiving stations, also known as transit stations in the LNG supply chain, undertake the crucial task of receiving natural gas from LNG carriers and storing or delivering it to downstream users. Only by achieving a precise balance between the unloading volume of LNG carriers and the storage capacity of LNG storage tanks can overstocking or understocking be effectively avoided. This means ensuring that the receiving station's inventory can readily meet downstream market demand while also retaining sufficient excess capacity in the storage tanks to accommodate the unloading volume of LNG carriers to ensure the normal operation of the LNG receiving station. Furthermore, to maximize the operational efficiency of the receiving station, it is important to maintain a high inventory level year-round.
[0004] Currently, traditional LNG receiving stations are mostly funded by a single user. However, with the development of society, LNG receiving stations jointly invested in and constructed by multiple parties have emerged. Each investor is allocated a certain initial inventory based on its capital investment in the receiving station. However, inventory information management is fragmented and lacks oversight. Across the entire LNG import and export planning and inventory process, data collection and management are not yet at an ideal level, posing challenges to effective inventory planning, scheduling, and tracking.
[0005] Receiving terminals have limited storage capacity and are often simultaneously handling ship arrivals and outbound shipments. Therefore, it's crucial to conduct advance calculations and assessments based on the ship arrival and outbound shipment schedules provided by each user, combined with the terminal's production and processing capabilities, to ensure a balanced storage capacity over the long term and avoid two unfavorable scenarios.
[0006] Scenario 1, which needs to be avoided, is that when the LNG carrier arrives at the receiving terminal, the storage capacity is full and the natural gas cannot be received. This situation not only makes the receiving terminal unable to fulfill its energy supply responsibilities, but also may trigger a chain reaction in the subsequent supply chain.
[0007] Situation 2 that needs to be avoided is that the next LNG tanker scheduled to arrive fails to arrive as scheduled, but one party's LNG delivery demand suddenly increases. If there is not enough inventory to meet this demand, it will affect the normal gas supply to downstream users and may even cause contract disputes or credibility issues.
[0008] Therefore, inventory management at LNG receiving terminals must consider both supply chain stability and maximizing operational efficiency, while also preventing potential risks caused by poor inventory management. This requires optimizing the receiving terminal's inventory management plan to ensure the efficient, safe, and stable operation of the entire LNG supply chain. Summary of the Invention
[0009] This invention aims to meet practical needs by providing an IoT-based LNG receiving terminal inventory optimization platform and method, aiming to avoid any inventory shortages or overstocks at receiving terminals. While ensuring that inventory levels at receiving terminals can readily meet downstream market demand, storage tanks should also have sufficient excess capacity to accommodate LNG ship unloading.
[0010] The first object of the present invention is to provide an LNG receiving station inventory optimization method based on the Internet of Things, comprising:
[0011] S1. Obtaining basic data through the Internet of Things; the basic data includes initial data of the LNG receiving station at the current moment, the LNG import and export plan data of the LNG receiving station within a preset future time, and predicted factors affecting the execution of the LNG import and export plan within the preset future time;
[0012] S2. Data preprocessing: Obtaining theoretical inventory of the LNG receiving station at the current time and within a preset future time using the initial data, the LNG input plan and LNG export plan data of the LNG receiving station within a preset future time;
[0013] S3. Inventory optimization: obtaining, based on the predicted factors, inventory adjustments that affect the execution of the LNG import plan and the LNG export plan within a preset future time period; superimposing the adjustments with the theoretical inventory to obtain an optimized inventory;
[0014] S4. Compare the optimized inventory with a preset inventory balance, and adjust the LNG import plan and LNG export plan to be executed within a preset time in the future according to the comparison result.
[0015] Preferably, the initial data is the sum of the initial inventories of all investors in the LNG receiving station at the current moment; the LNG import plan and LNG export plan data include the LNG import plan and LNG export plan data of each investor within a preset time in the future; and the predictive factors include weather and transportation route status.
[0016] Preferably, the process further includes S5, calculating storage fees and selecting a window conflict period; wherein:
[0017] The storage fee calculation is based on the user's short-lift volume. The LNG receiving station is invested by multiple parties. If the actual amount of LNG picked up by the user of the LNG receiving station on any pick-up day during the service period is less than 95% of the specified daily pick-up volume, the short-lift volume on that pick-up day is the difference between 95% of the specified daily pick-up volume and the actual amount picked up. Normal pick-up is on D day, and storage fees are calculated starting from D+2. Short-lift volumes need to be deducted. On any pick-up day, if the actual amount of LNG picked up by the user of the LNG receiving station exceeds 95% of the specified daily pick-up volume, the portion of the actual amount picked up that exceeds 95% of the specified daily pick-up volume will be deducted in priority from the short-lift volumes that occurred earlier before that pick-up day and have not been deducted.
[0018] The selection window conflict period is based on the shareholding ratio and delivery plan of each party of the LNG receiving station user, and the annual arrival window period is uniformly displayed in the system. Each LNG receiving station user can take turns in descending order of the equity ratio held to select and determine an arrival window period from the conflicting arrival windows.
[0019] Preferably, the basic data also includes sudden factors; the sudden factors include transportation interruptions caused by traffic control or natural disasters, LNG leakage caused by transportation failures, and emergency natural gas supply requirements; a mutation amount is obtained based on the sudden factors, and the mutation amount is added to the optimized inventory to obtain a secondary optimized inventory, and S4 is executed based on the secondary optimized inventory;
[0020] The natural gas emergency supply requirement refers to the amount of natural gas that receiving station users and other basic capacity users must bear in order to ensure the normal living and production needs of the basic people under specific circumstances. The natural gas supply amount is calculated according to the following formula:
[0021]
[0022] Among them, Q 应承担的保供气量 The gas volume that a user of a certain basic capacity should bear for guaranteed supply;
[0023] Q 保供气量The amount of natural gas (including gaseous and liquid forms) provided to meet the supply requirements of energy authorities;
[0024] S refers to the equity ratio held by the basic capacity user or its affiliates in the equity structure of the receiving station company;
[0025] ΣS' refers to the sum of the equity proportions of the receiving station company held by all basic capacity users or their affiliates who have signed a receiving station use agreement with the receiving station company.
