Park multi-energy resource scheduling method, system, equipment and medium

Abstract

The invention provides a park multi-energy resource scheduling method, system and device and a medium, and the method comprises the steps: determining the energy consumption complementation amount among various energy sources in a park according to the complementation relation of each energy consumption, and constructing a supply relation graph of energy scheduling in the park through the conflict relation between all the energy consumption complementation amounts and each energy consumption; constructing a demand relationship graph of energy scheduling in the park according to demand data in the scheduling demand information and a topological association relationship between various energy demands in the park; atlas fusion is carried out on energy reserve in resource scheduling through the supply relation atlas and the demand relation atlas, fusion intervals of various energy reserve quantities in the park are obtained, and dynamic scheduling is carried out on the multi-energy resources of the park based on the fusion intervals of the energy reserve quantities. According to the scheme, map fusion based on energy supply and demand information can be realized in park multi-energy resource scheduling, so that the supply and demand matching degree in park multi-energy resource scheduling can be improved.

Description

Technical Field

[0001] This application relates to the technical field of park resource scheduling. More specifically, this application relates to a method, system, device, and medium for multi-energy resource scheduling in a park. Background Art

[0002] In recent years, with the rapid development of information technology, artificial intelligence, and big data, the scheduling of multi-energy resources in parks has gradually become intelligent and automated. With the help of technologies such as the Internet of Things and machine learning, it is possible to monitor and predict various energy demands and supplies in real time, optimize scheduling strategies. At the same time, it provides a new solution for park energy management and improves the efficiency and reliability of energy scheduling.

[0003] In the scheduling of multi-energy resources in parks, traditional scheduling strategies often rely on historical data for demand forecasting. However, due to the large temporal and spatial volatility of energy demand, traditional methods often ignore the uncertainty and diversity of demand, resulting in demand forecasting deviations, which in turn lead to energy supply surpluses or shortages. And traditional scheduling strategies usually schedule in a "conservative" way. To ensure the security of energy supply, a large reserve is often set to prevent shortages during peak demand. Although the conservative strategy ensures security, it causes excessive redundancy in energy supply, resulting in unnecessary resource waste. The graph fusion method refines and quantifies the supply relationship and demand pattern by combining multi-dimensional information of energy supply and demand. Therefore, how to achieve graph fusion based on energy supply and demand information in the scheduling of multi-energy resources in parks, so as to improve the supply-demand matching degree in the scheduling of multi-energy resources in parks is a difficult problem faced by the industry. Summary of the Invention

[0004] This application provides a method, system, device, and medium for multi-energy resource scheduling in a park, which can achieve graph fusion based on energy supply and demand information in the scheduling of multi-energy resources in parks, thereby improving the supply-demand matching degree in the scheduling of multi-energy resources in parks.

[0005] In a first aspect, this application provides a method for multi-energy resource scheduling in a park, including: Collect resource supply information and scheduling demand information of various energies in the park; Extract the complementary relationship and conflict relationship of energy consumption between various energies from the resource supply information, determine the complementary amount of energy consumption between various energies in the park according to the complementary relationship of each energy consumption, and then construct a supply relationship graph of energy scheduling in the park through all the complementary amounts of energy consumption and the conflict relationship of each energy consumption; Determine the demand pattern of multi-energy resources in the park according to the demand data in the scheduling demand information, and construct a demand relationship graph of energy scheduling in the park through the demand pattern and the topological association relationship between various energy demands in the park; Fuse the energy reserves in resource scheduling through the supply relationship graph and the demand relationship graph to obtain the fusion interval of various energy reserve quantities in the park, and perform dynamic scheduling of the multi-energy resources in the park based on the fusion interval of each energy reserve quantity.

[0006] In some embodiments, extracting the complementary relationship and conflict relationship of energy consumption between various energies from the resource supply information specifically includes: Extract the energy consumption complementary quantity and conflict loss quantity between various energies from the resource supply information; Determine the complementary relationship of energy consumption between various energies through all the energy consumption complementary quantities; Determine the conflict relationship of energy consumption between various energies through all the conflict loss quantities.

[0007] In some embodiments, constructing the supply relationship graph of energy scheduling in the park through all the energy consumption complementary quantities and the conflict relationship of each energy consumption specifically includes: Obtain the topological structure of energy supply in the multi-energy resources of the park; Extract the conflict loss quantity between various energies from the conflict relationship of each energy consumption; Perform strength constraint on the relationship edges between each node in the topological structure of the energy supply through each conflict loss quantity and each energy consumption complementary quantity, and then obtain the supply relationship graph of energy scheduling in the park.

[0008] In some embodiments, determining the demand pattern of the multi-energy resources in the park according to the demand data in the scheduling demand information specifically includes: Extract the time-domain distribution characteristics and space-domain distribution characteristics of various energy demands from the demand data in the scheduling demand information; Determine the demand pattern of the multi-energy resources in the park through all the time-domain distribution characteristics and all the space-domain distribution characteristics.

