An energy scheduling method based on time and space distribution of multi-type energy storage resources

Abstract

The application discloses an energy scheduling method based on space-time distribution of multiple types of energy storage resources. The application comprises the following steps: S1: counting the types of energy resources in the substation area, and dividing the scheduling area according to the power grid topology; S2: integrating the time output characteristics of each energy resource according to the historical energy output of each energy in the scheduling area, and dividing the regulation time period; S3: obtaining the electricity demand of different scheduling areas in each regulation time period, and scheduling the energy in the area; S4: if the energy scheduling in the area cannot meet the electricity demand, then scheduling the energy between areas according to the energy storage accumulation of each scheduling area in the current regulation time period; S5: recording and storing the output of each energy resource and the energy scheduling process. The scheduling area is divided in space, the regulation time period is divided in time, the scene is finely divided in combination with the space-time characteristics, and the consideration is more comprehensive.

Description

Technical Field

[0001] This invention relates to the field of energy dispatching, and in particular to an energy dispatching method based on the spatiotemporal distribution of multiple types of energy storage resources. Background Technology

[0002] Under the dual-carbon goals, vigorously developing a new power system based on new energy sources has become an important measure for the clean and low-carbon transformation of the energy system. However, the spatiotemporal characteristics, operational characteristics, and regulation capabilities of various types of clean energy, such as wind, solar, and hydropower, differ significantly.

[0003] From a spatial perspective, for example, the generation of hydropower relies on a special geographical environment and is subject to geographical limitations, and the dispatch of electricity involves certain electricity transportation costs.

[0004] The multi-timescale uncertainties of new energy sources pose challenges to power grid operation. Different types of energy storage have different response characteristics and capacity levels, making them suitable for power system application scenarios at different timescales. In the short term, the uncertainty of power output from new energy sources such as wind and solar, as well as the volatility of load demand, place higher demands on the power grid's peak-shaving and frequency regulation capabilities. In the long term, wind, solar, and hydropower resources exhibit seasonal fluctuations, making cross-seasonal energy transfer a necessary means to meet the long-term supply and demand balance of electricity.

[0005] Currently, there are integrated energy collaborative operation schemes that consider multiple spatiotemporal scales. For example, a "Multi-Spatiotemporal Scale Collaborative Optimization Operation Method for Distributed Integrated Energy Systems" disclosed in Chinese patent literature (publication number CN113673739A) takes into account the energy input, production, conversion, storage, and consumption stages of the distributed integrated energy system. It considers the differences in response characteristics of various heterogeneous energy flows and establishes a multi-dimensional energy supply and demand balance model for the distributed integrated energy system. Based on this model, a hierarchical collaborative control architecture is established according to the response time and control range of different energy devices. Finally, based on this architecture, a multi-spatiotemporal scale collaborative optimization operation model is established and solved using a mixed-integer linear programming method. However, this scheme only considers a rough spatiotemporal distribution characteristic, resulting in imprecise calculation scenarios. Summary of the Invention

[0006] This invention primarily addresses the problem that existing integrated energy dispatching technologies only consider extensive spatiotemporal distribution characteristics, resulting in inaccurate calculation scenarios; it provides an energy dispatching method based on the spatiotemporal distribution of multiple types of energy storage resources.

[0007] The above-mentioned technical problems of the present invention are mainly solved by the following technical solutions: An energy dispatching method based on the spatiotemporal distribution of multiple types of energy storage resources includes the following steps: S1: Statistical analysis of energy resource types in the distribution area, and division of dispatch areas according to power grid topology; S2: Based on the historical energy output of each energy source in the dispatch area, integrate the temporal output characteristics of each energy resource and divide the control period; S3: Obtain the electricity demand of different dispatch areas during each control period and perform energy dispatch within the area; S4: If energy dispatch within the region cannot meet the electricity demand, then inter-regional energy dispatch will be carried out based on the energy storage accumulation of each dispatch area during the current control period. S5: Records and stores the output of each energy resource and the energy dispatch process.

[0008] The system divides scheduling areas spatially and control time periods temporally, combining spatiotemporal characteristics to create a more comprehensive and detailed scenario segmentation. Scheduling is then performed sequentially within time periods, both within specific areas and between time intervals, resulting in more precise scheduling.

