Regional energy system day-ahead scheduling method considering seasonal hydrogen storage
By obtaining and organizing weather and scheduling information from previous years, establishing seasonal division and constraints, and establishing a storage model for hydrogen energy storage systems, the problem of insufficient scheduling in the existing technology is solved, and more efficient energy scheduling and loss optimization are achieved.
Patent Information
- Application Number
- CN202411638371.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-16
- Publication Date
- 2025-02-25
AI Technical Summary
In the seasonal energy storage optimization scheduling, the prior art cannot effectively consider the interdependence and special weather conditions during typical week periods, resulting in insufficient precise scheduling.
By obtaining weather information and scheduling information from previous years, statistics and sorting, establishing seasonal division and constraints, establishing storage models for hydrogen energy storage systems, and performing model expression to obtain the optimal solution.
Improve the accuracy of scheduling forecasts, better considering interdependence and special weather conditions during typical week periods, and optimizing energy use and loss.
Smart Images
Figure CN119518976A_ABST
Abstract
Description
Technical Field
[0001] The present invention belongs to the technical field of distribution networks, and in particular relates to a day-ahead scheduling method for a regional energy system taking seasonal hydrogen storage into consideration. Background Art
[0002] The optimal scheduling of seasonal energy storage usually needs to consider time series across seasons or over a year, which is a computationally intensive task. In order to reduce the amount of computation, some researchers have proposed a method of extracting typical cycles, using the supply and demand characteristics of typical cycles to represent the supply and demand characteristics of a certain month or season. There are two problems with this method. First, previous studies generally believe that typical cycles are independent of each other and energy cannot be exchanged between typical cycles; second, previous studies generally believe that the same typical scenario will appear continuously, which will lead to the inability to take into account some special weather conditions, such as sporadic rainy weather. If there is no way to compare the data from previous years, there is no better way to schedule regional energy.
[0003] Therefore, in view of this situation, there is an urgent need to design and produce a day-ahead scheduling method for regional energy systems that takes into account seasonal hydrogen storage to meet actual needs. Summary of the invention
[0004] The purpose of the present invention is to provide a method for day-ahead scheduling of a regional energy system taking into account seasonal hydrogen storage, so as to solve the problems raised in the above-mentioned background technology.
[0005] To achieve the above object, the present invention provides the following technical solutions: A method for day-ahead scheduling of a regional energy system considering seasonal hydrogen storage comprises the following steps: Step 1: Obtain data: collect and sort out weather information and dispatch information from previous years, arrange them in order by date, divide them into regions by season, and indicate the special data; Step 2: Establish constraint conditions: According to the actual situation and factors of use, conduct comprehensive sorting and establish constraint conditions; Step 3: Prediction model: Describe the operation status and energy change status of the hydrogen energy storage system based on the data of previous years, and establish a storage model of the hydrogen energy storage system; Step 4: Model expression: Express the obtained storage model in a way that is easy for the staff to understand and obtain the result.
[0006] In a preferred embodiment, the data obtained by acquiring the data is stored in a cloud server, which is convenient for different staff members to retrieve and convenient for staff members who have obtained permission to modify.
[0007] In a preferred embodiment, the special data to be acquired include data of specific festivals, data of specific solar terms, and data that are too high or too low within a certain period of time, and the data include temperature, humidity, wind speed and weather conditions in each time period.
[0008] In a preferred embodiment, the noted requirement is to enable the staff to easily understand the data changes.
[0009] In a preferred embodiment, the constraints include equipment operation cost constraints, power balance constraints, temperature change constraints, and power supply line transmission power constraints.
[0010] In a preferred embodiment, the equipment operation cost constraints include equipment maintenance costs, hydrogen energy storage costs, electricity purchase costs and electricity sales revenues.
[0011] In a preferred embodiment, the results expressed by the model include the optimal solution, the objective function value of the optimal solution, and the values of the variables, and result analysis and subsequent decision-making are performed based on the output results.
