Oil product storage dynamic system and device

Abstract

The invention belongs to the technical field of oil depot oil product storage monitoring, and discloses an oil product storage dynamic system and device, and the oil product storage dynamic system comprises a label information building unit which is used for building label information for oil product storage data according to oil depot station information; the oil quantity data acquisition unit is used for acquiring oil quantity data of the oil product storage data corresponding to each piece of label information; the oil quantity data comprises storage quantity, oil delivery quantity and oil delivery time of different types of oil products; the oil quantity data judging unit is used for judging whether at least one oil product with the storage quantity smaller than a preset inventory threshold exists in the oil quantity data or not; and the oil product distribution matching unit is used for matching the optimal oil product distribution scheme for the oil depot station through a dynamic matching method. According to the invention, the optimal distribution scheme is searched through the dynamic matching algorithm according to the demand, the balance between the supply and demand of the oil product is ensured, the distribution cost is minimized, and the efficiency of the whole supply chain is improved.

Description

Technical Field

[0001] The invention relates to the technical field of oil storage monitoring in oil depots, and in particular to an oil storage dynamic system and device. Background Art

[0002] Oil depots, also known as oil depots, are facilities dedicated to receiving, sending and storing a variety of petroleum products such as crude oil, gasoline, kerosene, etc. Accurate inventory control can be achieved by effectively managing the entry and exit activities of various petroleum products in the oil depot. This management not only helps companies avoid excessive or insufficient inventory, thereby improving inventory turnover, but also alleviates the problem of capital occupation caused by inventory backlogs. Sophisticated inventory management is essential to optimize resource utilization, reduce costs and improve operational efficiency. Therefore, strict management of the entry and exit of petroleum products in the oil depot is a basic measure to ensure supply chain stability and financial health.

[0003] In the existing technology, traditional oil demand forecasting methods are often based on manual experience or simple statistical methods, which lack scientificity and accuracy. This forecasting method cannot accurately reflect the changing trend of market demand, resulting in an imbalance between oil supply and demand and increasing the operational risks of enterprises. At the same time, there is a lack of scientific planning and optimization in the oil distribution process, and distribution often relies on experience. This planning method is not only inefficient, but also costly. At the same time, due to the lack of an effective distribution resource evaluation and selection mechanism, the stability and efficiency of distribution are difficult to guarantee, thus failing to meet the needs of enterprises for efficient, accurate and stable oil storage and distribution.

[0004] Therefore, how to provide a dynamic system and device for oil storage is a problem that needs to be solved urgently. Summary of the invention

[0005] The embodiment of the present invention provides a dynamic system and device for oil storage to solve the problem that the planning method in the prior art is not only inefficient but also unable to meet the distribution demand.

[0006] In order to have a basic understanding of some aspects of the disclosed embodiments, a brief summary is given below. This summary is not intended to be a general review, nor is it intended to identify key / important components or to delineate the scope of protection of these embodiments. Its only purpose is to present some concepts in a simple form as a preface to the detailed description that follows.

[0007] According to a first aspect of an embodiment of the present invention, a dynamic system and device for storing oil is provided.

[0008] In one embodiment, a dynamic system for storing oil products comprises:

[0009] A label information establishing unit, used for acquiring oil product storage data corresponding to a plurality of oil depot stations, and establishing label information for the oil product storage data according to the oil depot station information;

[0010] An oil quantity data acquisition unit is used to acquire the oil quantity data of the oil product storage data corresponding to each tag information according to the tag information; the oil quantity data includes the storage quantity, oil delivery quantity and oil delivery time of different types of oil products;

[0011] The oil quantity data judgment unit is used to judge whether the storage quantity of at least one oil product in the oil quantity data is less than a preset inventory threshold value, and if so, analyze the oil demand of the oil product at the oil depot station through the oil demand prediction model based on the oil quantity data;

[0012] The oil distribution matching unit is used to match the optimal oil distribution plan for the oil depot station through a dynamic matching method according to the oil demand of the oil depot station.

[0013] Preferably, the label information establishing unit includes:

[0014] The communication connection establishment module is used to establish communication connections between oil depots in different regions and the monitoring background through the Internet of Things technology;

[0015] The data receiving module is used to receive the oil storage data uploaded by oil depots in different regions through the monitoring background;

[0016] The label information attaching module is used to attach the oil depot station label information to the oil product storage data according to the oil depot station label information pre-recorded in the monitoring background.

