Resource Scheduling Method, Apparatus, Electronic Device, and Storage Medium

Abstract

The present invention discloses a resource scheduling method, apparatus, electronic device and storage medium. The method includes: obtaining adjustable load resource data of a power system within a preset time period, inputting the adjustable load resource data into a preset low-carbon scheduling model on the power generation side to obtain n sets of resource scheduling methods, determining n sets of power generation characteristic indexes corresponding to the n sets of resource scheduling methods, inputting the n sets of resource scheduling methods into a preset low-carbon scheduling model on the load side to obtain n sets of load-side power consumption data, determining n sets of load-side power consumption characteristic indexes corresponding to the n sets of load-side power consumption data, determining n coordination degree values based on the n sets of power generation characteristic indexes and the n sets of load-side power consumption characteristic indexes, determining the maximum coordination degree value among the n coordination degree values, determining the resource scheduling method corresponding to the maximum coordination degree value, and obtaining the target resource scheduling method. By adopting the implementation manner of the present application, the coordination of resource scheduling in the power system is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of power system resource scheduling, and in particular, to a resource scheduling method, device, electronic device, and storage medium. Background Art

[0002] The operation of the power system directly affects the level of greenhouse gas emissions. In the traditional power system operation mode, the power generation side and the load side are usually independently planned and scheduled, lacking an effective coordination mechanism. This leads to the power generation side may overly rely on traditional fossil energy, not only causing excessive carbon emissions, but also triggering power supply-demand imbalance due to the failure to fully consider the dynamic changes in the load side demand. During the power consumption process, the load side also fails to form a close interaction with the power generation side, making it difficult to contribute to the low-carbon and efficient operation of the power system by adjusting the power consumption behavior, resulting in low overall operation efficiency and serious waste of power resources. Therefore, how to improve the coordination of power system resource scheduling is an urgent problem to be solved. Summary of the Invention

[0003] The embodiments of the present application provide a resource scheduling method, device, electronic device, and storage medium, which improve the coordination of power system resource scheduling.

[0004] In a first aspect, the embodiments of the present application provide a resource scheduling method, including:

[0005] Obtain the adjustable load resource data of the power system within a preset time period;

[0006] Input the adjustable load resource data into a preset low-carbon scheduling model of the power generation side to obtain n sets of resource scheduling methods; n is an integer greater than 1;

[0007] Determine the power generation characteristic indicators corresponding to the n sets of resource scheduling methods to obtain n sets of power generation characteristic indicators; each set of power generation characteristic indicators includes the power supply quantity of the power generation side, the carbon emissions of the power generation side, and the power generation cost of the power generation side;

[0008] Input the n sets of resource scheduling methods into a preset low-carbon scheduling model of the load side to obtain the load side power consumption data corresponding to each set of resource scheduling methods in the n sets of resource scheduling methods, to obtain n sets of load side power consumption data;

[0009] Determine the load side power consumption characteristic indicators corresponding to each set of load side power consumption data in the n sets of load side power consumption data to obtain n sets of load side power consumption characteristic indicators; each set of load side power consumption characteristic indicators includes the power demand of the load side, the carbon emissions of the load side, and the power consumption cost of the load side;

[0010] Determine the coordination degree value corresponding to each of the \(n\) resource scheduling methods based on the \(n\) groups of power generation characteristic indicators and the \(n\) groups of load - side power consumption characteristic indicators, obtaining \(n\) coordination degree values; the greater the coordination degree value of a resource scheduling method, the better the resource scheduling effect of the resource scheduling method.

[0011] Determine the maximum coordination degree value among the \(n\) coordination degree values.

[0012] Determine the resource scheduling method corresponding to the maximum coordination degree value, obtaining the target resource scheduling method.

[0013] In a second aspect, an embodiment of the present application provides a resource scheduling device, which includes an acquisition unit and a processing unit.

[0014] The acquisition unit is configured to acquire adjustable load resource data of a power system within a preset time period.

[0015] The processing unit is configured to input the adjustable load resource data into a preset low - carbon scheduling model on the power generation side to obtain \(n\) resource scheduling methods; \(n\) is an integer greater than 1.

[0016] Determine the power generation characteristic indicators corresponding to the \(n\) resource scheduling methods, obtaining \(n\) groups of power generation characteristic indicators; each group of power generation characteristic indicators includes power generation - side power supply, power generation - side carbon emissions, and power generation - side power generation cost.

[0017] Input the \(n\) resource scheduling methods into a preset low - carbon scheduling model on the load side to obtain the load - side power consumption data corresponding to each of the \(n\) resource scheduling methods, obtaining \(n\) groups of load - side power consumption data.

[0018] Determine the load - side power consumption characteristic indicators corresponding to each of the \(n\) groups of load - side power consumption data, obtaining \(n\) groups of load - side power consumption characteristic indicators; each group of load - side power consumption characteristic indicators includes load - side power demand, load - side carbon emissions, and load - side power consumption cost.

[0019] Determine the coordination degree value corresponding to each of the \(n\) resource scheduling methods based on the \(n\) groups of power generation characteristic indicators and the \(n\) groups of load - side power consumption characteristic indicators, obtaining \(n\) coordination degree values; the greater the coordination degree value of a resource scheduling method, the better the resource scheduling effect of the resource scheduling method.

[0020] Determine the maximum coordination degree value among the \(n\) coordination degree values.

[0021] Determine the resource scheduling method corresponding to the maximum coordination degree value, obtaining the target resource scheduling method.

[0022] In a third aspect, an embodiment of the present invention provides an electronic device, including: a processor, a memory, a communication interface, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor so that the electronic device executes the method as described in the first aspect.

[0023] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium storing a computer program, and the computer program is executed by a processor to implement the method as described in the first aspect.

[0024] In a fifth aspect, an embodiment of the present invention provides a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, such that a computer executes the method as described in the first aspect.

[0025] Implementing the embodiments of the present invention has the following beneficial effects:

[0026] It can be seen that in the resource scheduling method described in the embodiments of the present invention, first, the adjustable load resource data of the power system within a preset time period is obtained, then the adjustable load resource data is input into a preset low-carbon scheduling model on the power generation side to obtain n sets of resource scheduling methods. Then, the n sets of resource scheduling methods are input into a preset low-carbon scheduling model on the load side to obtain the load-side power consumption data corresponding to each set of resource scheduling methods in the n sets of resource scheduling methods, obtaining n sets of load-side power consumption data. Then, the power generation characteristic indexes corresponding to the n sets of resource scheduling methods are determined, obtaining n sets of power generation characteristic indexes, and the load-side power consumption characteristic indexes corresponding to each set of load-side power consumption data in the n sets of load-side power consumption data are also determined, obtaining n sets of load-side power consumption characteristic indexes. And based on the n sets of power generation characteristic indexes and the n sets of load-side power consumption characteristic indexes, the coordination degree values corresponding to each set of resource scheduling methods in the n sets of resource scheduling methods are determined, obtaining n coordination degree values, thereby determining the maximum coordination degree value among the n coordination degree values. Finally, the resource scheduling method corresponding to the maximum coordination degree value is determined, obtaining the target resource scheduling method, which improves the coordination of resource scheduling in the power system. Description of the Drawings

[0027] To more clearly illustrate the technical solutions in the embodiments of the present application or the background art, the following will describe the drawings required to be used in the embodiments of the present application or the background art.

[0028] Figure 1 is a schematic structural diagram of a resource scheduling system provided by an embodiment of the present application;

[0029] Figure 2 is a flowchart of a resource scheduling method provided by an embodiment of the present application;

[0030] Figure 3 is a flowchart for determining n coordination degree values provided by an embodiment of the present application;

[0031] Figure 4 is a flowchart for determining carbon emission reduction amount indicators provided by an embodiment of the present application;

[0032] Figure 5 is a flowchart for determining cost - benefit indicators provided by an embodiment of the present application;

[0033] Figure 6 is a flowchart for determining the coordination degree value corresponding to the first set of resource scheduling methods provided by an embodiment of the present application;

[0034] Figure 7 is a schematic structural diagram of a resource scheduling device provided by an embodiment of the present application;

[0035] Figure 8 is a schematic structural diagram of an electronic device provided by an embodiment of the present application. Detailed implementation manners

[0036] In order to enable those skilled in the art to better understand the solutions of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without making creative efforts belong to the scope of protection of the present application.

[0037] Terms such as "first" and "second" in the specification and claims of the present application and the above - mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "include" and "have" and any variations thereof are intended to cover non - exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not limited to the listed steps or units, but optionally further includes steps or units not listed, or optionally further includes other steps or units inherent to these processes, methods, products, or devices.

[0038] Referring to "embodiment" herein means that a specific feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the present application. The phrase appears at various positions in the specification and does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art will explicitly and implicitly understand that the embodiments described herein may be combined with other embodiments.

[0039] Please refer to Figure 1 , Figure 1 which is a schematic structural diagram of a resource scheduling system provided by an embodiment of the present application. The resource scheduling system 100 includes a preset low-carbon scheduling model 101 for the power generation side and a preset low-carbon scheduling model 102 for the load side.

[0040] In this embodiment, first, it is necessary to construct a preset low-carbon scheduling model 101 for the power generation side. The preset low-carbon scheduling model 101 for the power generation side is mainly composed of several constraint relationships such as objective function constraints, branch power flow constraints, node power balance constraints, generator ramp constraints, and carbon emission intensity constraints.

