Load balancing method, device, electronic equipment and storage medium for power system

Abstract

The present invention discloses a load balancing method, device, electronic device and storage medium for an electric power system, and relates to the field of electric power systems. The method comprises: in response to receiving a balancing request for performing load balancing operation on the electric power system, determining balancing demand information and balancing subject information corresponding to the balancing request; solving the load balancing model corresponding to the electric power system based on the balancing demand information and the balancing subject information, and obtaining a load balancing strategy for the electric power system, wherein the load balancing strategy includes the switch state and the required balancing power of the electric power equipment with load balancing capability at any time; performing load balancing operation on the electric power system according to the load balancing strategy, and obtaining a load balancing result, wherein the load balancing result is used to characterize whether the electric power system meets the load balancing demand. The present invention solves the technical problem of poor load balancing effect of the electric power system in the related art.

Description

Technical Field

[0001] The present invention relates to the field of power systems, and in particular to a load balancing method, device, electronic equipment and storage medium for a power system. Background Art

[0002] With the diversification of electricity market mechanisms, the operation of the power system faces greater uncertainty and volatility. As a key means to enhance the flexibility of the power system and promote the balance between supply and demand, the importance of power demand-side response is becoming increasingly prominent.

[0003] At present, the existing demand response strategies in related technologies lack a mature and reliable mechanism for the coordination of rigid control and flexible control of user resources. At the same time, because only the grid side is considered and the user side is lacking, no guiding regulation scheme has been formed, resulting in unsatisfactory response effects for some users under the power regulation strategy, which in turn leads to poor load balancing effects of the power system in related technologies.

[0004] To address the above-mentioned problems, no effective solution has been proposed yet. Summary of the invention

[0005] The embodiments of the present invention provide a load balancing method, device, electronic device and storage medium for an electric power system, so as to at least solve the technical problem of poor load balancing effect of the electric power system in the related art.

[0006] According to one aspect of an embodiment of the present invention, a load balancing method for an electric power system is provided, comprising: in response to receiving a balancing request for performing a load balancing operation on the electric power system, determining balancing demand information and balancing subject information corresponding to the balancing request, wherein the balancing demand information is used to characterize the load balancing demand of the electric power system, and the balancing subject information is information of electric power equipment with load balancing capability in the electric power system; solving a load balancing model corresponding to the electric power system based on the balancing demand information and the balancing subject information to obtain a load balancing strategy for the electric power system, wherein the load balancing strategy includes the switching state and the required balancing power of the electric power equipment with load balancing capability at any time; performing a load balancing operation on the electric power system according to the load balancing strategy to obtain a load balancing result, wherein the load balancing result is used to characterize whether the electric power system meets the load balancing demand.

[0007] Furthermore, the method also includes: determining multiple load balancing targets, wherein the multiple load balancing targets include at least two of the following: minimizing the volatility of load balancing operations on the grid side of the power system, minimizing the cost of load balancing on the grid side, and minimizing the cost of user-side participation in load balancing response of the power system; and constructing a load balancing model based on multiple load balancing targets.

[0008] Furthermore, a load balancing model is constructed based on the load balancing target, including: determining the weight of each load balancing target using a scaling construction method; determining target constraints corresponding to the load balancing model, wherein the target constraints are used to limit the solution space of the load balancing model; and constructing a load balancing model based on multiple load balancing targets, the weight of each load balancing target, and the target constraints.

[0009] Furthermore, the weight of each load balancing target is determined by using a scaling construction method, including: quantifying the importance of multiple load balancing targets to obtain quantified results of multiple load balancing targets; sorting the multiple load balancing targets based on the quantified results of the multiple load balancing targets to obtain multiple sorted load balancing targets; determining the scaling value of any two adjacent load balancing targets based on the quantified results of any two adjacent load balancing targets among the sorted multiple load balancing targets, wherein the scaling value is used to quantify the relative importance between two load balancing targets corresponding to any two adjacent objective functions, and the objective function is used to describe a mathematical expression for measuring the load balancing target; constructing a judgment matrix based on the scale values ​​of any two adjacent load balancing targets; and determining the weight of each objective function based on the judgment matrix.

[0010] Furthermore, the target constraint conditions corresponding to the load balancing model are determined, including: determining the safe load rate interval, voltage amplitude interval and current amplitude interval corresponding to the load balancing model; determining the operating load constraint conditions based on the safe load rate interval; determining the node voltage constraint conditions based on the voltage amplitude interval; determining the node current constraint conditions based on the current amplitude interval; determining the target constraint conditions based on the operating load constraint conditions, the node voltage constraint conditions and the node current constraint conditions.

[0011] Furthermore, a load balancing model is constructed based on multiple load balancing targets, the weight of each load balancing target and target constraints, including: weighting multiple load balancing targets based on the weight of each load balancing target to obtain a total balancing target; and constructing a load balancing model according to the total balancing target and target constraints.

[0012] Furthermore, based on the weight of each load balancing target, multiple load balancing targets are weighted to obtain a total balancing target, including: based on the multiple load balancing targets, determining multiple objective functions corresponding to the multiple load balancing targets; based on the weight of each load balancing target, weighting the multiple objective functions to obtain a total balancing target.

[0013] Furthermore, based on the weight of each load balancing target, multiple objective functions are weighted to obtain a total balancing target, including: dimensionlessly processing multiple objective functions to obtain multiple dimensionless results; based on the weight of each load balancing target, weighting multiple dimensionless results to obtain a total balancing target.

[0014] Furthermore, the load balancing model is solved based on the balancing demand information and the balancing subject information to obtain the load balancing strategy, including: using a particle swarm algorithm to solve the load balancing model based on the balancing demand information and the balancing subject information to obtain the load balancing strategy.

[0015] Furthermore, the load balancing information includes at least one of the following: the load amount to be balanced of the power system, the duration of balancing required by the power system, the front load of the power system, the balancing response subsidy electricity price, the subsidy coefficient, the time-of-use electricity price for users, and the power equipment in the power system that can respond to load balancing. The balancing subject information includes at least one of the following: the type of power equipment, the initial switching state of the power equipment, the starting power of the power equipment, the upward load boundary of the power equipment, and the downward load boundary of the power equipment.

[0016] According to another aspect of an embodiment of the present invention, a load balancing device for an electric power system is also provided, including: an acquisition module, for determining, in response to receiving a balancing request for performing a load balancing operation on the electric power system, balancing demand information and balancing subject information corresponding to the balancing request, wherein the balancing demand information is used to characterize the load balancing demand of the electric power system, and the balancing subject information is information of electric power equipment with load balancing capability in the electric power system; a solution module, for solving a load balancing model corresponding to the electric power system based on the balancing demand information and the balancing subject information, and obtaining a load balancing strategy for the electric power system, wherein the load balancing strategy includes the switching state and the required balancing power of the electric power equipment with load balancing capability at any time; and a balancing module, for performing a load balancing operation on the electric power system according to the load balancing strategy, and obtaining a load balancing result, wherein the load balancing result is used to characterize whether the electric power system meets the load balancing demand.

[0017] According to another aspect of an embodiment of the present invention, there is further provided an electronic device, comprising: a memory storing an executable program; and a processor for running the program, wherein the load balancing method of the power system described above is executed when the program is running.

