Flexible regulation and control method and device for air conditioner and charging pile cluster involving rebound

Abstract

The invention provides a rebound air conditioner and charging pile cluster flexible regulation and control method and device, which are applied to the technical field of data processing and comprise the following steps: determining an air conditioner two-dimensional response state point set of an air conditioner cluster based on an air conditioner load curve of the air conditioner cluster in a specified area; determining a charging pile two-dimensional response state point set of the charging pile cluster according to the charging and discharging power matrix of the charging pile cluster in the designated area; according to respective convex hull data of the air conditioner two-dimensional response state point set and the charging pile two-dimensional response state point set, a comprehensive two-dimensional response state point set of the air conditioner cluster and the charging pile cluster is determined; extracting at least one target state point from the comprehensive two-dimensional response state point set, wherein the comprehensive load reduction amount indicated by the target state point is greater than a preset reduction amount threshold value and the comprehensive load rebound amount is smaller than a preset rebound amount threshold value; and according to the air conditioner data and the charging pile data indicated by the at least one target state point, the flexible regulation and control strategy of the air conditioner cluster and the charging pile cluster in the designated area is adjusted.

Description

Technical Field

[0001] This disclosure relates to the field of data processing technology, specifically to the field of power system demand response technology, and more specifically to a flexible control method and device for air conditioning and charging pile clusters involving rebound. Background Technology

[0002] Against the backdrop of surging global electricity demand and large-scale grid connection of renewable energy, air conditioning and electric vehicles have become key demand-side flexible resources.

[0003] Both air conditioners and electric vehicles are prone to triggering a rebound effect after participating in demand response, forming a new round of peak electricity consumption. The rebound electricity may exceed the reduction electricity, resulting in negative net benefits for users. This leads to overload issues for air conditioners and electric vehicle charging piles during the demand response regulation process. Summary of the Invention

[0004] In view of the above problems, this disclosure provides a flexible control method and device for air conditioning and charging pile clusters involving rebound.

[0005] According to a first aspect of this disclosure, a flexible control method for air conditioning and charging pile clusters involving rebound is provided, comprising: determining a two-dimensional response state point set of the air conditioning cluster based on the air conditioning load curve of the air conditioning cluster in a specified area, wherein the two-dimensional response state point set characterizes the air conditioning load reduction of the air conditioning cluster during the response period and the air conditioning load rebound during the non-response period, for flexible control of the air conditioning cluster and charging pile cluster by the flexible resource control terminal in the specified area; determining a two-dimensional response state point set of the charging pile cluster based on the charging and discharging power matrix of the charging pile cluster in the specified area, wherein the two-dimensional response state point set of the charging pile characterizes the charging pile load reduction during the response period and the charging pile load rebound during the non-response period; determining a comprehensive two-dimensional response state point set of the air conditioning cluster and the charging pile cluster based on the convex hull data of their respective two-dimensional response state point sets of the air conditioning cluster and the charging pile cluster; extracting at least one target state point from the comprehensive two-dimensional response state point set, wherein the comprehensive load reduction indicated by the target state point is greater than a preset reduction threshold and the comprehensive load rebound is less than a preset rebound threshold; and adjusting the flexible control strategy of the air conditioning cluster and the charging pile cluster in the specified area based on the air conditioning data and charging pile data indicated by the at least one target state point.

[0006] According to embodiments of this disclosure, determining the two-dimensional response state point set of an air conditioning cluster based on the air conditioning load curve of the air conditioning cluster in a specified area includes: for any time step within a specified period and for any air conditioner in the air conditioning cluster, determining the power consumption benefit of the air conditioner based on the changes in the power consumption of the air conditioner and the user cost-benefit loss of the users associated with the air conditioner; for any air conditioner in the air conditioning cluster, determining multiple target power consumption benefits from the power consumption benefits of multiple time steps within the specified period based on a particle swarm optimization algorithm, the multiple target power consumption benefits including the target power consumption benefit of the air conditioner during the response period and the power consumption benefit during non-response periods; for any air conditioner in the air conditioning cluster, processing the multiple target power consumption benefits using a target model to construct an air conditioning load curve; and determining the two-dimensional response state point set of the air conditioning cluster based on the respective air conditioning load curves of the multiple air conditioners in the air conditioning cluster.

[0007] According to embodiments of this disclosure, multiple target electricity benefits are processed using a target model to construct an air conditioning load curve, including: constructing an air conditioning temperature change curve based on multiple air conditioning temperature data indicated by multiple target electricity benefits; processing the temperature change curve using the target model to obtain the air conditioning load curve; and determining the air conditioning load curve based on the multiple air conditioning load curves of the air conditioning cluster.

[0008] According to embodiments of this disclosure, determining a comprehensive two-dimensional response state point set for an air conditioning cluster and a charging pile cluster based on the respective convex hull data of the air conditioning two-dimensional response state point set and the charging pile two-dimensional response state point set includes: performing convex hull calculations on the air conditioning two-dimensional response state point set and the charging pile two-dimensional response state point set respectively to obtain air conditioning convex hull data of the air conditioning two-dimensional response state point set and charging pile convex hull data of the charging pile two-dimensional response state point set; fusing the air conditioning convex hull data and the charging pile convex hull data to obtain fused convex hull data; and determining the comprehensive two-dimensional response state point set for the air conditioning cluster and the charging pile cluster from the two-dimensional coordinate system indicated by the fused convex hull data.

[0009] According to embodiments of this disclosure, determining a comprehensive two-dimensional response state point set of air conditioning clusters and charging pile clusters from a two-dimensional coordinate system indicated by fused convex hull data includes: determining a target quadrant from the two-dimensional coordinate system; determining a load reduction threshold and a load rebound threshold based on the load of the air conditioning cluster and the load of the charging pile cluster; dividing the target quadrant using the load reduction threshold and the load rebound threshold to obtain a target quadrant region; and constructing a comprehensive two-dimensional response state point set of the air conditioning clusters and charging pile clusters based on the two-dimensional response state points indicated by the target quadrant region.

[0010] According to embodiments of this disclosure, determining a load reduction threshold and a load rebound threshold based on the load of the air conditioning cluster and the load of the charging pile cluster includes: for a response period, for any time step, determining a first air conditioning load difference between the load of the air conditioning cluster in the response state and the load of the air conditioning cluster in the non-response state; for any time step, determining a first charging pile load difference between the load of the charging pile cluster in the response state and the load of the charging pile cluster in the non-response state; determining an average load reduction during the response period based on the ratio of the first air conditioning load difference and the first charging pile load difference to the number of time steps; and determining a load reduction threshold based on the average load reduction during the response period and the total load in the non-response state.

[0011] According to embodiments of this disclosure, determining a load reduction threshold and a load rebound threshold based on the load of the air conditioning cluster and the load of the charging pile cluster further includes: for non-response periods, for any time step, determining a second air conditioning load difference between the load of the air conditioning cluster in the response state and the load of the air conditioning cluster in the non-response state; for any time step, determining a second charging pile load difference between the load of the charging pile cluster in the response state and the load of the charging pile cluster in the non-response state; determining the average rebound load of the response period based on the ratio of the second air conditioning load difference and the second charging pile load difference of multiple time steps to the number of time steps; and determining the load rebound threshold based on the average rebound load of the response period and the total load in the non-response state.

[0012] According to embodiments of this disclosure, the method further includes: dividing the response time period into batches to obtain multiple response batches when flexibly controlling the air conditioning cluster, wherein there is a time step interval between every two response batches; and performing flexible control on different air conditioners in different response batches based on the different response batches.

[0013] According to embodiments of this disclosure, the matrix elements in the charge / discharge power matrix represent the charge / discharge power of different charging piles at different time steps during a specified period; wherein, the method further includes: when constructing the charge / discharge power matrix of a charging pile cluster in a specified area, collecting the charge / discharge power that meets the constraints; wherein, the constraints include that the charge / discharge power is within the rated charge / discharge power range of the charging pile.