[0009] In some embodiments, constructing the demand relationship graph of energy scheduling in the park through the demand pattern and the topological correlation relationship between various energy demands in the park specifically includes: Identify the peak-valley characteristics and regional load characteristics of various energy demands in the park through the demand pattern; Extract the topological structure and correlation value between the energy demands in the park from the topological correlation relationship between various energy demands in the park; Perform strength constraint on the relationship edges between each node in the topological structure through all the correlation values, the peak-valley characteristics of various energy demands and the regional load characteristics, and then obtain the demand relationship graph of energy scheduling in the park.

[0010] In some embodiments, performing dynamic scheduling of the multi-energy resources in the park based on the fusion interval of each energy reserve quantity specifically includes: For various energies in the park, when the reserve quantity of the energy in the park is not within the fusion interval of the reserve quantity, the reserve quantity of the energy in the park is replenished, thereby completing the dynamic scheduling of the multi-energy resources in the park.

[0011] In some embodiments, the multi-energy resources in the park include electric energy, thermal energy, cold energy, natural gas, and solar energy.

[0012] In a second aspect, the present application provides a multi-energy resource scheduling system for a park, including: An acquisition module, configured to acquire resource supply information and scheduling demand information of various energies in the park; A processing module, configured to extract the complementary relationship and conflict relationship of energy consumption among various energies from the resource supply information, determine the energy consumption complementarity amount among various energies in the park according to the complementary relationship of each energy consumption, and then construct a supply relationship map of energy scheduling in the park through all the energy consumption complementarity amounts and the conflict relationship of each energy consumption; The processing module is further configured to determine the demand pattern of the multi-energy resources in the park according to the demand data in the scheduling demand information, and construct a demand relationship map of energy scheduling in the park through the demand pattern and the topological association relationship among the demands of various energies in the park; An execution module, configured to perform map fusion on the energy reserve in the resource scheduling through the supply relationship map and the demand relationship map to obtain a fusion interval of the reserve quantity of various energies in the park, and perform dynamic scheduling on the multi-energy resources in the park based on the fusion interval of each energy reserve quantity.

[0013] In a third aspect, the present application provides a computer device, where the computer device includes a memory and a processor, the memory is used to store a computer program, and the processor is used to call and run the computer program from the memory, so that the computer device executes the above-mentioned multi-energy resource scheduling method for the park.

[0014] In a fourth aspect, the present application provides a computer-readable storage medium, where instructions or codes are stored in the computer-readable storage medium, and when the instructions or codes are run on a computer, the computer is enabled to execute the above-mentioned multi-energy resource scheduling method for the park.

[0015] The technical solutions provided by the disclosed embodiments of the present application have the following beneficial effects: In a method, system, device and medium for multi - energy resource scheduling in a park provided by the present application, resource supply information and scheduling demand information of various energies in the park are collected; the complementary relationship and conflict relationship of energy consumption among various energies are extracted from the resource supply information, the complementary amount of energy consumption among various energies in the park is determined according to the complementary relationship of each energy consumption, and then a supply relationship map of energy scheduling in the park is constructed through all the complementary amounts of energy consumption and the conflict relationship of each energy consumption; the demand mode of multi - energy resources in the park is determined according to the demand data in the scheduling demand information, and a demand relationship map of energy scheduling in the park is constructed through the demand mode and the topological correlation relationship among various energy demands in the park; the energy reserves in resource scheduling are subjected to map fusion through the supply relationship map and the demand relationship map to obtain a fusion interval of the reserve amounts of various energies in the park, and the multi - energy resources in the park are dynamically scheduled based on the fusion interval of each energy reserve amount.

[0016] It can be seen that in the present application, the energy reserves in resource scheduling are subjected to map fusion through the supply relationship map and the demand relationship map to obtain a fusion interval of the reserve amounts of various energies in the park, and the multi - energy resources in the park are dynamically scheduled based on the fusion interval of each energy reserve amount. First of all, in the process of determining the supply relationship map, the complementary relationship and conflict relationship of energy consumption among various energies are extracted from the resource supply information, and then the state of energy supply and the interaction mode between supply and demand in the multi - energy resources of the park are calculated. The complementary amount of energy consumption reflects the cooperative relationship between different energies, while the conflict relationship reveals the possible resource conflicts that may occur when different energies are used simultaneously. The supply strategy of various energies can be dynamically adjusted to minimize resource waste and conflict phenomena to the greatest extent. The supply relationship map can provide a dynamic and adjustable energy supply framework for the park, enabling the cooperative effect between different energies to be fully utilized, thus improving the supply - demand matching degree in the multi - energy resource scheduling of the park. Then, the establishment of the demand relationship map can accurately reflect the spatio - temporal characteristics of each energy demand, regional load characteristics and peak - valley fluctuation rules, so as to identify the energy demand patterns in different time periods and regions, and then provide accurate demand prediction for the supply side, which helps the park to reasonably plan energy supply, avoid uneven energy supply, ensure that the supply can quickly respond to demand fluctuations during peak hours, and reduce unnecessary reserves and waste during low - demand periods. In addition, the demand relationship map can help the park flexibly adjust the resource allocation strategy to adapt to the changing demand environment and further improve the supply - demand matching degree of energy scheduling. To sum up, based on the above - mentioned scheme, map fusion based on energy supply and demand information can be realized in the multi - energy resource scheduling of the park, thereby improving the supply - demand matching degree in the multi - energy resource scheduling of the park. Brief Description of the Drawings