[0041] Specifically, the objective function of the preset low-carbon scheduling model 101 for the power generation side satisfies the following constraints:

[0042]

[0043]

[0044] Among them, is the objective function for the power generation side, is the unit time, is the set of time points at intervals of as the unit time, is the engine that is generating electricity, is the set of all generators on the power generation side, is the power generation cost function, is the penalty cost for the unit carbon emission of the generator, is the carbon emission coefficient of the generator at time is the active power output by the generator at time and are the coefficients of the power generation cost function.

[0045] The branch power flow of the low-carbon scheduling model 101 for the power generation side satisfies the following constraints:

[0046]

[0047]

[0048] Among them, and are respectively the active and reactive power flows on branch measured at node . The active power flow refers to the flow of active power transmitted in the power system branch, and the reactive power flow refers to the flow of reactive power transmitted in the power system branch. and The directions are all for the nodes to node , and are respectively the voltage of node and node at time and are respectively the phase angles of node and node at time is the conductance of branch , is the susceptance of branch , is the set of all branches in the system. It should be explained that the nodes in the branch power flow of the low-carbon dispatching model 101 on the power generation side refer to the points used to describe various positions in the power grid in the power system. These points can be power plants, substations, load centers, or connection points of transmission lines, etc. The branches in the branch power flow of the low-carbon dispatching model 101 on the power generation side are the power lines or components connecting nodes, used to transmit electric energy, including transmission lines, which are the main electric energy transmission channels, delivering the electric energy of power plants to each load center or substation; transformers, used to change the voltage level to adapt to different transmission and power consumption requirements; and some other power equipment, such as reactors, capacitors, etc., which can also be used as branch components to adjust the parameters and operating states of the power system.

[0049] The node power balance of the low-carbon dispatching model 101 on the power generation side satisfies the following constraints:

[0050]

[0051]

[0052] Among them, is the reactive power output by the generator at time , is the carbon emission intensity at node at time is the optimal active power of load at time. This power is related to the carbon emission intensity of the load node, indicating that the load demand of users changes with the carbon emission intensity of the node. In the traditional optimal operation of the power system, the node load is fixed. The present invention considers that the user load is related to the carbon emission intensity of the node. When the carbon emission intensity of the node is relatively high, users will reduce their power consumption load. On the contrary, users will increase their power consumption load, enabling users to actively adjust their own power consumption load according to the change of the carbon emission intensity of the node. is the load 's power factor, is the set of all generators at node ; is the set of all loads at node ; is the set of all nodes in the system.

[0053] The generator ramp of the low-carbon dispatching model 101 on the generation side satisfies the following constraints:

[0054]

[0055] Among them, is the lower limit of the generator output power ramp rate, is the upper limit of the generator output power ramp rate.

[0056] The node voltage and phase of the low-carbon dispatching model 101 on the generation side satisfy the following constraints:

[0057]

[0058]

[0059] Among them, and are the lower limits of the voltage and phase angle of node ; and are the upper limits of the voltage and phase angle of node ;

[0060] The node carbon emission intensity of the low-carbon dispatching model 101 on the generation side satisfies the following constraints:

[0061]

[0062]

[0063]

[0064]

[0065] Among them, is the carbon emission intensity at node at time ; is the carbon emission intensity at node at time ; is the set of generators associated with node ; is the set of adjacent nodes of node ; and are two introduced auxiliary power flow variables used to replace the true active power flow of the branch , so as to avoid the influence of the power flow direction and facilitate the calculation and solution of the model.

[0066] In this embodiment, it is also necessary to construct a preset low-carbon dispatching model 102 for the load side. The preset low-carbon dispatching model 102 for the load side is mainly composed of several constraint relationships, including objective function constraints, power consumption constraints of adjustable load resources, and total energy consumption constraints of adjustable load resources within a unit time period.

[0067] Specifically, the objective function of the preset low-carbon dispatching model 102 for the load side satisfies the following constraints:

[0068]

[0069] Among them, is the objective function for the load side, is the penalty cost for the unit carbon emission of the adjustable load, is the node at the carbon emission intensity at time is the electricity price at node at time is the active power consumed by the load at time

[0070] The power consumption of the adjustable load resources in the preset low-carbon dispatching model 102 for the load side satisfies the following constraints:

[0071]

[0072] Among them, is the lower limit of the power consumption of the load at time is the upper limit of the power consumption of the load at time

[0073] The total energy consumed by the adjustable load resources within a unit time period in the preset low-carbon dispatching model 102 for the load side satisfies the following constraints:

[0074]

[0075] In the formula, is the lower limit of the total energy consumed by the adjustable load resources within the time period is the upper limit of the total energy consumed by the adjustable load resources within the time period The upper limit of total energy consumption.

[0076] It should be explained that, in this embodiment, the preset low-carbon dispatch model 101 on the power generation side is a tool based on mathematical algorithms and rules, which is used to generate n groups of resource dispatching methods according to the input adjustable load resource data to achieve the low-carbon dispatching goal on the power generation side. It comprehensively considers various factors of the power generation system, and aims to optimize the allocation of power generation resources, while meeting the operation requirements of the power system, to reduce the carbon emissions and power generation costs on the power generation side as much as possible, and reasonably determine the power supply on the power generation side. The input of the preset low-carbon dispatch model 101 on the power generation side is the adjustable load resource data, which may include the power generation capacity, adjustable range, current load level of different power sources (such as thermal power, hydropower, wind power, photovoltaic power, etc.), and the load demand forecast of the power system in a preset time period, the transmission capacity of the power grid and other related information. The output of the preset low-carbon dispatch model 101 on the power generation side is n groups of resource dispatching methods, and each group of resource dispatching methods clarifies how various power generation resources (different types of power generation units, etc.) should be dispatched within a preset time period, such as when to start or stop a certain unit, how to adjust the power generation of each unit, etc., so as to achieve low-carbon and economic operation on the power generation side. The preset power generation side low-carbon dispatch model 101 dispatches resources by constructing branch flow constraints, node power balance constraints, click power generation capacity constraints, node voltage and phase constraints, node carbon emission intensity and other constraints to obtain a resource dispatching method that meets the conditions.

[0077] It should be noted that in this embodiment, the preset low-carbon dispatching model 102 on the load side is used to calculate the load-side power consumption data corresponding to each of the given n sets of resource dispatching methods, and further determine the power consumption characteristic indexes on the load side. Its purpose is to evaluate the impact of different resource dispatching methods on the power consumption of users from the perspective of the load side, including the power demand, carbon emissions, and power consumption cost on the load side, etc., so as to achieve low-carbon and economical power consumption on the load side. The input of the preset low-carbon dispatching model 102 on the load side is n sets of resource dispatching methods, and these dispatching methods determine the power supply situation on the power generation side, including information such as the power supply quantity and power supply price at different time periods, which is the input basis of the low-carbon dispatching model on the load side. The output of the preset low-carbon dispatching model 102 on the load side is n sets of load-side power consumption data and the corresponding n sets of load-side power consumption characteristic indexes. Each set of load-side power consumption data describes the changes in the power consumption behavior of each power-consuming device or user group on the load side under the corresponding resource dispatching method, such as the power consumption quantity and power consumption power at different time periods, while each set of load-side power consumption characteristic indexes is a comprehensive quantitative evaluation of the power consumption situation on the load side, including the power demand on the load side (reflecting the satisfaction degree of the actual power consumption demand of users), the carbon emissions on the load side (considering the indirect carbon emissions generated during the power consumption process due to different power sources), and the power consumption cost on the load side (the fees paid by users for power consumption). The preset low-carbon dispatching model 102 on the load side needs to consider various factors on the load side, such as the power consumption behavior patterns of users (the power consumption habits of different user types, peak and off-peak power consumption time periods, etc.), the price response characteristics (the reaction of users to different electricity price levels, such as adjusting the power consumption time to reduce costs), and the energy efficiency characteristics of power equipment, etc. By establishing corresponding mathematical models to describe the relationships between these factors, for example, calculating the change in the power consumption quantity of users according to the electricity price and the demand elasticity of users, and then calculating the carbon emissions on the load side according to the carbon emission factors of the power sources, and then, according to the input resource dispatching methods, combining these models and relationships, calculating the power consumption data and characteristic indexes on the load side.

[0078] Please refer to Figure 2 , Figure 2 which is a flowchart of a resource dispatching method provided by an embodiment of the present application, including but not limited to the following steps:

[0079] S201: Obtain the adjustable load resource data of the power system within a preset time period.

[0080] In this embodiment, smart meters and sensors can be installed at each load node of the power system. These devices can monitor and record the power consumption information of the load in real time, including parameters such as power, voltage, and current. The data is transmitted to the data center through the communication network. After data processing and analysis, adjustable load resource data is extracted. For example, the smart meters installed on large motors of industrial users and air-conditioning systems of commercial buildings can accurately measure the power consumption of the devices, providing data support for analyzing their adjustability. For some users who can participate in demand response, such as large industrial users and commercial parks, the power company can encourage users to actively declare information about their adjustable load resources, including the adjustable power range, adjustment time, and adjustment cost, by formulating relevant policies and incentive measures. During the actual operation, users feedback their load adjustment situations to the power company according to the dispatching requirements of the power system, so as to obtain real-time adjustable load resource data. It is also possible to rely on the operation monitoring and control platform of the power system, such as the energy management system and the distribution management system, to monitor the operation status of the system in real time, obtain the load information of the entire network, screen and analyze this information to identify adjustable load resources, and extract the corresponding data. For example, the load changes of each node in the power grid can be monitored in real time, and combined with the operation status and constraints of the devices, it can be determined which loads are adjustable and the degree of adjustability.