[0014] The second aspect of this disclosure provides a flexible control device for air conditioning and charging pile clusters involving rebound, comprising: a first determining module, configured to determine a two-dimensional response state point set of the air conditioning cluster based on the air conditioning load curve of the air conditioning cluster in a specified area, wherein the two-dimensional response state point set characterizes the air conditioning load reduction of the air conditioning cluster during the response period and the air conditioning load rebound during the non-response period, and configured to supply energy to the air conditioning cluster and the charging pile cluster from the flexible resource control terminal in the specified area; and a second determining module, configured to determine a two-dimensional response state point set of the charging pile cluster based on the charging and discharging power matrix of the charging pile cluster in the specified area, wherein the two-dimensional response state point set of the charging pile characterizes the charging pile load reduction during the response period. The system includes: a charging pile load reduction amount and a charging pile load rebound amount during non-response periods; a third determining module, used to determine the comprehensive two-dimensional response state point set of the air conditioning cluster and the charging pile cluster based on the convex hull data of their respective two-dimensional response state point sets; a first extraction module, used to extract at least one target state point from the comprehensive two-dimensional response state point set, wherein the comprehensive load reduction amount indicated by the target state point is greater than a preset reduction amount threshold and the comprehensive load rebound amount is less than a preset rebound amount threshold; and a first adjustment module, used to adjust the flexible control strategy of the air conditioning cluster and the charging pile cluster in a specified area based on the air conditioning data and charging pile data indicated by at least one target state point.

[0015] A third aspect of this disclosure provides an electronic device comprising: one or more processors; and a memory for storing one or more computer programs, wherein the one or more processors execute the one or more computer programs to implement the steps of the method described above.

[0016] A fourth aspect of this disclosure also provides a computer-readable storage medium having a computer program or instructions stored thereon, which, when executed by a processor, implement the steps of the above-described method.

[0017] The fifth aspect of this disclosure also provides a computer program product, including a computer program or instructions that, when executed by a processor, implement the steps of the above-described method.

[0018] According to embodiments of this disclosure, a two-dimensional response state point set for the air conditioning cluster is determined based on the air conditioning load curve of the air conditioning cluster in a specified area; a two-dimensional response state point set for the charging pile cluster is determined based on the charging and discharging power matrix of the charging pile cluster in the specified area; a comprehensive two-dimensional response state point set for the air conditioning cluster and the charging pile cluster is determined based on the convex hull data of their respective two-dimensional response state point sets; at least one target state point is extracted from the comprehensive two-dimensional response state point set; and a flexible control strategy for the air conditioning cluster and the charging pile cluster in the specified area is adjusted based on the air conditioning data and charging pile data indicated by the at least one target state point. By utilizing the air conditioning load curve of the air conditioning cluster to determine the two-dimensional response state point set of the air conditioning cluster, it is possible to analyze the load change of the air conditioning cluster with temperature at different time steps. Similarly, by utilizing the charging and discharging power matrix to determine the two-dimensional response state point set of the charging pile cluster, it is possible to analyze the load change of the charging pile cluster with charging and discharging power at different time steps. Furthermore, by merging the two-dimensional response state point sets of the air conditioning and charging piles, a comprehensive analysis can be performed. This allows for maximizing the load reduction of both air conditioning and charging piles while minimizing load rebound, achieving coordinated control of the air conditioning and charging pile clusters by the flexible resource control terminal. This avoids overload issues for both air conditioning and charging piles when responding to flexible control, thereby improving operational stability. Attached Figure Description

[0019] The foregoing contents, as well as other objects, features, and advantages of this disclosure, will become clearer from the following description of embodiments with reference to the accompanying drawings, in which:

[0020] Figure 1 The diagram illustrates an application scenario of a flexible control method, apparatus, device, medium, and program product for air conditioning and charging pile clusters involving rebound, according to embodiments of this disclosure.

[0021] Figure 2 A flowchart of a flexible control method for air conditioning and charging pile clusters involving rebound, according to an embodiment of the present disclosure, is shown.

[0022] Figure 3 A comparison diagram is shown of flexible control strategies for air conditioning and charging pile clusters involving rebound according to embodiments of the present disclosure.

[0023] Figure 4 A structural block diagram of a flexible control device for air conditioning and charging pile clusters involving rebound, according to an embodiment of the present disclosure, is shown.

[0024] Figure 5 A block diagram of an electronic device suitable for implementing a flexible control method for air conditioning and charging pile clusters involving rebound, according to an embodiment of the present disclosure, is shown. Detailed Implementation

[0025] The embodiments of the present disclosure will now be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the disclosure. In the following detailed description, numerous specific details are set forth to provide a thorough understanding of the embodiments of the present disclosure for ease of explanation. However, it will be apparent that one or more embodiments may be practiced without these specific details. Furthermore, descriptions of well-known structures and techniques are omitted in the following description to avoid unnecessarily obscuring the concepts of the present disclosure.

[0026] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit this disclosure. The terms “comprising,” “including,” etc., as used herein indicate the presence of the stated features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0027] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein are to be interpreted in a manner consistent with the context of this specification, and not in an idealized or overly rigid way.

[0028] When using expressions such as "at least one of A, B and C", they should generally be interpreted in accordance with the meaning that is commonly understood by those skilled in the art (e.g., "a system having at least one of A, B and C" should include, but is not limited to, a system having A alone, a system having B alone, a system having C alone, a system having A and B, a system having A and C, a system having B and C, and / or a system having A, B and C, etc.).

[0029] Against the backdrop of surging global electricity demand and large-scale grid integration of renewable energy, air conditioning and electric vehicles have become key flexible resources for demand-side response. However, the participation of these two types of resources in the response can easily trigger a "rebound effect," creating a new round of peak electricity consumption. The rebound in electricity volume may even exceed the reduction in electricity volume, and in severe cases, it can lead to negative net benefits for users, thus restricting the large-scale application of demand response.

[0030] To suppress the rebound effect, related technologies mainly adopt two strategies: First, air conditioning systems use time-series control methods such as batch adjustment and staggered recovery to disperse the impact of air conditioning load. Second, air conditioning is combined with flexible resources such as lighting to complement and aggregate them, in order to smooth out fluctuations. However, the above methods have obvious limitations: the batch strategy is affected by sudden changes in the external environment and interference from user energy consumption behavior, making it difficult to completely eliminate the rebound and potentially sacrificing user comfort; while the adjustment capacity of resources such as lighting is limited, resulting in poor synergistic effects.

[0031] Complementing air conditioning with electric vehicles that have bidirectional charging and discharging capabilities is an effective way to suppress rebound. However, existing research mainly focuses on optimizing response effect and economy, and has failed to establish a quantitative model of the global coupling relationship between "reduction-rebound". It also lacks a systematic exploration of the mechanism for the two types of resources to work together to suppress rebound, resulting in insufficient flexibility of control strategies and difficulty in adapting to diverse grid dispatching needs.

[0032] The embodiments of this disclosure provide a flexible control method for air conditioning and charging pile clusters involving rebound. Based on the air conditioning load curve of the air conditioning cluster in a specified area, a two-dimensional response state point set for the air conditioning cluster is determined. This set represents the load reduction during the response period and the load rebound during the non-response period, and is used by the flexible resource control terminal in the specified area to supply energy to the air conditioning cluster and charging pile cluster. Based on the charging and discharging power matrix of the charging pile cluster in the specified area, a two-dimensional response state point set for the charging pile cluster is determined. This set represents the load reduction during the response period and the load rebound during the non-response period. Based on the convex hull data of the air conditioning and charging pile two-dimensional response state point sets, a comprehensive two-dimensional response state point set for the air conditioning and charging pile clusters is determined. At least one target state point is extracted from the comprehensive two-dimensional response state point set, where the comprehensive load reduction indicated by the target state point is greater than a preset reduction threshold and the comprehensive load rebound is less than a preset rebound threshold. Based on the air conditioning data and charging pile data indicated by at least one target state point, the flexible control strategy for the air conditioning and charging pile clusters in the specified area is adjusted.