[0017] To more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the accompanying drawings required for the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0018] Figure 1 is an exemplary flowchart of a multi - energy resource scheduling method for a park according to some embodiments of the present application; Figure 2 is a schematic flowchart of multi - energy resource scheduling in a park according to some embodiments of the present application; Figure 3 is a schematic flowchart of realizing map fusion according to some embodiments of the present application; Figure 4 is a schematic structural diagram of a multi - energy resource scheduling system for a park according to some embodiments of the present application; Figure 5 is a schematic structural diagram of a computer device for realizing the multi - energy resource scheduling method of a park according to some embodiments of the present application. Detailed implementation manners

[0019] To better understand the technical solutions of the present application, the following will combine the accompanying drawings of the specification and specific implementation manners to elaborate on the technical solutions of the present application in detail.

[0020] Refer to Figure 1 , this figure is an exemplary flowchart of a multi - energy resource scheduling method for a park according to some embodiments of the present application. The multi - energy resource scheduling method for the park mainly includes the following steps: In step 101, collect the resource supply information and scheduling demand information of various energies in the park.

[0021] It should be noted that in the present application, the resource supply information represents the source, scale, and time of energy supply in the park, and the scheduling demand information represents the demand scale and time of energy consumption. The multi - energy resources in the park include electric energy, heat energy, cold energy, natural gas, and solar energy.

[0022] In specific implementation, for various energies in the park, the supply records and demand records of the energy within a specified time period (by default, the most recent month) can be collected. The set of all supply records is used as the resource supply information of the energy, and the set of all demand records is used as the scheduling demand information of the energy. Through the above method, the resource supply information and scheduling demand information of various energies in the park can be obtained. Among them, the supply record includes the supply supplement amount and mutual loss amount of other energies in each supply. The supply supplement amount represents the supplement value between different energy demands in the park's resource scheduling. For example, there is a demand complementarity between solar power generation and the power grid during low-load periods. The mutual loss amount represents the energy loss caused by mutual competition and resource surplus between different energies in the park. For example, when there is sufficient natural gas supply, a high grid load may lead to overproduction of electricity and energy waste, and there is a certain conflict loss between natural gas and electricity.

[0023] In some embodiments, referring to Figure 2 As described, this figure is a schematic flowchart of the multi-energy resource scheduling in the park shown in some embodiments of the present application. This figure shows an efficient resource management mechanism that optimizes resource allocation and configuration through real-time monitoring and business prediction. First, the system tracks the usage status of current resources through the real-time monitoring function, and at the same time uses business prediction to estimate the resource requirements in the short term. This information is used to guide the decision-making of resource allocation and resource configuration to ensure that resources can be reasonably scheduled according to user needs and system load.

[0024] In the multi-energy resource scheduling in the park, resources are divided into two categories: available resources and dormant resources. Available resources are the resources that can currently be allocated to users for use, while dormant resources are the resources that are temporarily unused and in a standby state. Through the intelligent management of the resource scheduling module, these resources are effectively allocated to the virtual resource pool to meet the needs of users; the virtual resource pool, as a centralized resource management platform, can dynamically adjust resource allocation according to the results of real-time monitoring and business prediction to ensure the efficient use of resources and the stable operation of the system.

[0025] In step 102, the complementary relationship and conflict relationship of energy consumption between various energies are extracted from the resource supply information. According to the complementary relationship of each energy consumption, the energy consumption complement amount between various energies in the park is determined, and then the supply relationship map of energy scheduling in the park is constructed through all the energy consumption complement amounts and the conflict relationships of each energy consumption.

[0026] In some embodiments, the extraction of the complementary relationship and conflict relationship of energy consumption between various energies from the resource supply information can be implemented by the following steps: Extract the energy consumption complement amount and conflict loss amount between various energies from the resource supply information; Determine the complementary relationship of energy consumption among various energy sources through all the complementary energy consumption quantities; Determine the conflict relationship of energy consumption among various energy sources through all the conflict loss quantities.

[0027] It should be noted that in this application, the conflict relationship represents the influence intensity of resource competition among different energy sources, the conflict loss quantity represents the energy loss caused by mutual competition and resource surplus among different energy sources in the park; the complementary relationship represents the interdependent relationship among different energy supplies in the park, and the complementary energy consumption quantity represents the mutual supplement quantity among different energy sources in the park.