[0081] The adjustable load resource data can include data such as load type, load location, load capacity, load adjustable power range, load adjustment speed, load adjustment duration, load adjustment flexibility, and load adjustment cost.

[0082] S202: Input the adjustable load resource data into a preset low-carbon dispatching model on the power generation side to obtain n sets of resource dispatching methods.

[0083] In this embodiment, n is an integer greater than 1. It should be noted that the preset low-carbon dispatching model on the power generation side in this embodiment can be Figure 1 the preset low-carbon dispatching model 101 in [reference], and the adjustable load resource data can be input into the preset low-carbon dispatching model 101 to obtain n sets of resource dispatching methods.

[0084] The adjustable load resource data includes various information about the adjustable loads in the power system, such as the types of loads (industrial loads, commercial loads, residential loads, etc.), the adjustable power range of the loads, the adjustment speed, the adjustment cost, etc. Inputting this data into the preset low-carbon dispatching model on the power generation side is to enable the model to fully consider the adjustability of the loads when making power generation resource dispatching decisions, so as to better balance the relationship between power generation and power consumption. When the preset low-carbon dispatching model on the power generation side receives the adjustable load resource data, it will perform calculations and optimizations based on its own algorithms and constraint conditions. By solving the objective function and constraint equations, the model will output multiple possible power generation resource dispatching schemes, that is, n sets of resource dispatching methods. Each set of resource dispatching methods details the specific operation strategies such as the power generation power distribution and power generation time arrangement of different power generation equipment within the preset time period to achieve low-carbon and economic operation on the power generation side. For example, a certain set of resource dispatching methods may arrange to reduce the power generation power of thermal power plants and increase the power generation proportion of wind farms and photovoltaic power plants during the low load period, thereby reducing carbon emissions and power generation costs.

[0085] S203: Determine the power generation characteristic indicators corresponding to the n sets of resource dispatching methods to obtain n sets of power generation characteristic indicators.

[0086] In this embodiment, each set of power generation characteristic indicators includes the power supply quantity on the power generation side, the carbon emissions on the power generation side, and the power generation cost on the power generation side. In order to comprehensively evaluate the operation status and performance of the power generation side under different resource scheduling methods, specific indicators are required for quantification and description. These indicators can reflect the key elements and influencing factors in the power generation process. The power supply quantity on the power generation side refers to the quantity of electricity actually supplied by the power generation side to the power system when a certain resource scheduling method is adopted. It is an important indicator to measure the ability of the power generation system to meet the load demand. The amount of power supply is directly related to whether the power system can meet the electricity demand of users. If the power supply is insufficient, it may lead to power shortages and affect production and life. If the power supply is excessive, it may cause resource waste and an increase in power generation costs. By analyzing the power supply quantity on the power generation side under different resource scheduling methods, the ability and adaptability of each method to meet the load demand can be understood, providing a basis for reasonably arranging the power generation plan. The carbon emissions on the power generation side refer to the quantity of greenhouse gases such as carbon dioxide generated and emitted into the atmosphere during the power generation process due to the combustion of fossil fuels and other energy sources. It reflects the degree of impact of power generation activities on the environment. With the global emphasis on environmental protection and response to climate change, reducing carbon emissions has become an important goal for the development of the power industry. Different resource scheduling methods may lead to different energy utilization efficiencies and carbon emissions. Analyzing the carbon emissions on the power generation side can help evaluate the environmental friendliness of each resource scheduling method, prompting the power system to preferentially select low-carbon emission methods when scheduling resources to reduce the negative impact on the environment and achieve sustainable development. The power generation cost on the power generation side covers various costs generated during the power generation process, including fuel costs, equipment maintenance costs, personnel salaries, equipment depreciation, etc. It reflects the economic input of power generation activities. The power generation cost is one of the important indicators concerned by power enterprises, directly affecting the economic benefits of enterprises and the price of power supply. By comparing the power generation costs under different resource scheduling methods, it can help the power system optimize resource allocation, select a scheduling method with a lower cost to improve power generation efficiency and reduce operating costs, and also contribute to the reasonable formulation of electricity prices and ensure the stable operation of the power market.

[0087] By determining the power generation characteristic indicators corresponding to each of these n sets of resource scheduling methods, namely the power supply quantity on the power generation side, the carbon emissions on the power generation side, and the power generation cost on the power generation side, the comprehensive performance of different resource scheduling methods on the power generation side can be comprehensively evaluated from multiple dimensions, providing detailed data support for subsequent further analysis and optimization of resource scheduling, so as to make more scientific and reasonable decisions and achieve the coordinated development of the power system in terms of economy, environment, and power supply reliability.

[0088] S204: Input the n sets of resource scheduling methods into a preset low-carbon scheduling model on the load side to obtain the load-side electricity consumption data corresponding to each set of resource scheduling methods among the n sets of resource scheduling methods, and obtain n sets of load-side electricity consumption data.

[0089] In this embodiment, the preset low-carbon scheduling model on the load side may be Figure 1 the preset low-carbon scheduling model 102 in

[0090] The power consumption data on the load side corresponding to each set of resource scheduling methods in the n sets of resource scheduling methods can be obtained by inputting the n sets of resource scheduling methods into the preset low-carbon scheduling model 102 on the load side, so as to obtain n sets of power consumption data on the load side.

[0091] S205: Determine the load-side power consumption characteristic indexes corresponding to each set of power consumption data on the load side among the n sets of power consumption data on the load side, and obtain n sets of load-side power consumption characteristic indexes.

[0092] In this embodiment, each set of load-side power consumption characteristic indexes includes the power demand on the load side, the carbon emission on the load side, and the power consumption cost on the load side. For each set of power consumption data on the load side, the corresponding load-side power consumption characteristic indexes need to be determined respectively, so that n sets of load-side power consumption characteristic indexes can be obtained. Through these indexes, the power consumption situation on the load side under different resource scheduling methods can be understood more comprehensively and deeply. The power demand on the load side refers to the total amount of power required on the load side under the corresponding resource scheduling method. This index directly reflects the magnitude of the power demand of users or electrical equipment within a specific time period and is a key index for measuring whether the power system can meet the load requirements. For example, the operation of industrial production equipment and the use of household appliances by residents will generate a certain amount of power demand. Summing up the power demands of these different users and equipment will obtain the power demand on the load side. The carbon emission on the load side is the carbon emission indirectly generated during the power consumption process on the load side. Different power sources have different carbon emission factors. For example, using thermal power will generate higher carbon emissions, while using clean energy such as hydropower and wind power will have lower carbon emissions. By calculating the power consumption of different power sources used on the load side and the corresponding carbon emission factors, the carbon emission on the load side can be obtained. This index is used to evaluate the impact degree of power use on the environment. The power consumption cost on the load side refers to the cost required for equipment maintenance during the power consumption process by users, the cost consumed during the power transmission on the load side, etc.

[0093] S206: Determine the coordination degree value corresponding to each group of resource scheduling methods among the n groups of resource scheduling methods based on the n groups of power generation characteristic indicators and the n groups of load - side power consumption characteristic indicators, obtaining n coordination degree values.

[0094] In this embodiment, the larger the coordination degree value of the resource scheduling method, the better the resource scheduling effect of the resource scheduling method. Please refer to Figure 3 , Figure 3 FIG. is a flowchart for determining n coordination degree values provided by an embodiment of the present application, including but not limited to the following steps:

[0095] S301: Obtain the power supply quantity on the power generation side, the carbon emission on the power generation side, and the power generation cost on the power generation side corresponding to the first group of power generation characteristic indicators, obtaining the first power supply quantity on the power generation side, the first carbon emission on the power generation side, and the first power generation cost on the power generation side.

[0096] In this embodiment, the first group of power generation characteristic indicators is the power generation characteristic indicators corresponding to the first group of resource scheduling methods among the n groups of power generation characteristic indicators, and the first group of resource scheduling methods is any group of resource scheduling methods among the n groups of resource scheduling methods.

[0097] Each group of power generation characteristic indicators includes three specific indicators: the power supply quantity on the power generation side, the carbon emission on the power generation side, and the power generation cost on the power generation side. Extract the values of these three indicators from the first group of power generation characteristic indicators, respectively obtaining the first power supply quantity on the power generation side, the first carbon emission on the power generation side, and the first power generation cost on the power generation side. This step is to analyze the specific situation on the power generation side under a specific resource scheduling method, extract key numerical information, and facilitate subsequent analysis.

[0098] S302: Obtain the power demand quantity on the load side, the carbon emission on the load side, and the power consumption cost on the load side corresponding to the first group of load - side power consumption characteristic indicators, obtaining the first power demand quantity on the load side, the first carbon emission on the load side, and the first power consumption cost on the load side.

[0099] In this embodiment, the first group of load - side power consumption characteristic indicators is the load - side power consumption characteristic indicators corresponding to the first group of power generation characteristic indicators among the n groups of load - side power consumption characteristic indicators.

[0100] Each group of load - side power consumption characteristic indicators includes three indicators: the power demand quantity on the load side, the carbon emission on the load side, and the power consumption cost on the load side. Extract the values of these three indicators from the first group of load - side power consumption characteristic indicators, respectively obtaining the first power demand quantity on the load side, the first carbon emission on the load side, and the first power consumption cost on the load side. This is to obtain the key power consumption information on the load side under a specific resource scheduling method, so as to conduct subsequent comprehensive analysis together with the power generation - side information.