[0026] Preferably, the limiting factors affecting the inventory balance include: the total storage capacity of the LNG receiving station, the maximum gasification capacity of the LNG receiving station, the maximum loading capacity of the LNG receiving station, the maximum ship receiving capacity of the LNG receiving station, the total initial inventory of the LNG receiving station, the initial inventory of each investor, the maximum storage capacity for safe operation of the LNG receiving station, the minimum storage capacity for safe operation of the LNG receiving station, the minimum storage capacity of each investor, the basic storage capacity of each investor, and the basic storage capacity of each investor according to the proportion of shareholders.
[0027] A second object of the present invention is to provide an LNG receiving terminal inventory optimization platform based on the Internet of Things, comprising:
[0028] The LNG receiving station IoT is used to obtain basic data; the basic data includes the initial data of the LNG receiving station at the current moment, the LNG import and export plan data of the LNG receiving station within a preset time in the future, and the predicted factors that affect the execution of the LNG import and export plan within the preset time in the future;
[0029] The cloud platform receives the basic data of the LNG receiving station's IoT and performs pre-processing and optimization on the basic data. Specifically, it includes:
[0030] A data preprocessing module obtains the theoretical inventory of the LNG receiving station at the current moment and within a preset future time through the initial data, the LNG input plan and the LNG export plan data of the LNG receiving station within a preset future time;
[0031] The inventory optimization module obtains the inventory and LNG export plan adjustment amount that will affect the execution of the LNG import plan within a preset time in the future based on the predicted factors; superimposes the adjustment amount with the theoretical inventory to obtain the optimized inventory;
[0032] The result feedback module compares the optimized inventory with a preset inventory balance, and adjusts the LNG import plan and LNG export plan to be executed within a preset time in the future according to the comparison result.
[0033] Preferably, the LNG receiving station Internet of Things includes:
[0034] A sensor group that obtains basic data of the LNG receiving station;
[0035] A data collection terminal that obtains data on each investor's LNG import and export plans within a preset timeframe;
[0036] A meteorological data acquisition terminal for obtaining weather conditions along the routes during each LNG import plan and LNG export plan;
[0037] A 5G network that enables data interaction among sensor groups, data acquisition terminals, and cloud platforms.
[0038] Preferably, the sensor group includes a liquid level sensor, a temperature sensor, a pressure sensor and a density sensor installed on the LNG tank; the cloud platform includes a crawler module for crawling data related to the LNG receiving station.
[0039] Preferably, it also includes a storage fee calculation module and a window conflict period selection module; wherein:
[0040] The storage fee calculation module calculates the LNG storage fee based on the user's short-lift volume. The LNG receiving station is invested by multiple parties. When the actual amount of LNG picked up by the user of the LNG receiving station on any pick-up day during the service period is less than 95% of the specified pick-up volume on that pick-up day, the short-lift volume on that pick-up day is the difference between 95% of the specified pick-up volume on that pick-up day and the actual amount picked up. Normal pick-up is on D day, and storage fees are calculated starting from D+2 day. Short-lift volume needs to be deducted. On any pick-up day, when the actual amount of LNG picked up by the user of the LNG receiving station exceeds 95% of the specified pick-up volume on that pick-up day, the portion of the actual amount picked up that exceeds 95% of the specified pick-up volume on that day will be deducted first in the order in which the short-lift volume was generated against the undeducted short-lift volume that occurred earlier before that pick-up day.
[0041] The window conflict period selection module uniformly displays the annual arrival window period in the system according to the shareholding ratio and delivery plan of each party of the LNG receiving station user. Each LNG receiving station user can take turns to select and determine an arrival window period from the conflicting arrival windows in order of the equity ratio held from large to small.
[0042] Preferably, the initial data is the sum of the initial inventories of all investors in the LNG receiving station at the current moment; the LNG import plan and LNG export plan data include the LNG import plan and LNG export plan data of each investor within a preset time in the future;
[0043] The predictive factors include weather and transportation route status;
[0044] The basic data also includes sudden factors; the sudden factors include transportation interruptions caused by traffic control or natural disasters, LNG leaks caused by transportation failures, LNG tank leaks in LNG receiving stations, and emergency natural gas supply requirements; the inventory optimization module obtains a mutation amount based on the sudden factors, adds the mutation amount to the optimized inventory to obtain a secondary optimized inventory, and the result feedback module compares the secondary optimized inventory with the preset inventory balance, and adjusts the LNG import plan and LNG export plan to be executed within a preset time period in the future based on the comparison result;
[0045] The limiting factors affecting the inventory balance include: the total storage capacity of the LNG receiving station, the maximum gasification capacity of the LNG receiving station, the maximum loading capacity of the LNG receiving station, the maximum ship receiving capacity of the LNG receiving station, the total initial inventory of the LNG receiving station, the initial inventory of each investor, the maximum storage capacity for safe operation of the LNG receiving station, the minimum storage capacity for safe operation of the LNG receiving station, the minimum storage capacity of each investor, the basic storage capacity of each investor, and the basic storage capacity of each investor based on the proportion of shareholders;
[0046] The natural gas emergency supply requirement refers to the amount of natural gas that receiving station users and other basic capacity users must bear in order to ensure the normal living and production needs of the basic people under specific circumstances. The natural gas supply amount is calculated according to the following formula:
[0047]
[0048] Among them, Q 应承担的保供气量 The gas volume that a user of a certain basic capacity should bear for guaranteed supply;
[0049] Q 保供气量 The amount of natural gas (including gaseous and liquid forms) provided to meet the supply requirements of the energy authorities;
[0050] S refers to the equity ratio held by the basic capacity user or its affiliates in the equity structure of the receiving station company;
[0051] ΣS' refers to the sum of the equity proportions of the receiving station company held by all basic capacity users or their affiliates who have signed a receiving station use agreement with the receiving station company.