[0009] As a preferred method, dispatching areas are divided based on the power topology coupling locations of different energy resources and the geographical locations of equipment. The specific process is as follows: Construct power topologies with different energy resources as the head devices respectively; Based on the coupling positions of each power topology, determine whether the regions corresponding to the power topologies should be integrated into the first region; Based on the geographical location of each power device in the first region, devices whose distance from adjacent power devices is greater than the distance range threshold are divided into different regions, and the division is further refined to form a scheduling region.

[0010] The geographical areas for power regulation are divided according to the power topology and the geographical location of the equipment, which facilitates power dispatching.

[0011] Preferably, the coupling positions of the power topology include coupling of the middle equipment and isolation of the tail equipment, coupling of the tail equipment, and discontinuous coupling of the topology equipment; When the middle equipment in a power topology is coupled to the tail equipment and isolated, the power topology is divided into the same first region; When tail-end devices are coupled in a power topology, the tail-end coupling region in the power topology is divided into the same first region, and the regions corresponding to power devices in other parts of the same power topology are also divided into the same first region. When devices in a power topology are intermittently coupled, the power topology is divided into the same first region.

[0012] As a preferred method, historical energy output and historical environmental data changes are obtained, and correlation coefficients between various environmental factors and energy output are fitted. The process of fitting the correlation coefficients includes: 1) Qualitative screening of correlation parameters: Several environment-output correlation coordinate systems are constructed by using each environmental factor as the horizontal axis and each energy output as the vertical axis; the historical energy output data and corresponding historical environmental data of each energy resource are plotted in the corresponding environment-output correlation coordinate systems. The data points in the coordinate system are fitted to a smooth curve. The curves that are positively or negatively correlated with the environmental data and the power output data are selected. The corresponding environmental factors are the correlation parameters of the corresponding type of energy storage resources. 2) Quantitatively calculate the correlation coefficient: For the same type of energy resources, environmental factors that are positively correlated with them are classified into the first cluster, and environmental factors that are negatively correlated with them are classified into the second cluster. By treating the correlation coefficients of environmental factors in the first and second clusters as unknowns, a multivariate function is constructed, and the corresponding data is substituted into it to fit and calculate the correlation coefficients.

[0013] First, qualitative screening is performed, followed by quantitative calculation. Historical data is used to quantitatively describe the relationship between environmental factors and the output of various types of energy storage. Then, real-time environmental data is used to predict the output of each type of energy. By combining historical data with real-time data, the accuracy of energy output prediction is improved, and the temporal characteristics of energy output are obtained.

[0014] As a preferred method, the estimated environmental data changes for the whole day are obtained based on weather forecasts; the output characteristics of each energy resource for the whole day are obtained by weighted calculation using correlation coefficients as weights. The process of dividing the regulation time period according to the time output characteristics of each energy resource is as follows: Construct a time-output coordinate system with time as the horizontal axis and energy output as the vertical axis; Plot the calculated energy output variation curve throughout the day in the corresponding time-output coordinate system; The point where the slope k is 0 is taken as the first dividing point; Based on the energy output difference between adjacent first boundary points, threshold comparison is performed to eliminate noise points and obtain the second boundary point; All types of energy output variation curves throughout the day are plotted on the same time-output coordinate system, and the corresponding second dividing points are plotted on the same time axis, with each adjacent second dividing point constituting a time period.

[0015] Dividing time periods according to the characteristics of different types of energy output changes facilitates precise control and coordinated scheduling for each time period.

[0016] As a preferred approach, all first boundary points are traversed, and the energy output difference between adjacent first boundary points and the time difference between adjacent first boundary points are calculated. When the energy storage output difference between adjacent first boundary points is greater than or equal to the boundary difference threshold, the adjacent first boundary points are all second boundary points. When the energy output difference between adjacent first boundary points is less than the boundary difference threshold and the time difference is less than the time threshold, the adjacent first boundary points are assigned to the same fluctuation set. Fluctuation sets with intersections are merged, and the two first boundary points with the largest time difference in each fluctuation set are taken as the second boundary points. Remove all remaining first boundary points.

[0017] Removing interference from boundary points makes the division of time periods more accurate.

[0018] As a preferred option, the process of energy dispatch within the region is as follows: Determine whether the total output of all energy resources in the same dispatch area during the current time period meets the electricity demand; if so, consume the output of each energy source locally; otherwise, call upon historical energy storage resources. Determine whether the total output of all energy storage resources in the current time period within the dispatch area meets the electricity demand by combining the sum of historical energy storage. If so, combine energy output with energy storage resources; otherwise, conduct inter-regional dispatch.