[0101] S303: Determine the power supply - demand balance rate based on the power supply of the first power generation side and the power demand of the first load side.

[0102] In this embodiment, the power supply of the first power generation side represents the power quantity supplied by the power generation side under the first - group resource scheduling method, and the power demand of the first load side represents the power consumption demand of the load side under this resource scheduling method.

[0103] The power supply - demand balance rate is an index used to measure the matching degree between the power supply of the power generation side and the power demand of the load side. The calculation of the power supply - demand balance rate satisfies the following formula:

[0104] Power supply - demand balance rate = Power supply of the first power generation side / Power demand of the first load side;

[0105] According to the above formula, the power supply - demand balance rate can be determined based on the power supply of the first power generation side and the power demand of the first load side.

[0106] The power supply - demand balance rate can reflect whether the power supply and demand of the power system are balanced and the degree of balance under this resource scheduling method. If the power supply - demand balance rate is close to 1, it indicates that the power supply quantity and the demand quantity are relatively well - matched; if the value is greater than 1, it may indicate an oversupply, and if it is less than 1, it may indicate an undersupply. Therefore, the closer the power supply - demand balance rate is to 1, the more balanced the power supply and demand of the power system are.

[0107] S304: Determine the carbon emission reduction index based on the carbon emissions of the first power generation side and the carbon emissions of the first load side.

[0108] In this embodiment, please refer to Figure 4 , Figure 4 is a flowchart for determining the carbon emission reduction index provided by the embodiment of the present application, including but not limited to the following steps:

[0109] S401: Obtain the historical carbon emissions of the power generation side and the historical carbon emissions of the load side of the power system during the historical time period.

[0110] In this embodiment, the end time of the historical time period is earlier than the start time of the preset time period, and the duration of the historical time period is the same as the duration of the preset time period.

[0111] By comparing the carbon emissions of the power generation side and the load side of the power system at different time periods, the change in the carbon emissions of the power system is evaluated. The preset time period is the time period in which the current resource scheduling to be studied is located, while the historical time period is used as a reference. The historical time period and the preset time period have the same duration, and the end time of the former is earlier than the start time of the latter, which ensures that the two time periods are independent of each other and excludes the interference of overlapping time periods on the analysis. On this basis, the carbon emissions generated by the power generation side of the power system and the carbon emissions indirectly generated by the load side due to electricity consumption during the historical time period are collected.

[0112] S402: Determine the difference between the first power generation side carbon emissions and the historical power generation side carbon emissions to obtain the power generation side carbon emissions difference.

[0113] In this embodiment, the first power generation side carbon emissions come from the power generation characteristic indicators corresponding to the first set of resource scheduling methods during the preset time period. Compare it with the historical power generation side carbon emissions during the historical time period. By calculating the difference between the two, understand the value by which the power generation side carbon emissions decrease compared to the historical situation after adopting the first set of resource scheduling methods during the preset time period, which helps to analyze the impact direction and degree of the current resource scheduling method on the power generation side carbon emissions.

[0114] S403: Determine the difference between the first load side carbon emissions and the historical load side carbon emissions to obtain the load side carbon emissions difference.

[0115] In this embodiment, the first load side carbon emissions also come from the load side electricity consumption characteristic indicators corresponding to the first set of resource scheduling methods during the preset time period. Compare it with the historical load side carbon emissions during the historical time period. Calculating the load side carbon emissions difference can reflect the change in the carbon emissions generated by the load side due to electricity consumption compared to the historical situation during the preset time period.

[0116] S404: Determine the carbon emissions reduction value based on the power generation side carbon emissions difference and the load side carbon emissions difference.

[0117] In this embodiment, perform a comprehensive operation on the previously obtained power generation side carbon emissions difference and the load side carbon emissions difference. The operation method can be simple addition, or different weights can be assigned according to the importance of the carbon emissions on the power generation side and the load side and then calculated. The carbon emissions reduction value obtained through calculation can overall reflect the overall change in the carbon emissions of the power generation side and the load side of the power system after adopting the first set of resource scheduling methods during the preset time period, clarify whether the carbon emissions increase or decrease, and the specific amplitude of the change.

[0118] S405: Determine the carbon emissions reduction index based on the carbon emissions reduction value.

[0119] In this embodiment, it may be a mapping relationship between a preset carbon emission reduction value and a carbon emission reduction index. Based on this mapping relationship, the carbon emission reduction index can be determined based on the carbon emission reduction value.

[0120] It can be seen that by calculating the difference in carbon emissions between the power generation side and the load side in different time periods, the carbon emission reduction value can be accurately obtained, and then the carbon emission reduction index can be determined. In this way, the emission reduction effect of the power system under a specific resource scheduling method can be quantitatively evaluated, and it can intuitively reflect the impact of the current scheduling method on carbon emissions compared with the historical situation. Calculating the difference in carbon emissions between the power generation side and the load side separately helps to clarify the respective roles of the power generation link and the load link in the carbon emission change, so as to determine the key links and responsible entities for emission reduction, providing a basis for formulating targeted emission reduction measures. The carbon emission reduction index can provide data support for the optimization of the resource scheduling method. According to this index, it can be judged whether the current scheduling strategy is conducive to reducing carbon emissions, and then the resource scheduling plan can be adjusted and optimized to improve the low-carbon operation level of the power system.

[0121] S305: Determine a cost-benefit index based on the first power generation side power generation cost and the first load side power consumption cost.

[0122] In this embodiment, please refer to Figure 5 , Figure 5 which is a flowchart for determining a cost-benefit index provided by an embodiment of the present application, including but not limited to the following steps:

[0123] S501: Determine a target power consumption cost based on the first power generation side power generation cost and the first load side power consumption cost.

[0124] In this embodiment, the first power generation side power generation cost refers to the various costs paid by the power generation side to generate electricity under the first set of resource scheduling methods, including fuel costs, equipment maintenance costs, personnel salaries, etc. The first load side power consumption cost is the cost that the load side users need to bear for using electricity under the same first set of resource scheduling methods, such as electricity bills and possible additional maintenance costs of electrical equipment. The target power consumption cost can be obtained by adding the first power generation side power generation cost and the first load side power consumption cost.

[0125] S502: Obtain the economic benefits corresponding to the first set of resource scheduling methods to obtain the target economic benefits.

[0126] In this embodiment, the first set of resource scheduling methods will have various impacts on the operation of the power system, and these impacts will bring corresponding economic benefits. The sources of economic benefits may include multiple aspects. For example, through reasonable resource scheduling, the utilization efficiency of power generation equipment is improved, the power generation cost is reduced, thus increasing the profit. Or by guiding the electricity consumption behavior on the load side, the allocation of power resources is optimized, the overall operation efficiency of the power system is improved, and additional economic benefits are brought. Evaluate and calculate the economic benefits generated by the first set of resource scheduling methods to obtain a specific value, which is the target economic benefit. The evaluation process may need to consider multiple factors, such as power generation income, changes in electricity consumption costs, returns on equipment investment, etc. Determine the final target economic benefit by comprehensively analyzing these factors.

[0127] S503: Determine the cost-benefit index based on the target electricity cost and the target economic benefit.

[0128] In this embodiment, the cost-benefit index is an important index for measuring the relationship between the cost and benefit of the power system under the first set of resource scheduling methods. It reflects the situation of the economic benefit (i.e., the target economic benefit) obtained under the condition of investing a certain cost (i.e., the target electricity cost). According to the two values of the target electricity cost and the target economic benefit, determine the cost-benefit index through a specific calculation method. A common calculation method may be to divide the target economic benefit by the target electricity cost, and the obtained ratio is the cost-benefit index. The larger the value of this index, the higher the economic benefit obtained per unit cost under this resource scheduling method, and the better the cost-benefit of the resource scheduling method. On the contrary, it means that the cost-benefit is poor.

[0129] It can be seen that by comprehensively considering the power generation cost on the first power generation side and the electricity consumption cost on the first load side to determine the target electricity cost, the cost factors of the two key links of power generation and electricity consumption are comprehensively covered. Combining with the target economic benefit to determine the cost-benefit index can objectively and comprehensively evaluate the first set of resource scheduling methods as a whole, rather than one-sidedly only focusing on the cost of a certain aspect of power generation or electricity consumption, making the evaluation result more scientific and accurate, so as to better measure the feasibility and rationality of this resource scheduling method at the economic level. The cost-benefit index provides a clear quantitative basis for resource scheduling decisions. When facing multiple resource scheduling methods, it is possible to compare and screen according to this index, and give priority to the method with high cost-benefit, which helps to reasonably allocate power resources, improve resource utilization efficiency, avoid waste of resources, and make the power system reach a better state in terms of economic operation.

[0130] S306: Determine the coordination degree value corresponding to the first set of resource scheduling methods based on the power supply-demand balance rate, the carbon emission reduction amount index, and the cost-benefit index.

[0131] In this embodiment, please refer to Figure 6 , Figure 6 which is a flowchart for determining the coordination degree value corresponding to the first set of resource scheduling methods provided by the embodiment of the present application, including but not limited to the following steps:

[0132] S601: Determine the difference between the power supply-demand balance rate and the preset power supply-demand balance rate to obtain the power supply-demand balance rate difference.