[0052] The advantages and positive effects of this application are:
[0053] The present invention can avoid any form of inventory shortage or surplus at the receiving station. Specifically:
[0054] The present invention first obtains, through the Internet of Things, initial data of an LNG receiving station at the current moment, data on an LNG input plan and an LNG export plan of the LNG receiving station within a preset future time, and predictive factors that affect the execution of the LNG input plan and the LNG export plan within the preset future time; then, through the initial data and the data on the LNG input plan and the LNG export plan of the LNG receiving station within the preset future time, obtains the theoretical inventory of the LNG receiving station at the current moment and within the preset future time; then, based on the predictive factors, obtains an adjustment amount of the inventory and the LNG export plan that affect the execution of the LNG input plan within the preset future time; superimposes the adjustment amount on the theoretical inventory to obtain an optimized inventory; finally, compares the optimized inventory with a preset inventory balance, and adjusts the execution of the LNG input plan and the LNG export plan within the preset future time according to the comparison result.
[0055] Clearly, this invention, building on theoretical inventory, comprehensively considers predictive factors to determine the inventory and LNG export plan adjustments that will impact the execution of the LNG import and export plans within a preset future timeframe, thereby making the forecasts more accurate and reliable. This provides adjustment strategies for the execution of these plans. The invention also considers unexpected factors, resulting in a secondary optimized inventory. The resulting adjustments are more accurate and reliable.
[0056] At the same time, since the LNG receiving station in the present invention includes joint investment from multiple users (LNG receiving stations in traditional technologies are all invested by a single user), each user holds a different proportion of shares. Therefore, in order to balance the interests of all parties, the calculation of storage fees and the priority of selecting window conflict periods are also scientifically and reasonably designed; it can well ensure the balance of interests among all parties.
[0057] In summary, by adopting the above technical solutions, the present invention ensures that the inventory level of the receiving station can meet the needs of the downstream market at any time, while the storage tank should also have sufficient remaining space to accommodate the unloading volume of the LNG ship; these technologies. BRIEF DESCRIPTION OF THE DRAWINGS
[0058] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.
[0059] Figure 1 shows a flow chart provided by a preferred embodiment of the present invention;
[0060] Figure 2Shows a structural block diagram provided by a preferred embodiment of the present invention;
[0061] Figure 3 shows a platform planning data diagram provided by a preferred embodiment of the present invention;
[0062] Figure 4 A diagram showing factors affecting inventory balance provided by a preferred embodiment of the present invention is shown;
[0063] Figure 5 shows a system block diagram provided by a preferred embodiment of the present invention;
[0064] Figure 6 The inventory planning trend chart and early warning chart obtained by using the platform of the present invention are displayed;
[0065] Figure 7 The actual inventory trend chart and early warning chart obtained by using the platform of the present invention are displayed;
[0066] Figure 8 The gaseous outflow trend diagram and early warning diagram obtained by using the platform of the present invention;
[0067] Figure 9 The liquid outflow trend diagram and early warning diagram obtained by using the platform of the present invention are shown;
[0068] Figure 10 This is a display of the external transmission trend chart and early warning chart obtained using the platform of the present invention. DETAILED DESCRIPTION
[0069] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.
[0070] See also Figures 1 to 10
[0071] An LNG receiving station inventory optimization method based on the Internet of Things includes the following steps:
[0072] S1. Obtain basic data through the Internet of Things; the basic data includes the initial data of the LNG receiving station at the current moment, the LNG import and export plan data of the LNG receiving station within a preset future time, and the predicted factors that affect the execution of the LNG import and export plan within the preset future time; wherein:
[0073] The initial data is the sum of the initial inventories of all investors in the LNG receiving station at the current moment; the initial data may also include the current operating status data of the LNG receiving station and the status data of the LNG tanks;
[0074] The LNG import plan data includes the LNG import plan data of each investor within a preset time in the future;
[0075] The LNG export plan data includes the LNG export plan data of each investor within a preset time in the future;
[0076] The predictive factors mainly include weather and transportation route status; the weather mainly includes local weather data of the LNG receiving station, and may also include weather data on the route during the execution of each LNG import plan and LNG export plan;
[0077] S2. Data preprocessing: Obtaining theoretical inventory of the LNG receiving station at the current time and within a preset future time using the initial data, the LNG input plan and LNG export plan data of the LNG receiving station within a preset future time;
[0078] S3. Inventory optimization: obtaining, based on the predicted factors, inventory adjustments that affect the execution of the LNG import plan and the LNG export plan within a preset future time period; superimposing the adjustments with the theoretical inventory to obtain an optimized inventory;
[0079] S4. Compare the optimized inventory with a preset inventory balance, and adjust the LNG import plan and LNG export plan to be executed within a preset time in the future according to the comparison result.
[0080] To further improve the credibility of the optimization, the basic data also includes sudden factors; the sudden factors include transportation interruptions caused by traffic control or natural disasters, LNG leaks caused by transportation failures, and emergency natural gas supply requirements; a mutation amount is obtained based on the sudden factors, and the mutation amount is added to the optimized inventory to obtain a secondary optimized inventory, and S4 is executed based on the secondary optimized inventory.