[0018] According to another aspect of an embodiment of the present invention, a computer-readable storage medium is also provided, including a stored executable program, wherein when the executable program runs, the device where the storage medium is located is controlled to execute the above-mentioned load balancing method for the power system.

[0019] According to another aspect of an embodiment of the present invention, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the load balancing method of the power system described above is implemented.

[0020] In an embodiment of the present invention, first, in response to receiving a balancing request for performing load balancing operation on the power system, the balancing demand information and balancing subject information corresponding to the balancing request are determined; then, based on the balancing demand information and balancing subject information, the load balancing model corresponding to the power system is solved to obtain the load balancing strategy of the power system; finally, the power system is load balancing according to the load balancing strategy to obtain the load balancing result. It is easy to notice that the present application obtains the load balancing strategy corresponding to the balancing demand information and balancing subject information of the power system by solving the load balancing model, and then performs balancing operation on the power system according to the load balancing strategy to obtain the load balancing result of the power system, thereby realizing the judgment of the load balancing demand capacity of the power system, and at the same time realizing the precise control of the load balancing operation of the power system, thereby solving the technical problem of poor load balancing effect of the power system in the related technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0022] Figure 1 is a flow chart of a load balancing method for a power system according to an embodiment of the present invention;

[0023] Figure 2 It is a schematic diagram of an optional load balancing device of an electric power system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0024] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0025] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0026] According to an embodiment of the present invention, an embodiment of a load balancing method for an electric power system is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0027] Figure 1 is a flow chart of a load balancing method for a power system according to an embodiment of the present invention. Figure 1 As shown, the method comprises the following steps:

[0028] Step S102, in response to receiving a balancing request for performing load balancing operation on the power system, determining the balancing demand information and balancing subject information corresponding to the balancing request, wherein the balancing demand information is used to characterize the load balancing demand of the power system, and the balancing subject information is the information of the power equipment in the power system that has load balancing capability.

[0029] The power system in the above steps is used to describe the power system composed of power stations, transmission networks, substations and distribution networks. Power stations can be coal-fired power generation, hydropower generation, nuclear power generation, wind power generation, etc.; electric energy is transmitted to the distribution network through the transmission network, and the distribution network distributes the electric energy to end users. The power system is an important part of the infrastructure of modern society, which can ensure the stable supply of electricity and support the power needs of industry, commerce and residents.

[0030] The load balancing operation in the above steps is used to describe a series of adjustment measures taken by the power system to maintain the balance between supply and demand. The types of load balancing operations may include but are not limited to adjusting the output of generator sets, changing the load distribution of transmission lines, initiating demand-side management measures, etc. The role of load balancing operations includes but is not limited to ensuring the stable operation of the power system, preventing equipment damage and energy waste, etc.

[0031] The balancing request in the above steps is used to describe the instruction issued by the power system control center, which realizes the overall supply and demand balance of the power system by requiring the load in the power system to be adjusted.

[0032] The above-mentioned balancing request may be issued in the following ways, but is not limited to:

[0033] The first case: it can be automatically generated and issued by the power system control center, usually triggered by the power system monitoring equipment when load imbalance is detected;

[0034] The second situation: it can be manually issued, usually by an operator who issues a balancing request based on the specific situation of the power system.

[0035] The above-mentioned method of issuing the balancing request is only an example. The specific method of issuing the balancing request needs to be determined according to the actual situation of the power system and is not limited here.

[0036] The balancing demand information in the above steps is the data and parameters used to describe the load balancing demand of the power system within a specific time. The balancing demand information can be used to guide load balancing operations and help system managers understand the current load status and future demand trends, so as to make corresponding adjustments.

[0037] The balancing subject information in the above steps is used to describe the information of the power equipment with load balancing capability in the power system, which can respond to load balancing requests and make corresponding adjustments. The types of balancing subject information may include but are not limited to equipment information such as motor groups and transformers, and the role of balancing subject information may include but is not limited to identifying and regulating equipment that can participate in load balancing, ensuring that the equipment will adjust the power output according to demand to meet the needs of load balancing.

[0038] In an optional embodiment, when a request for load balancing operation is received, it is first necessary to determine the balancing demand information and balancing subject information corresponding to the balancing request. The balancing demand information refers to the specific situation of the current load distribution of the power system, including which areas or time periods have power demand exceeding the supply capacity, or which areas have excess power supply. The balancing demand information helps the system determine the specific degree and location of the load balancing operation. The balancing subject information involves those power equipment that can participate in load balancing, such as generator sets, energy storage equipment, demand response systems, etc. These equipment have the ability to adjust power absorption and can help the system to achieve load redistribution. Determining the balancing demand information and balancing subject information based on the balancing request is the basis for performing load balancing operations. Based on the balancing demand information and balancing subject information, the power system can formulate a set of load balancing plans, and then adjust the working status of the power equipment according to the load balancing plan, such as increasing or decreasing the power generation, or starting the demand response program, to achieve the purpose of load balancing of the power system.

[0039] Step S104, solving the load balancing model corresponding to the power system based on the balancing demand information and the balancing subject information to obtain the load balancing strategy of the power system, wherein the load balancing strategy includes the switching state and the required balancing power of the power equipment with load balancing capability at any time.

[0040] The load balancing model in the above steps is used to describe a mathematical model for solving the load balancing problem in the power system. The load balancing model can adjust the internal parameters of the model based on different constraints and different balancing objectives. The load balancing model can predict and optimize the operation of the power system to ensure that the power system can meet user needs at any time.

[0041] The load balancing strategy in the above steps is used to describe a series of measures and decisions taken to achieve load balancing in the power system. The load balancing strategy may include but is not limited to the switching state of the power equipment and the power that needs to be balanced. The role of the load balancing strategy includes but is not limited to improving the stability and reliability of the power system, reducing voltage fluctuations and equipment losses caused by uneven load, and improving energy utilization efficiency.

[0042] In an optional embodiment, to achieve load balancing of the power system, it is first necessary to obtain balancing demand information and balancing subject information, and then establish a load balancing model for solving the switch state, switch time and power required to be provided by the power equipment, and then solve the load balancing model based on the balancing demand information and balancing subject information to obtain the actual load balancing strategy of the power system. The above process involves real-time monitoring and dynamic adjustment of the power system, and optimizes the allocation of power resources through the load balancing model, which reduces energy waste and improves the reliability of the power system while ensuring that user needs are met.

[0043] Step S106, performing load balancing operation on the power system according to the load balancing strategy to obtain a load balancing result, wherein the load balancing result is used to indicate whether the power system meets the load balancing requirement.

[0044] The load balancing results in the above steps are used to describe the power supply and demand status of the power system after the load balancing operation, that is, to characterize whether the power system meets the load balancing requirements. The load balancing results may include but are not limited to the power system meeting the load balancing requirements and the power system not meeting the load balancing requirements. The specific load balancing results need to be determined based on the actual situation of the power system and are not limited here.