[0028] When specifically implemented, first, for various energy sources in the resource supply information, extract the average value of all supply supplement quantities between the energy source and other energy sources from each supply record in the resource supply information as the complementary energy consumption quantity, and extract the average value of all mutual loss quantities between the energy source and other energy sources from each supply record in the resource supply information as the conflict loss quantity. Through the above method, the complementary energy consumption quantity and conflict loss quantity between various energy sources and other energy sources can be obtained, and thus the complementary energy consumption quantity and conflict loss quantity among various energy sources can be obtained; then, the set of all complementary energy consumption quantities can be used as the complementary relationship of energy consumption among various energy sources; finally, the set of all conflict loss quantities can be used as the conflict relationship of energy consumption among various energy sources.

[0029] In some embodiments, determining the complementary energy consumption quantity among various energy sources in the park according to the complementary relationship of each energy consumption can be implemented by the following method, that is: for various energy sources in the park, obtain the complementary energy consumption quantity between the energy source and other energy sources from the complementary relationship of each energy consumption. Through the above method, the complementary energy consumption quantity between various energy sources and other energy sources can be obtained, and thus the complementary energy consumption quantity among various energy sources in the park can be obtained.

[0030] It should be noted that the complementary energy consumption quantity reflects the cooperative relationship among different energy sources, while the conflict relationship reveals the possible resource conflicts that may occur when certain energy sources are used simultaneously. The supply strategy of various energy sources can be dynamically adjusted to minimize resource waste and conflict phenomena. Specifically, when the supply quantity of a certain energy source is greater than the demand, the system can adjust the energy flow and preferentially allocate redundant resources to other scarce energy sources to optimize the supply-demand relationship, thereby avoiding energy supply shortages or excessive waste.

[0031] In some embodiments, constructing the supply relationship map of energy dispatch in the park through all the complementary energy consumption quantities and the conflict relationship of each energy consumption can be implemented by the following steps: Obtain the topological structure of energy supply in the multi-energy resources of the park; Extract the conflict loss quantity between various energy sources from the conflict relationship of each energy consumption; Intensity constraints are imposed on the relationship edges between each node in the topological structure of the energy supply through each conflict loss amount and each energy consumption complementary amount, thereby obtaining a supply relationship map for energy scheduling in the park.

[0032] It should be noted that in this application, the supply relationship map is a map representing the supply relationship between multi-energy resources in the park; the topological structure of the energy supply refers to the distribution nodes of various energies in the park and the interaction relationship between the distribution nodes. The nodes of the topological structure represent different energies, and the edges represent the relationship of energy flow or energy conversion.

[0033] When specifically implemented, first, the topological structure of the energy supply in the multi-energy resources of the park can be obtained from the central control console of the park; then, the conflict loss amounts between various energies can be extracted from the conflict relationships of each energy consumption; finally, for the relationship edges between each node in the topological structure of the energy supply, the energies corresponding to the two nodes of the relationship edge can be obtained. The difference between the complementary amount and the conflict loss amount between the two energies can be used as the intensity constraint value of the relationship edge. Through the above method, the intensity constraint values of the relationship edges between each node in the topological structure of the energy supply can be obtained, thereby completing the intensity constraint of the relationship edges in the topological structure of the energy supply. The topological structure of the energy supply after intensity constraint can be used as the supply relationship map for energy scheduling in the park.

[0034] In step 103, according to the demand data in the scheduling demand information, the demand pattern of the multi-energy resources in the park is determined, and a demand relationship map for energy scheduling in the park is constructed through the demand pattern and the topological association relationship between various energy demands in the park.

[0035] In some embodiments, determining the demand pattern of the multi-energy resources in the park according to the demand data in the scheduling demand information can be implemented by the following steps: Extract the time-domain distribution characteristics and spatial distribution characteristics of various energy demands from the demand data in the scheduling demand information; Determine the demand pattern of the multi-energy resources in the park through all the time-domain distribution characteristics and all the spatial distribution characteristics.

[0036] It should be noted that in this application, the demand pattern refers to the overall regular performance of various energy demands in the park in the time domain and space; the time-domain distribution characteristics represent the change situation of various energy demands in the park in different time periods. The time-domain distribution characteristics reflect the fluctuation characteristics of energy demand over time, such as peak periods, low periods, and periodic fluctuations; the spatial distribution characteristics represent the spatial differences of various energy demands in the park between different regions or different energy users. The spatial distribution characteristics describe the distribution characteristics of energy demand in space, such as certain regions having higher demands for electricity or heat energy, while other regions are relatively lower.