[0033] Figure 1 The diagram illustrates an application scenario of a flexible control method, apparatus, device, medium, and program product for air conditioning and charging pile clusters involving rebound, according to embodiments of this disclosure.

[0034] like Figure 1 As shown, the application scenarios according to this embodiment may include flexible resource control terminals, air conditioning clusters, and charging pile clusters.

[0035] The air conditioning cluster and the charging pile cluster each collect their own load-related data and send them to the flexible resource control terminal.

[0036] After receiving load-related data from the air conditioning cluster and the charging pile cluster respectively, the flexible resource control terminal analyzes the load of the air conditioning cluster and the charging pile cluster to obtain a flexible control strategy, and then performs flexible control on the air conditioning cluster and the charging pile cluster based on the source supply strategy.

[0037] The following will be based on Figure 1 The scenario described herein provides a detailed description of the flexible control method for air conditioning and charging pile clusters involving rebound, based on the disclosed embodiments.

[0038] Figure 2 A flowchart of a flexible control method for air conditioning and charging pile clusters involving rebound, according to an embodiment of the present disclosure, is shown.

[0039] like Figure 2 As shown, the flexible resource regulation method of this embodiment includes operations S210 to S250.

[0040] In operation S210, the two-dimensional response state point set of the air conditioning cluster is determined based on the air conditioning load curve of the air conditioning cluster in the specified area. The two-dimensional response state point set of the air conditioning cluster represents the amount of air conditioning load reduction during the response period and the amount of air conditioning load rebound during the non-response period. It is used by the flexible resource control terminal of the specified area to supply energy to the air conditioning cluster and the charging pile cluster.

[0041] The designated area can be an area where resources can be provided by the flexible resource control mechanism, such as an industrial park or a residential area.

[0042] An air conditioning cluster can be a cluster consisting of all the air conditioners in a designated area.

[0043] An air conditioning load curve is a curve composed of the load generated by multiple air conditioners in an air conditioning cluster at different time steps and different air conditioning temperatures. It is used to represent the change of the air conditioning cluster load with air conditioning temperature. The time steps indicated by the air conditioning load curve include the response period and the non-response period.

[0044] The response period is the time when the air conditioner responds to the flexible resource control of the flexible resource control terminal, and the non-response period is the time when the air conditioner does not respond to the flexible resource control of the flexible resource control terminal, such as the pre-cooling stage and the recovery stage of the air conditioner. The pre-cooling stage can be the stage of storing "cooling capacity" in the room in advance by utilizing the thermal inertia of the building envelope, furniture, etc., in preparation for subsequent reduction or transfer of electricity consumption. The recovery stage can be the stage of allowing the room temperature to return to the normal comfort setting value.

[0045] The two-dimensional response state point set of air conditioning represents the amount of air conditioning load reduction during the response period and the amount of air conditioning load rebound during the non-response period. The amount of air conditioning load reduction can be the load saved during the response period relative to the non-response state (baseline state), and the amount of air conditioning load rebound can be the load higher than the baseline state during the non-response period.

[0046] Based on the two-dimensional response state point set of air conditioners, the flexible resource regulation terminal can analyze the optimal flexible regulation strategy for supplying energy to air conditioner clusters and charging pile clusters to reduce load rebound.

[0047] In operation S220, based on the charging and discharging power matrix of the charging pile cluster in the specified area, the two-dimensional response state point set of the charging pile cluster is determined. The two-dimensional response state point set of the charging piles represents the charging pile load reduction during the response period and the charging pile load rebound during the non-response period.

[0048] A charging pile cluster can be a cluster consisting of all the charging piles in a specified area.

[0049] The charging and discharging power matrix can be a matrix composed of the charging and discharging power of charging piles at different time steps.

[0050] The two-dimensional response state point set of the charging pile represents the charging pile load reduction during the response period and the charging pile load rebound during the non-response period. The charging pile load reduction can be the load saved relative to the baseline state during the response period, and the charging pile load rebound can be the load higher than the baseline state during the non-response period.

[0051] In operation S230, the comprehensive two-dimensional response state point set of the air conditioning cluster and the charging pile cluster is determined based on the convex hull data of their respective two-dimensional response state point sets.

[0052] By calculating the two-dimensional response state point set of the air conditioner and the two-dimensional response state point set of the charging pile respectively, the convex hull data of each of the two-dimensional response state point sets of the air conditioner and the charging pile can be obtained. The convex hull data is a polygon in a two-dimensional coordinate system, which includes each two-dimensional response state point in the two-dimensional response state point set.

[0053] After determining the convex hull data of the two-dimensional response state point sets of air conditioners and charging piles, multiple two-dimensional response state points are selected to form a comprehensive two-dimensional response state point set of the air conditioner cluster and the charging pile cluster by analyzing the polygons in the two-dimensional coordinate system.

[0054] In operation S240, at least one target state point is extracted from the set of integrated two-dimensional response state points. The integrated load reduction indicated by the target state point is greater than the preset reduction threshold and the integrated load rebound is less than the preset rebound threshold.

[0055] In operation S250, the flexible control strategy of the air conditioning cluster and charging pile cluster in the specified area is adjusted based on the air conditioning data and charging pile data indicated by at least one target state point.

[0056] After determining the comprehensive two-dimensional response state point set, the air conditioning data and charging pile data indicated by the target state points in the comprehensive two-dimensional response state point set are extracted. The air conditioning data includes air conditioning temperature data, and the charging pile data includes charging and discharging power data of the charging pile.

[0057] Based on the air conditioning data and charging pile data indicated by the target state point, the flexible control strategy of the air conditioning cluster and charging pile cluster in the designated area is adjusted. The air conditioning temperature and charging / discharging power indicated by the flexible control strategy are close to or consistent with the air conditioning data and charging pile data indicated by the target state point. This results in an increase in the load reduction and a decrease in the load rebound when the air conditioning cluster and charging pile cluster in the designated area operate based on the flexible resource control indicated by the flexible control strategy.

[0058] Flexible control strategies may include: Strategy 1: All charging pile clusters must meet the charging demand; Strategy 2: All charging pile clusters do not restrict the charging demand; Strategy 3: Users of high-power (60kW) charging pile clusters must meet their charging demand, while users of low-power (21kW, 7kW) charging pile clusters are not restricted; Strategy 4: High-power (60kW) charging pile clusters do not restrict the charging demand, while users of low-power (21kW, 7kW) charging pile clusters must meet the charging demand.

[0059] According to embodiments of this disclosure, a two-dimensional response state point set for the air conditioning cluster is determined based on the air conditioning load curve of the air conditioning cluster in a specified area; a two-dimensional response state point set for the charging pile cluster is determined based on the charging and discharging power matrix of the charging pile cluster in the specified area; a comprehensive two-dimensional response state point set for the air conditioning cluster and the charging pile cluster is determined based on the convex hull data of their respective two-dimensional response state point sets; at least one target state point is extracted from the comprehensive two-dimensional response state point set; and a flexible control strategy for the air conditioning cluster and the charging pile cluster in the specified area is adjusted based on the air conditioning data and charging pile data indicated by the at least one target state point. By utilizing the air conditioning load curve of the air conditioning cluster to determine the two-dimensional response state point set of the air conditioning cluster, it is possible to analyze the load change of the air conditioning cluster with temperature at different time steps. Similarly, by utilizing the charging and discharging power matrix to determine the two-dimensional response state point set of the charging pile cluster, it is possible to analyze the load change of the charging pile cluster with charging and discharging power at different time steps. Furthermore, by merging the two-dimensional response state point sets of the air conditioning and charging piles, a comprehensive analysis can be performed. This allows for maximizing the load reduction of both air conditioning and charging piles while minimizing load rebound, achieving coordinated control of the air conditioning and charging pile clusters by the flexible resource control terminal. This avoids overload issues for both air conditioning and charging piles when responding to flexible resource control, thereby improving operational stability.