[0045] In an optional embodiment, a load balancing operation is performed on the power system based on a load balancing strategy to obtain a load balancing result. When the obtained load balancing result is that the power system meets the load balancing demand, it indicates that the power system has reached a load balancing state after the load balancing operation; when the obtained load balancing result is that the power system does not meet the load balancing demand, it indicates that the power system has not reached a load balancing state after the load balancing operation. At this time, the power system can be further subjected to load balancing operations according to the load balancing method proposed in the present application until the power system reaches a load balancing state. The above process reflects whether the power system has successfully achieved the goal of load balancing through the load balancing result, which can enable users to more intuitively know the status of the power system, help improve the operating efficiency of the power system, reduce energy waste, reduce operating costs, and improve the user's power usage experience.

[0046] In an embodiment of the present invention, first, in response to receiving a balancing request for performing load balancing operation on the power system, the balancing demand information and balancing subject information corresponding to the balancing request are determined; then, based on the balancing demand information and balancing subject information, the load balancing model corresponding to the power system is solved to obtain the load balancing strategy of the power system; finally, the power system is load balancing according to the load balancing strategy to obtain the load balancing result. It is easy to notice that the present application obtains the load balancing strategy corresponding to the balancing demand information and balancing subject information of the power system by solving the load balancing model, and then performs balancing operation on the power system according to the load balancing strategy to obtain the load balancing result of the power system, thereby realizing the judgment of the load balancing demand capacity of the power system, and at the same time realizing the precise control of the load balancing operation of the power system, thereby solving the technical problem of poor load balancing effect of the power system in the related technology.

[0047] Optionally, the method also includes: determining multiple load balancing targets, wherein the multiple load balancing targets include at least two of the following: minimizing the volatility of load balancing operations on the grid side of the power system, minimizing the cost of load balancing on the grid side, and minimizing the cost of user-side participation in load balancing response of the power system; and constructing a load balancing model based on the multiple load balancing targets.

[0048] The above-mentioned multiple load balancing goals are used to describe the specific goals pursued when achieving load balancing in the power system. The multiple load balancing goals may include but are not limited to at least two of the following load balancing goals: minimizing the volatility of load balancing operations on the power grid side of the power system, minimizing the cost of load balancing on the power grid side, and minimizing the cost of the user side of the power system participating in the load balancing response. The above-mentioned load balancing goals are only examples. The specific load balancing goals can be determined according to the actual needs of the power system and are not limited here. The role of multiple load balancing goals may include but is not limited to guiding the power system to formulate specific strategies to achieve efficient, economical and stable power supply.

[0049] In an optional embodiment, before performing load balancing operations on the power system, it is first necessary to clarify the load balancing target, that is, the specific target pursued when achieving load balancing. The multiple load balancing targets may include but are not limited to at least two of the following load balancing targets: the minimum volatility of the load balancing operation on the power grid side of the power system, the minimum cost of load balancing on the power grid side, and the minimum cost of the user side of the power system participating in the load balancing response. Then, a load balancing model is constructed according to the determined load balancing targets. The above process, by comprehensively considering the stability and economy of the power grid side and the cost-effectiveness of the user side, can reduce the fluctuation of the power grid, improve the reliability of power supply, and reduce the economic burden of the power grid and users while achieving efficient and economical operation of the power system. It can also achieve the reasonable allocation and utilization of power resources.

[0050] Optionally, constructing a load balancing model based on the load balancing target includes: determining the weight of each load balancing target using a scaling construction method; determining target constraints corresponding to the load balancing model, wherein the target constraints are used to limit the solution space of the load balancing model; and constructing a load balancing model based on multiple load balancing targets, the weight of each load balancing target, and the target constraints.

[0051] The scale construction method in the above steps is used to describe a method for determining the weights of load balancing objectives by assigning a numerical weight to different objectives to indicate their relative importance in the overall objective.

[0052] The weights in the above steps are used to describe the weights assigned to multiple load balancing targets, and are used to indicate the importance of the load balancing target in the overall load balancing process. The types of weights may include, but are not limited to, the weight of the load balancing target with the least volatility in load balancing operations on the grid side of the power system, the weight of the load balancing target with the least cost for load balancing on the grid side, and the weight of the load balancing target with the least cost for participating in the load balancing response on the user side of the power system. The above weight types are only examples, and the specific weight type depends on the type of load balancing target, which is not limited here.

[0053] The above-mentioned target constraints are used to describe the rules used to limit the solution space in the load balancing model. The target constraints may include but are not limited to operating load constraints, node voltage constraints, node current constraints, constraints on the grid side not seeing new peaks or valleys, constraints on the potential for regulating resources, and constraints on the source-load side not responding. The specific target constraints need to be determined based on actual conditions and are not limited here.

[0054] In an optional embodiment, a load balancing model is constructed based on a load balancing target. First, a scaling construction method is used to assign weights to multiple load balancing targets, that is, the relative importance of multiple load balancing targets is quantified according to the importance of the load balancing target and the impact on the overall system performance; then, the target constraint conditions of the load balancing model need to be determined. The target constraint conditions limit the solution space of the model to ensure that the solution not only meets the target but also meets the actual operation limitations of the system; finally, a load balancing model is constructed based on multiple load balancing targets, the weight of each load balancing target, and the target constraint conditions. The above process involves determining the load balancing target, assigning weights to multiple load balancing targets, setting constraints, and finally forming a mathematical model that can guide actual operations. The purpose is to ensure that the system can maintain high efficiency and stability in actual operations while meeting various performance indicators.

[0055] Optionally, the weight of each load balancing target is determined using a scaling construction method, including: quantifying the importance of multiple load balancing targets to obtain quantified results of multiple load balancing targets; sorting the multiple load balancing targets based on the quantified results of the multiple load balancing targets to obtain multiple sorted load balancing targets; determining the scaling value of any two adjacent load balancing targets based on the quantified results of any two adjacent load balancing targets among the sorted multiple load balancing targets, wherein the scaling value is used to quantify the relative importance between two load balancing targets corresponding to any two adjacent objective functions, and the objective function is used to describe a mathematical expression for measuring the load balancing target; constructing a judgment matrix based on the scale values ​​of any two adjacent load balancing targets; and determining the weight of each objective function based on the judgment matrix.

[0056] The above-mentioned quantitative results are used to describe the importance of multiple load balancing targets converted into numerical form as quantitative results. The quantitative results may include but are not limited to other numerical forms such as fractions and percentages. The quantitative results may be used to provide a basis for subsequent weight allocation and decision-making.

[0057] The above scale value is used to describe the relative importance between any two adjacent load balancing targets.

[0058] The above judgment matrix is ​​used to describe the relative importance relationship between any two adjacent load balancing objectives, and can be directly used to determine the weights of multiple load balancing objectives.

[0059] In an optional embodiment, when determining the weight of the load balancing target, the scale construction method can be used to evaluate and quantify the importance of each target. First, it is necessary to quantify the importance of multiple load balancing targets and obtain the quantitative results of multiple load balancing targets; secondly, based on the quantification results, the multiple load balancing targets are sorted according to their importance so as to more clearly identify which targets are more critical; then, in order to further refine the relative importance between multiple load balancing targets, based on the quantification results of any two adjacent load balancing targets in the sorted multiple load balancing targets, the scale value between any two adjacent load balancing targets is determined, and the scale value reflects the degree of difference in importance between the two adjacent targets; then, a judgment matrix is ​​constructed based on the scale values ​​of any two adjacent load balancing targets; finally, the weight of each objective function is calculated using the judgment matrix. The determination of the weight is based on the quantitative evaluation of the relative importance between the targets, which can help decision makers to allocate resources and concerns more scientifically and reasonably when performing load balancing to achieve the optimal balancing effect. This method not only improves the transparency of decision-making, but also enhances the rationality and effectiveness of decision-making.