[0081] The natural gas emergency supply requirement refers to the amount of natural gas that receiving station users and other basic capacity users must bear in order to ensure the normal living and production needs of the basic people under specific circumstances. The natural gas supply amount is calculated according to the following formula:
[0082]
[0083] Q 应承担的保供气量 The gas volume that a user of a certain basic capacity should bear for guaranteed supply;
[0084] Q 保供气量The amount of natural gas (including gaseous and liquid forms) provided to meet the supply requirements of the energy authorities;
[0085] S refers to the equity ratio held by the basic capacity user or its affiliates in the equity structure of the receiving station company;
[0086] ΣS' refers to the sum of the equity proportions of the receiving station company held by all basic capacity users or their affiliates who have signed a receiving station use agreement with the receiving station company.
[0087] Before executing S1, the LNG receiving station IoT is first constructed, and the basic data of the LNG receiving station is collected and accessed through IoT technology;
[0088] S3 predicts the inventory change trend within a preset time period in the future (such as one month), and provides early warning of future inventory conditions that may lead to congestion and low storage capacity, thereby providing a decision-making basis for the input and output plans of LNG receiving station operators and inventory users.
[0089] The present invention can calculate the inventory of a receiving station within a certain period of time based on two factors: the receiving station's input LNG plan and the receiving station's output LNG plan.
[0090] The present invention can compare and judge LNG input data / output data, inventory data and limiting factors affecting inventory balance to obtain inventory balance result data.
[0091] The limiting factors affecting the inventory balance include: the total storage capacity of the LNG receiving station, the maximum gasification capacity of the LNG receiving station, the maximum loading capacity of the LNG receiving station, the maximum ship receiving capacity of the LNG receiving station, the total initial inventory of the LNG receiving station, the initial inventory of each investor, the maximum storage capacity for safe operation of the LNG receiving station, the minimum storage capacity for safe operation of the LNG receiving station, the minimum storage capacity of each investor, the basic storage capacity of each investor, and the basic storage capacity of each investor based on the proportion of shareholders.
[0092] S5. Conflict period between storage fee calculation and selection window; among which:
[0093] Storage fees are automatically calculated by the platform based on the user's short-lift volume. Because this LNG receiving station has multiple users, if a user's actual withdrawal volume on any pickup day during the service period is less than 95% of the designated pickup volume for that pickup day, the short-lift volume for that pickup day will be the difference between 95% of the designated pickup volume and the actual withdrawal volume. Storage fees are calculated starting on the third day (D+2) of a normal pickup day (D). However, short-lift volumes are subject to crediting. On any pickup day, if the user's actual withdrawal volume exceeds 95% of the designated pickup volume for that pickup day, the excess over 95% of the designated pickup volume will be credited against any uncredited short-lift volumes incurred prior to that pickup day, in the order in which the short-lift volumes were generated.
[0094] The platform displays the annual arrival window period uniformly in the system based on the shareholding ratios and cargo pickup plans of each receiving station user. Each user can then take turns selecting a conflicting arrival window period in descending order of equity in the receiving station company. That is, when multiple arrival windows conflict between two or more basic capacity users, the basic capacity user with the largest equity ratio will be given priority to select a window period, followed by the basic capacity user with the second largest equity ratio, and so on, until all window period conflicts are resolved.
[0095] LNG receiving stations have limited storage capacity and multiple users. By calculating storage capacity balance in advance, combined with the station's production capacity, we can avoid congestion and low inventory situations. When congestion and low inventory occur, LNG receiving station operators can coordinate with users based on the forecast results to adjust incoming ships or outbound shipments to ensure storage capacity balance.
[0096] When the user inputs the ship arrival plan data, export plan data and the initial inventory volume monitored by the platform for a certain time period, the formula for calculating the inventory volume of the receiving station or each user on any day within this time period is as follows:
[0097]
[0098] Where: i = 0, 1, 2, ..., n-1; n is an integer ≥ 1;
[0099] i refers to the i-th day, A represents the inventory, B represents the initial inventory, C represents the planned incoming ship volume, D represents the planned gas export volume, and E represents the planned liquid export volume. Indicates the user's inventory on day n; B 用户 Indicates the user's initial inventory; represents the planned number of ships arriving on the user's i-th day; represents the planned gaseous output volume of the user on day i; It represents the planned liquid delivery volume of the user on day i. Specifically:
[0100] represents the total inventory at the receiving station on day n;
[0101] represents the inventory of user 1 on day n;
[0102] represents the inventory of user 2 on day n;
[0103] represents the inventory of user 3 on day n;
[0104] Indicates the inventory of user 4 on day n; and so on;
[0105] The sum of each user's inventory is equal to the total inventory;
[0106] B 总 represents the total initial inventory at the receiving station;
[0107] B 用户1 represents the initial inventory of user 1;
[0108] B 用户2 represents the initial inventory of user 2;
[0109] B 用户3 represents the initial inventory of user 3;
[0110] B 用户4 Indicates the initial inventory of user 4; and so on;
[0111] The sum of each user's initial inventory is equal to the total initial inventory;
[0112] It represents the total planned arrival volume of ships at the receiving station on day i;
[0113] represents the planned number of ships arriving by user 1 on day i;
[0114] represents the planned number of ships arriving by user 2 on day i;
[0115] represents the planned number of ships arriving by user 3 on day i;
[0116] represents the planned number of ships arriving by user 4 on day i; and so on;
[0117] The sum of the planned ship arrivals of each user is equal to the total planned ship arrivals;
[0118] It represents the planned gaseous output volume of the receiving station on day i;
[0119] represents the planned gas export volume of user 1 on day i;
[0120] represents the planned gas export volume of user 2 on day i;
[0121] represents the planned gaseous output of user 3 on day i;
[0122] represents the planned gas export volume of user 4 on day i; and so on;
[0123] The sum of the planned gas export volumes of each user is equal to the total planned gas export volume;
[0124] represents the planned liquid outflow volume of the receiving station on day i;
[0125] represents the planned liquid delivery volume of user 1 on day i;
[0126] represents the planned liquid export volume of user 2 on day i;
[0127] represents the planned liquid export volume of user 3 on day i;
[0128] represents the planned liquid export volume of user 4 on day i; and so on;
[0129] The sum of each user's planned liquid export volume is equal to the total planned liquid export volume;
[0130] The inventory balance must meet the following conditions:
[0131] 1. The total storage capacity of the LNG receiving station cannot be exceeded;
[0132] 2. The sum of the gas export plans of each investor cannot exceed the maximum gasification capacity of the LNG receiving station;
[0133] 3. The sum of the liquid export plans of each investor cannot exceed the maximum loading capacity of the receiving station;
[0134] 4. It is not allowed to exceed the maximum storage capacity for safe operation;
[0135] 5. It cannot be lower than the minimum storage capacity;
[0136] 6. Taking into account the proportions of all parties, the storage capacity of each investor shall not be less than its corresponding minimum storage capacity;
[0137] 7. Combined with the proportions of each party, it shows whether the current storage capacity exceeds the allocated basic storage capacity;
[0138] 8. Combined with the proportions of each party, it shows whether the current storage capacity exceeds the storage capacity allocated to the shareholders;
[0139] Application Cases:
[0140] See also Figures 6 to 10 A coastal LNG receiving station implemented this solution, enabling it to predict future inventory levels and, based on inventory balance priorities, ensure that inventory levels remain above the safety reserve level, effectively reducing the occurrence of overstocking and shortages at LNG receiving stations. Results show that using this inventory optimization solution for LNG receiving stations can effectively control inventory at these stations.