[0133] In this embodiment, the power supply-demand balance rate is an index for measuring the balance degree between power supply and demand in the power system, and the preset power supply-demand balance rate is an ideal balance state index value set in advance according to the planning and operation requirements of the power system. By calculating the difference between the actual power supply-demand balance rate and the preset power supply-demand balance rate, the gap between the current supply-demand situation of the power system and the ideal state can be clarified. This difference is the power supply-demand balance rate difference, which reflects the deviation degree of the power supply-demand balance.

[0134] S602: When the power supply-demand balance rate difference is less than or equal to the preset power supply-demand balance rate difference, determine the coordination degree value corresponding to the first set of resource scheduling methods based on the carbon emission reduction amount index and the cost-benefit index.

[0135] In this embodiment, when the calculated power supply-demand balance rate difference is within an acceptable range, that is, less than or equal to the preset power supply-demand balance rate difference, it indicates that the supply-demand balance situation of the power system is relatively good and within an acceptable fluctuation range. At this time, the carbon emission reduction amount index and the cost-benefit index are further considered to determine the coordination degree value corresponding to the first set of resource scheduling methods.

[0136] Exemplarily, obtain the first mapping relationship between the carbon emission reduction amount index and the coordination degree value, and the second mapping relationship between the cost-benefit index and the coordination degree value. Specifically, by analyzing a large amount of historical data, observe how different carbon emission reduction amount indexes and cost-benefit indexes respectively correspond to the coordination degree values, so as to summarize the rules between them and form the corresponding mapping relationships, thereby obtaining the first mapping relationship between the carbon emission reduction amount index and the coordination degree value, and the second mapping relationship between the cost-benefit index and the coordination degree value.

[0137] Exemplarily, determine the first coordination degree value corresponding to the carbon emission reduction index based on the first mapping relationship. Specifically, after obtaining the first mapping relationship between the carbon emission reduction index and the coordination degree value, substitute the carbon emission reduction index in the first set of resource scheduling methods currently concerned into this mapping relationship, and then the coordination degree value corresponding to this carbon emission reduction index, that is, the first coordination degree value, can be determined.

[0138] Exemplarily, determine the second coordination degree value corresponding to the cost-benefit index based on the second mapping relationship. Specifically, according to the second mapping relationship between the cost-benefit index and the coordination degree value, substitute the cost-benefit index in the first set of resource scheduling methods into it, so as to obtain the coordination degree value corresponding to this cost-benefit index, that is, the second coordination degree value.

[0139] Exemplarily, determine the first weight corresponding to the first coordination degree value and the second weight corresponding to the second coordination degree value, and the sum of the first weight and the second weight is 1. Specifically, if in the current power system planning, more attention is paid to the impact of carbon emission reduction on the overall coordination, then a relatively large weight may be assigned to the first coordination degree value. If more importance is attached to the cost-benefit aspect, the weight of the second coordination degree value will be correspondingly increased. The determination of the weight usually needs to comprehensively consider various factors to ensure that the evaluation result can accurately reflect the actual coordination of the resource scheduling method.

[0140] Exemplarily, determine the coordination degree value corresponding to the first set of resource scheduling methods based on the first coordination degree value, the second coordination degree value, the first weight, and the second weight. Exemplarily, calculate based on the first coordination degree value, the second coordination degree value, the first weight, and the second weight to obtain a reference coordination degree value. Specifically, calculate the reference coordination degree value according to the following formula:

[0141] Reference coordination degree value = First coordination degree value × First weight + Second coordination degree value × Second weight;

[0142] According to the above formula, the reference coordination degree value can be calculated based on the first coordination degree value, the second coordination degree value, the first weight, and the second weight.

[0143] Exemplarily, determine the proportion of new energy output corresponding to the first set of resource scheduling methods. Specifically, the proportion of new energy output refers to the proportion of the electricity provided by new energy (such as solar energy, wind energy, etc.) in the total power output under the first set of resource scheduling methods. Determining the proportion of new energy output can understand the participation degree and importance of new energy in resource scheduling. A higher proportion of new energy output helps to improve the stability of energy supply, and then improves the coordination degree of resource scheduling methods. New energy such as solar energy and wind energy is widely distributed and renewable. When the proportion of new energy output is high, it can reduce the dependence on traditional fossil energy to a certain extent and reduce the risks brought by resource shortage or supply interruption. At the same time, multiple energy sources complement each other, making the power supply more flexible, enhancing the ability of the entire energy system to cope with emergencies and meet the power demand at different times, promoting the coordination of resource scheduling in time and space. The increase in the proportion of new energy output is more environmentally friendly and can improve the coordination degree of resource scheduling methods. The proportion of new energy output has a complex impact on the cost-effectiveness of resource scheduling methods, and then affects the coordination degree.

[0144] Exemplarily, determine the target adjustment parameter corresponding to the proportion of new energy output. Specifically, it can be a preset mapping relationship between the proportion of new energy output and the adjustment parameter. Based on this mapping relationship, the target adjustment parameter corresponding to the proportion of new energy output can be determined.

[0145] Exemplarily, adjust the reference coordination degree value based on the target adjustment parameter to obtain the coordination degree value corresponding to the first set of resource scheduling methods. Specifically, calculate the coordination degree value corresponding to the first set of resource scheduling methods according to the following formula:

[0146] The coordination degree value corresponding to the first set of resource scheduling methods = reference coordination degree value × (1 + target adjustment parameter);

[0147] According to the above formula, the reference coordination degree value can be adjusted based on the target adjustment parameter to obtain the coordination degree value corresponding to the first set of resource scheduling methods.

[0148] It can be seen that by comprehensively considering the first coordination degree value, the second coordination degree value, the first weight, and the second weight to calculate the reference coordination degree value, factors in different dimensions such as the carbon emission reduction amount and cost-benefit can be taken into account, avoiding the evaluation of the coordination of resource scheduling methods from a single perspective, thus more comprehensively and accurately reflecting the comprehensive performance of resource scheduling methods. By clearly incorporating the factor of the proportion of new energy output and adjusting the reference coordination degree value by determining its corresponding target adjustment parameter, the importance of new energy in resource scheduling can be fully reflected. The development of new energy plays a key role in achieving energy transformation, reducing carbon emissions, and ensuring sustainable energy supply. This method can encourage more utilization of new energy in resource scheduling and promote the transformation of the energy structure towards a green and low-carbon direction. By dynamically determining the target adjustment parameter according to the proportion of new energy output and then adjusting the reference coordination degree value, the evaluation results can flexibly change according to the actual situation. Different resource scheduling methods may vary in the utilization of new energy. Through this dynamic adjustment mechanism, the coordination degree of various scheduling methods in different scenarios can be more accurately reflected, providing a more targeted basis for resource scheduling decisions. A higher proportion of new energy output usually corresponds to more favorable target adjustment parameters, which will prompt resource scheduling plans to pay more attention to improving the utilization efficiency and proportion of new energy during the formulation and implementation process, while taking into account factors such as carbon emission reduction amount and cost-benefit, so as to achieve the overall optimization and sustainable development of resource scheduling.

[0149] S603: When the difference in power supply-demand balance rate is greater than the preset difference in power supply-demand balance rate, determine that the coordination degree value corresponding to the first set of resource scheduling methods is 0.

[0150] In this embodiment, if the difference in power supply-demand balance rate exceeds the preset range, that is, greater than the preset difference in power supply-demand balance rate, it means that there is a large deviation in the power supply-demand balance of the power system, and there may be relatively serious problems such as insufficient or excessive power supply. In this case, regardless of how the resource scheduling method performs in terms of carbon emission reduction and cost-benefit, it is considered that the resource scheduling method is overall uncoordinated and cannot meet the most basic power supply-demand balance requirements of the power system. Therefore, directly determine the coordination degree value corresponding to the first set of resource scheduling methods as 0, indicating that the resource scheduling method is not advisable in the current situation, and the resource scheduling method needs to be adjusted or re-planned to restore the power supply-demand balance, and then consider other aspects of coordination on this basis.

[0151] It should be noted that since the first set of resource scheduling methods is any one of the n sets of resource scheduling methods, the determination method of the coordination degree value corresponding to each set of resource scheduling methods in the n sets of resource scheduling methods is the same as the determination method of the coordination degree value corresponding to the first set of resource scheduling methods. Based on the determination method of the coordination degree value corresponding to the first set of resource scheduling methods, it is possible to determine the coordination degree value corresponding to each set of resource scheduling methods in the n sets of resource scheduling methods based on the n sets of power generation characteristic indicators and the n sets of load-side power consumption characteristic indicators, and obtain n coordination degree values.

[0152] S207: Determine the maximum coordination degree value among the n coordination degree values.

[0153] In this embodiment, among the obtained n coordination degree values, the largest one is found through comparison and screening. This maximum coordination degree value represents the evaluation index value corresponding to the scheduling method with the best comprehensive performance among all the calculated resource scheduling methods.

[0154] S208: Determine the resource scheduling method corresponding to the maximum coordination degree value to obtain the target resource scheduling method.

[0155] In this embodiment, after finding the maximum coordination degree value, determine the set of resource scheduling methods corresponding to this value. This set of resource scheduling methods is considered to be the best way for resource scheduling after considering various factors on the power generation side and the load side. It is used as the target resource scheduling method and can be used as a reference or implementation plan for actual power system resource scheduling to achieve the optimal operation of the power system in terms of low carbon, economy, reliability, etc.