[0060] In an optional embodiment, the weight of each load balancing target is determined by using a scale construction method. First, the importance of multiple load balancing targets is quantified to obtain quantified results of multiple load balancing targets, and based on the quantified results of the multiple load balancing targets, the multiple load balancing targets are sorted to obtain multiple sorted load balancing targets; then, based on the quantified results of any two adjacent load balancing targets in the sorted multiple load balancing targets, the scale values ​​of any two adjacent load balancing targets are determined, wherein the scale value determination method is as follows:

[0061] Compared with two load balancing objectives, they have the same importance, so the scale value is 1.0; compared with the two load balancing objectives, the former is slightly more important than the latter, so the scale value is 1.2; compared with the two load balancing objectives, the former is obviously more important than the latter, so the scale value is 1.4; compared with the two load balancing objectives, the former is more important than the latter, so the scale value is 1.6; compared with the two load balancing objectives, the former is more important than the latter, so the scale value The above load balancing target judgment standard and scale value are only examples. The specific scale value needs to be determined according to actual needs and is not limited here.

[0062] Suppose there are n load balancing targets , the indicators are subjectively sorted according to the principle of non-decreasing importance, and the sorting results are , determine the scale value based on the above scale judgment method, and record the corresponding scale as , and finally get the scale value between all adjacent indicators , according to the transitivity of importance, we can get other elements in the judgment matrix, then the final judgment matrix , judgment matrix The expression is as follows:

[0063] ;

[0064] Where n is the number of load balancing targets, is the scale value corresponding to the load balancing target, and ∏ is the product operation.

[0065] The above judgment matrix satisfies consistency and can be directly used for weight calculation without verification. The weight calculation formula of the objective function is as follows:

[0066] ;

[0067] Where n is the number of load balancing targets, is the judgment matrix The element in row i and column j in It represents the weight corresponding to the i-th objective function, ∏ is the product operation, and ∑ is the summation operation.

[0068] Optionally, determining the target constraint conditions corresponding to the load balancing model includes: determining the safe load rate interval, voltage amplitude interval and current amplitude interval corresponding to the load balancing model; determining the operating load constraint conditions based on the safe load rate interval; determining the node voltage constraint conditions based on the voltage amplitude interval; determining the node current constraint conditions based on the current amplitude interval; determining the target constraint conditions based on the operating load constraint conditions, the node voltage constraint conditions and the node current constraint conditions.

[0069] The above-mentioned safe load rate interval is used to describe the load range in which the system or equipment can operate safely, usually expressed as a percentage, and can be used to ensure that the system will not be damaged or fail due to overload. The types of safe load rate intervals may include but are not limited to static safe load rate intervals and dynamic safe load rate intervals. The specific safe load rate interval type can be determined based on the power system design and operating conditions, and is not limited here.

[0070] The above voltage amplitude range is used to describe the voltage range in which the system or device can operate safely, and can be used to ensure that the device will not be damaged due to excessively high or low voltage. The voltage amplitude range is usually determined according to the type of device and is not limited here.

[0071] The above current amplitude range is used to describe the current range in which the system or device can operate safely, and can be used to prevent overheating or damage to the device due to excessive current. The current amplitude range is usually determined based on the electrical characteristics of the device and is not limited here.

[0072] The above-mentioned operating load constraints are used to describe the maximum and minimum load limits during system operation determined based on the safe load rate range. The types of operating load constraints may include but are not limited to hard constraints, flexible constraints, and both hard constraints and flexible constraints. The specific constraint type can be determined based on the system design and control strategy, and is not limited here.

[0073] The above node voltage constraint condition is used to describe the voltage limit of each node in the system determined based on the voltage amplitude range, which can be used to ensure that the node voltage is within a safe range and avoid equipment damage caused by excessively high or low voltage.

[0074] The node current constraint condition mentioned above is used to describe the current limit of each node in the system determined based on the current amplitude range, which can be used to prevent the device from overheating or being damaged due to excessive current.

[0075] In an optional embodiment, in order to ensure the stability and reliability of the system, it is necessary to determine the target constraints corresponding to the load balancing model. First, it is necessary to determine the safe load rate interval, voltage amplitude interval and current amplitude interval corresponding to the load balancing model; then, based on the safe load rate interval, the operating load constraint is determined to ensure that the actual load does not exceed the safe range; secondly, the node voltage constraint is determined based on the voltage amplitude interval to ensure that the node voltage is within the safe range; finally, the node current constraint is determined based on the current amplitude interval to ensure that the current is within the safe range. Combining the above constraints, a complete load balancing model is constructed to ensure the stable operation of the power system. The above process not only considers the safe range of load, voltage and current, but also considers the mutual influence between them, thereby achieving the optimal operation of the system. In this way, the efficiency and reliability of the power system can be improved, while reducing the risk of failures and accidents.

[0076] In an optional embodiment, the constraints corresponding to the load balancing model are determined, including determining the operating load constraints, node voltage constraints, node current constraints, grid-side power flow balance constraints, grid-side no new peaks and valleys constraints, resource regulation potential constraints, and source-load side no-response constraints. The specific determination method of the above constraints is as follows:

[0077] 1. Operation load constraint conditions. The constraint condition formula is as follows:

[0078] ;

[0079] ;

[0080] In the formula, is the safe load rate range, is the maximum operating capacity of the regional distribution network lines, is the rated voltage at the head end of the distribution network line, is the current carrying capacity of the distribution network line, is the load that needs to be regulated at time t, To regulate the front load for the power grid, The power factor is usually taken as 100% of the overload boundary, and 80% of the heavy load boundary can be taken in some important load power consumption areas.

[0081] 2. Node voltage constraints. The constraint formula is as follows:

[0082] ;

[0083] In the formula, and are the lower and upper bounds of the voltage amplitude at node i, respectively. is the voltage of node i at time t, and N is the node set.

[0084] 3. Node current constraint condition. The constraint condition formula is as follows:

[0085] ;

[0086] In the formula, To pass the line The upper bound of the current amplitude is For Line The current at time t is It is the collection of all lines on the grid.

[0087] 4. No new peak or valley constraint condition appears on the power grid side. The constraint condition formula is as follows:

[0088] ;

[0089] ;

[0090] In the formula, and are the peak and valley values ​​of regional load before regulation, and They are the peak and valley values ​​of the region after regulation, respectively.

[0091] 5. Constraints of the potential for regulation of resources. The constraint formula is as follows:

[0092] ;

[0093] In the formula, and are the load increase boundary and load decrease boundary of equipment m at time t, is the power that needs to be regulated by device m at time t. This constraint is mainly for flexible resource devices.