[0037] In specific implementation, first, for various energy sources, the set of demand records of the energy sources in the scheduling demand information can be used as demand data. Thus, time series analysis algorithms can be used to extract the peak periods, trough periods, periodic fluctuations, and regional demand volumes of the demands in each demand record in the demand data. The set of all peak periods, trough periods, and periodic fluctuations can be used as the time-domain distribution characteristics of the energy demand, and clustering algorithms (such as K-means clustering) can be used to cluster the regional demand volumes of different regions in the park in the demand data, so as to identify the regional demand volumes of the clustering regions in different clustering clusters. The set of all regional demand volumes can be used as the spatial distribution characteristics of the energy demand. Through the above methods, the time-domain distribution characteristics and spatial distribution characteristics of various energy demands can be obtained. Then, the set of all time-domain distribution characteristics and all spatial distribution characteristics can be used as the demand patterns of the multi-energy resources in the park.

[0038] In some embodiments, constructing a demand relationship graph of energy scheduling in the park through the topological association relationship between the demand patterns and various energy demands in the park can be implemented by the following steps: Identify the peak-valley characteristics and regional load characteristics of various energy demands in the park through the demand patterns; Extract the topological structure and association values between the energy demands in the park from the topological association relationship between various energy demands in the park; Perform intensity constraints on the relationship edges between the nodes in the topological structure through all the association values, the peak-valley characteristics, and the regional load characteristics of various energy demands, so as to obtain the demand relationship graph of energy scheduling in the park.

[0039] It should be noted that in this application, the demand relationship graph; the topological association relationship refers to the distribution nodes of various energy demands in the park and the demand associations between the distribution nodes; the topological structure represents the distribution structure of the energy demand nodes in the park; the association value; the peak-valley characteristics reflect the intensity and regularity of the demand fluctuations in the park; the regional load characteristics represent the distribution characteristics of the energy demands in each region in the park.

[0040] In specific implementation, first, for various energy demands, obtain the time-domain distribution characteristics and spatial distribution characteristics of the energy demands from the demand pattern. Then, screen out the overlapping periods from all peak periods in the time-domain distribution characteristics as peak sub-characteristics, and screen out the overlapping periods from all low periods in the time-domain distribution characteristics as underestimated sub-characteristics. The set of peak sub-characteristics and low sub-characteristics can be used as the peak-valley characteristics of the energy demands. Obtain the average value of the demand quantities of all regions from the spatial distribution characteristics as the regional load characteristics of the energy demands. Then, the topological correlation relationship of the energy supply in the multi-energy resources of the park can be obtained from the central control console of the park. The spatial structure of the distribution nodes of various energy demands in the topological correlation relationship can be used as the topological structure between the energy demands in the park, and the initial quantization value of the demand correlation between the distribution nodes in the topological correlation relationship can be used as the correlation value between the energy demands in the park. Finally, initialize a shortest path model based on graph theory algorithms. The peak-valley characteristics of various energy demands can be used as the time-domain constraint adjustment in this shortest path model, the regional load characteristics of various energy demands can be used as the spatial constraint adjustment in the shortest path model, the topological structure can be used as the constraint target of the shortest path model, and each correlation value can be used as the initial path length of the constraint target in the shortest path model. Use this shortest path model to perform intensity constraints on the relationship edges between each node in the constraint target, and the result of the intensity constraint of this shortest path model can be updated to the relationship edges in the topological structure, so that the updated topological structure can be used as the demand relationship map for energy scheduling in the park.

[0041] It should be noted that the shortest path model is a graph theory algorithm model, aiming to meet the time-domain, spatial constraints and topological structure objectives in the multi-energy resource scheduling of the park by optimizing the path length. This shortest path model takes the peak-valley characteristics of the energy demands as the time-domain constraint adjustment, the regional load characteristics of the energy demands as the spatial constraint adjustment, and the topological structure of the park as the constraint target. The shortest path between each node is calculated through the shortest path algorithm. During the calculation process, the correlation value is used as the initial path length of each relationship edge in the constraint target. The shortest path algorithm optimizes the energy flow and scheduling efficiency by adjusting the intensity (such as distance) of the path. Finally, by updating the intensity value of the relationship edges in the topological structure, a new demand relationship map is formed to help more accurately reflect the dynamic changes and optimization results of energy scheduling in the park.

[0042] In step 104, map fusion is performed on the energy reserves in the resource scheduling through the supply relationship map and the demand relationship map to obtain the fusion interval of the reserve quantities of various energies in the park, and dynamic scheduling of the multi-energy resources of the park is performed based on the fusion interval of each energy reserve quantity.

[0043] In some embodiments, through the supply relationship graph and the demand relationship graph, graph fusion is performed on the energy reserve in resource scheduling to obtain the fusion interval of various energy reserve amounts in the park. Refer to Figure 3 As described, this figure is a schematic flowchart of implementing graph fusion in some embodiments of the present application. In this embodiment, graph fusion can be implemented by the following steps: In step 1041, the supply impact factor and the demand impact factor of the energy reserve in resource scheduling are determined through the supply and demand relationships of various energies in the park; In step 1042, the fusion information of various energy reserve amounts in the park is determined according to the supply impact factor and the demand impact factor; In step 1043, based on the fusion information, the supply relationship graph and the demand relationship graph are fused, and then the fusion interval of various energy reserve amounts in the park is obtained.