[0060] According to embodiments of this disclosure, determining the two-dimensional response state point set of an air conditioning cluster based on the air conditioning load curve of the air conditioning cluster in a specified area includes: for any time step within a specified period and for any air conditioner in the air conditioning cluster, determining the power consumption benefit of the air conditioner based on the changes in the power consumption of the air conditioner and the user cost-benefit loss of the users associated with the air conditioner; for any air conditioner in the air conditioning cluster, determining multiple target power consumption benefits from the power consumption benefits of multiple time steps within the specified period based on a particle swarm optimization algorithm, the multiple target power consumption benefits including the target power consumption benefit of the air conditioner during the response period and the power consumption benefit during non-response periods; for any air conditioner in the air conditioning cluster, processing the multiple target power consumption benefits using a target model to construct an air conditioning load curve; and determining the two-dimensional response state point set of the air conditioning cluster based on the respective air conditioning load curves of the multiple air conditioners in the air conditioning cluster.

[0061] Changes in electricity consumption can be the changes in electricity consumption caused by temperature changes in air conditioners at any given time step.

[0062] Users associated with the air conditioner can be those who use the air conditioner. The user cost-benefit loss associated with the air conditioner can be the cost loss incurred in performing tasks based on the air conditioner temperature at any given time step, such as the degree of reduction in workload or task cost loss.

[0063] For any air conditioner, the energy efficiency of the air conditioner can be determined based on formula (1).

[0064] (1).

[0065] in, For the electricity consumption efficiency at a certain time step, This represents the change in electricity consumption at this time step. This represents the user's cost-benefit loss at this time step.

[0066] For any air conditioner, after determining the power consumption benefits of multiple time steps based on the above formula (1), the target power consumption benefit is selected from the power consumption benefits of multiple time steps using the particle swarm algorithm.

[0067] The target electricity efficiency can be the highest among the electricity efficiency benefits at multiple time steps. For example, it can be ranked from largest to smallest according to the electricity efficiency values, and the top five electricity efficiency benefits can be used as the target electricity efficiency benefits. In addition, there must be at least one electricity efficiency benefit as the target electricity efficiency benefit during both the response period and the non-response period.

[0068] After determining multiple target electricity benefits, the target model is used to analyze the air conditioning temperature indicated by the multiple target electricity benefits and determine the air conditioning load curves corresponding to the multiple target electricity benefits.

[0069] The target model can be a model built based on building energy consumption simulation software. The target model simulates the building energy consumption load of the air conditioning temperature consumption in the specified area based on meteorological data, thermal parameters of the building envelope, occupancy rate, and equipment operation schedule.

[0070] The load of air conditioning at different time steps, as indicated by the air conditioning load curve, is analyzed to determine the two-dimensional response state point set of the air conditioning cluster.

[0071] According to embodiments of this disclosure, the power consumption of air conditioners is determined by considering the changes in power consumption of air conditioners and the user cost-benefit losses of users associated with air conditioners. When analyzing the air conditioner load curve, the loads that affect multi-dimensional benefits can be considered, so that the obtained flexible control strategy can be flexibly adapted to different air conditioner users in subsequent operations.

[0072] According to embodiments of this disclosure, multiple target electricity benefits are processed using a target model to construct an air conditioning load curve, including: constructing an air conditioning temperature change curve based on multiple air conditioning temperature data indicated by multiple target electricity benefits; processing the temperature change curve using the target model to obtain the air conditioning load curve; and determining the air conditioning load curve based on the multiple air conditioning load curves of the air conditioning cluster.

[0073] Based on multiple air conditioning temperature data with multiple target electricity efficiency indicators, temperature change curves for different air conditioning temperatures at different time steps are plotted.

[0074] After obtaining the temperature change curve, the target model is used to process the temperature change curve to simulate the load generated by different air conditioning temperatures, so as to construct the air conditioning load curve based on the temperature change curve.

[0075] After determining the individual air conditioning load curves of multiple air conditioners, the individual air conditioning load curves of multiple air conditioners are merged to obtain the air conditioning load curve of the air conditioning cluster.

[0076] According to embodiments of this disclosure, multiple target power consumption benefits are processed using a target model. The target model can simulate the building environment where the air conditioner is located, obtain the load caused by different temperatures in different buildings, and make the obtained air conditioner load curve more accurate.

[0077] According to embodiments of this disclosure, determining a comprehensive two-dimensional response state point set for an air conditioning cluster and a charging pile cluster based on the respective convex hull data of the air conditioning two-dimensional response state point set and the charging pile two-dimensional response state point set includes: performing convex hull calculations on the air conditioning two-dimensional response state point set and the charging pile two-dimensional response state point set respectively to obtain air conditioning convex hull data of the air conditioning two-dimensional response state point set and charging pile convex hull data of the charging pile two-dimensional response state point set; fusing the air conditioning convex hull data and the charging pile convex hull data to obtain fused convex hull data; and determining the comprehensive two-dimensional response state point set for the air conditioning cluster and the charging pile cluster from the two-dimensional coordinate system indicated by the fused convex hull data.

[0078] Convex hull calculations are performed on the two-dimensional response state point set of the air conditioner and the two-dimensional response state point set of the charging pile, respectively. Based on the two-dimensional response state points of the air conditioner in the two-dimensional response state point set, a polygon in a two-dimensional coordinate system is drawn to obtain the convex hull data of the air conditioner in the two-dimensional response state point set. Based on the two-dimensional response state points of the charging pile in the two-dimensional response state point set, a polygon in a two-dimensional coordinate system is drawn to obtain the convex hull data of the charging pile in the two-dimensional response state point set of the charging pile.

[0079] Fusing air conditioner convex hull data and charging pile convex hull data can be achieved by calculating the sum of the coordinates of all convex hull vertices in both datasets, extracting the boundary of the merged convex hull, and obtaining the fused convex hull data. For example, the fused convex hull data might be... Among them, the data for the air conditioner convex bulge is The charging pile convex hull data is , Charging pile clusters corresponding to different power levels (such as 7kW, 21kW, 60kW).

[0080] The two-dimensional coordinate system indicated by the fused convex hull data divides the fused convex hull data into four quadrants. Based on the fused convex hull data indicated by different quadrants, the comprehensive two-dimensional response state point set of the charging pile cluster and the charging pile cluster is determined from the two-dimensional coordinate system.

[0081] According to embodiments of this disclosure, by fusing air conditioning convex hull data and charging pile convex hull data, fused convex hull data is obtained. This fused convex hull data can comprehensively consider the load of the air conditioning cluster and the charging pile cluster, so that the comprehensive two-dimensional response state point set determined based on the fused convex hull data can simultaneously reflect the load status of the air conditioning cluster and the charging pile cluster. This allows the flexible control strategy obtained based on the comprehensive two-dimensional response state point set to coordinate the load of the air conditioning cluster and the charging pile cluster, so that the load of the air conditioning cluster and the charging pile cluster tends to stabilize during the response.

[0082] According to embodiments of this disclosure, determining a comprehensive two-dimensional response state point set of air conditioning clusters and charging pile clusters from a two-dimensional coordinate system indicated by fused convex hull data includes: determining a target quadrant from the two-dimensional coordinate system; determining a load reduction threshold and a load rebound threshold based on the load of the air conditioning cluster and the load of the charging pile cluster; dividing the target quadrant using the load reduction threshold and the load rebound threshold to obtain a target quadrant region; and constructing a comprehensive two-dimensional response state point set of the air conditioning clusters and charging pile clusters based on the two-dimensional response state points indicated by the target quadrant region.

[0083] The two-dimensional coordinate system indicated by the fused convex hull data is divided into four quadrants: Quadrant 1 (invalid region): no reduction but bounce; Quadrant 2 (invalid region): no reduction and no bounce; Quadrant 3 (ideal region): reduction but no bounce; Quadrant 4 (normal region): reduction and bounce.