[0012] An electronic device comprises a memory and a processor and computer instructions stored in the memory and running on the processor, wherein the steps are completed when the computer instructions are run by the processor.
[0013] A computer-readable storage medium is used to store computer instructions, and when the computer instructions are executed by a processor, the steps described are completed.
[0014] Compared with the prior art, the technical effects and advantages of the present invention are as follows: The method for day-ahead dispatching of a regional energy system considering seasonal hydrogen storage obtains data in advance, especially weather information and dispatching information of previous years, and collects and sorts them out, compares the data, and thus understands the degree of change each year, and predicts the dispatching data for each period. Compared with direct prediction, the prediction accuracy is higher; The day-ahead dispatching method of the regional energy system considering seasonal hydrogen storage and the design of constraint conditions facilitate the staff to understand the energy loss. The precise grasp of multiple constraint conditions makes the predicted data more accurate. The day-ahead scheduling method for regional energy systems that considers seasonal hydrogen storage can not only predict data more accurately based on data from previous years, but also make the predicted data more accurate based on constraints. BRIEF DESCRIPTION OF THE DRAWINGS
[0015] The above and / or additional aspects and advantages of the present invention will become apparent and easily understood from the description of the embodiments in conjunction with the following drawings, in which: Figure 1 It is a flow chart of the method of the present invention. DETAILED DESCRIPTION
[0016] In the following description, a large number of specific details are provided to provide a more thorough understanding of the present invention. However, it is apparent to those skilled in the art that the present invention can be implemented without one or more of these details. In other examples, in order to avoid confusion with the present invention, some technical features well known in the art are not described.
[0017] Refer to the following Figure 1 The technical solutions of some embodiments of the present invention are described.
[0018] Example 1
[0019] The present invention provides a method for day-ahead scheduling of a regional energy system taking into account seasonal hydrogen storage, such as Figure 1 As shown, Figure 1 It is a flow chart of the method of the present invention, comprising the following steps: Step 1, obtain data: collect and sort out the weather information and dispatch information of previous years, arrange them in sequence according to date, divide them into regions according to seasons, and mark the special data. The special data obtained includes data of specific festivals, data of specific solar terms, and data that is too high or too low in a certain period of time. The data includes temperature, humidity, wind speed and weather conditions in each period. The data can also include other data to ensure the accuracy of the obtained data and make the prediction more accurate. Step 2: Establish constraint conditions: According to the actual use situation and factors, conduct comprehensive sorting and establish constraint conditions. Constraint conditions include equipment operation cost constraint, power balance constraint, temperature change constraint, power transmission power constraint of power supply line. Constraint conditions are also adjusted according to different regions. Constraint conditions in different environments are different. For example, coastal areas are mostly windy and rainy, and northern areas are mostly rainy and snowy. Equipment operation cost constraints include equipment maintenance cost, hydrogen energy storage cost, electricity purchase cost and electricity sales income. The equipment operation cost in different regions is also different. Step 3: Prediction model: Describe the operating status and energy change status of the hydrogen energy storage system based on data from previous years, establish a storage model of the hydrogen energy storage system, and express the storage model in a way that is easy to grasp; Step 4: Model expression: The stored model is expressed in a way that is easy for the staff to understand to obtain the result. The result of the model expression includes the optimal solution, the objective function value of the optimal solution, and the value of the variable. The result analysis and subsequent decision-making are carried out based on the output results.
[0020] The data obtained is stored in the cloud server, which is convenient for different staff to retrieve and for staff with permission to modify.
[0021] The noted requirement is to enable staff to easily understand data changes.
[0022] Example 2
[0023] Based on the same inventive concept, an embodiment of the present invention further provides an electronic device, including a memory and a processor, and computer instructions stored in the memory and running on the processor, and steps completed when the computer instructions are run by the processor.
[0024] Example 3
[0025] Based on the same inventive concept, an embodiment of the present invention further provides a computer-readable storage medium for storing computer instructions, which complete steps when the computer instructions are executed by a processor.