[0156] It can be seen that by obtaining the adjustable load resource data and analyzing it from the power generation side and the load side respectively, comprehensively considering the power generation characteristic indicators (such as power supply quantity, carbon emissions, power generation cost) and the load side electricity consumption characteristic indicators (such as electricity demand, carbon emissions, electricity consumption cost), it is possible to comprehensively and systematically evaluate the performance of different resource scheduling methods in the power system, avoid the one-sidedness brought by evaluating from a single perspective, determine the coordination degree value for each group of resource scheduling methods, quantify the resource scheduling effect, make different scheduling methods comparable, and by comparing these quantified values, it is possible to intuitively judge which resource scheduling method is better, provide a clear basis for resource scheduling decisions, determine the target resource scheduling method corresponding to the maximum coordination degree value, help find a resource scheduling plan that achieves the best balance between the power generation side and the load side, thus realizing the optimal allocation of power system resources, improving resource utilization efficiency, reducing the overall cost, reducing carbon emissions, and enhancing the overall operation efficiency and benefits of the power system. Obtaining multiple groups of resource scheduling methods and their corresponding characteristic indicators and coordination degree values enables the power system to find relatively optimal resource scheduling methods when facing different preset time periods, different adjustable load resource data, and different system operation requirements, enhancing the power system's ability to cope with various complex situations and meet diverse needs.

[0157] In summary, implementing the embodiments of the present invention has the following beneficial effects:

[0158] It can be seen that in the resource scheduling method described in the embodiments of the present invention, first, the adjustable load resource data of the power system within a preset time period is obtained, and then the adjustable load resource data is input into a preset low-carbon scheduling model on the power generation side to obtain n groups of resource scheduling methods. Then, the n groups of resource scheduling methods are input into a preset low-carbon scheduling model on the load side to obtain the load side electricity consumption data corresponding to each group of resource scheduling methods in the n groups of resource scheduling methods, obtaining n groups of load side electricity consumption data. Then, the power generation characteristic indicators corresponding to the n groups of resource scheduling methods are determined, obtaining n groups of power generation characteristic indicators, and also determining the load side electricity consumption characteristic indicators corresponding to each group of load side electricity consumption data in the n groups of load side electricity consumption data, obtaining n groups of load side electricity consumption characteristic indicators, and based on the n groups of power generation characteristic indicators and the n groups of load side electricity consumption characteristic indicators, determining the coordination degree value corresponding to each group of resource scheduling methods in the n groups of resource scheduling methods, obtaining n coordination degree values, thereby determining the maximum coordination degree value among the n coordination degree values, and finally determining the resource scheduling method corresponding to the maximum coordination degree value, obtaining the target resource scheduling method, which improves the coordination of power system resource scheduling.

[0159] Please refer to Figure 7 , Figure 7It is a schematic structural diagram of a resource scheduling device provided by an embodiment of the present application. The resource scheduling device 700 includes: an acquisition unit 701 and a processing unit 702;

[0160] The acquisition unit 701 is configured to acquire adjustable load resource data of the power system within a preset time period;

[0161] The processing unit 702 is configured to input the adjustable load resource data into a preset low-carbon scheduling model on the power generation side to obtain n sets of resource scheduling methods; n is an integer greater than 1;

[0162] Determine the power generation characteristic indexes corresponding to the n sets of resource scheduling methods to obtain n sets of power generation characteristic indexes; each set of power generation characteristic indexes includes the power supply amount on the power generation side, the carbon emission amount on the power generation side, and the power generation cost on the power generation side;

[0163] Input the n sets of resource scheduling methods into a preset low-carbon scheduling model on the load side to obtain the load-side power consumption data corresponding to each set of resource scheduling methods in the n sets of resource scheduling methods, and obtain n sets of load-side power consumption data;

[0164] Determine the load-side power consumption characteristic indexes corresponding to each set of load-side power consumption data in the n sets of load-side power consumption data to obtain n sets of load-side power consumption characteristic indexes; each set of load-side power consumption characteristic indexes includes the power demand amount on the load side, the carbon emission amount on the load side, and the power consumption cost on the load side;

[0165] Based on the n sets of power generation characteristic indexes and the n sets of load-side power consumption characteristic indexes, determine the coordination degree values corresponding to each set of resource scheduling methods in the n sets of resource scheduling methods to obtain n coordination degree values; the greater the coordination degree value of the resource scheduling method, the better the resource scheduling effect of the resource scheduling method;

[0166] Determine the maximum coordination degree value among the n coordination degree values;

[0167] Determine the resource scheduling method corresponding to the maximum coordination degree value to obtain the target resource scheduling method.

[0168] In some possible implementation manners, in terms of determining the coordination degree values corresponding to each set of resource scheduling methods in the n sets of resource scheduling methods based on the n sets of power generation characteristic indexes and the n sets of load-side power consumption characteristic indexes to obtain n coordination degree values, the processing unit 702 is specifically configured to:

[0169] Obtain the power generation side power supply, power generation side carbon emissions, and power generation side power generation cost corresponding to the first set of power generation characteristic indicators, and obtain the first power generation side power supply, the first power generation side carbon emissions, and the first power generation side power generation cost; the first set of power generation characteristic indicators is the power generation characteristic indicators corresponding to the first set of resource scheduling methods among the n sets of power generation characteristic indicators, and the first set of resource scheduling methods is any set of resource scheduling methods among the n sets of resource scheduling methods;

[0170] Obtain the load side power demand, load side carbon emissions, and load side power consumption cost corresponding to the first set of load side power consumption characteristic indicators, and obtain the first load side power demand, the first load side carbon emissions, and the first load side power consumption cost; the first set of load side power consumption characteristic indicators is the load side power consumption characteristic indicators corresponding to the first set of power generation characteristic indicators among the n sets of load side power consumption characteristic indicators;

[0171] Determine the power supply and demand balance rate based on the first power generation side power supply and the first load side power demand;

[0172] Determine the carbon emission reduction index based on the first power generation side carbon emissions and the first load side carbon emissions;

[0173] Determine the cost-benefit index based on the first power generation side power generation cost and the first load side power consumption cost;

[0174] Determine the coordination degree value corresponding to the first set of resource scheduling methods based on the power supply and demand balance rate, the carbon emission reduction index, and the cost-benefit index.

[0175] In some possible implementation manners, in terms of determining the carbon emission reduction index based on the first power generation side carbon emissions and the first load side carbon emissions, the processing unit 702 is specifically configured to:

[0176] Obtain the historical power generation side carbon emissions and historical load side carbon emissions of the power system during the historical time period; the end time of the historical time period is earlier than the start time of the preset time period, and the duration of the historical time period is the same as the duration of the preset time period;

[0177] Determine the difference between the first power generation side carbon emissions and the historical power generation side carbon emissions to obtain the power generation side carbon emission difference;

[0178] Determine the difference between the first load side carbon emissions and the historical load side carbon emissions to obtain the load side carbon emission difference;

[0179] Determine the carbon emission reduction value based on the power generation side carbon emission difference and the load side carbon emission difference;

[0180] Determine the carbon emission reduction index based on the carbon emission reduction value.

[0181] In some possible implementation manners, in terms of determining the cost-benefit index based on the first power generation side power generation cost and the first load side power consumption cost, the processing unit 702 is specifically configured to:

[0182] Determine the target power consumption cost based on the first power generation side power generation cost and the first load side power consumption cost;

[0183] Obtain the economic benefit corresponding to the first set of resource scheduling manners to obtain the target economic benefit;

[0184] Determine the cost-benefit index based on the target power consumption cost and the target economic benefit.

[0185] In some possible implementation manners, in terms of determining the coordination degree value corresponding to the first set of resource scheduling manners based on the power supply-demand balance rate, the carbon emission reduction index, and the cost-benefit index, the processing unit 702 is specifically configured to:

[0186] Determine the difference between the power supply-demand balance rate and the preset power supply-demand balance rate to obtain the power supply-demand balance rate difference;

[0187] When the power supply-demand balance rate difference is less than or equal to the preset power supply-demand balance rate difference, determine the coordination degree value corresponding to the first set of resource scheduling manners based on the carbon emission reduction index and the cost-benefit index;

[0188] When the power supply-demand balance rate difference is greater than the preset power supply-demand balance rate difference, determine that the coordination degree value corresponding to the first set of resource scheduling manners is 0.

[0189] In some possible implementation manners, in terms of determining the coordination degree value corresponding to the first set of resource scheduling manners based on the carbon emission reduction index and the cost-benefit index, the processing unit 702 is specifically configured to:

[0190] Obtain the first mapping relationship between the carbon emission reduction index and the coordination degree value, and the second mapping relationship between the cost-benefit index and the coordination degree value;

[0191] Determine the first coordination degree value corresponding to the carbon emission reduction index based on the first mapping relationship;

[0192] Determine the second coordination degree value corresponding to the cost-benefit index based on the second mapping relationship;

[0193] Determine a first weight corresponding to the first coordination degree value and a second weight corresponding to the second coordination degree value; the sum of the first weight and the second weight is 1;

[0194] Based on the first coordination degree value, the second coordination degree value, the first weight, and the second weight, determine the coordination degree value corresponding to the first set of resource scheduling methods.