[0044] It should be noted that in the present application, the supply impact factor refers to the degree of influence of the energy supply situation in the park on the reserve demand; the demand impact factor refers to the degree of influence of the fluctuation of the energy demand in the park on the energy reserve amount; the supply and demand relationship represents the interdependence and influence relationship between the energy supply situation and the demand pattern in the park. The supply and demand relationship includes energy redundancy, supply sufficiency, demand volatility, and demand concentration. Energy redundancy represents the proportion of the redundant part in the energy supply in the park, and energy redundancy = (supply amount - demand amount) / demand amount. Specifically, when calculating, the supply amount and demand amount at each moment in the historical record can be collected, and then the average value of a large number of energy redundancies can be calculated as the energy redundancy in the supply and demand relationship; the degree to which the energy supply in the park can meet the demand, supply sufficiency = total supply amount / total demand amount. Specifically, when calculating, the total supply amount and total demand amount within a specified time period (by default, within the most recent 1 day) can be collected for calculation; demand volatility reflects the intensity of the change of the energy demand in the park over time. In areas with large volatility, the demand is unstable and more reserves and scheduling flexibility are required. The standard deviation of all collected demand amounts can be used as the demand volatility; demand concentration represents the spatial distribution characteristics of the energy demand in the park. The ratio of the standard deviation to the average value of all collected demand amounts can be used as the demand concentration.

[0045] In specific implementation, first, the supply impact factor and demand impact factor of energy reserves in resource scheduling can be determined based on the supply-demand relationships of various energies in the park, which can be achieved in the following way: for various energies in the park, the energy redundancy, supply sufficiency, demand volatility, and demand concentration of the energy can be obtained from the supply-demand relationship of the energy. The ratio of the supply sufficiency to the energy redundancy can be used as the impact of the reserve volume of the energy on the supply, and the ratio of the demand concentration to the demand volatility can be used as the impact of the reserve volume of the energy on the demand. Through the above method, the impact of the reserve volume of various energies on the supply and demand can be obtained. The set of the impacts of the reserve volume of all energies on the supply is used as the value range of the supply impact factor of energy reserves in resource scheduling, and thus the supply impact factor of energy reserves in resource scheduling can be obtained. The set of the impacts of the reserve volume of all energies on the demand is used as the value range of the demand impact factor of energy reserves in resource scheduling, and thus the demand impact factor of energy reserves in resource scheduling can be obtained.

[0046] Then, in specific implementation, the fusion information of the reserve volumes of various energies in the park can be determined based on the supply impact factor and the demand impact factor, which can be achieved in the following way: the set of all values of the supply impact factor and the set of all values of the demand impact factor are used as the fusion information of the reserve volumes of various energies in the park. It should be noted that in this application, the fusion information refers to the impact weight information of the supply-demand relationships of various types of energies in the park on the reserve volume.

[0047] Finally, in specific implementation, the supply relationship graph and the demand relationship graph can be fused based on the fusion information, and then the fusion interval of the reserve volumes of various energies in the park can be obtained, which can be achieved in the following way: for various energies in the park, one energy is selected from other energies as the comparison energy. The intensity value of the relationship edge between the corresponding node of the energy and the corresponding node of the comparison energy is obtained from the supply relationship graph as the supply relationship value between the energy and the comparison energy. The intensity value of the relationship edge between the corresponding node of the energy and the corresponding node of the comparison energy is obtained from the demand relationship graph as the demand relationship value between the energy and the comparison energy. The values of the supply impact factor and the demand impact factor of the energy are obtained from the fusion information, and the two values are used as the weights of the supply relationship value and the demand relationship value respectively. The sum of the weights of the supply relationship value and the demand relationship value is calculated as the fusion value between the energy and the comparison energy in the park. Repeat the above steps to select other energies for comparison, and the fusion values between the energy and each other energy can be obtained. The range from the minimum value to the maximum value among all the fusion values can be used as the fusion interval of the reserve volume of the energy. Through the above method, the fusion intervals of the reserve volumes of various energies can be obtained, where the fusion interval reflects the reasonable range of various resource reserves in energy scheduling.

[0048] In some embodiments, the dynamic scheduling of multi-energy resources in the park based on the fusion interval of each energy reserve can be achieved by the following steps: For various energies in the park, when the reserve of the energy in the park is not within the fusion interval of the reserve, the reserve of the energy in the park is replenished, thereby completing the dynamic scheduling of the multi-energy resources in the park.