[0017] Preferably, the oil quantity data determination unit comprises:

[0018] It is used to determine whether the storage volume of at least one oil product in the oil volume data is less than the preset inventory threshold. If so, the oil demand of the oil depot station is analyzed based on the oil volume data through the oil demand prediction model;

[0019] A comparison and judgment module is used to compare the storage volume data of each oil product with a preset inventory threshold and obtain a comparison result;

[0020] A prediction model building module is used to build a prediction model for the oil demand of each oil product based on the oil quantity data using a feature analysis method;

[0021] The oil product demand prediction module is used to analyze the oil product demand of the oil depot station according to the oil demand prediction model when it is determined that the storage volume of at least one oil product is less than a preset inventory threshold.

[0022] Preferably, the method of constructing an oil demand prediction model for each oil product by using a characteristic analysis method includes:

[0023] Collect historical oil volume data of each oil product at the oil depot station and perform feature extraction to obtain a feature set;

[0024] The obtained feature set is used as input and fed into the pre-selected initial training model;

[0025] The historical oil demand corresponding to each oil product in the historical oil volume data of each oil product is used as a training standard to train the initial training model to obtain the oil demand prediction model for each oil product.

[0026] Preferably, the historical oil volume data of each oil product at the oil depot station is collected and feature extraction is performed to obtain a feature set including:

[0027] Preprocessing the collected historical oil volume data, including data cleaning and standardization;

[0028] Extracting the historical oil storage volume, historical oil delivery volume and historical oil delivery time from the historical oil volume data as the first time series feature;

[0029] Extract the daily oil delivery volume of historical oil products from the historical oil volume data, divide the delivery season according to the corresponding delivery time, and use the delivery season as the second time series feature;

[0030] The first time series feature and the second time series feature are combined to obtain a feature set.

[0031] Preferably, the oil distribution matching unit includes:

[0032] A capacity assessment module is used to obtain the oil supply source of the oil depot station and assess the oil distribution capacity of the oil supply source;

[0033] An information acquisition module is used to obtain the available oil type, quantity and location information of the oil supply source in real time;

[0034] Dynamic matching module, used to match the oil supply source through dynamic matching algorithm according to the oil demand of the oil depot station and the available oil type, quantity, location information and oil distribution capacity of the oil supply source;

[0035] The planning module is used to formulate oil distribution plans based on the matched oil supply sources, including distribution time, distribution route and transportation method.

[0036] Preferably, obtaining the oil supply source of the oil depot station and evaluating the oil distribution capacity of the oil supply source includes:

[0037] Based on the oil supply source of the oil depot station, collect the distribution resources of the oil supply source in the preset time period and analyze the change trend of the distribution resources in the preset time period;

[0038] Analyze the distribution resource index of the oil supply source in a preset time period and the change trend of the distribution resource index in the preset time period to calculate the distribution energy efficiency value of the oil supply source;

[0039] The distribution capacity of the oil supply source is evaluated and analyzed based on the distribution energy efficiency value of the oil supply source.

[0040] Preferably, the calculation formula for calculating the distribution energy efficiency value of the oil product supply source by analyzing the distribution resource index of the oil product supply source in the preset time period and the change trend of the distribution resource index in the preset time period is:

[0041]

[0042] In the formula, G i represents the distribution energy efficiency value of the i-th distribution resource; H i A represents the distribution resource index of the i-th distribution resource; i and A j Both represent dimension conversion coefficients; P i and P j They respectively represent the changing trends of the i-th distribution resource and the j-th distribution resource between the preset time periods; n represents the number of distribution resources.

[0043] Preferably, the oil supply sources matched by the dynamic matching algorithm according to the oil demand of the oil depot station and in combination with the available oil types, quantities, location information and oil distribution capabilities of the oil supply sources include:

[0044] Establish constraints based on the available oil types, quantities, location information and oil distribution capabilities of oil supply sources;

[0045] Taking minimizing the oil distribution cost as the objective function, a linear programming model is constructed according to the constraints;

[0046] The linear programming model is solved by linear programming method to obtain the oil supply source that can be used for oil distribution at the oil depot station.