[0195] In some possible implementation manners, in terms of determining the coordination degree value corresponding to the first set of resource scheduling methods based on the first coordination degree value, the second coordination degree value, the first weight, and the second weight, the processing unit 702 is specifically configured to:

[0196] Perform calculations based on the first coordination degree value, the second coordination degree value, the first weight, and the second weight to obtain a reference coordination degree value;

[0197] Determine the proportion of new energy output corresponding to the first set of resource scheduling methods;

[0198] Determine a target adjustment parameter corresponding to the proportion of new energy output;

[0199] Adjust the reference coordination degree value based on the target adjustment parameter to obtain the coordination degree value corresponding to the first set of resource scheduling methods.

[0200] Please refer to Figure 8 , Figure 8 is a schematic structural diagram of an electronic device provided by an embodiment of the present application. As Figure 8 shown, the electronic device 800 includes a transceiver 801, a processor 802, and a memory 803. They are connected through a bus 804. The memory 803 is used to store computer programs and data, and the transceiver 801 can transmit the data stored in the memory 803 to the processor 802. The above program includes instructions for performing the following steps:

[0201] Obtain adjustable load resource data of the power system within a preset time period;

[0202] Input the adjustable load resource data into a preset low-carbon scheduling model on the power generation side to obtain n sets of resource scheduling methods; n is an integer greater than 1;

[0203] Determine the power generation characteristic indicators corresponding to the n sets of resource scheduling methods to obtain n sets of power generation characteristic indicators; each set of power generation characteristic indicators includes the power generation side power supply, the power generation side carbon emissions, and the power generation side power generation cost;

[0204] Input the n sets of resource scheduling methods into a preset low-carbon scheduling model on the load side to obtain the load-side electricity consumption data corresponding to each set of resource scheduling methods in the n sets of resource scheduling methods, and obtain n sets of load-side electricity consumption data;

[0205] Determine the load-side electricity consumption characteristic indexes corresponding to each set of load-side electricity consumption data in the n sets of load-side electricity consumption data, and obtain n sets of load-side electricity consumption characteristic indexes; Each set of load-side electricity consumption characteristic indexes includes the load-side electricity demand, the load-side carbon emission, and the load-side electricity cost;

[0206] Based on the n sets of power generation characteristic indexes and the n sets of load-side electricity consumption characteristic indexes, determine the coordination degree value corresponding to each set of resource scheduling methods in the n sets of resource scheduling methods, and obtain n coordination degree values; The greater the coordination degree value of the resource scheduling method, the better the resource scheduling effect of the resource scheduling method;

[0207] Determine the maximum coordination degree value among the n coordination degree values;

[0208] Determine the resource scheduling method corresponding to the maximum coordination degree value to obtain the target resource scheduling method.

[0209] In some possible implementation manners, in terms of determining the coordination degree value corresponding to each set of resource scheduling methods in the n sets of resource scheduling methods based on the n sets of power generation characteristic indexes and the n sets of load-side electricity consumption characteristic indexes, the above program includes instructions for performing the following steps:

[0210] Obtain the power generation-side power supply amount, the power generation-side carbon emission, and the power generation-side power generation cost corresponding to the first set of power generation characteristic indexes, and obtain the first power generation-side power supply amount, the first power generation-side carbon emission, and the first power generation-side power generation cost; The first set of power generation characteristic indexes is the power generation characteristic indexes corresponding to the first set of resource scheduling methods in the n sets of power generation characteristic indexes, and the first set of resource scheduling methods is any set of resource scheduling methods in the n sets of resource scheduling methods;

[0211] Obtain the load-side electricity demand, the load-side carbon emission, and the load-side electricity cost corresponding to the first set of load-side electricity consumption characteristic indexes, and obtain the first load-side electricity demand, the first load-side carbon emission, and the first load-side electricity cost; The first set of load-side electricity consumption characteristic indexes is the load-side electricity consumption characteristic indexes corresponding to the first set of power generation characteristic indexes in the n sets of load-side electricity consumption characteristic indexes;

[0212] Determine the power supply-demand balance rate based on the first power generation-side power supply amount and the first load-side electricity demand;

[0213] Determine the carbon emission reduction amount index based on the first power generation-side carbon emission and the first load-side carbon emission;

[0214] Determine a cost - benefit index based on the first power generation - side generation cost and the first load - side electricity consumption cost;

[0215] Determine the coordination degree value corresponding to the first set of resource scheduling methods based on the power supply - demand balance rate, the carbon emission reduction amount index, and the cost - benefit index.

[0216] In some possible implementation manners, in terms of determining the carbon emission reduction amount index based on the first power generation - side carbon emissions and the first load - side carbon emissions, the above - mentioned procedure includes instructions for performing the following steps:

[0217] Obtain the historical power generation - side carbon emissions and historical load - side carbon emissions of the power system within a historical time period; the end time of the historical time period is earlier than the start time of the preset time period, and the duration of the historical time period is the same as the duration of the preset time period;

[0218] Determine the difference between the first power generation - side carbon emissions and the historical power generation - side carbon emissions to obtain the power generation - side carbon emission difference;

[0219] Determine the difference between the first load - side carbon emissions and the historical load - side carbon emissions to obtain the load - side carbon emission difference;

[0220] Determine the carbon emission reduction value based on the power generation - side carbon emission difference and the load - side carbon emission difference;

[0221] Determine the carbon emission reduction amount index based on the carbon emission reduction value.

[0222] In some possible implementation manners, in terms of determining the cost - benefit index based on the first power generation - side generation cost and the first load - side electricity consumption cost, the above - mentioned procedure includes instructions for performing the following steps:

[0223] Determine the target electricity consumption cost based on the first power generation - side generation cost and the first load - side electricity consumption cost;

[0224] Obtain the economic benefit corresponding to the first set of resource scheduling methods to get the target economic benefit;

[0225] Determine the cost - benefit index based on the target electricity consumption cost and the target economic benefit.

[0226] In some possible implementation manners, in terms of determining the coordination degree value corresponding to the first set of resource scheduling methods based on the power supply - demand balance rate, the carbon emission reduction amount index, and the cost - benefit index, the above - mentioned procedure includes instructions for performing the following steps:

[0227] Determine the difference between the power supply-demand balance rate and the preset power supply-demand balance rate to obtain the power supply-demand balance rate difference;

[0228] When the power supply-demand balance rate difference is less than or equal to the preset power supply-demand balance rate difference, determine the coordination degree value corresponding to the first set of resource scheduling methods based on the carbon emission reduction amount index and the cost-benefit index;

[0229] When the power supply-demand balance rate difference is greater than the preset power supply-demand balance rate difference, determine that the coordination degree value corresponding to the first set of resource scheduling methods is 0.

[0230] In some possible implementation manners, in terms of determining the coordination degree value corresponding to the first set of resource scheduling methods based on the carbon emission reduction amount index and the cost-benefit index, the above program includes instructions for performing the following steps:

[0231] Obtain a first mapping relationship between the carbon emission reduction amount index and the coordination degree value, and a second mapping relationship between the cost-benefit index and the coordination degree value;

[0232] Determine a first coordination degree value corresponding to the carbon emission reduction amount index based on the first mapping relationship;

[0233] Determine a second coordination degree value corresponding to the cost-benefit index based on the second mapping relationship;

[0234] Determine a first weight value corresponding to the first coordination degree value and a second weight value corresponding to the second coordination degree value; the sum of the first weight value and the second weight value is 1;

[0235] Determine the coordination degree value corresponding to the first set of resource scheduling methods based on the first coordination degree value, the second coordination degree value, the first weight value, and the second weight value.

[0236] In some possible implementation manners, in terms of determining the coordination degree value corresponding to the first set of resource scheduling methods based on the first coordination degree value, the second coordination degree value, the first weight value, and the second weight value, the above program includes instructions for performing the following steps:

[0237] Perform calculations based on the first coordination degree value, the second coordination degree value, the first weight value, and the second weight value to obtain a reference coordination degree value;

[0238] Determine the proportion of new energy output corresponding to the first set of resource scheduling methods;

[0239] Determine a target adjustment parameter corresponding to the proportion of new energy output;

[0240] Adjust the reference coordination degree value based on the target adjustment parameter to obtain the coordination degree value corresponding to the first set of resource scheduling methods.

[0241] It should be understood that the electronic devices in this application may include resource scheduling devices, smart phones (such as Android phones, iOS phones, Windows Phone phones, etc.), tablet computers, handheld computers, laptop computers, mobile Internet devices MID (Mobile Internet Devices, abbreviated as: MID), or wearable devices, or servers, edge computing nodes, etc. The above-mentioned electronic devices are only examples, not an exhaustive list, and include but are not limited to the above-mentioned electronic devices.

[0242] This application embodiment also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program, and the computer program is executed by a processor to implement part or all of the steps of any one of the resource scheduling methods described in the above method embodiments.

[0243] This application embodiment also provides a computer program product. The computer program product includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to execute part or all of the steps of any one of the resource scheduling methods described in the above method embodiments.

[0244] It should be noted that for the foregoing method embodiments, for the sake of simple description, they are all expressed as a series of action combinations. However, those skilled in the art should know that this application is not limited by the described action sequence, because according to this application, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily essential to this application.

[0245] In the above embodiments, the descriptions of each embodiment have their own emphases. For the parts not detailed in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0246] In several embodiments provided by this application, it should be understood that the disclosed device can be implemented in other ways. For example, the device embodiments described above are only illustrative. For example, the division of units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed mutual coupling or direct coupling or communication connection can be through some interfaces, and the indirect coupling or communication connection of the device or unit can be in an electrical or other form.