[0141] An IoT-based LNG receiving terminal inventory optimization platform, including:
[0142] The LNG receiving station IoT is used to obtain basic data; the basic data includes the initial data of the LNG receiving station at the current moment, the LNG import and export plan data of the LNG receiving station within a preset time in the future, and the predicted factors that affect the execution of the LNG import and export plan within the preset time in the future;
[0143] The cloud platform receives the basic data of the LNG receiving station's IoT and performs pre-processing and optimization on the basic data. Specifically, it includes:
[0144] A data preprocessing module obtains the theoretical inventory of the LNG receiving station at the current moment and within a preset future time through the initial data, the LNG input plan and the LNG export plan data of the LNG receiving station within a preset future time;
[0145] The inventory optimization module obtains the inventory and LNG export plan adjustment amount that will affect the execution of the LNG import plan within a preset time in the future based on the predicted factors; superimposes the adjustment amount with the theoretical inventory to obtain the optimized inventory;
[0146] A result feedback module compares the optimized inventory with a preset inventory balance and adjusts the LNG import plan and LNG export plan to be executed within a preset time in the future according to the comparison result;
[0147] The storage fee calculation module automatically calculates LNG storage fees based on the user's short-lift volume. Because this LNG receiving station has multiple users, if a user's actual withdrawal volume on any pickup day during the service period is less than 95% of the designated pickup volume for that pickup day, the short-lift volume for that pickup day will be the difference between 95% of the designated pickup volume and the actual withdrawal volume. Storage fees are calculated starting on the third day (D+2) of a normal pickup day (D). However, short-lift volumes are subject to deduction. On any pickup day, if the actual withdrawal volume of a receiving station user exceeds 95% of the designated pickup volume for that pickup day, the excess of the actual withdrawal volume over 95% of the designated pickup volume will be deducted from any undeducted short-lift volumes incurred prior to that pickup day, in the order in which the short-lift volumes were generated.
[0148] Select the Window Conflict module. The platform will uniformly display the annual arrival windows in the system based on the shareholding ratios and cargo pickup plans of each receiving station user. Each user can take turns selecting a conflicting arrival window in descending order of equity in the receiving station company. That is, when the arrival windows of two or more basic capacity users conflict, the basic capacity user with the largest equity ratio will be given priority to select a window, followed by the basic capacity user with the second largest equity ratio, and so on, until all window conflicts are resolved.
[0149] In the present invention, the platform architecture is divided into perception layer, transmission layer, infrastructure layer, platform layer, application layer, display layer and user layer, which can complete data collection and acquisition, data access, data analysis and data application display.
[0150] The LNG receiving station Internet of Things includes:
[0151] A sensor group for obtaining basic data of the LNG receiving station; the sensor group includes a liquid level sensor, a temperature sensor, a pressure sensor, and a density sensor installed on the LNG tank;
[0152] A data collection terminal that obtains data on each investor's LNG import and export plans within a preset timeframe;
[0153] A meteorological data acquisition terminal for obtaining weather conditions along the routes during each LNG import plan and LNG export plan;
[0154] A 5G network that enables data interaction among sensor groups, data acquisition terminals, and cloud platforms.
[0155] 1) Perception layer:
[0156] Provides front-end data sensing services to collect basic data information from tank farms. Sensing equipment primarily includes level gauges, continuous level-temperature-density (LTD) monitoring instruments, and weather monitoring stations, enabling automated sensing and collection of LNG tank inventory information and surrounding weather information.
[0157] Liquid level gauge: LNG tanks are equipped with high-precision, independent liquid level gauges to prevent tank overflow;
[0158] Liquid level-temperature-density (LTD) continuous monitoring instrument: The instrument is deployed on the LNG tank to monitor the tank's liquid level, temperature, density and other working status data in real time;
[0159] Scada: Collects real-time data from the tank area within the LNG receiving station, including pressure, temperature, liquid level, etc., and feeds accurate measurement information back to management personnel. If it exceeds the normal range, an alarm will be generated to alert management personnel.
[0160] Weather station: collects weather data around the LNG receiving station to provide a reference for decision-making on inventory optimization.