[0026] Example 4
[0027] The present invention provides a method for day-ahead scheduling of a regional energy system taking into account seasonal hydrogen storage, comprising the following steps: Step 1: Obtain data: collect and sort out the weather information and dispatch information of previous years, arrange them in sequence according to date, divide them into regions according to seasons, and mark the special data. The special data obtained include data on specific festivals, data on specific solar terms, and data that is too high or too low in a certain period of time; Step 2: Establish constraint conditions: According to the actual situation and factors of use, conduct comprehensive sorting and establish constraint conditions, which include equipment operation cost constraint, power balance constraint, temperature change constraint, and power transmission power constraint of power supply line; Step 3: Prediction model: Describe the operating status and energy change status of the hydrogen energy storage system based on data from previous years, establish a storage model of the hydrogen energy storage system, and express the storage model in a way that is easy to grasp; Step 4: Model expression: The stored model is expressed in a way that is easy for the staff to understand to obtain the result. The result of the model expression includes the optimal solution, the objective function value of the optimal solution, and the value of the variable. The result analysis and subsequent decision-making are carried out based on the output results.
[0028] Comprehensively comparing Example 2 with Example 1, Example 1 is more comprehensive, while Example 2 is simpler.
[0029] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.
[0030] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.
[0031] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.
[0032] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.
[0033] Finally, it should be noted that the above are only preferred specific implementation modes of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.
Claims
1. A method for day-ahead scheduling of a regional energy system considering seasonal hydrogen storage, characterized in that: The following steps are involved: Step 1. Obtain data: collect and sort out the weather information and dispatch information of previous years, arrange them in sequence by date, divide them into regions according to seasons, and mark the special data; Step 2. Establish constraints: According to the actual situation and factors of use, conduct comprehensive sorting and establish constraints; Step 3. Prediction model: Describe the operation status and energy change status of the hydrogen energy storage system based on the data of previous years, and establish a storage model of the hydrogen energy storage system; Step 4. Model expression: Express the obtained storage model in a way that is easy for the staff to understand and obtain the result.
2. A method for day-ahead scheduling of a regional energy system considering seasonal hydrogen storage according to claim 1, characterized in that: The data obtained by the data acquisition is stored in the cloud server, which is convenient for different staff to retrieve and convenient for staff with permission to modify.
3. A method for day-ahead scheduling of a regional energy system considering seasonal hydrogen storage according to claim 1, characterized in that: The special data obtained include data of specific festivals, data of specific solar terms and data that are too high or too low in a certain period of time. The data include temperature, humidity, wind speed and weather conditions in each time period.
4. The method for day-ahead scheduling of a regional energy system considering seasonal hydrogen storage according to claim 1, characterized in that: The noted requirements are to enable staff to easily understand data changes.
5. The method for day-ahead scheduling of a regional energy system considering seasonal hydrogen storage according to claim 1, characterized in that: The constraints include equipment operation cost constraints, power balance constraints, temperature change constraints, and power supply line transmission power constraints.
6. A method for day-ahead scheduling of a regional energy system considering seasonal hydrogen storage according to claim 5, characterized in that: The equipment operation cost constraints include equipment maintenance costs, hydrogen energy storage costs, electricity purchase costs and electricity sales revenues.
7. The method for day-ahead scheduling of a regional energy system considering seasonal hydrogen storage according to claim 1, characterized in that: The results expressed by the model include the optimal solution, the objective function value of the optimal solution, and the values of variables, and result analysis and subsequent decisions are performed based on the output results.
8. An electronic device, characterized in that: The method comprises a memory and a processor and computer instructions stored in the memory and executed on the processor. When the computer instructions are executed by the processor, the steps of the method for day-ahead scheduling of a regional energy system taking into account seasonal hydrogen storage as described in any one of claims 1 to 7 are completed.
9. A computer-readable storage medium, characterized in that: Used to store computer instructions, which, when executed by a processor, complete the steps of the method for day-ahead scheduling of a regional energy system taking into account seasonal hydrogen storage as described in any one of claims 1 to 7.