[0084] Determining the target quadrant from a two-dimensional coordinate system can be achieved by defining the aforementioned third and fourth quadrants as the target quadrants.

[0085] The load reduction threshold can be determined based on the average load reduction of the air conditioning cluster and the charging pile cluster during the response period, and is used to limit the range of fused convex hull data in the third and fourth quadrants.

[0086] The load rebound threshold can be determined based on the average load rebound of the air conditioning cluster and the charging pile cluster during the response period, and is used to limit the range of fused convex hull data in the third and fourth quadrants.

[0087] In addition, multiple thresholds of different levels can be generated based on the load reduction threshold and the load rebound threshold.

[0088] After determining the target quadrant, load reduction threshold, and load rebound threshold, the two-dimensional coordinate system indicated by the fused convex hull data is divided to obtain the target quadrant region.

[0089] Two-dimensional response state points indicated by fused convex hull data are extracted in the target quadrant region to construct a comprehensive two-dimensional response state point set for the air conditioning cluster and the charging pile cluster based on multiple two-dimensional response state points.

[0090] According to embodiments of this disclosure, dividing the two-dimensional coordinate system indicated by the fused convex hull data can filter out effective data in the third and fourth quadrants from the fused convex hull data. Further dividing based on load reduction threshold and load rebound threshold can further narrow down the effective data to select a better set of comprehensive two-dimensional response state points.

[0091] According to embodiments of this disclosure, determining a load reduction threshold and a load rebound threshold based on the load of the air conditioning cluster and the load of the charging pile cluster includes: for a response period, for any time step, determining a first air conditioning load difference between the load of the air conditioning cluster in the response state and the load of the air conditioning cluster in the non-response state; for any time step, determining a first charging pile load difference between the load of the charging pile cluster in the response state and the load of the charging pile cluster in the non-response state; determining an average load reduction during the response period based on the ratio of the first air conditioning load difference and the first charging pile load difference to the number of time steps; and determining a load reduction threshold based on the average load reduction during the response period and the total load in the non-response state.

[0092] The response state can be the state in which the air conditioning cluster or charging pile cluster is intervened by the flexible resource control terminal, while the non-response state, i.e. the baseline state, can be the state in which the air conditioning cluster or charging pile cluster is not intervened by the flexible resource control terminal.

[0093] The average load reduction during the response period can be calculated using formula (2).

[0094] (2).

[0095] The average load reduction during the response period is: , The first air conditioning load difference / the first charging pile load difference at any time step. Let the load of the air conditioning cluster in the response state at any time step be the load of the charging pile cluster in the response state. The load of the air conditioning cluster in a non-responsive state / the load of the charging pile cluster in a non-responsive state. This represents the number of time steps.

[0096] After determining the average load reduction during the response period, the total load under non-response conditions is obtained to determine the load reduction threshold using formula (3).

[0097] (3).

[0098] in, The load reduction threshold, It is the ratio of the total load to the number of time steps in the non-response state.

[0099] According to embodiments of this disclosure, a load reduction threshold is calculated based on the load of the air conditioning cluster / charging pile cluster in the response state and the load of the air conditioning cluster / charging pile cluster in the non-response state. This allows the obtained load reduction threshold to flexibly adapt to the load of the air conditioning cluster / charging pile cluster, making the division of the target quadrant based on the load reduction threshold more reasonable.

[0100] According to embodiments of this disclosure, determining a load reduction threshold and a load rebound threshold based on the load of the air conditioning cluster and the load of the charging pile cluster further includes: for non-response periods, for any time step, determining a second air conditioning load difference between the load of the air conditioning cluster in the response state and the load of the air conditioning cluster in the non-response state; for any time step, determining a second charging pile load difference between the load of the charging pile cluster in the response state and the load of the charging pile cluster in the non-response state; determining the average rebound load of the response period based on the ratio of the second air conditioning load difference and the second charging pile load difference of multiple time steps to the number of time steps; and determining the load rebound threshold based on the average rebound load of the response period and the total load in the non-response state.

[0101] The average load reduction during non-response periods can be calculated using formula (4).

[0102] (4).

[0103] The average load reduction during the response period is: , The second air conditioning load difference / the second charging pile load difference at any time step. Let the load of the air conditioning cluster in the response state at any time step be the load of the charging pile cluster in the response state. The load of the air conditioning cluster in a non-responsive state / the load of the charging pile cluster in a non-responsive state. This represents the number of time steps.

[0104] After determining the average load reduction during the response period, the total load under non-response conditions is obtained to determine the load reduction threshold using formula (5).

[0105] (5).

[0106] in, The load reduction threshold, It is the ratio of the total load to the number of time steps in the non-response state.

[0107] According to embodiments of this disclosure, a load rebound threshold is calculated based on the load of the air conditioning cluster / charging pile cluster in the response state and the load of the air conditioning cluster / charging pile cluster in the non-response state. This allows the obtained load rebound threshold to flexibly adapt to the load of the air conditioning cluster / charging pile cluster, making the division of the target quadrant based on the load rebound threshold more reasonable.

[0108] According to embodiments of this disclosure, the method further includes: dividing the response time period into batches to obtain multiple response batches when performing flexible resource regulation on the air conditioning cluster, wherein there is a time step between each two response batches; and performing flexible resource regulation on different air conditioners in different response batches based on the different response batches.

[0109] For any given response batch, set up pre-conditioning, response, and reversal phases. Each phase must have at least one time step. For example, under each response batch, the pre-conditioning and reversal phases each contain one time step, and the response phase contains four time steps. The length of each time step can be set to 15 minutes, or it can be adjusted according to actual needs.

[0110] When implementing flexible resource control for air conditioning clusters, at least one air conditioner is subject to flexible resource control in each batch, and different air conditioners are subject to flexible resource control in different batches.

[0111] According to embodiments of this disclosure, flexible resource regulation is performed on different air conditioners in different response batches, thereby achieving load balancing when the flexible resource regulation terminal performs flexible resource regulation. At the same time, different flexible regulation strategies for different air conditioners can be used to provide differentiated supply based on different response batches.

[0112] According to embodiments of this disclosure, the matrix elements in the charge / discharge power matrix represent the charge / discharge power of different charging piles at different time steps during a specified period; wherein, the method further includes: when constructing the charge / discharge power matrix of a charging pile cluster in a specified area, collecting the charge / discharge power that meets the constraints; wherein, the constraints include that the charge / discharge power is within the rated charge / discharge power range of the charging pile.

[0113] The charge / discharge power matrix can be represented as ,in, The charging or discharging power of the i-th (1≤i≤m) electric vehicle at the j-th (1≤j≤n) time step based on the i-th charging pile is expressed in kW. It is a positive value when charging and a negative value when discharging.

[0114] The constraints include the charging and discharging power being within the rated charging and discharging power range of the charging station, for example... ,in, and The rated charging and discharging power of the charging pile. The charging and discharging power of each charging station.

[0115] The constraints also include ,in, The elements of the charge / discharge power matrix, when not connected It is 0.

[0116] Furthermore, when implementing flexible resource management for charging stations, it is necessary to constrain the total net charging and discharging energy supplied by the charging stations to electric vehicles, for example... ,in, The length of a time step, in hours (h). The charging and discharging power of the i-th (1≤i≤m) electric vehicle at the j-th (1≤j≤n) time step based on the i-th charging pile is expressed in kW. The total amount of electricity charged and discharged by the i-th (1≤i≤m) electric vehicle based on the i-th charging pile during the entire response period (n time steps), in kWh; and Let represent the minimum and maximum charging amounts for the i-th electric vehicle, in kWh.

[0117] According to embodiments of this disclosure, by constraining the charging and discharging power of the charging pile, the rationality and stability of the charging and discharging power are improved.