[0161] 2) Transport layer:
[0162] By building a 5G network, we can achieve full network coverage of the receiving station, providing a network foundation for data transmission of various IoT devices and mobile office equipment on site.
[0163] 3) Infrastructure layer:
[0164] Provides basic services such as storage, CPU, and network for the platform. Mainly includes computer room construction (servers, storage, firewalls, and other equipment).
[0165] 4) Platform layer:
[0166] The platform layer mainly provides a basic platform framework to support upper-layer application development, including microservice architecture and big data platform.
[0167] Microservice architecture development and operation and maintenance integrated platform: The platform includes CMDB (configuration management database service), ACS (automated scheduling core service), UIS (front-end service), MCS (message-driven service for connecting to the front end), DDS (data discovery service) and other modules. Each module runs independently and does not affect each other. It supports horizontal expansion, distributed deployment, online expansion and contraction of modules, and load balancing high-availability deployment methods, enabling flexible adjustment of functional modules. Through horizontal expansion, the application's concurrent processing capabilities can be greatly improved. The system front-end uses a progressive VUE framework for building a user interface, and the back-end uses springcloud technology to achieve front-end and back-end separation, ensuring development efficiency. The microservice architecture mainly supports the construction of complex and large-scale distributed systems on this platform, providing a set of support for distribution, high availability, high security, elastic scaling, and has the advantages of system health monitoring, containerization, and integrated development and operation and maintenance.
[0168] Big data platform: Through mature big data processing technology, build a data collection, processing, analysis and display platform.
[0169] 1. Data collection and storage: The platform can collect various types of data from multiple sources such as the perception layer and store them in appropriate data storage systems.
[0170] 2. Data processing and analysis: Support efficient data processing and analysis through distributed computing frameworks and real-time stream processing systems.
[0171] 3. Data management and cleaning: To ensure data quality and consistency, the platform provides data management tools and ETL (extraction, transformation, loading) functions to process raw data.
[0172] 4. Visualization and reporting: Big data platforms typically include visualization tools for creating dashboards, reports, and data visualizations, enabling users to understand data in an intuitive way and gain decision support from it.
[0173] 5. The core of the big data platform is the intelligent inventory optimization forecasting model: Based on the LNG receiving station's input and output plans, combined with factors influencing inventory balance (such as weather factors, the receiving station's total storage capacity, the receiving station's maximum gasification capacity, the receiving station's maximum loading capacity, and the receiving station's maximum ship receiving capacity), it predicts inventory information for a period of time in the future. If these multiple factors predict that inventory will exceed the standard on a certain day in the future, an inventory warning function can be provided. (See the Big Data Platform section below for specific formulas and forecasting methods.)
[0174] 5) Application layer:
[0175] This system is used to implement the corresponding functions of the system application. Functional modules include receiving station parameter settings, ship arrival plan management, ship arrival actual management, export plan management, and inventory simulation analysis and early warning. Through system application simulation calculations, inventory issues are promptly identified, providing data support for operators to manage inventory, ensuring inventory security and efficient operations.
[0176] 6) Presentation layer:
[0177] The system supports multiple output display methods, including web display, large screen display, and mobile terminal.
[0178] 7) User layer:
[0179] LNG receiving station operators and LNG receiving station inventory users.
[0180] The cloud platform may include a crawler module for crawling data related to the LNG receiving station.
[0181] The initial data is the sum of the initial inventories of all investors in the LNG receiving station at the current moment; the LNG import plan and LNG export plan data include the LNG import plan and LNG export plan data of each investor within a preset time in the future;
[0182] The cloud platform has the following functions:
[0183] LNG Receiving Station Parameter Settings: Customize basic terminal parameters, including storage capacity, maximum regasification capacity, maximum loading capacity, inventory limits, initial inventory, basic information for each user, allocated storage capacity for each user, and vessel pickup requirements. Operators can add, delete, and modify user information. Receiving station inventory is displayed in five units: tons, 10,000 cubic meters of LNG, 10,000 cubic meters of NG, MMbtu, and MJ.
[0184] Ship Arrival Plan Management: Customize the planned ship arrival volume for each user at the receiving station. Export and import functions facilitate quick data submission. Display data in five units: tons, 10,000 cubic meters of LNG, 10,000 cubic meters of NG, MMbtu, and MJ.
[0185] Ship Incoming Volume Management: Customize the actual volume of incoming ships for each user at the receiving station. Export and import functions facilitate quick data reporting. Displays data in five units: tons, 10,000 cubic meters of LNG, 10,000 cubic meters of NG, and MJ.
[0186] Transmission Plan Management: Customize transmission plans for each user at the receiving station. Export and import functions facilitate quick data reporting. Transmission plan reporting allows users to complete a month's transmission plan with one click. Display data in five units: tons, 10,000 cubic meters of LNG, 10,000 cubic meters of NG, MMbtu, and MJ.
[0187] Inventory simulation analysis and early warning: Based on the inventory data automatically collected by the receiving station, the data maintained in the ship arrival plan and the external transmission plan as the basic data source support, and meteorological monitoring data, combined with the inventory management needs of the receiving station, four types of calculation and simulation are presented through visual charts: the inventory trend of the receiving station, the inventory trend of each user, the liquid external transmission trend, and the gaseous external transmission trend.