[0047] According to a second aspect of an embodiment of the present invention, there is provided an oil product storage dynamic device, the oil product storage dynamic device comprising: a processor and a memory for storing instructions executable by the processor;

[0048] Wherein, the processor is configured to:

[0049] Obtaining oil storage data corresponding to a number of oil depot stations, and establishing label information for the oil storage data according to the oil depot station information;

[0050] According to the label information, the oil quantity data of the oil product storage data corresponding to each label information is respectively obtained; the oil quantity data includes the storage quantity, oil delivery quantity and oil delivery time of different types of oil products;

[0051] Determine whether the storage volume of at least one oil product in the oil volume data is less than a preset inventory threshold; if so, analyze the oil product demand of the oil depot station through the oil demand prediction model based on the oil volume data;

[0052] According to the oil demand of the oil depot station, the optimal oil distribution plan is matched for the oil depot station through dynamic matching method.

[0053] The technical solution provided by the embodiment of the present invention may have the following beneficial effects:

[0054] 1. The present invention establishes label information for each oil storage data of the oil depot station, making data tracking and query more convenient, increasing the operability and transparency of data management, collecting and updating information such as the storage volume, oil delivery volume and oil delivery time of oil products, and providing accurate storage dynamics. By monitoring the storage volume of oil products and comparing it with the preset inventory threshold, the storage risk can be discovered in time, and the optimal distribution plan can be found through a dynamic matching algorithm according to demand, ensuring the balance between supply and demand of oil products, minimizing distribution costs, and improving the efficiency of the entire supply chain.

[0055] 2. The present invention can construct a more refined feature set by comprehensively utilizing multi-dimensional information such as storage volume, oil delivery volume and oil delivery time in historical oil volume data, which helps to capture the complex pattern of oil demand, thereby improving the accuracy of prediction. The prediction model can foresee future oil demand, help oil depots and stations plan and manage inventory more effectively, and reduce losses caused by oversupply or undersupply, thereby helping enterprises improve efficiency, reduce costs and enhance market competitiveness.

[0056] 3. The present invention evaluates the distribution capability of the oil supply source, and can ensure that the selected supply source has efficient distribution capability, thereby improving the overall distribution efficiency. The present invention uses a dynamic matching algorithm, combined with the oil demand of the oil depot station, the actual situation of the supply source and the distribution capability, to match the most suitable oil supply source for the oil depot station, which helps to reduce unnecessary transportation costs and time, optimize resource allocation, and the formulated oil distribution plan includes distribution time, distribution route and transportation method, which can ensure the smooth progress of the distribution process and reduce potential delays and confusion, which helps to improve the intelligence level of oil storage and distribution, optimize resource allocation, reduce costs, and improve efficiency and emergency response capabilities.

[0057] It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0059] Figure 1 is a principle block diagram of an oil storage dynamic system according to an exemplary embodiment;

[0060] Figure 2 The figure is a schematic diagram showing the structure of a computer device according to an exemplary embodiment. DETAILED DESCRIPTION

[0061] The following description and accompanying drawings fully illustrate the specific embodiments of this article so that those skilled in the art can practice them. Parts and features of some embodiments may be included in or replace parts and features of other embodiments. The scope of the embodiments of this article includes the entire scope of the claims, as well as all available equivalents of the claims. Herein, the terms "first", "second", etc. are only used to distinguish one element from another, without requiring or implying any actual relationship or order between these elements. In fact, the first element can also be called the second element, and vice versa. Moreover, the terms "include", "comprise" or any other variant thereof are intended to cover non-exclusive inclusion, so that the structure, device or equipment including a series of elements includes not only those elements, but also other elements that are not explicitly listed, or also include elements inherent to such structure, device or equipment. In the absence of more restrictions, the elements defined by the sentence "including one..." do not exclude the existence of other identical elements in the structure, device or equipment including the elements. Each embodiment is described in a progressive manner herein, and each embodiment focuses on the differences from other embodiments, and the same and similar parts between the embodiments can be referred to each other.