[0019] Preferably, the process of inter-regional energy dispatch is as follows: Obtain the accumulated energy storage within the region after energy dispatch is completed in the current time period; The scheduling area is selected based on the number of objects in the surrounding area that require inter-regional energy dispatch and the energy storage accumulation in each scheduling interval. Based on the remaining electricity demand, energy coordination and dispatch will be carried out between selected dispatch areas.

[0020] As a preferred option, the process for selecting the scheduling region is as follows: For each scheduling region, set a selection flag that is initially set to 0. If there is an object that requires inter-regional energy dispatch, the flag indicating the selection of the dispatch area around that object is incremented by one. The flag indicating the selection of objects requiring inter-regional energy dispatch is always 0; Based on the selected flags sorted from smallest to largest, the scheduling region with the smallest selected flag is selected. Determine whether the energy storage accumulation of the selected dispatch area meets the remaining electricity demand of all surrounding objects that need inter-regional energy dispatch; if so, dispatch according to the scheme; otherwise, select the next dispatch area as the dispatch area for coordinated dispatch based on the ranking.

[0021] As preferred options, energy output includes hydrogen, wind, hydro, thermal, and photovoltaic power; environmental factors include wind strength, wind direction, precipitation intensity, precipitation duration, sunlight angle, sunlight intensity, temperature, and humidity.

[0022] The beneficial effects of this invention are: This solution divides the scheduling area spatially and the control time period temporally. It performs scheduling within the area and between time periods in sequence. Combining spatiotemporal characteristics, it makes detailed division of the scenario, making the scheduling more precise and comprehensive. Attached Figure Description

[0023] Figure 1 This is a flowchart of the energy dispatching method of the present invention. Detailed Implementation

[0024] The technical solution of the present invention will be further described in detail below through embodiments and in conjunction with the accompanying drawings.

[0025] Example: This embodiment presents an energy dispatching method based on the spatiotemporal distribution of multiple types of energy storage resources, such as... Figure 1 As shown, it includes the following steps: S1: Statistically analyze the types of energy resources in the distribution area and divide the dispatching area according to the power grid topology.

[0026] The dispatching areas are divided based on the power topology coupling location of different energy resources and the geographical location of the equipment. The specific process is as follows: 1) Construct power topologies with different energy resources as the head devices. Energy resources include hydrogen, wind, hydro, thermal, and photovoltaic, etc.

[0027] 2) Based on the coupling position of each power topology, determine whether the region corresponding to the power topology is integrated into the first region.

[0028] The coupling locations in a power topology include coupling of mid-level equipment and isolation of tail-level equipment, coupling of tail-level equipment, and discontinuous coupling of topology equipment. Different coupling locations integrate different regional ranges, facilitating joint dispatching of power resources within the region.

[0029] When the middle equipment in a power topology is coupled to the tail equipment and isolated, the power topology is divided into the same first region.

[0030] When tail-end devices are coupled in a power topology, the tail-end coupling region in the power topology is divided into the same first region, and the regions corresponding to power devices in other parts of the same power topology are also divided into the same first region.

[0031] When devices in a power topology are intermittently coupled, the power topology is divided into the same first region.

[0032] 3) Based on the geographical location of each power device in the first region, devices with a distance greater than the distance range threshold between adjacent power devices are divided into different regions, and the division is further refined to form a scheduling region.

[0033] The geographical areas for power regulation are divided according to the power topology and the geographical location of the equipment, which facilitates power dispatching.

[0034] S2: Based on the historical energy output of each energy source in the dispatch area, integrate the time output characteristics of each energy resource and divide the control period.

[0035] S201: Obtain historical energy output and historical environmental data changes, and fit the correlation coefficients between various environmental factors and energy output.

[0036] Energy output includes hydrogen, wind, hydro, thermal, and solar power. Environmental factors include wind strength, wind direction, precipitation intensity, precipitation duration, sunlight angle, sunlight intensity, temperature, and humidity.

[0037] The process of fitting the correlation coefficient includes: 1) Qualitative screening of correlation parameters: Several environmental-output correlation coordinate systems are constructed by combining each environmental factor as the horizontal axis and each energy output as the vertical axis.

[0038] Historical energy output data and corresponding historical environmental data of each energy resource are plotted on the corresponding environmental-output correlation coordinate system.