[0188] The predictive factors include weather and transportation route status;
[0189] The basic data also includes sudden factors; the sudden factors include transportation interruptions caused by traffic control or natural disasters, LNG leaks caused by transportation failures, LNG tank leaks in LNG receiving stations, and emergency natural gas supply requirements; the inventory optimization module obtains a mutation amount based on the sudden factors, adds the mutation amount to the optimized inventory to obtain a secondary optimized inventory, and the result feedback module compares the secondary optimized inventory with the preset inventory balance, and adjusts the LNG import plan and LNG export plan to be executed within a preset time period in the future based on the comparison result;
[0190] The limiting factors affecting the inventory balance include: the total storage capacity of the LNG receiving station, the maximum gasification capacity of the LNG receiving station, the maximum loading capacity of the LNG receiving station, the maximum ship receiving capacity of the LNG receiving station, the total initial inventory of the LNG receiving station, the initial inventory of each investor, the maximum storage capacity for safe operation of the LNG receiving station, the minimum storage capacity for safe operation of the LNG receiving station, the minimum storage capacity of each investor, the basic storage capacity of each investor, and the basic storage capacity of each investor based on the proportion of shareholders;
[0191] The natural gas emergency supply requirement refers to the amount of natural gas that receiving station users and other basic capacity users must bear in order to ensure the normal living and production needs of the basic people under specific circumstances. The natural gas supply amount is calculated according to the following formula:
[0192]
[0193] Among them, Q 应承担的保供气量 The gas volume that a user of a certain basic capacity should bear for guaranteed supply;
[0194] Q 保供气量 The amount of natural gas (including gaseous and liquid forms) provided to meet the supply requirements of the energy authorities;
[0195] S refers to the equity ratio held by the basic capacity user or its affiliates in the equity structure of the receiving station company;
[0196] ΣS' refers to the sum of the equity proportions of the receiving station company held by all basic capacity users or their affiliates who have signed a receiving station use agreement with the receiving station company.
[0197] In the above embodiments, all or part of the embodiments can be implemented by software, hardware, firmware, or any combination thereof. When 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 or executed on a computer, the process or function described in the embodiment of the present invention 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 device. 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 one website, computer, server, or data center to another website, computer, server, or data center via a wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL) or wireless (e.g., infrared, wireless, microwave, etc.)) method. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that includes one or more available media integrated. 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 drive (SSD)).
[0198] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.
Claims
1. An LNG receiving station inventory optimization method based on the Internet of Things, characterized in that: include: S1. Obtaining basic data through the Internet of Things; the basic data includes initial data of the LNG receiving station at the current moment, the LNG import and export plan data of the LNG receiving station within a preset future time, and predicted factors affecting the execution of the LNG import and export plan within the preset future time; S2. Data preprocessing: Obtaining theoretical inventory of the LNG receiving station at the current time and within a preset future time using the initial data, the LNG input plan and LNG export plan data of the LNG receiving station within a preset future time; S3. Inventory optimization: obtaining, based on the predicted factors, the inventory and adjustment amount of the LNG export plan that will affect the execution of the LNG import plan within a preset time in the future; superimposing the adjustment amount with the theoretical inventory; Get optimized inventory; S4. Compare the optimized inventory with a preset inventory balance, and adjust the LNG import plan and LNG export plan to be executed within a preset time in the future according to the comparison result.
2. The method for optimizing inventory of LNG receiving stations based on the Internet of Things according to claim 1, characterized in that: The initial data is the sum of the initial inventories of all investors in the LNG receiving station at the current moment; the LNG import plan and LNG export plan data include the LNG import plan and LNG export plan data of each investor within a preset time in the future; The predictive factors include weather and transportation route status.
3. The method for optimizing inventory of LNG receiving stations based on the Internet of Things according to claim 2, characterized in that: Also includes S5, storage fee calculation and selection window conflict period; among which: The storage fee calculation is based on the user's short-lift volume. The LNG receiving station is invested by multiple parties. If the actual amount of LNG picked up by the user of the LNG receiving station on any pick-up day during the service period is less than 95% of the specified daily pick-up volume, the short-lift volume on that pick-up day is the difference between 95% of the specified daily pick-up volume and the actual amount picked up. Normal pick-up is on D day, and storage fees are calculated starting from D+2. Short-lift volumes need to be deducted. On any pick-up day, if the actual amount of LNG picked up by the user of the LNG receiving station exceeds 95% of the specified daily pick-up volume, the portion of the actual amount picked up that exceeds 95% of the specified daily pick-up volume will be deducted in priority from the short-lift volumes that occurred earlier before that pick-up day and have not been deducted. The selection window conflict period is based on the shareholding ratio and delivery plan of each party of the LNG receiving station user, and the annual arrival window period is uniformly displayed in the system. Each LNG receiving station user can take turns in descending order of the equity ratio held to select and determine an arrival window period from the conflicting arrival windows.
4. The method for optimizing inventory of LNG receiving stations based on the Internet of Things according to claim 1, characterized in that: The basic data also includes sudden factors; the sudden factors include transportation interruptions caused by traffic control or natural disasters, LNG leakage caused by transportation failures, and emergency natural gas supply requirements; a mutation amount is obtained based on the sudden factors, and the mutation amount is added to the optimized inventory to obtain a secondary optimized inventory, and S4 is executed based on the secondary optimized inventory; The natural gas emergency supply requirement refers to the amount of natural gas that receiving station users and other basic capacity users must bear in order to ensure the normal living and production needs of the basic people under specific circumstances. The natural gas supply amount is calculated according to the following formula: Among them, Q 应承担的保供气量 The gas volume that a user of a certain basic capacity should bear for guaranteed supply; Q 保供气量 The amount of natural gas (including gaseous and liquid forms) provided to meet the supply requirements of the energy authorities; S refers to the equity ratio held by the basic capacity user or its affiliates in the equity structure of the receiving station company; ΣS' refers to the sum of the equity proportions of the receiving station company held by all basic capacity users or their affiliates who have signed a receiving station use agreement with the receiving station company.