[0094] 6. The source-load side does not exceed the response constraint condition. The constraint condition formula is as follows:

[0095] ;

[0096] In the formula, represents the sum of all equipment control loads at time t, is the load that needs to be regulated at time t, is the over-response weighting coefficient, which is taken as 1.05 for safety considerations. The over-response weighting coefficient here is only an example, and its specific size should be determined based on the actual situation of the power system.

[0097] Optionally, a load balancing model is constructed based on multiple load balancing targets, the weight of each load balancing target and target constraints, including: weighting multiple load balancing targets based on the weight of each load balancing target to obtain a total balancing target; and constructing a load balancing model based on the total balancing target and target constraints.

[0098] The total balance target in the above steps is used to describe a comprehensive balance target obtained by weighting and summarizing the weights corresponding to multiple load balancing targets. The total balance target reflects the overall goal that the system needs to achieve under the premise of considering the importance of multiple load balancing targets.

[0099] In an optional embodiment, when constructing a load balancing model, it is first necessary to determine the weight of each load balancing target in the load balancing task. The determined weight reflects the importance of the load balancing target in the overall optimization process. Then, the load balancing targets are weighted and merged into a total balancing target. The total balancing target integrates the priority and influence of all load balancing targets. Then, a load balancing model is constructed based on the total balancing target and target constraints to guide the system to distribute loads to achieve the optimal balance state. The above method can ensure the overall performance and stability of the system while meeting all load balancing targets.

[0100] Optionally, based on the weight of each load balancing target, multiple load balancing targets are weighted to obtain an overall balancing target, including: based on the multiple load balancing targets, determining multiple objective functions corresponding to the multiple load balancing targets; based on the weight of each load balancing target, weighting the multiple objective functions to obtain an overall balancing target.

[0101] The objective function in the above steps is a mathematical expression used to describe and measure multiple load balancing objectives in the system. The types of objective functions include but are not limited to the objective function corresponding to the load balancing objective of minimizing the volatility of load balancing operations on the grid side of the power system, the objective function corresponding to the load balancing objective of minimizing the cost of load balancing on the grid side, and the objective function corresponding to the load balancing objective of minimizing the cost of participating in load balancing response on the user side of the power system. The type of objective function depends on the load balancing objective requirements and is not limited here. The role of the objective function may include but is not limited to providing a clear optimization direction for the load balancing model, weighing different load balancing objectives and performance evaluation, etc.

[0102] In an optional embodiment, first define an objective function for each load balancing target, which can quantify the degree of achievement of each target; then, assign weights to each load balancing target according to its importance, and these weights reflect the priority of each load balancing target in the overall load balancing strategy; then, weight the objective function corresponding to each load balancing target according to its corresponding weight to obtain the overall balancing target, which can balance the relationship between multiple load balancing targets and ensure that while satisfying one load balancing target, other load balancing targets will not be excessively sacrificed. Through the above process, a more flexible and effective load balancing strategy can be constructed to adapt to different business needs and network conditions.

[0103] Optionally, based on the weight of each load balancing target, multiple objective functions are weighted to obtain an overall balancing target, including: dimensionlessly processing multiple objective functions to obtain multiple dimensionless results; based on the weight of each load balancing target, weighting multiple dimensionless results to obtain an overall balancing target.

[0104] The dimensionless processing in the above steps is used to describe the process of converting the objective functions of multiple load balancing objectives into a unitless form. The dimensionless processing enables data of different dimensions to be compared on the same scale. The types of dimensionless processing may include but are not limited to standardization, normalization, and logarithmic transformation. The specific dimensionless processing method needs to be determined according to actual needs and is not limited here.

[0105] The dimensionless results in the above steps are used to describe the results obtained by dimensionless processing of the objective functions of multiple load balancing objectives. The dimensionless results remove the influence of the dimensions of the objective functions of multiple load balancing objectives, making the subsequent weighting of the dimensionless results more reasonable.

[0106] In an optional embodiment, multiple objective functions are first dimensionally processed, and the data is converted into a unitless form to eliminate the influence of different dimensions, so that the dimensionless results can be compared under the same standard; then, according to the weights of multiple load balancing objectives, the dimensionless results are weighted and summed to obtain a comprehensive balancing objective. The above method can ensure that when performing load distribution, not only a single load balancing objective is considered, but also the balance of multiple load balancing objectives is comprehensively considered, so that the final load distribution is more reasonable and effective. In this way, not only the influence of different dimensions can be eliminated, and the comparison and judgment of the results can be facilitated, but also the efficiency and performance of the system can be improved to meet multiple different optimization objectives.

[0107] In an optional embodiment, firstly, a plurality of load balancing objectives are determined, wherein the plurality of load balancing objectives include at least two of the following: minimizing the volatility of load balancing operation on the grid side of the power system, minimizing the cost of load balancing on the grid side, and minimizing the cost of user side of the power system participating in load balancing response; secondly, a load balancing model is constructed based on the plurality of load balancing objectives, and the expression of the load balancing model is as follows:

[0108] ;

[0109] ;

[0110] ;

[0111] ;

[0112] In the formula, They are the objective functions corresponding to the three load balancing objectives, namely, the objective function corresponding to the minimum volatility objective of the load balancing operation on the grid side of the power system, the objective function corresponding to the minimum cost objective of the load balancing operation on the grid side, and the objective function corresponding to the minimum cost objective of the user side of the power system participating in the load balancing response; The load of the front area is regulated at time t; The load that needs to be regulated at time t; is the switching state of device m at time t; is the power required to be regulated by device m at time t; for the above formula, if device m is a rigid control device, the decision variable of device m is the switch switching state at time t ; If device m is a flexible control device, the decision variable of device m is the switch switching state at time t And the power to be regulated ; The number of devices that can participate in regulation in a region; The subsidy standard; is the subsidy coefficient; Provide users with time-of-use electricity prices.

[0113] Since different load balancing objectives have inconsistent dimensions, the objective functions corresponding to multiple load balancing objectives need to be dimensionless before they are combined. The dimensionless formula is as follows:

[0114] ;

[0115] In the formula, is the dimensionless result of the i-th objective function value, is the i-th objective function, The minimum objective function value when the i-th objective function is optimized separately.

[0116] The final load balancing model is as follows:

[0117] ;

[0118] In the formula, is the load multi-objective function, They are the dimensionless results of the three objective function values, are the weights corresponding to the three objective functions respectively.

[0119] Optionally, solving the load balancing model based on the balancing demand information and the balancing subject information to obtain the load balancing strategy includes: using a particle swarm algorithm to solve the load balancing model based on the balancing demand information and the balancing subject information to obtain the load balancing strategy.

[0120] The particle swarm algorithm in the above steps is an optimization algorithm based on swarm intelligence. In the load balancing model, the particle swarm algorithm can be used to optimize resource allocation to achieve system load balancing. The types of particle swarm algorithms may include but are not limited to standard particle swarm algorithm, particle swarm algorithm with inertia weight, discrete particle swarm algorithm and adaptive particle swarm algorithm. The specific particle swarm algorithm can be determined according to actual needs and is not limited here.