[0039] The data points in the coordinate system are fitted to a smooth curve. Curves with positive or negative correlation between environmental data and power output data are selected, and the corresponding environmental factors are the correlation parameters of the corresponding type of energy storage resources.

[0040] The fitting process for the smooth curve is as follows: A: Calculate the variance of energy storage output under each environmental data in the same environment-output correlation coordinate system; if the variance of energy storage output is greater than the preset variance threshold, then remove the data point; otherwise, retain it.

[0041] B: Perform K-means processing on the remaining data points to obtain several mean points. Connect the mean points in sequence and smooth the curve to obtain a smooth curve.

[0042] Remove noise and reduce interference from other environmental factors on the judgment.

[0043] 2) Quantitatively calculate the correlation coefficient: For the same type of energy resource, environmental factors that are positively correlated with it are classified into the first cluster, and environmental factors that are negatively correlated with it are classified into the second cluster.

[0044] By treating the correlation coefficients of environmental factors in the first and second clusters as unknowns, a multivariate function is constructed, and the corresponding data is substituted into it to fit and calculate the correlation coefficients.

[0045] First, qualitative screening is performed, followed by quantitative calculation. Historical data is used to quantitatively describe the relationship between environmental factors and the output of various types of energy storage. Then, real-time environmental data is used to predict the output of each type of energy. By combining historical data with real-time data, the accuracy of energy output prediction is improved, and the temporal characteristics of energy output are obtained.

[0046] S202: Obtain the estimated environmental data changes for the entire day based on weather forecasts; using correlation coefficients as weights, calculate the daily output characteristics of each energy resource, expressed as: Among them, P j (t) represents the output of the j-th energy type at time t.

[0047] R ij Let be the correlation coefficient between the i-th environmental factor and the j-th type of energy.

[0048] E i (t) represents the i-th environmental factor collected at time t.

[0049] N represents the total number of environmental factors.

[0050] By combining historical data with real-time data, the accuracy of energy storage output forecasts can be improved.

[0051] S203: The process of dividing the regulation time period according to the time output characteristics of each energy resource is as follows: 1) Construct a time-output coordinate system with time as the horizontal axis and energy output as the vertical axis.

[0052] 2) Plot the calculated energy output variation curve throughout the day in the corresponding time-output coordinate system.

[0053] 3) Take the point where the slope k is 0 as the first dividing point.

[0054] 4) Based on the energy output difference between adjacent first boundary points, threshold comparison is performed to eliminate noise points and obtain the second boundary point.

[0055] The process of removing noise points is as follows: A: Traverse all first boundary points and calculate the energy output difference between adjacent first boundary points and the time difference between adjacent first boundary points.

[0056] B: When the energy storage output difference between adjacent first boundary points is greater than or equal to the boundary difference threshold, the adjacent first boundary points are all second boundary points.

[0057] C: When the energy output difference between adjacent first boundary points is less than the boundary difference threshold and the time difference is less than the time threshold, the adjacent first boundary points are assigned to the same fluctuation set. Fluctuation sets with intersections are merged, and the two first boundary points with the largest time difference in each fluctuation set are taken as the second boundary points.

[0058] D: Remove all remaining first boundary points.

[0059] Removing interference from boundary points makes the division of time periods more accurate.

[0060] 5) Plot the daily output variation curves of all types of energy in the same time-output coordinate system, and plot the corresponding second dividing points on the same time axis, with each adjacent second dividing point being a time period.

[0061] Dividing time periods according to the characteristics of different types of energy output changes facilitates precise control and coordinated scheduling for each time period.

[0062] S3: Obtain the electricity demand of different dispatch areas during each control period and carry out energy dispatch within the area.

[0063] The process of energy dispatch within the region is as follows: Determine whether the total output of all energy resources in the same dispatch area during the current time period meets the electricity demand; if so, consume the output of each energy source locally; otherwise, call upon historical energy storage resources.

[0064] Determine whether the total output of all energy storage resources in the current time period within the dispatch area meets the electricity demand by combining the sum of historical energy storage. If so, combine energy output with energy storage resources; otherwise, conduct inter-regional dispatch.

[0065] S4: If energy dispatch within the region cannot meet the electricity demand, then inter-regional energy dispatch will be carried out based on the energy storage accumulation of each dispatch area during the current control period.

[0066] The process of inter-regional energy dispatch is as follows: 1) Obtain the accumulated energy storage after the completion of energy dispatch within the current time period.