[0247] The unit described as a separate component may or may not be physically separated. The component shown as a unit may or may not be a physical unit, that is, it may be located in one place or may be distributed over multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0248] In addition, each functional unit in various embodiments of the present application may be integrated in a processing unit, may exist physically separately for each unit, or two or more units may be integrated in one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of a software program module.

[0249] If the integrated unit is implemented in the form of a software program module and sold or used as an independent product, it can be stored in a computer-readable memory. Based on such an understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods in various embodiments of the present application. The aforementioned memory includes: USB flash drives, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), mobile hard disks, magnetic disks, or optical discs and other various media that can store program codes.

[0250] Those of ordinary skill in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing relevant hardware through a program. This program can be stored in a computer-readable memory. The memory may include: flash drives, read-only memories (abbreviation: ROM), random access memories (abbreviation: RAM), magnetic disks, or optical discs, etc.

[0251] The above has introduced the embodiments of the present application in detail. Specific examples are used in this article to elaborate on the principle and embodiments of the present application. The description of the above embodiments is only used to help understand the method and its core idea of the present application; at the same time, for those of ordinary skill in the art, according to the idea of the present application, there will be changes in the specific embodiments and application scopes. In summary, the content of this specification should not be construed as a limitation to the present application.

Claims

1. A resource scheduling method, characterized in that: include: Obtaining adjustable load resource data of the power system within a preset time period; Input the adjustable load resource data into a preset power generation side low-carbon scheduling model to obtain n groups of resource scheduling methods; n is an integer greater than 1; Determine the power generation characteristic indicators corresponding to the n groups of resource scheduling modes to obtain n groups of power generation characteristic indicators; each group of power generation characteristic indicators includes power supply on the power generation side, carbon emissions on the power generation side, and power generation cost on the power generation side; Inputting the n groups of resource scheduling methods into a preset load-side low-carbon scheduling model, obtaining load-side electricity consumption data corresponding to each group of resource scheduling methods in the n groups of resource scheduling methods, and obtaining n groups of load-side electricity consumption data; Determine the load side power consumption characteristic index corresponding to each set of load side power consumption data in the n sets of load side power consumption data, and obtain n sets of load side power consumption characteristic indexes; each set of load side power consumption characteristic indexes includes load side power demand, load side carbon emissions, and load side power consumption cost; Determine the coordination degree value corresponding to each of the n groups of resource scheduling modes based on the n groups of power generation characteristic indicators and the n groups of load-side power consumption characteristic indicators, and obtain n coordination degree values; The greater the coordination degree value of the resource scheduling method, the better the resource scheduling effect of the resource scheduling method; Determining the maximum coordination degree value among the n coordination degree values; Determine the resource scheduling method corresponding to the maximum coordination degree value, and obtain the target resource scheduling method.

2. The method according to claim 1, characterized in that The determining of the coordination degree value corresponding to each of the n groups of resource scheduling modes based on the n groups of power generation characteristic indicators and the n groups of load-side power consumption characteristic indicators to obtain n coordination degree values ​​includes: Obtaining the power supply on the power generation side, the carbon emissions on the power generation side, and the power generation cost on the power generation side corresponding to the first group of power generation characteristic indicators, and obtaining the first power supply on the power generation side, the first carbon emissions on the power generation side, and the first power generation cost on the power generation side; the first group of power generation characteristic indicators is the power generation characteristic indicators corresponding to the first group of resource scheduling methods in the n groups of power generation characteristic indicators, and the first group of resource scheduling methods is any group of resource scheduling methods in the n groups of resource scheduling methods; Obtain the load side power demand, load side carbon emissions, and load side power cost corresponding to the first group of load side power consumption characteristic indicators to obtain the first load side power demand, the first load side carbon emissions, and the first load side power cost; the first group of load side power consumption characteristic indicators are the load side power consumption characteristic indicators corresponding to the first group of power generation characteristic indicators in the n groups of load side power consumption characteristic indicators; Determining a power supply and demand balance rate based on the power supply at the first power generation side and the power demand at the first load side; Determining a carbon emission reduction index based on the first power generation side carbon emissions and the first load side carbon emissions; Determining a cost-effectiveness index based on the first power generation side power generation cost and the first load side power consumption cost; The coordination degree value corresponding to the first group of resource scheduling methods is determined based on the electricity supply and demand balance rate, the carbon emission reduction index and the cost-effectiveness index.

3. The method according to claim 2, characterized in that The determining of the carbon emission reduction index based on the first power generation side carbon emissions and the first load side carbon emissions includes: Acquire the historical generation-side carbon emissions and the historical load-side carbon emissions of the power system in a historical time period; the end time of the historical time period is earlier than the start time of the preset time period, and the duration of the historical time period is the same as the duration of the preset time period; Determine the difference between the first power generation side carbon emissions and the historical power generation side carbon emissions to obtain the power generation side carbon emissions difference; Determine the difference between the first load-side carbon emissions and the historical load-side carbon emissions to obtain a load-side carbon emissions difference; Determine a carbon emission reduction value based on the difference between the carbon emission on the power generation side and the carbon emission on the load side; The carbon emission reduction indicator is determined based on the carbon emission reduction value.

4. The method according to claim 2, characterized in that The determining of the cost-effectiveness index based on the first power generation side power generation cost and the first load side power consumption cost includes: Determine a target electricity cost based on the first power generation side power generation cost and the first load side power cost; Obtaining the economic benefits corresponding to the first group of resource scheduling methods to obtain target economic benefits; The cost-effectiveness index is determined based on the target electricity cost and the target economic benefit.

5. The method according to any one of claims 2 to 4, characterized in that: The determining of the coordination degree value corresponding to the first group of resource scheduling modes based on the power supply and demand balance rate, the carbon emission reduction index and the cost-effectiveness index includes: Determine the difference between the power supply and demand balance rate and a preset power supply and demand balance rate to obtain the power supply and demand balance rate difference; When the power supply and demand balance rate difference is less than or equal to a preset power supply and demand balance rate difference, determining a coordination degree value corresponding to the first group of resource scheduling modes based on the carbon emission reduction index and the cost-effectiveness index; When the power supply and demand balance rate difference is greater than the preset power supply and demand balance rate difference, it is determined that the coordination degree value corresponding to the first group of resource scheduling methods is 0.

6. The method according to claim 5, characterized in that The determining the coordination degree value corresponding to the first group of resource scheduling modes based on the carbon emission reduction index and the cost-effectiveness index includes: Obtaining a first mapping relationship between a carbon emission reduction index and a coordination degree value, and a second mapping relationship between a cost-effectiveness index and a coordination degree value; Determine a first coordination degree value corresponding to the carbon emission reduction indicator based on the first mapping relationship; Determine a second coordination degree value corresponding to the cost-effectiveness indicator based on the second mapping relationship; Determine a first weight corresponding to the first coordination degree value and a second weight corresponding to the second coordination degree value; the sum of the first weight and the second weight is 1; The coordination degree value corresponding to the first group of resource scheduling modes is determined based on the first coordination degree value, the second coordination degree value, the first weight and the second weight.

7. The method according to claim 6, characterized in that The determining the coordination degree value corresponding to the first group of resource scheduling modes based on the first coordination degree value, the second coordination degree value, the first weight value, and the second weight value includes: Calculating based on the first coordination degree value, the second coordination degree value, the first weight value, and the second weight value to obtain a reference coordination degree value; Determine the proportion of new energy output corresponding to the first group of resource scheduling methods; Determine the target adjustment parameter corresponding to the new energy output ratio; The reference coordination degree value is adjusted based on the target adjustment parameter to obtain the coordination degree value corresponding to the first group of resource scheduling methods.

8. A resource scheduling device, characterized in that: The device comprises: an acquisition unit and a processing unit; The acquisition unit is used to acquire the adjustable load resource data of the power system within a preset time period; The processing unit is used to input the adjustable load resource data into a preset power generation side low-carbon scheduling model to obtain n groups of resource scheduling methods; n is an integer greater than 1; Determine the power generation characteristic indicators corresponding to the n groups of resource scheduling modes to obtain n groups of power generation characteristic indicators; each group of power generation characteristic indicators includes power supply on the power generation side, carbon emissions on the power generation side, and power generation cost on the power generation side; Inputting the n groups of resource scheduling methods into a preset load-side low-carbon scheduling model, obtaining load-side electricity consumption data corresponding to each group of resource scheduling methods in the n groups of resource scheduling methods, and obtaining n groups of load-side electricity consumption data; Determine the load side power consumption characteristic index corresponding to each set of load side power consumption data in the n sets of load side power consumption data, and obtain n sets of load side power consumption characteristic indexes; each set of load side power consumption characteristic indexes includes load side power demand, load side carbon emissions, and load side power consumption cost; Determine the coordination degree value corresponding to each of the n groups of resource scheduling modes based on the n groups of power generation characteristic indicators and the n groups of load-side power consumption characteristic indicators, and obtain n coordination degree values; the greater the coordination degree value of the resource scheduling mode, the better the resource scheduling effect of the resource scheduling mode; Determining the maximum coordination degree value among the n coordination degree values; Determine the resource scheduling method corresponding to the maximum coordination degree value, and obtain the target resource scheduling method.

9. An electronic device, characterized in that: The method comprises a processor, a memory, a communication interface and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, and the one or more programs include instructions for executing the steps in the 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 a computer program, and the computer program is executed by a processor to implement the method according to any one of claims 1 to 7.

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