[0118] According to embodiments of this disclosure, the flexible resource control terminal acquires the changes in electricity consumption of air conditioning clusters and the user cost-benefit losses of users associated with air conditioning in a designated area to determine the electricity efficiency of air conditioning. Based on this electricity efficiency, an air conditioning load curve is determined, and subsequently, a two-dimensional response state point set for the air conditioning cluster is determined based on the air conditioning load curve. The flexible resource control terminal acquires the charging and discharging power matrix of charging pile clusters in a designated area. Based on the charging and discharging power of the charging pile clusters, the load of the charging pile clusters is analyzed, thereby determining a two-dimensional response state point set for the charging pile clusters. Further, the flexible resource control terminal performs convex hull calculations on both the air conditioning and charging pile two-dimensional response state point sets to obtain air conditioning convex hull data and charging pile convex hull data. The air conditioning and charging pile convex hull data are then fused to obtain fused convex hull data. This allows for the division of the two-dimensional coordinate system indicated by the fused convex hull data, resulting in a comprehensive two-dimensional response state point set for the air conditioning and charging pile clusters. Based on this comprehensive two-dimensional response state point set, a flexible control strategy for the air conditioning and charging pile clusters in the designated area is determined.

[0119] Figure 3 A comparison diagram of flexible control strategies according to embodiments of the present disclosure is shown.

[0120] The embodiments of this disclosure use actual operational data from an industrial park comprising four typical office buildings and 44 electric vehicle charging piles (including five 60kW piles, nine 21kW piles, and thirty 7kW piles) for verification. Figure 3As shown, experimental results indicate that while the traditional single-air conditioning centralized response strategy (HVAC_CR) can achieve a 39.0% load reduction, it also triggers a 34.8% load rebound after the response ends, seriously threatening the stability of the power grid. In contrast, by applying the method disclosed in this invention, all flexible control strategies can successfully control the rebound rate below 20%, and the peak shaving capacity is significantly improved. This invention, through the heterogeneous resource aggregation and optimization of air conditioning and electric vehicles, can effectively overcome the regulation bottleneck of a single resource while flexibly adapting to the differentiated energy needs of users, achieving a dual improvement in peak shaving capacity and load rebound suppression.

[0121] Based on the aforementioned flexible control method for air conditioning and charging pile clusters involving rebound, this disclosure also provides a flexible control device for air conditioning and charging pile clusters involving rebound. The following will be combined with... Figure 4 The device is described in detail.

[0122] Figure 4 A structural block diagram of a flexible control device for air conditioning and charging pile clusters involving rebound, according to an embodiment of the present disclosure, is shown.

[0123] like Figure 4 As shown, the flexible control device 400 for air conditioning and charging pile clusters involving rebound in this embodiment includes a first determining module 410, a second determining module 420, a third determining module 430, a first extracting module 440, and a first adjusting module 450.

[0124] The first determining module 410 is used to determine the two-dimensional response state point set of the air conditioning cluster based on the air conditioning load curve of the air conditioning cluster in a specified area. The two-dimensional response state point set represents the air conditioning load reduction of the air conditioning cluster during the response period and the air conditioning load rebound during the non-response period, and is used by the flexible resource control terminal of the specified area to supply energy to the air conditioning cluster and the charging pile cluster. In one embodiment, the first determining module 410 can be used to perform the operation S210 described above, which will not be repeated here.

[0125] The second determining module 420 is used to determine the two-dimensional response state point set of the charging piles in the charging pile cluster based on the charging and discharging power matrix of the charging pile cluster in the specified area. The two-dimensional response state point set of the charging piles represents the charging pile load reduction during the response period and the charging pile load rebound during the non-response period. In one embodiment, the second determining module 420 can be used to perform the operation S220 described above, which will not be repeated here.

[0126] The third determining module 430 is used to determine the comprehensive two-dimensional response state point set of the air conditioning cluster and the charging pile cluster based on the convex hull data of their respective two-dimensional response state point sets. In one embodiment, the third determining module 430 can be used to perform the operation S230 described above, which will not be repeated here.

[0127] The first extraction module 440 is used to extract at least one target state point from the set of integrated two-dimensional response state points, wherein the integrated load reduction indicated by the target state point is greater than a preset reduction threshold and the integrated load rebound is less than a preset rebound threshold. In one embodiment, the first extraction module 440 may be used to perform the operation S240 described above, which will not be repeated here.

[0128] The first adjustment module 450 is used to adjust the flexible control strategy of the air conditioning cluster and charging pile cluster in a specified area based on the air conditioning data and charging pile data indicated by at least one target state point. In one embodiment, the first adjustment module 450 can be used to perform the operation S250 described above, which will not be repeated here.

[0129] According to embodiments of this disclosure, a two-dimensional response state point set for the air conditioning cluster is determined based on the air conditioning load curve of the air conditioning cluster in a specified area; a two-dimensional response state point set for the charging pile cluster is determined based on the charging and discharging power matrix of the charging pile cluster in the specified area; a comprehensive two-dimensional response state point set for the air conditioning cluster and the charging pile cluster is determined based on the convex hull data of their respective two-dimensional response state point sets; at least one target state point is extracted from the comprehensive two-dimensional response state point set; and a flexible control strategy for the air conditioning cluster and the charging pile cluster in the specified area is adjusted based on the air conditioning data and charging pile data indicated by the at least one target state point. By utilizing the air conditioning load curve of the air conditioning cluster to determine the two-dimensional response state point set of the air conditioning cluster, it is possible to analyze the load change of the air conditioning cluster with temperature at different time steps. Similarly, by utilizing the charging and discharging power matrix to determine the two-dimensional response state point set of the charging pile cluster, it is possible to analyze the load change of the charging pile cluster with charging and discharging power at different time steps. Furthermore, by merging the two-dimensional response state point sets of the air conditioning and charging piles, a comprehensive analysis can be performed. This allows for maximizing the load reduction of both air conditioning and charging piles while minimizing load rebound, achieving coordinated control of the air conditioning and charging pile clusters by the flexible resource control terminal. This avoids overload issues for both air conditioning and charging piles when responding to flexible resource control, thereby improving operational stability.

[0130] According to embodiments of this disclosure, the first determining module 410 includes a first determining submodule, a second determining submodule, a first constructing submodule, and a third determining submodule.

[0131] The first determination submodule is used to determine the power efficiency of an air conditioner for any time step within a specified period and for any air conditioner in the air conditioning cluster, based on the changes in the power consumption of the air conditioner and the user cost-benefit loss of the users associated with the air conditioner.

[0132] The second determination submodule is used to determine multiple target power consumption benefits for any air conditioner in the air conditioning cluster based on the particle swarm optimization algorithm from the power consumption benefits of each time step within a specified period. The multiple target power consumption benefits include the target power consumption benefits of the air conditioner during the response period and the power consumption benefits during non-response periods.

[0133] The first construction submodule is used to process multiple target power consumption benefits for any air conditioner in the air conditioning cluster using the target model, and construct the air conditioning load curve.

[0134] The third determining submodule is used to determine the set of two-dimensional response state points of the air conditioning cluster based on the individual air conditioning load curves of the multiple air conditioners in the air conditioning cluster.

[0135] According to embodiments of this disclosure, the first construction submodule includes a first construction unit, a first obtaining unit, and a first determining unit.

[0136] The first building unit is used to construct the temperature change curve of the air conditioner based on multiple air conditioner temperature data indicated by multiple target electricity efficiency indicators.

[0137] The first unit is used to process the temperature change curve using the target model to obtain the air conditioning load curve.

[0138] The first determining unit is used to determine the air conditioning load curve based on multiple air conditioning load curves of the air conditioning cluster.

[0139] According to embodiments of this disclosure, the third determining module 430 includes a first calculation submodule, a first fusion submodule, and a fourth determining submodule.