[0062] The terms "longitudinal", "lateral", "upper", "lower", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc. in this document indicate the orientation or position relationship based on the orientation or position relationship shown in the drawings, and are only for the convenience of describing this document and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operate in a specific orientation, and therefore cannot be understood as a limitation on the present invention. In the description of this document, unless otherwise specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a mechanical connection or an electrical connection, it can also be the internal communication of two elements, it can be a direct connection, or it can be an indirect connection through an intermediate medium. For ordinary technicians in this field, the specific meanings of the above terms can be understood according to specific circumstances.

[0063] As used herein, the term "plurality" means two or more than two, unless otherwise specified.

[0064] In this document, the character " / " indicates that the preceding and following objects are in an "or" relationship. For example, A / B means: A or B.

[0065] In this article, the term "and / or" is a description of the association relationship between objects, indicating that three relationships may exist. For example, A and / or B means: A or B, or, A and B.

[0066] It should be understood that, although the various steps in the flow chart are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear description in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the figure may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these sub-steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

[0067] Each module in the device or system of the present application can be implemented in whole or in part by software, hardware, or a combination thereof. The above modules can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to the above modules.

[0068] In the absence of conflict, the embodiments of the present invention and the features of the embodiments may be combined with each other.

[0069] Figure 1 An embodiment of the oil storage dynamic system of the present invention is shown.

[0070] In this optional embodiment, the oil storage dynamic system includes:

[0071] The label information establishing unit 101 is used to obtain oil product storage data corresponding to a number of oil depot stations, and establish label information for the oil product storage data according to the oil depot station information;

[0072] It should be noted that the oil product storage data is different types of oil product storage information.

[0073] The oil quantity data acquisition unit 103 is used to acquire the oil quantity data of the oil product storage data corresponding to each tag information according to the tag information; the oil quantity data includes the storage quantity, oil delivery quantity and oil delivery time of different types of oil products;

[0074] The oil quantity data judging unit 105 is used to judge whether the storage quantity of at least one oil product in the oil quantity data is less than a preset inventory threshold, and if so, analyze the oil demand of the oil product at the oil depot station through the oil demand prediction model based on the oil quantity data;

[0075] The oil product distribution matching unit 107 is used to match the optimal oil product distribution plan for the oil depot station through a dynamic matching method according to the oil product demand of the oil depot station.

[0076] In this optional embodiment, the label information establishing unit 101 includes:

[0077] The communication connection establishment module is used to establish communication connections between oil depots in different regions and the monitoring background through the Internet of Things technology;

[0078] The data receiving module is used to receive the oil storage data uploaded by oil depots in different regions through the monitoring background;

[0079] The label information attaching module is used to attach the oil depot station label information to the oil product storage data according to the oil depot station label information pre-recorded in the monitoring background.

[0080] In this optional embodiment, the oil quantity data determination unit 105 includes:

[0081] It is used to determine whether the storage volume of at least one oil product in the oil volume data is less than the preset inventory threshold. If so, the oil demand of the oil depot station is analyzed based on the oil volume data through the oil demand prediction model;

[0082] A comparison and judgment module is used to compare the storage volume data of each oil product with a preset inventory threshold and obtain a comparison result;

[0083] A prediction model building module is used to build a prediction model for the oil demand of each oil product based on the oil quantity data using a feature analysis method;

[0084] The oil product demand prediction module is used to analyze the oil product demand of the oil depot station according to the oil demand prediction model when it is determined that the storage volume of at least one oil product is less than a preset inventory threshold.

[0085] In this optional embodiment, the use of feature analysis to construct an oil demand prediction model for each oil product includes: collecting historical oil quantity data for each oil product at the oil depot station and performing feature extraction to obtain a feature set; using the obtained feature set as input and inputting it into a pre-selected initial training model; using the historical oil demand corresponding to each oil product in the historical oil quantity data of each oil product as a training standard, training the initial training model, and obtaining an oil demand prediction model for each oil product.

[0086] In this optional embodiment, the historical oil volume data of each oil product at the oil depot station is collected and feature extraction is performed to obtain a feature set, including: preprocessing the collected historical oil volume data, the preprocessing including data cleaning and standardization; extracting the historical oil product storage volume, historical oil delivery volume and historical oil delivery time in the historical oil volume data as the first time series feature; extracting the historical oil product daily delivery volume in the historical oil volume data, and dividing the delivery season according to the corresponding delivery time, and taking the delivery season as the second time series feature; merging the first time series feature and the second time series feature to obtain a feature set.