5. The method for optimizing inventory of LNG receiving stations based on the Internet of Things according to claim 1, characterized in that: The limiting factors affecting the inventory balance include: the total storage capacity of the LNG receiving station, the maximum gasification capacity of the LNG receiving station, the maximum loading capacity of the LNG receiving station, the maximum ship receiving capacity of the LNG receiving station, the total initial inventory of the LNG receiving station, the initial inventory of each investor, the maximum storage capacity for safe operation of the LNG receiving station, the minimum storage capacity for safe operation of the LNG receiving station, the minimum storage capacity of each investor, the basic storage capacity of each investor, and the basic storage capacity of each investor based on the proportion of shareholders.
6. An LNG receiving station inventory optimization platform based on the Internet of Things, characterized by: include: LNG receiving station IoT, used to obtain basic data; The basic data includes the initial data of the LNG receiving station at the current moment, the LNG import plan and LNG export plan data of the LNG receiving station within a preset time in the future, and the predicted factors that affect the execution of the LNG import plan and LNG export plan within the preset time in the future; The cloud platform receives the basic data of the LNG receiving station's IoT and performs pre-processing and optimization on the basic data. Specifically, it includes: A data preprocessing module obtains the theoretical inventory of the LNG receiving station at the current moment and within a preset future time through the initial data, the LNG input plan and the LNG export plan data of the LNG receiving station within a preset future time; The inventory optimization module obtains the inventory and LNG export plan adjustment amount that will affect the execution of the LNG import plan within a preset time in the future based on the predicted factors; superimposes the adjustment amount with the theoretical inventory to obtain the optimized inventory; The result feedback module compares the optimized inventory with a preset inventory balance, and adjusts the LNG import plan and LNG export plan to be executed within a preset time in the future according to the comparison result.
7. The LNG receiving station inventory optimization platform based on the Internet of Things according to claim 6 is characterized in that: The LNG receiving station Internet of Things includes: A sensor group that obtains basic data of the LNG receiving station; A data collection terminal that obtains data on each investor's LNG import and export plans within a preset timeframe; A meteorological data acquisition terminal for obtaining weather conditions along the routes during each LNG import plan and LNG export plan; A 5G network that enables data interaction among sensor groups, data acquisition terminals, and cloud platforms.
8. The LNG receiving station inventory optimization platform based on the Internet of Things according to claim 7 is characterized in that: The sensor group includes a liquid level sensor, a temperature sensor, a pressure sensor and a density sensor installed on the LNG tank; the cloud platform includes a crawler module for crawling data related to the LNG receiving station.
9. The LNG receiving station inventory optimization platform based on the Internet of Things according to claim 8 is characterized in that: It also includes a storage fee calculation module and a window conflict period selection module; among which: The storage fee calculation module calculates the LNG storage fee based on the user's short-lift volume. The LNG receiving station is invested by multiple parties. When the actual amount of LNG picked up by the user of the LNG receiving station on any pick-up day during the service period is less than 95% of the specified pick-up volume on that pick-up day, the short-lift volume on that pick-up day is the difference between 95% of the specified pick-up volume on that pick-up day and the actual amount picked up. Normal pick-up is on D day, and storage fees are calculated starting from D+2 day. Short-lift volume needs to be deducted. On any pick-up day, when the actual amount of LNG picked up by the user of the LNG receiving station exceeds 95% of the specified pick-up volume on that pick-up day, the portion of the actual amount picked up that exceeds 95% of the specified pick-up volume on that day will be deducted first in the order in which the short-lift volume was generated against the undeducted short-lift volume that occurred earlier before that pick-up day. The window conflict period selection module uniformly displays the annual arrival window period in the system according to the shareholding ratio and delivery plan of each party of the LNG receiving station user. Each LNG receiving station user can take turns to select and determine an arrival window period from the conflicting arrival windows in order of the equity ratio held from large to small.
10. The LNG receiving station inventory optimization platform based on the Internet of Things according to claim 6, characterized in that: The initial data is the sum of the initial inventories of all investors in the LNG receiving station at the current moment; the LNG import plan and LNG export plan data include the LNG import plan and LNG export plan data of each investor within a preset time in the future; The predictive factors include weather and transportation route status; The basic data also includes unexpected factors; the unexpected factors include transportation interruptions caused by traffic control or natural disasters, LNG leakage caused by transportation failures, LNG tank leakage in LNG receiving stations, and emergency natural gas supply requirements; The inventory optimization module obtains a mutation amount based on the sudden factors, and adds the mutation amount to the optimized inventory to obtain a secondary optimized inventory. The result feedback module compares the secondary optimized inventory with the preset inventory balance, and adjusts the LNG import plan and LNG export plan to be executed within the preset time in the future based on the comparison result; The limiting factors affecting the inventory balance include: the total storage capacity of the LNG receiving station, the maximum gasification capacity of the LNG receiving station, the maximum loading capacity of the LNG receiving station, the maximum ship receiving capacity of the LNG receiving station, the total initial inventory of the LNG receiving station, the initial inventory of each investor, the maximum storage capacity for safe operation of the LNG receiving station, the minimum storage capacity for safe operation of the LNG receiving station, the minimum storage capacity of each investor, the basic storage capacity of each investor, and the basic storage capacity of each investor based on the proportion of shareholders; The natural gas emergency supply requirement refers to the amount of natural gas that receiving station users and other basic capacity users must bear in order to ensure the normal living and production needs of the basic people under specific circumstances. The natural gas supply amount is calculated according to the following formula: Among them, Q 应承担的保供气量 The gas volume that a user of a certain basic capacity should bear for guaranteed supply; Q 保供气量 The amount of natural gas (including gaseous and liquid forms) provided to meet the supply requirements of energy authorities; S refers to the equity ratio held by the basic capacity user or its affiliates in the equity structure of the receiving station company; ∑S' refers to the sum of the equity proportions of the receiving station company held by all basic capacity users or their affiliates who have signed a receiving station use agreement with the receiving station company.