[0140] The first calculation submodule is used to perform convex hull calculations on the two-dimensional response state point set of the air conditioner and the two-dimensional response state point set of the charging pile, respectively, to obtain the convex hull data of the air conditioner two-dimensional response state point set and the convex hull data of the charging pile two-dimensional response state point set.

[0141] The first fusion submodule is used to fuse the air conditioner convex hull data and the charging pile convex hull data to obtain fused convex hull data.

[0142] The fourth determination submodule is used to determine the comprehensive two-dimensional response state point set of the air conditioning cluster and the charging pile cluster from the two-dimensional coordinate system indicated by the fused convex hull data.

[0143] According to embodiments of this disclosure, the fourth determining submodule includes a second determining unit, a third determining unit, a first dividing unit, and a second constructing unit.

[0144] The second determining unit is used to determine the target quadrant from the two-dimensional coordinate system.

[0145] The third determining unit is used to determine the load reduction threshold and the load rebound threshold based on the load of the air conditioning cluster and the load of the charging pile cluster.

[0146] The first division unit is used to divide the target quadrant using the load reduction threshold and the load rebound threshold to obtain the target quadrant region.

[0147] The second building unit is used to construct a comprehensive two-dimensional response state point set for the air conditioning cluster and the charging pile cluster based on the two-dimensional response state points indicated by the target quadrant region.

[0148] According to embodiments of this disclosure, the first division unit includes a first determining subunit, a second determining subunit, a third determining subunit, and a fourth determining subunit.

[0149] The first determining subunit is used to determine, for any time step during the response period, the first air conditioning load difference between the load of the air conditioning cluster in the response state and the load of the air conditioning cluster in the non-response state.

[0150] The second determining subunit is used to determine, for any given time step, a first charging pile load difference between the load of the charging pile cluster in the response state and the load of the charging pile cluster in the non-response state.

[0151] The third determining subunit is used to determine the average load reduction during the response period based on the ratio of the first air conditioning load difference and the first charging pile load difference to the number of time steps.

[0152] The fourth determining sub-unit is used to determine the load reduction threshold based on the average load reduction during the response period and the total load under non-response conditions.

[0153] According to embodiments of this disclosure, the first division unit further includes a fifth determining subunit, a sixth determining subunit, a seventh determining subunit, and an eighth determining subunit.

[0154] The fifth determining subunit is used to determine, for any time step during the non-response period, the second air conditioning load difference between the load of the air conditioning cluster in the response state and the load of the air conditioning cluster in the non-response state.

[0155] The sixth determining subunit is used to determine, for any given time step, the second charging pile load difference between the load of the charging pile cluster in the response state and the load of the charging pile cluster in the non-response state.

[0156] The seventh determining subunit is used to determine the average rebound load during the response period based on the ratio of the second air conditioning load difference and the second charging pile load difference to the number of time steps.

[0157] The eighth determining subunit is used to determine the load rebound threshold based on the average rebound load during the response period and the total load under non-response conditions.

[0158] According to embodiments of this disclosure, the flexible control device 400 for air conditioning and charging pile clusters involving rebound also includes a first division module and a first supply module.

[0159] The first partitioning module is used to partition the response time period into multiple response batches when flexibly controlling the resources of the air conditioning cluster. Each two response batches are separated by a time step.

[0160] The first supply module is used to flexibly adjust resources to different air conditioners within different response batches.

[0161] According to embodiments of this disclosure, the flexible control device 400 for air conditioning and charging pile clusters involving rebound also includes a first acquisition module.

[0162] The first acquisition module is used to acquire the charging and discharging power that meets the constraints when constructing the charging and discharging power matrix of the charging pile cluster in a specified area; wherein, the constraints include that the charging and discharging power is within the rated charging and discharging power range of the charging pile.

[0163] According to embodiments of this disclosure, any plurality of modules among the first determining module 410, the second determining module 420, the third determining module 430, the first extraction module 440, and the first adjusting module 450 may be combined into one module, or any one of these modules may be split into multiple modules. Alternatively, at least part of the functionality of one or more of these modules may be combined with at least part of the functionality of other modules and implemented in one module. According to embodiments of this disclosure, at least one of the first determining module 410, the second determining module 420, the third determining module 430, the first extraction module 440, and the first adjusting module 450 may be at least partially implemented as hardware circuitry, such as a field-programmable gate array (FPGA), a programmable logic array (PLA), a system-on-a-chip, a system-on-a-substrate, a system-on-package, an application-specific integrated circuit (ASIC), or implemented in hardware or firmware by any other reasonable means of integrating or packaging the circuitry, or implemented in any one of the three implementation methods of software, hardware, and firmware, or in a suitable combination of any of these. Alternatively, at least one of the first determining module 410, the second determining module 420, the third determining module 430, the first extracting module 440, and the first adjusting module 450 may be at least partially implemented as a computer program module, which can perform corresponding functions when the computer program module is run.

[0164] Figure 5A block diagram of an electronic device suitable for implementing a flexible control method for air conditioning and charging pile clusters involving rebound, according to an embodiment of the present disclosure, is shown.

[0165] like Figure 5 As shown, an electronic device 500 according to an embodiment of the present disclosure includes a processor 501, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 502 or a program loaded from a storage portion 508 into a random access memory (RAM) 503. The processor 501 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or an associated chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 501 may also include onboard memory for caching purposes. The processor 501 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present disclosure.

[0166] RAM 503 stores various programs and data required for the operation of electronic device 500. Processor 501, ROM 502, and RAM 503 are interconnected via bus 504. Processor 501 performs various operations of the method flow according to embodiments of the present disclosure by executing programs in ROM 502 and / or RAM 503. It should be noted that the programs may also be stored in one or more memories other than ROM 502 and RAM 503. Processor 501 may also perform various operations of the method flow according to embodiments of the present disclosure by executing programs stored in said one or more memories.

[0167] According to embodiments of this disclosure, the electronic device 500 may further include an input / output (I / O) interface 505, which is also connected to a bus 504. The electronic device 500 may also include one or more of the following components connected to the I / O interface 505: an input section 506 including a keyboard, mouse, etc.; an output section 507 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 508 including a hard disk, etc.; and a communication section 509 including a network interface card such as a LAN card, modem, etc. The communication section 509 performs communication processing via a network such as the Internet. A drive 510 is also connected to the I / O interface 505 as needed. A removable medium 511, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on the drive 510 as needed so that computer programs read from it can be installed into the storage section 508 as needed.

[0168] This disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or it may exist independently and not assembled into the device / apparatus / system. The computer-readable storage medium carries one or more programs that, when executed, implement the method according to the embodiments of this disclosure.

[0169] According to embodiments of this disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium, such as including, but not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this disclosure, the computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. For example, according to embodiments of this disclosure, the computer-readable storage medium may include ROM 502 and / or RAM 503 and / or one or more memories other than ROM 502 and RAM 503 described above.

[0170] Embodiments of this disclosure also include a computer program product comprising a computer program containing program code for performing the methods shown in the flowchart. When the computer program product is run on a computer system, the program code is used to enable the computer system to implement the flexible control method for air conditioning and charging pile clusters involving rebound provided in embodiments of this disclosure.

[0171] When the computer program is executed by the processor 501, it performs the functions defined in the system / apparatus of this disclosure embodiments. According to embodiments of this disclosure, the systems, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0172] In one embodiment, the computer program may rely on a tangible storage medium such as an optical storage device or a magnetic storage device. In another embodiment, the computer program may also be transmitted and distributed in the form of signals over a network medium, and may be downloaded and installed via the communication section 509, and / or installed from a removable medium 511. The program code contained in the computer program can be transmitted using any suitable network medium, including but not limited to: wireless, wired, etc., or any suitable combination thereof.