[0067] 2) Select the scheduling area based on the number of objects in the surrounding area that need inter-regional energy scheduling and the energy storage accumulation of each scheduling interval.

[0068] The specific process for selecting the scheduling area is as follows: A: Set a selection flag (flag) that is initially set to 0 for each scheduling region.

[0069] B: If there is an object that requires inter-regional energy dispatch, then the flag indicating the selection of the dispatch area around that object is incremented by one.

[0070] C: The flag for selecting objects that require inter-regional energy dispatch is always 0.

[0071] D: Sort the selected flags from smallest to largest and select the scheduling region with the smallest selected flag.

[0072] E: Determine whether the energy storage accumulation of the selected dispatch area meets the remaining electricity demand of all surrounding objects that need inter-regional energy dispatch; if so, dispatch according to the scheme; otherwise, select the next dispatch area as the dispatch area for coordinated dispatch according to the ranking.

[0073] 3) Based on the remaining electricity demand, energy coordination dispatch between selected dispatch areas is carried out.

[0074] S5: Records and stores the output of each energy resource and the energy dispatch process.

[0075] The solution in this embodiment divides the scheduling area spatially and the control time period temporally. It performs scheduling within the area and scheduling between time periods in sequence, combining spatiotemporal characteristics to make the scene more detailed and the scheduling more comprehensive.

[0076] It should be understood that the embodiments are for illustrative purposes only and are not intended to limit the scope of the invention. Furthermore, it should be understood that after reading the teachings of this invention, those skilled in the art can make various alterations or modifications to the invention, and these equivalent forms also fall within the scope defined by the appended claims.

Claims

1. An energy dispatching method based on the spatiotemporal distribution of multiple types of energy storage resources, characterized in that, Includes the following steps: S1: Statistical analysis of energy resource types in the distribution area, and division of dispatch areas according to power grid topology; S2: Based on the historical energy output of each energy source in the dispatch area, integrate the temporal output characteristics of each energy resource and divide the control period; S201: Correlation coefficients between various environmental factors and energy output; S202: Using correlation coefficients as weights, the daily output characteristics of each energy resource are obtained through weighted calculation. S203: Divide the control period according to the time output characteristics of each energy resource; Construct a time-output coordinate system, and plot the calculated energy output variation curve throughout the day in the corresponding time-output coordinate system; The point where the slope k is 0 is taken as the first dividing point; Based on the energy output difference between adjacent first boundary points, threshold comparison is performed to eliminate noise points and obtain the second boundary point; All types of energy output variation curves throughout the day are plotted on the same time-output coordinate system, and the corresponding second dividing points are plotted on the same time axis, with each adjacent second dividing point constituting a time period; S3: Obtain the electricity demand of different dispatch areas during each control period and perform energy dispatch within the area; S4: If energy dispatch within the region cannot meet the electricity demand, then inter-regional energy dispatch will be carried out based on the energy storage accumulation of each dispatch area during the current control period. S5: Records and stores the output of each energy resource and the energy dispatch process.

2. The energy dispatching method based on the spatiotemporal distribution of multiple types of energy storage resources according to claim 1, characterized in that, The dispatching areas are divided based on the power topology coupling location of different energy resources and the geographical location of the equipment. The specific process is as follows: Construct power topologies with different energy resources as the head devices respectively; Based on the coupling positions of each power topology, determine whether the regions corresponding to the power topologies should be integrated into the first region; Based on the geographical location of each power device in the first region, devices whose distance from adjacent power devices is greater than the distance range threshold are divided into different regions, and the division is further refined to form a scheduling region.

3. The energy dispatching method based on the spatiotemporal distribution of multiple types of energy storage resources according to claim 2, characterized in that, The coupling positions of the power topology include coupling of the middle equipment and isolation of the tail equipment, coupling of the tail equipment, and discontinuous coupling of the topology equipment; When the middle equipment in a power topology is coupled to the tail equipment and isolated, the power topology is divided into the same first region; When tail-end devices are coupled in a power topology, the tail-end coupling region in the power topology is divided into the same first region, and the regions corresponding to power devices in other parts of the same power topology are also divided into the same first region. When devices in a power topology are intermittently coupled, the power topology is divided into the same first region.