[0087] It should be noted that the first time series feature is information about the storage volume, delivery volume and delivery time of oil products extracted from historical data. These features directly reflect the usage pattern and storage dynamics of oil products.

[0088] The second time series feature is to analyze the daily oil delivery volume of oil products and identify different oil delivery seasons in combination with the delivery time. Seasonal changes are an important factor affecting oil demand and can be used to improve the accuracy of demand forecasts.

[0089] The first time series and the second time series features are combined into a comprehensive feature set, which will be used as the input of the prediction model. The model is trained with the feature set by using random forests, neural networks, etc. as the initial training model, using the oil demand in the historical oil volume data as the training target (label). The purpose of model training is to find a mathematical function that can predict the future oil demand based on the input feature set. After the model training is completed, it can be applied to the current data to predict the future oil demand. This helps the oil depot station better plan its resource allocation and inventory management, thereby optimizing operational efficiency and costs.

[0090] In this optional embodiment, the oil distribution matching unit 107 includes:

[0091] A capacity assessment module is used to obtain the oil supply source of the oil depot station and assess the oil distribution capacity of the oil supply source;

[0092] An information acquisition module is used to obtain the available oil type, quantity and location information of the oil supply source in real time;

[0093] Dynamic matching module, used to match the oil supply source through dynamic matching algorithm according to the oil demand of the oil depot station and the available oil type, quantity, location information and oil distribution capacity of the oil supply source;

[0094] The planning module is used to formulate oil distribution plans based on the matched oil supply sources, including distribution time, distribution route and transportation method.

[0095] Specifically, the formulation of oil distribution plans based on matched oil supply sources includes: determining the most suitable time for distribution based on the demand of the oil depot and the availability of the supply source; for example, using the Dijkstra algorithm or A* search algorithm to find the route with the lowest cost or shortest time; selecting the most appropriate mode of transportation based on the distribution distance, oil type, cost and environmental impact. Common modes of transportation include trucks, railways, pipelines and ships. Develop a detailed schedule for each distribution, including the scheduled time for loading, transportation and unloading.

[0096] In this optional embodiment, the obtaining of the oil supply source of the oil depot station and the evaluation of the oil distribution capacity of the oil supply source include: based on the oil supply source of the oil depot station, collecting the distribution resources of the oil supply source in a preset time period (the distribution equipment is equipment for transporting oil, such as vehicles, railways, shipping, etc.) and analyzing the changing trend of the distribution resources in the preset time period; analyzing the distribution resource indicators of the oil supply source in the preset time period and the changing trend of the distribution resource indicators in the preset time period to calculate the distribution energy efficiency value of the oil supply source; and evaluating and analyzing the distribution capacity of the oil supply source according to the distribution energy efficiency value of the oil supply source.

[0097] Specifically, the distribution capacity of the oil product supply source is evaluated and analyzed according to the distribution energy efficiency value of the oil product supply source, including: evaluating the distribution capacity of each supply source by comparing the calculated distribution energy efficiency value. A high distribution energy efficiency value means lower transportation cost and higher transportation efficiency, which is a key criterion for selecting a supply source for priority cooperation.

[0098] Specifically, the calculation formula for calculating the distribution energy efficiency value of the oil supply source by analyzing the distribution resource index of the oil supply source in the preset time period and the change trend of the distribution resource index in the preset time period is:

[0099]

[0100] In the formula, G i represents the distribution energy efficiency value of the i-th distribution resource, and its value range is [0,1]; H i A represents the distribution resource index of the i-th distribution resource; i and A j Both represent dimension conversion coefficients; P i and P j They respectively represent the changing trends of the i-th distribution resource and the j-th distribution resource between the preset time periods; n represents the number of distribution resources.

[0101] In this optional embodiment, the oil supply source matched by the dynamic matching algorithm based on the oil demand of the oil depot station and in combination with the available oil type, quantity, location information and oil distribution capacity of the oil supply source includes: establishing constraints according to the available oil type, quantity, location information and oil distribution capacity of the oil supply source; taking minimizing the oil distribution cost as the objective function, and constructing a linear programming model according to the constraints; solving the linear programming model using the linear programming solution method to obtain the oil supply source that can distribute oil to the oil depot station.