[0049] Specifically, for various energies in the park, when the reserve of the energy in the park is within the fusion interval of the reserve, the reserve is maintained; when the reserve of the energy in the park is not within the fusion interval of the reserve, the reserve of the energy in the park is replenished until the reserve of the energy in the park is within the fusion interval of the reserve. Through the above, the dynamic scheduling of the multi-energy resources in the park can be completed.

[0050] In addition, on the other hand of the present application, in some embodiments, the present application provides a multi-energy resource scheduling system for a park. Refer to Figure 4 , this figure is a schematic structural diagram of the multi-energy resource scheduling system for a park shown according to some embodiments of the present application. The multi-energy resource scheduling system for a park includes: a collection module 201, a processing module 202, and an execution module 203, which are described as follows: Collection module 201, in the present application, the collection module 201 is mainly used to collect the resource supply information and scheduling demand information of various energies in the park; Processing module 202, in the present application, the processing module 202 is used to extract the complementary relationship and conflict relationship of energy consumption among various energies from the resource supply information, determine the complementary amount of energy consumption among various energies in the park according to each complementary relationship of energy consumption, and then construct a supply relationship map of energy scheduling in the park through all the complementary amounts of energy consumption and each conflict relationship of energy consumption; It should be noted that the processing module 202 is further used to determine the demand mode of the multi-energy resources in the park according to the demand data in the scheduling demand information, and construct a demand relationship map of energy scheduling in the park through the demand mode and the topological association relationship among the demands of various energies in the park; Execution module 203, in the present application, the execution module 203 is mainly used to perform map fusion on the energy reserves in the resource scheduling through the supply relationship map and the demand relationship map to obtain the fusion interval of the reserve of each energy in the park, and perform dynamic scheduling of the multi-energy resources in the park based on the fusion interval of each energy reserve.

[0051] The above has introduced in detail the examples of the multi-energy resource scheduling method, system, device and medium provided by the embodiments of the present application. It can be understood that, in order to implement the above functions, the corresponding device includes the corresponding hardware structure and / or software module for executing each function. Those skilled in the art should easily realize that, combining the units and algorithm steps of each example described in the embodiments disclosed herein, the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a certain function is executed in the way of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present application.

[0052] In some embodiments, the present application further provides a computer device, which includes a memory and a processor. The memory is used to store a computer program, and the processor is used to call and run the computer program from the memory, so that the computer device executes the above-mentioned multi-energy resource scheduling method for the park.

[0053] In some embodiments, referring to Figure 5 , the dotted line in this figure indicates that the unit or the module is optional. This figure is a schematic structural diagram of a computer device for implementing the multi-energy resource scheduling method for the park according to the embodiments of the present application. The multi-energy resource scheduling method described in the above embodiments can be implemented by Figure 5 the computer device shown. The computer device includes at least one processor 301, a memory 302, and at least one communication unit 305. The computer device can be a terminal device, a server, or a chip.

[0054] The processor 301 can be a general-purpose processor or a special-purpose processor. For example, the processor 301 can be a central processing unit (CPU). The CPU can be used to control the computer device, execute software programs, and process the data of software programs. The computer device can also include a communication unit 305 for implementing the input (receiving) and output (sending) of signals.

[0055] For example, the computer device can be a chip, and the communication unit 305 can be the input and / or output circuit of the chip, or the communication unit 305 can be the communication interface of the chip. The chip can be used as a component of a terminal device, a network device, or other devices.

[0056] Again, for example, the computer device can be a terminal device or a server, and the communication unit 305 can be the transceiver of the terminal device or the server, or the communication unit 305 can be the transceiver circuit of the terminal device or the server.

[0057] One or more memories 302 may be included in the computer device, on which a program 304 is stored. The program 304 can be run by the processor 301 to generate instructions 303, enabling the processor 301 to execute the methods described in the above method embodiments according to the instructions 303. Optionally, data (such as a target audit model) may also be stored in the memory 302. Optionally, the processor 301 may also read the data stored in the memory 302. This data may be stored at the same storage address as the program 304, or it may be stored at a different storage address from the program 304.

[0058] The processor 301 and the memory 302 may be provided separately or integrated together. For example, they may be integrated on a system on chip (SOC) of the terminal device.

[0059] It should be understood that each step of the above method embodiments can be completed by a logic circuit in hardware form or instructions in software form in the processor 301. The processor 301 may be a CPU, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), or other programmable logic devices. For example, discrete gate, transistor logic devices, or discrete hardware components.

[0060] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk memories, CD-ROMs, optical memories, etc.) containing computer-usable program code.

[0061] For example, in some embodiments, the present application also provides a computer-readable storage medium, in which instructions or code are stored. When the instructions or code run on a computer, the computer is enabled to execute the above-mentioned multi-energy resource scheduling method for the park.