[0121] In an optional embodiment, after receiving a balancing request for load balancing operation on the power system, the balancing demand information and balancing subject information of the power system are determined, and then in the load balancing model, the particle swarm algorithm is used to combine the balancing demand information and the balancing subject information to find the best resource allocation strategy. In this way, the model can dynamically adjust resource allocation to adapt to changing needs and conditions. For example, in the power system, when the demand in a certain area suddenly increases, the model can quickly adjust the output of the power plant to ensure the balance between supply and demand. Solving the load balancing model using the particle swarm algorithm can not only improve the utilization efficiency of resources, but also reduce the overall energy consumption of the system and improve the response speed and reliability of the system.

[0122] In an optional embodiment, a particle swarm algorithm is used to solve the load balancing model. The particle swarm algorithm solving process is as follows:

[0123] First, determine the position vector of particle i in D-dimensional space as , the velocity vector is , then the iterative formula for particle velocity and position is:

[0124] ;

[0125] ;

[0126] In the formula, k is the number of particle iterations; is the velocity of particle i in the jth dimension in the kth iteration; ω is the inertia weight coefficient, which is a kind of preservation of the original motion state of the particle; is the local optimal solution found by particle i in the kth iteration; is the global optimal solution found by particle i in the kth iteration, is the j-dimensional position of particle i in the k-th iteration; c1 and c2 are learning factors; rand1 and rand2 are random numbers between [0,1].

[0127] In the particle swarm algorithm, the decision variable of the load balancing model is each particle. The particle swarm algorithm is used to solve the control schemes of different types of equipment in the regional equipment cluster at different times, including the switch state of the rigid control equipment in the power equipment at any time t. , and the switch state of the flexible control device in the power equipment at any time t And the power to be regulated For rigid control devices, if the switch state of the control decision variable and the initial switch state of the device If the switch is consistent, the device m does not need to perform switch state switching control at time t. If the switch is inconsistent, the device m needs to perform switch state switching control at time t. For flexible control devices, if If it is a positive value, it means that the device m needs to reduce the power at time t. ,like If it is a negative value, the device m needs to increase the power at time t. .

[0128] Optionally, the load balancing information includes at least one of the following: the load amount to be balanced of the power system, the duration of balancing required for the power system, the front load of the power system, the balancing response subsidy electricity price, the subsidy coefficient, the time-of-use electricity price for users, and the power equipment in the power system that can respond to load balancing. The balancing subject information includes at least one of the following: the type of power equipment, the initial switching state of the power equipment, the starting power of the power equipment, the upward load boundary of the power equipment, and the downward load boundary of the power equipment.

[0129] The load that needs to be balanced of the power system in the above steps is used to describe the total load that the power system needs to adjust within a specific time to achieve load balancing. The types of loads that need to be balanced of the power system may include but are not limited to total load, peak load, valley load, etc. The specific types of loads that need to be balanced of the power system need to be determined according to actual conditions and are not limited here. The role of the load that needs to be balanced of the power system may include but is not limited to ensuring that the load distribution of the power system is reasonable in different time periods to avoid excessive or light load on the system.

[0130] The required balancing time of the power system in the above steps is used to describe the control time of the power system for load balancing control. The required balancing time of the power system can be a few hours, a few days or a few weeks. The required balancing time of the power system needs to be determined according to the actual situation and is not limited here.

[0131] The pre-balancing load of the power system in the above steps is used to describe the current load state of the power system before the load balancing operation is performed. The pre-balancing load of the power system can be used as a benchmark for the load balancing operation to calculate the load amount that needs to be adjusted.

[0132] The equilibrium response subsidy electricity price in the above steps is used to describe the subsidized electricity price provided by the power system to encourage users or power equipment to participate in load balancing. The equilibrium response subsidy electricity price can be used to encourage users or power equipment to reduce or increase electricity consumption when the power system needs it to achieve load balancing.

[0133] The subsidy coefficient in the above steps is used to describe the proportional coefficient between the subsidized electricity price and the normal electricity price. The subsidy coefficient can be used to calculate the actual subsidy amount, thereby affecting the willingness of users or power equipment to participate.

[0134] The user's time-of-use electricity price in the above steps is used to describe the different electricity prices charged by the power company to users according to different electricity consumption times. The types of user's time-of-use electricity prices may include but are not limited to peak electricity prices, normal electricity prices, valley electricity prices, etc. The user's time-of-use electricity price can be used to guide users to use electricity during periods of low electricity demand through a price mechanism, thereby achieving load balancing.

[0135] The power equipment capable of responding to load balancing in the power system in the above steps is used to describe the power equipment that can adjust its own load according to the needs of the power system. The types of power equipment that can respond to load balancing may include but are not limited to industrial equipment, household appliances, etc. The specific power equipment that can respond to load balancing should be determined according to actual conditions and is not limited here. The above-mentioned power equipment can be used to help the power system achieve load balancing by adjusting its own power load.

[0136] The type of power equipment in the above steps is used to describe the classification of power equipment that can participate in load balancing. The type of power equipment may include but is not limited to rigid control equipment or flexible control equipment, etc., wherein a rigid control device refers to a device that plays a fixed, non-adjustable role in the power system. The state of the rigid control device can be directly controlled by a switch, and is usually used to ensure the stability and safety of the power system. The rigid control device may specifically include but is not limited to circuit breakers, grounding devices, disconnect switches, etc.; a flexible control device refers to a device that plays an adjustable and adaptable role in the power system. The state of the flexible control device can be continuously controlled by power, and can be used to improve the flexibility and adaptability of the power system. The flexible control device may specifically include but is not limited to a voltage regulator, an active power controller, a reactive power controller, etc. The specific type of power equipment can be determined based on actual conditions and is not limited here. The role of determining the type of power equipment may include but is not limited to determining which devices can participate in load balancing and determining their role in load balancing.

[0137] The initial switch state of the power equipment in the above steps is used to describe the switch state of the power equipment when the load balancing operation starts. The initial switch state may include but is not limited to the on state or the off state, etc. The specific initial switch state should be determined according to the actual state of the power equipment. No limitation is made here. The initial switch state of the power equipment can be used to determine the starting point of the load balancing operation.

[0138] The starting power of the power equipment in the above steps is used to describe the power of the power equipment at the beginning of the load balancing operation. The starting power of the power equipment may include but is not limited to the rated power, actual power, etc. The specific starting power should be determined according to the actual situation of the power equipment. No limitation is made here. The starting power of the power equipment can be used to calculate the power range that needs to be adjusted in the load balancing operation.

[0139] The load increase boundary of the power equipment in the above steps is used to describe the maximum value of the load that the power equipment can increase during the load balancing operation. The load increase boundary of the power equipment may include but is not limited to power boundaries, time boundaries, etc. The specific load increase boundary of the power equipment should be determined based on the actual situation of the power equipment and is not limited here. The load increase boundary of the power equipment can be used to limit the range of load increase of the power equipment during the load balancing operation.

[0140] The load reduction boundary of the power equipment in the above steps is used to describe the maximum value of the load that the power equipment can reduce during load balancing operation. The load reduction boundary of the power equipment may include but is not limited to power boundaries, time boundaries, etc. The specific load reduction boundary of the power equipment should be determined based on the actual situation of the power equipment and is not limited here. The load reduction boundary of the power equipment can be used to limit the range of load reduction of the power equipment during load balancing operation.