[0102] It should be noted that the corresponding constraints are established according to the available oil types, quantities, location information and oil distribution capabilities of the oil supply sources. For example, ensure that the oil types match, the quantity is sufficient, the location is reasonable (such as close to the oil depot station), the distribution capabilities are strong, etc., and minimize the oil distribution costs including transportation costs, time costs, oil loss costs, etc.; according to the constraints and objective functions, a linear programming model is constructed. The decision variables in the model can be which oil supply sources are selected for distribution, the distribution volume, etc.

[0103] Using linear programming to find the optimal or feasible solution is a common operations research method used to deal with resource optimization problems. Linear programming models usually consist of an objective function and a series of constraints. In the context of oil distribution, this can help minimize costs or maximize efficiency.

[0104] In one embodiment, a dynamic oil storage device is provided, the dynamic oil storage device comprising: a processor and a memory for storing instructions executable by the processor;

[0105] Wherein, the processor is configured to:

[0106] Obtaining oil storage data corresponding to a number of oil depot stations, and establishing label information for the oil storage data according to the oil depot station information;

[0107] According to the label information, the oil quantity data of the oil product storage data corresponding to each label information is respectively obtained; the oil quantity data includes the storage quantity, oil delivery quantity and oil delivery time of different types of oil products;

[0108] Determine whether the storage volume of at least one oil product in the oil volume data is less than a preset inventory threshold; if so, analyze the oil product demand of the oil depot station through the oil demand prediction model based on the oil volume data;

[0109] According to the oil demand of the oil depot station, the optimal oil distribution plan is matched for the oil depot station through dynamic matching method.

[0110] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 2As shown. The computer device includes a processor, a memory and a network interface connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store static information and dynamic information data. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, the steps in the above method embodiment are implemented.

[0111] Those skilled in the art will understand that Figure 2 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present invention, and does not constitute a limitation on the computer device to which the solution of the present invention is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0112] In addition, the present invention also provides a computer device, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above method embodiment when executing the computer program.

[0113] In addition, the present invention further provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps in the above method embodiment are implemented.

[0114] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided by the present invention can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory or optical memory, etc. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0115] The present invention is not limited to the structures which have been described above and shown in the drawings, and various modifications and changes may be made without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

Claims

1. A dynamic oil storage system, characterized in that: include: A label information establishing unit, used for acquiring oil product storage data corresponding to a plurality of oil depot stations, and establishing label information for the oil product storage data according to the oil depot station information; An oil quantity data acquisition unit is used to acquire the oil quantity data of the oil product storage data corresponding to each tag information according to the tag information; the oil quantity data includes the storage quantity, oil delivery quantity and oil delivery time of different types of oil products; The oil quantity data judgment unit is used to judge whether the storage quantity of at least one oil product in the oil quantity data is less than a preset inventory threshold value, and if so, analyze the oil demand of the oil product at the oil depot station through the oil demand prediction model based on the oil quantity data; The oil distribution matching unit is used to match the optimal oil distribution plan for the oil depot station through a dynamic matching method according to the oil demand of the oil depot station.

2. The oil storage dynamic system according to claim 1, characterized in that: The label information establishing unit comprises: The communication connection establishment module is used to establish communication connections between oil depots in different regions and the monitoring background through the Internet of Things technology; The data receiving module is used to receive the oil storage data uploaded by oil depots in different regions through the monitoring background; The label information attaching module is used to attach the oil depot station label information to the oil product storage data according to the oil depot station label information pre-recorded in the monitoring background.

3. The oil storage dynamic system according to claim 1, characterized in that: The oil quantity data determination unit comprises: It is used to determine whether the storage volume of at least one oil product in the oil volume data is less than the preset inventory threshold. If so, the oil demand of the oil depot station is analyzed based on the oil volume data through the oil demand prediction model; A comparison and judgment module is used to compare the storage volume data of each oil product with a preset inventory threshold and obtain a comparison result; A prediction model building module is used to build a prediction model for the oil demand of each oil product based on the oil quantity data using a feature analysis method; The oil product demand prediction module is used to analyze the oil product demand of the oil depot station according to the oil demand prediction model when it is determined that the storage volume of at least one oil product is less than a preset inventory threshold.