[0062] Although the preferred embodiments of the present application have been described, those skilled in the art can make additional changes and modifications once they know the basic creative concepts. Therefore, the appended claims are intended to be construed as including the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0063] Obviously, those skilled in the art can make various changes and modifications to this application without departing from the spirit and scope of this application. Thus, if these modifications and variations of this application fall within the scope of the claims of this application and their equivalent technologies, this application is also intended to include these modifications and variations.

Claims

1. A method for scheduling multi-energy resources in a park, characterized in that: The steps include: Collect resource supply information and scheduling demand information of various energy sources in the park; Extracting the complementary relationship and conflict relationship of energy consumption between various energy sources from the resource supply information, determining the complementary amount of energy consumption between various energy sources in the park according to the complementary relationship of each energy consumption, and then constructing a supply relationship map of energy scheduling in the park through all the complementary amounts of energy consumption and the conflict relationship of each energy consumption; Determine the demand pattern of the multi-energy resources in the park according to the demand data in the scheduling demand information, and construct a demand relationship map of energy scheduling in the park through the topological association relationship between the demand pattern and various energy demands in the park; The energy reserves in resource scheduling are graph-fused through the supply relationship graph and the demand relationship graph to obtain the fusion intervals of various energy reserves in the park, and the multi-energy resources in the park are dynamically scheduled based on the fusion intervals of various energy reserves.

2. The method according to claim 1, characterized in that Extracting the complementary relationship and conflict relationship of energy consumption between various energy sources from the resource supply information specifically includes: Extracting energy consumption complementation and conflict loss between various energy sources from the resource supply information; Determine the complementary relationship between energy consumption of various energy sources through all complementary energy consumption quantities; The conflict relationship between energy consumption of various energy sources is determined through all conflicting losses.

3. The method according to claim 1, characterized in that The supply relationship map of energy scheduling in the park is constructed through all energy consumption complementarity and the conflict relationship of each energy consumption, including: Obtain the topological structure of energy supply in the park's multi-energy resources; Extract the conflict loss between various energy sources from the conflict relationship of each energy consumption; The relationship edges between the nodes in the topological structure of the energy supply are strength-constrained by means of each conflict loss amount and each energy consumption complement amount, thereby obtaining a supply relationship graph for energy scheduling in the park.

4. The method according to claim 1, characterized in that Determining the demand pattern of the park's multi-energy resources according to the demand data in the scheduling demand information specifically includes: Extracting temporal distribution characteristics and spatial distribution characteristics of various energy demands from the demand data in the scheduling demand information; The demand pattern of the park's multi-energy resources is determined through all time domain distribution characteristics and all spatial distribution characteristics.

5. The method according to claim 1, characterized in that The demand relationship map of energy scheduling in the park is constructed by using the topological association relationship between the demand pattern and various energy demands in the park, which specifically includes: Identify peak and valley characteristics and regional load characteristics of various energy demands in the park through the demand pattern; Extract the topological structure and correlation value between energy demands in the park from the topological correlation relationship between various energy demands in the park; Through all the associated values, peak and valley characteristics of various energy demands and regional load characteristics, the relationship edges between the nodes in the topological structure are constrained in strength, thereby obtaining a demand relationship map for energy scheduling in the park.

6. The method according to claim 1, characterized in that Dynamic scheduling of multi-energy resources in the park based on the fusion interval of each energy reserve includes: For various energy sources in the park, when the energy reserves in the park are not within the fusion range of the reserves, the energy reserves in the park are replenished to complete the dynamic scheduling of the park's multi-energy resources.

7. The method according to claim 1, characterized in that The multi-energy resources of the park include electric energy, thermal energy, cold energy, natural gas and solar energy.

8. A multi-energy resource scheduling system for a park, characterized in that: include: The collection module is used to collect the resource supply information and scheduling demand information of various energy sources in the park; A processing module, used to extract the complementary relationship and conflict relationship of energy consumption between various energy sources from the resource supply information, determine the energy consumption complementarity between various energy sources in the park according to the complementary relationship of each energy consumption, and then construct a supply relationship map of energy scheduling in the park through all the energy consumption complementarity and the conflict relationship of each energy consumption; The processing module is also used to determine the demand pattern of the multi-energy resources in the park according to the demand data in the scheduling demand information, and to construct a demand relationship map of energy scheduling in the park through the topological association relationship between the demand pattern and various energy demands in the park; The execution module is used to perform graph fusion on the energy reserves in resource scheduling through the supply relationship graph and the demand relationship graph, obtain the fusion interval of various energy reserves in the park, and dynamically schedule the multi-energy resources of the park based on the fusion interval of each energy reserve.

9. A computer device, characterized in that: The computer device includes a memory and a processor, the memory is used to store a computer program, and the processor is used to call and run the computer program from the memory, so that the computer device executes the campus multi-energy resource scheduling method described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions or codes, and when the instructions or codes are executed on a computer, the computer implements the campus multi-energy resource scheduling method as described in any one of claims 1 to 7.

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