4. The energy dispatching method based on the spatiotemporal distribution of multiple types of energy storage resources according to claim 1, characterized in that, Obtain historical energy output and historical environmental data changes, and fit the correlation coefficients between various environmental factors and energy output. The process of fitting the correlation coefficients includes: 1) Qualitative screening of correlation parameters: Several environment-output correlation coordinate systems are constructed by combining each environmental factor as the horizontal axis and each energy output as the vertical axis. Historical energy output data and corresponding historical environmental data of each energy resource are plotted in the corresponding environmental-output coordinate system. The data points in the coordinate system are fitted to a smooth curve. The curves that are positively or negatively correlated with the environmental data and the power output data are selected. The corresponding environmental factors are the correlation parameters of the corresponding type of energy storage resources. 2) Quantitatively calculate the correlation coefficient: For the same type of energy resources, environmental factors that are positively correlated with them are classified into the first cluster, and environmental factors that are negatively correlated with them are classified into the second cluster. By treating the correlation coefficients of environmental factors in the first and second clusters as unknowns, a multivariate function is constructed, and the corresponding data is substituted into it to fit and calculate the correlation coefficients.

5. An energy dispatching method based on the spatiotemporal distribution of multiple types of energy storage resources according to claim 1 or 4, characterized in that, The forecast of environmental data changes throughout the day is obtained based on weather forecasts; the daily output characteristics of each energy resource are obtained by weighted calculation using correlation coefficients as weights. The process of dividing the regulation time period according to the time output characteristics of each energy resource is as follows: Construct a time-output coordinate system with time as the horizontal axis and energy output as the vertical axis.

6. The energy dispatching method based on the spatiotemporal distribution of multiple types of energy storage resources according to claim 5, characterized in that, Iterate through all first boundary points and calculate the energy output difference between adjacent first boundary points and the time difference between adjacent first boundary points; When the energy storage output difference between adjacent first boundary points is greater than or equal to the boundary difference threshold, the adjacent first boundary points are all second boundary points. When the energy output difference between adjacent first boundary points is less than the boundary difference threshold and the time difference is less than the time threshold, the adjacent first boundary points are assigned to the same fluctuation set. Fluctuation sets with intersections are merged, and the two first boundary points with the largest time difference in each fluctuation set are taken as the second boundary points. Remove all remaining first boundary points.

7. The energy dispatching method based on the spatiotemporal distribution of multiple types of energy storage resources according to claim 1, characterized in that, The process of energy dispatch within the region is as follows: Determine whether the total output of all energy resources in the same dispatch area during the current time period meets the electricity demand; if so, consume the output of each energy source locally; otherwise, call upon historical energy storage resources. Determine whether the total output of all energy storage resources in the current time period within the dispatch area meets the electricity demand by combining the sum of historical energy storage. If so, combine energy output with energy storage resources; otherwise, conduct inter-regional dispatch.

8. An energy dispatching method based on the spatiotemporal distribution of multiple types of energy storage resources according to claim 1, 6, or 7, characterized in that, The process of inter-regional energy dispatch is as follows: Obtain the accumulated energy storage within the region after energy dispatch is completed in the current time period; The scheduling area is selected based on the number of objects in the surrounding area that require inter-regional energy dispatch and the energy storage accumulation in each scheduling interval. Based on the remaining electricity demand, energy coordination and dispatch will be carried out between selected dispatch areas.

9. An energy dispatching method based on the spatiotemporal distribution of multiple types of energy storage resources according to claim 8, characterized in that, The specific process for selecting the scheduling area is as follows: For each scheduling region, set the selection flag to 0 initially; If there is an object that requires inter-regional energy dispatch, the flag indicating the selection of the dispatch area around that object is incremented by one. The flag indicating the selection of objects requiring inter-regional energy dispatch is always 0; Based on the selected flags sorted from smallest to largest, the scheduling region with the smallest selected flag is selected. Determine whether the energy storage accumulation of the selected dispatch area meets the remaining electricity demand of all surrounding objects that need inter-regional energy dispatch; if so, dispatch according to the scheme; otherwise, select the next dispatch area as the dispatch area for coordinated dispatch based on the ranking.

10. An energy dispatching method based on the spatiotemporal distribution of multiple types of energy storage resources according to claim 4, characterized in that, Energy output includes hydrogen, wind, hydro, thermal, and solar power; environmental factors include wind strength, wind direction, precipitation intensity, precipitation duration, sunlight angle, sunlight intensity, temperature, and humidity.

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