[0141] In an optional embodiment, the load balancing information includes multiple key parameters, such as the amount of load that the power system needs to balance, the length of time required for balancing, the load state before balancing, the subsidized electricity price in response to load balancing, the subsidy coefficient, and the time-of-use electricity price of the user's electricity consumption. Determining the load balancing information helps the grid operator understand the current power demand and cost, so as to make more effective scheduling decisions. The balancing subject information involves the power equipment that can respond to load balancing, including the type of equipment, the initial switching state, the starting power, and the upward and downward load boundaries of the equipment. The balancing subject information determines which equipment can participate in load balancing and the adjustment capabilities of these equipment when the load changes. The integration of load balancing information and balancing subject information can more accurately predict and control power demand, optimize the allocation of power resources, reduce energy waste, and improve the reliability and efficiency of the power grid.

[0142] According to another aspect of an embodiment of the present invention, a load balancing device for an electric power system is also provided. The device can execute the load balancing method for the electric power system provided in the above embodiment. The specific implementation method and preferred application scenario are the same as the above embodiment and will not be repeated here.

[0143] Figure 2 is a schematic diagram of an optional load balancing device for a power system according to an embodiment of the present invention, such as Figure 2As shown, the device includes: an acquisition module 202, which is used to determine the balancing demand information and balancing subject information corresponding to the balancing request in response to receiving a balancing request for performing load balancing operation on the power system, wherein the balancing demand information is used to characterize the load balancing demand of the power system, and the balancing subject information is the information of the power equipment with load balancing capability in the power system; a solution module 204, which is used to solve the load balancing model corresponding to the power system based on the balancing demand information and the balancing subject information, and obtain the load balancing strategy of the power system, wherein the load balancing strategy includes the switching state and the required balancing power of the power equipment with load balancing capability at any time; a balancing module 206, which is used to perform load balancing operation on the power system according to the load balancing strategy, and obtain a load balancing result, wherein the load balancing result is used to characterize whether the power system meets the load balancing demand.

[0144] Optionally, the device also includes: a determination module, which determines multiple load balancing targets, wherein the multiple load balancing targets include at least two of the following: minimizing the volatility of load balancing operations on the grid side of the power system, minimizing the cost of load balancing on the grid side, and minimizing the cost of user side of the power system participating in the load balancing response; and a construction module, which constructs a load balancing model based on multiple load balancing targets.

[0145] Optionally, the construction module includes: a first determination unit, which uses a scaling construction method to determine the weight of each load balancing target; a second determination unit, which determines the constraints corresponding to the load balancing model, wherein the constraints are used to limit the solution space of the load balancing model; and a construction unit, which constructs the load balancing model based on multiple load balancing targets, the weight of each load balancing target and the constraints.

[0146] Optionally, the first determination unit includes: a quantification subunit, which quantifies the importance of multiple load balancing targets to obtain quantification results of the multiple load balancing targets; a sorting subunit, which sorts the multiple load balancing targets based on the quantification results of the multiple load balancing targets to obtain multiple sorted load balancing targets; a first determination subunit, which determines the scale value of any two adjacent load balancing targets based on the quantification results of any two adjacent load balancing targets among the sorted multiple load balancing targets, wherein the scale value is used to quantify the relative importance between two load balancing targets corresponding to any two adjacent objective functions, and the objective function is used to describe the mathematical expression for measuring the load balancing target; a first construction subunit, which constructs a judgment matrix based on the scale values ​​of any two adjacent load balancing targets; and a second determination subunit, which determines the weight of each objective function based on the judgment matrix.

[0147] Optionally, the second determination unit includes: a third determination subunit, which determines the safe load rate interval, voltage amplitude interval and current amplitude interval corresponding to the load balancing model; a fourth determination subunit, which determines the operating load constraint condition based on the safe load rate interval; a fifth determination subunit, which determines the node voltage constraint condition based on the voltage amplitude interval; a sixth determination subunit, which determines the node current constraint condition based on the current amplitude interval; and a seventh determination subunit, which determines the target constraint condition based on the operating load constraint condition, the node voltage constraint condition and the node current constraint condition.

[0148] Optionally, the construction unit includes: a weighting subunit, which weights multiple load balancing targets based on the weight of each load balancing target to obtain a total balancing target; and a second construction subunit, which constructs a load balancing model according to the total balancing target and target constraints.

[0149] Optionally, the weighting subunit includes: determining multiple objective functions corresponding to the multiple load balancing targets based on the multiple load balancing targets; and weighting the multiple objective functions based on the weight of each load balancing target to obtain a total balancing target.

[0150] Optionally, based on the weight of each load balancing target, multiple objective functions are weighted to obtain an overall balancing target, including: dimensionlessly processing multiple objective functions to obtain multiple dimensionless results; based on the weight of each load balancing target, weighting multiple dimensionless results to obtain an overall balancing target.

[0151] Optionally, the solution module includes: using a particle swarm algorithm to solve a load balancing model based on balancing demand information and balancing subject information to obtain a load balancing strategy.

[0152] Optionally, the load balancing information includes at least one of the following: the load amount to be balanced of the power system, the duration of balancing required for the power system, the front load of the power system, the balancing response subsidy electricity price, the subsidy coefficient, the time-of-use electricity price for users, and the power equipment in the power system that can respond to load balancing. The balancing subject information includes at least one of the following: the type of power equipment, the initial switching state of the power equipment, the starting power of the power equipment, the upward load boundary of the power equipment, and the downward load boundary of the power equipment.

[0153] According to another aspect of an embodiment of the present invention, there is further provided an electronic device, comprising: a memory storing an executable program; and a processor for running the program, wherein the method in each embodiment of the present invention is executed when the program is running.

[0154] According to another aspect of an embodiment of the present invention, a computer-readable storage medium is provided. The computer-readable storage medium includes a stored program. When the program is executed, a processor of a device is controlled to execute the methods of various embodiments of the present invention.

[0155] The computer storage medium in the above steps can be a medium used to store certain discontinuous physical quantities in a computer memory, and the computer storage medium mainly includes semiconductors, magnetic cores, magnetic drums, magnetic tapes, laser disks, etc. The stored program included in the computer-readable storage medium can be a set of instructions that can be recognized and executed by a computer, running on an electronic computer, and is an information tool that meets certain needs of people.

[0156] According to another aspect of an embodiment of the present invention, a computer program product is provided, including a computer program. When the computer program is executed by a processor, the method in each embodiment of the present invention is implemented.

[0157] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0158] In the above embodiments of the present invention, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0159] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of units can be a logical function division. There may be other division methods in actual implementation. 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 mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0160] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed over multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0161] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0162] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, 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. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or optical disk, etc. Various media that can store program codes.