4. The oil storage dynamic system according to claim 3, characterized in that: The method of using the characteristic analysis method to construct the oil demand prediction model for each oil product includes: Collect historical oil volume data of each oil product at the oil depot station and perform feature extraction to obtain a feature set; The obtained feature set is used as input and fed into the pre-selected initial training model; The historical oil demand corresponding to each oil product in the historical oil volume data of each oil product is used as a training standard to train the initial training model to obtain the oil demand prediction model for each oil product.

5. The oil storage dynamic system according to claim 4, characterized in that: The historical oil volume data of each oil product at the oil depot station is collected and feature extracted to obtain a feature set including: Preprocessing the collected historical oil volume data, including data cleaning and standardization; Extracting the historical oil storage volume, historical oil delivery volume and historical oil delivery time from the historical oil volume data as the first time series feature; Extract the daily oil delivery volume of historical oil products from the historical oil volume data, divide the delivery season according to the corresponding delivery time, and use the delivery season as the second time series feature; The first time series feature and the second time series feature are combined to obtain a feature set.

6. The oil storage dynamic system according to claim 1, characterized in that: The oil product distribution matching unit comprises: A capacity assessment module is used to obtain the oil supply source of the oil depot station and assess the oil distribution capacity of the oil supply source; An information acquisition module is used to obtain the available oil type, quantity and location information of the oil supply source in real time; Dynamic matching module, used to match the oil supply source through dynamic matching algorithm according to the oil demand of the oil depot station and the available oil type, quantity, location information and oil distribution capacity of the oil supply source; The planning module is used to formulate oil distribution plans based on the matched oil supply sources, including distribution time, distribution route and transportation method.

7. The oil storage dynamic system according to claim 6, characterized in that: The obtaining of the oil supply source of the oil depot station and evaluating the oil distribution capacity of the oil supply source includes: Based on the oil supply source of the oil depot station, collect the distribution resources of the oil supply source in the preset time period and analyze the change trend of the distribution resources in the preset time period; Analyze the distribution resource index of the oil supply source in a preset time period and the change trend of the distribution resource index in the preset time period to calculate the distribution energy efficiency value of the oil supply source; The distribution capacity of the oil supply source is evaluated and analyzed based on the distribution energy efficiency value of the oil supply source.

8. The oil storage dynamic system according to claim 7, characterized in that: The calculation formula for calculating the distribution energy efficiency value of the oil product supply source by analyzing the distribution resource index of the oil product supply source in the preset time period and the change trend of the distribution resource index in the preset time period is: In the formula, G i represents the distribution energy efficiency value of the i-th distribution resource; H i and H j They represent the distribution resource indicators of the i-th distribution resource and the j-th distribution resource respectively; A i and A j Both represent dimension conversion coefficients; P i and P j They respectively represent the changing trends of the i-th distribution resource and the j-th distribution resource between the preset time periods; n represents the number of distribution resources.

9. The oil storage dynamic system according to claim 7, characterized in that: The oil supply sources matched by the dynamic matching algorithm according to the oil demand of the oil depot station and the available oil types, quantities, location information and oil distribution capabilities of the oil supply sources include: Establish constraints based on the available oil types, quantities, location information and oil distribution capabilities of oil supply sources; Taking minimizing the oil distribution cost as the objective function, a linear programming model is constructed according to the constraints; The linear programming model is solved by linear programming method to obtain the oil supply source that can be used for oil distribution at the oil depot station.

10. A dynamic device for storing oil, characterized in that: The oil storage dynamic device comprises: a processor and a memory for storing instructions executable by the processor; Wherein, the processor is configured to: Obtaining oil storage data corresponding to a number of oil depot stations, and establishing label information for the oil storage data according to the oil depot station information; According to the label information, the oil quantity data of the oil product storage data corresponding to each label information is respectively obtained; the oil quantity data includes the storage quantity, oil delivery quantity and oil delivery time of different types of oil products; Determine whether the storage volume of at least one oil product in the oil volume data is less than a preset inventory threshold; if so, analyze the oil product demand of the oil depot station through the oil demand prediction model based on the oil volume data; According to the oil demand of the oil depot station, the optimal oil distribution plan is matched for the oil depot station through dynamic matching method.

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