[0163] The above are only preferred embodiments of the present invention. It should be pointed out that, for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A load balancing method for a power system, characterized in that: include: In response to receiving a balancing request for performing a load balancing operation on an electric power system, determining balancing demand information and balancing subject information corresponding to the balancing request, wherein the balancing demand information is used to characterize the load balancing demand of the electric power system, and the balancing subject information is information of electric power equipment with load balancing capability in the electric power system, and the balancing demand information includes at least one of the following: the load amount to be balanced of the electric power system, the duration of balancing required by the electric power system, the front load of the electric power system, the subsidized electricity price for balanced response, the subsidy coefficient, the time-of-use electricity price for user electricity, and the electric power equipment in the electric power system that can respond to load balancing, and the balancing subject information includes at least one of the following: the type of electric power equipment, the initial switching state of the electric power equipment, the starting power of the electric power equipment, the load increase boundary of the electric power equipment, and the load decrease boundary of the electric power equipment; The load balancing model corresponding to the power system is solved based on the balancing demand information and the balancing subject information to obtain the load balancing strategy of the power system, wherein the load balancing strategy includes the switch state and the required balancing power of the power equipment with load balancing capability at any time, and the load balancing model is constructed based on multiple constraints and multiple load balancing targets, and the multiple constraints are determined based on multiple constraint intervals. The multiple constraints are used to represent the rules used to limit the solution space in the load balancing model, and the multiple load balancing targets include the following three: minimizing the volatility of load balancing operations on the power grid side of the power system, minimizing the cost of load balancing on the power grid side, and minimizing the cost of the user side of the power system participating in the load balancing response. The multiple constraints include at least one of the following: operating load constraints, node voltage constraints, node current constraints, power grid side flow balance constraints, no new peaks or valleys on the power grid side, regulation resource regulation potential constraints, and source-load side over-response constraints; Performing a load balancing operation on the power system according to the load balancing strategy to obtain a load balancing result, wherein the load balancing result is used to indicate whether the power system meets the load balancing requirement; The method further includes: performing dimensionless processing on multiple objective functions to obtain multiple dimensionless results; weighting the multiple dimensionless results based on the weight of each load balancing target to obtain a total balancing target, wherein the multiple objective functions are used to represent mathematical expressions that describe the multiple load balancing targets in the measurement system, the dimensionless processing is used to describe the process of converting the objective functions of the multiple load balancing targets into a unitless form, and the total balancing target is used to represent the overall target of the power system determined based on the importance of the multiple load balancing targets.

2. The load balancing method of the power system according to claim 1, characterized in that: The method further comprises: Determine multiple load balancing targets; The load balancing model is constructed based on the multiple load balancing objectives.

3. The load balancing method of the power system according to claim 2, characterized in that: Constructing the load balancing model based on the load balancing target includes: The weight of each load balancing objective is determined using the scaling construction method; Determining a target constraint condition corresponding to the load balancing model, wherein the target constraint condition is used to limit a solution space of the load balancing model; The load balancing model is constructed based on the multiple load balancing objectives, the weight of each load balancing objective and the objective constraint condition.

4. The load balancing method of the power system according to claim 3, characterized in that: The weight of each load balancing objective is determined using the scaling construction method, including: quantifying the importance of the multiple load balancing objectives to obtain quantified results of the multiple load balancing objectives; Based on the quantified results of the multiple load balancing targets, the multiple load balancing targets are sorted to obtain a plurality of sorted load balancing targets; Based on the quantization results of any two adjacent load balancing targets among the sorted multiple load balancing targets, determine the scale values ​​of the any two adjacent load balancing targets, wherein the scale value is used to quantify the relative importance between the two load balancing targets corresponding to any two adjacent objective functions, and the objective function is used to describe a mathematical expression for measuring the load balancing target; Based on the scale values ​​of any two adjacent load balancing targets, constructing a judgment matrix; The weight of each objective function is determined based on the judgment matrix.

5. The load balancing method of the power system according to claim 3, characterized in that: Determining the target constraint conditions corresponding to the load balancing model includes: Determine the safe load rate range, voltage amplitude range and current amplitude range corresponding to the load balancing model; Determining the operating load constraint condition based on the safe load rate interval; Determining the node voltage constraint condition based on the voltage amplitude range; Determining the node current constraint condition based on the current amplitude interval; The target constraint condition is determined based on the operating load constraint condition, the node voltage constraint condition, and the node current constraint condition.

6. The load balancing method of the power system according to claim 3, characterized in that: The load balancing model is constructed based on the multiple load balancing objectives, the weight of each load balancing objective and the objective constraint condition, including: Based on the weight of each load balancing target, weighting the multiple load balancing targets to obtain the overall balancing target; The load balancing model is constructed according to the overall balancing target and the target constraint conditions.

7. The load balancing method of the power system according to claim 6, characterized in that: Based on the weight of each load balancing target, the multiple load balancing targets are weighted to obtain a total balancing target, including: Based on the multiple load balancing objectives, determining the multiple objective functions corresponding to the multiple load balancing objectives; Based on the weight of each load balancing target, the multiple objective functions are weighted to obtain the overall balancing target.

8. A load balancing device for an electric power system, characterized in that: include: An acquisition module, configured to, in response to receiving a balancing request for performing a load balancing operation on a power system, determine balancing demand information and balancing subject information corresponding to the balancing request, wherein the balancing demand information is used to characterize the load balancing demand of the power system, and the balancing subject information is information of power equipment with load balancing capability in the power system, and the balancing demand information includes at least one of the following: the amount of load to be balanced of the power system, the duration of balancing required by the power system, the front load of the power system, the balanced response subsidy price, the subsidy coefficient, the time-of-use electricity price for user electricity, and the power equipment in the power system that can respond to load balancing, and the balancing subject information includes at least one of the following: the type of power equipment, the initial switching state of the power equipment, the starting power of the power equipment, the load increase boundary of the power equipment, and the load decrease boundary of the power equipment; A solution module is used to solve the load balancing model corresponding to the power system based on the balancing demand information and the balancing subject information to obtain the load balancing strategy of the power system, wherein the load balancing strategy includes the switch state and the required balancing power of the power equipment with load balancing capability at any time, the load balancing model is constructed based on multiple constraints and multiple load balancing targets, the multiple constraints are determined based on multiple constraint intervals, the multiple constraints are used to represent the rules used to limit the solution space in the load balancing model, the multiple load balancing targets include the following three: the volatility of the load balancing operation on the power grid side of the power system is minimized, the cost of load balancing on the power grid side is minimized, and the cost of the user side of the power system participating in the load balancing response is minimized, and the multiple constraints include at least one of the following: operating load constraint, node voltage constraint, node current constraint, power grid side flow balance constraint, no new peak or valley constraint on the power grid side, regulation resource regulation potential constraint, source load side over-response constraint; A balancing module, used for performing a load balancing operation on the power system according to the load balancing strategy to obtain a load balancing result, wherein the load balancing result is used to indicate whether the power system meets the load balancing requirement; Among them, the device is also used to perform dimensionless processing on multiple objective functions to obtain multiple dimensionless results; based on the weight of each load balancing target, the multiple dimensionless results are weighted to obtain a total balancing target, wherein the multiple objective functions are used to represent mathematical expressions that describe the multiple load balancing targets in the measurement system, the dimensionless processing is used to describe the process of converting the objective functions of the multiple load balancing targets into a unitless form, and the total balancing target is used to represent the overall target of the power system determined based on the importance of the multiple load balancing targets.

9. An electronic device, characterized in that: include: A memory storing an executable program; A processor, configured to run the program, wherein the program executes the method according to any one of claims 1 to 7 when running.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored executable program, wherein when the executable program is run, the device where the storage medium is located is controlled to execute the method according to any one of claims 1 to 7.

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