[0173] In such an embodiment, the computer program can be downloaded and installed from a network via communication section 509, and / or installed from removable medium 511. When the computer program is executed by processor 501, it performs the functions defined in the system of this disclosure embodiment. According to embodiments of this disclosure, the systems, devices, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0174] According to embodiments of this disclosure, program code for executing the computer programs provided in embodiments of this disclosure can be written in any combination of one or more programming languages. Specifically, these computational programs can be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, languages ​​such as Java, C++, Python, "C", or similar programming languages. The program code can execute entirely on a user's computing device, partially on a user's device, partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0175] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0176] Those skilled in the art will understand that the features described in the various embodiments and / or claims of this disclosure can be combined or combined in various ways, even if such combinations or combinations are not explicitly described in this disclosure. In particular, the features described in the various embodiments and / or claims of this disclosure can be combined or combined in various ways without departing from the spirit and teachings of this disclosure. All such combinations and / or combinations fall within the scope of this disclosure.

[0177] The embodiments of this disclosure have been described above. However, these embodiments are for illustrative purposes only and are not intended to limit the scope of this disclosure. Although various embodiments have been described above, this does not mean that the measures in the various embodiments cannot be used advantageously in combination. The scope of this disclosure is defined by the appended claims and their equivalents. Various substitutions and modifications can be made by those skilled in the art without departing from the scope of this disclosure, and all such substitutions and modifications should fall within the scope of this disclosure.

Claims

1. A method for flexible regulation of air conditioning and charging pile clusters involving rebounding, characterized in that, The method includes: Based on the air conditioning load curve of the air conditioning cluster in the specified area, the two-dimensional response state point set of the air conditioning cluster is determined. The two-dimensional response state point set of the air conditioning cluster represents the air conditioning load reduction during the response period and the air conditioning load rebound during the non-response period. It is used by the flexible resource control terminal of the specified area to perform flexible control on the air conditioning cluster and the charging pile cluster. Based on the charging and discharging power matrix of the charging pile cluster in the designated area, the two-dimensional response state point set of the charging pile cluster is determined. The two-dimensional response state point set of the charging pile represents the charging pile load reduction during the response period and the charging pile load rebound during the non-response period. Based on the convex hull data of the air conditioner two-dimensional response state point set and the charging pile two-dimensional response state point set respectively, the comprehensive two-dimensional response state point set of the air conditioner cluster and the charging pile cluster is determined. At least one target state point is extracted from the set of integrated two-dimensional response state points, wherein the integrated load reduction indicated by the target state point is greater than a preset reduction threshold and the integrated load rebound is less than a preset rebound threshold. Based on the air conditioning data and charging pile data indicated by the at least one target state point, adjust the flexible control strategy of the air conditioning cluster and charging pile cluster in the designated area.

2. The method of claim 1, wherein, The step of determining the two-dimensional response state point set of the air conditioning cluster based on the air conditioning load curve of the air conditioning cluster in a specified area includes: For any time step within a specified period and for any air conditioner in the air conditioning cluster, the energy efficiency of the air conditioner is determined based on the changes in the energy consumption of the air conditioner and the user cost-benefit loss of the users associated with the air conditioner. For any air conditioner in the air conditioning cluster, based on the particle swarm optimization algorithm, multiple target power consumption benefits are determined from the power consumption benefits of each of the multiple time steps within a specified period. The multiple target power consumption benefits include the target power consumption benefits of the air conditioner in the response period and the power consumption benefits in the non-response period. For any air conditioner in the air conditioning cluster, the target model is used to process multiple target power consumption benefits to construct an air conditioning load curve; Based on the individual air conditioning load curves of multiple air conditioners in the air conditioning cluster, the set of two-dimensional response state points of the air conditioning cluster is determined.

3. The method according to claim 2, characterized in that, The process of using a target model to process multiple target electricity benefits and construct the air conditioning load curve includes: Based on multiple air conditioner temperature data indicating multiple target electricity efficiency indicators, construct the temperature change curve of the air conditioner; The temperature change curve is processed using the target model to obtain the air conditioning load curve of the air conditioner; The air conditioning load curve is determined based on multiple air conditioning load curves of the air conditioning cluster.

4. The method according to claim 1, characterized in that, The step of determining the comprehensive two-dimensional response state point set of the air conditioning cluster and the charging pile cluster based on the convex hull data of the respective two-dimensional response state point sets of the air conditioners and the charging piles includes: Convex hull calculations are performed on the two-dimensional response state point set of the air conditioner and the two-dimensional response state point set of the charging pile respectively to obtain the air conditioner convex hull data of the two-dimensional response state point set of the air conditioner and the charging pile convex hull data of the two-dimensional response state point set of the charging pile. The air conditioner convex hull data and the charging pile convex hull data are fused to obtain fused convex hull data; Based on the two-dimensional coordinate system indicated by the fused convex hull data, a comprehensive two-dimensional response state point set for the air conditioning cluster and the charging pile cluster is determined from the two-dimensional coordinate system.

5. The method according to claim 4, characterized in that, The step of determining the comprehensive two-dimensional response state point set of the air conditioning cluster and the charging pile cluster from the two-dimensional coordinate system indicated by the fused convex hull data includes: Determine the target quadrant from the two-dimensional coordinate system; Based on the load of the air conditioning cluster and the load of the charging pile cluster, determine the load reduction threshold and the load rebound threshold; The target quadrant is divided using the load reduction threshold and the load rebound threshold to obtain the target quadrant region; Based on the two-dimensional response state points indicated by the target quadrant region, a comprehensive two-dimensional response state point set for the air conditioning cluster and the charging pile cluster is constructed.

6. The method according to claim 5, characterized in that, The step of determining the load reduction threshold and the load rebound threshold based on the load of the air conditioning cluster and the load of the charging pile cluster includes: Regarding the response period, For any given time step, determine a first air conditioning load difference between the load of the air conditioning cluster in the response state and the load of the air conditioning cluster in the non-response state. For any given time step, determine a first charging pile load difference between the load of the charging pile cluster in the response state and the load of the charging pile cluster in the non-response state. The average load reduction during the response period is determined based on the ratio of the first air conditioning load difference and the first charging pile load difference to the number of time steps across multiple time steps. The load reduction threshold is determined based on the average load reduction during the response period and the total load under non-response conditions.

7. The method according to claim 6, characterized in that, The step of determining the load reduction threshold and the load rebound threshold based on the load of the air conditioning cluster and the load of the charging pile cluster further includes: For non-response periods, For any given time step, determine a second air conditioning load difference between the load of the air conditioning cluster in the response state and the load of the air conditioning cluster in the non-response state; For any given time step, determine a second charging pile load difference between the load of the charging pile cluster in the response state and the load of the charging pile cluster in the non-response state. The average rebound load during the response period is determined by the ratio of the second air conditioning load difference and the second charging pile load difference to the number of time steps. The load rebound threshold is determined based on the average rebound load during the response period and the total load under non-response conditions.

8. The method according to claim 1, characterized in that, The method further includes: In the case of flexible control of the air conditioning cluster, the response time period is divided into batches to obtain multiple response batches, wherein there is a time step between each two response batches; Based on different response batches, flexible control is applied to different air conditioners within each response batch.

9. The method according to any one of claims 1-8, characterized in that, The matrix elements in the charging and discharging power matrix represent the charging and discharging power of different charging piles at different time steps during a specified period. The method further includes: When constructing the charging and discharging power matrix of the charging pile cluster in a specified area, the charging and discharging power that meets the constraints is collected. The constraints include that the charging and discharging power is within the rated charging and discharging power range of the charging pile.

10. A flexible control device for air conditioning and charging pile clusters involving rebound, characterized in that, The device includes: The first determining module is used to determine the two-dimensional response state point set of the air conditioning cluster based on the air conditioning load curve of the air conditioning cluster in a specified area. The two-dimensional response state point set represents the air conditioning load reduction of the air conditioning cluster during the response period and the air conditioning load rebound during the non-response period. It is used by the flexible resource control terminal of the specified area to perform flexible control on the air conditioning cluster and the charging pile cluster. The second determining module is used to determine the two-dimensional response state point set of the charging pile cluster based on the charging and discharging power matrix of the charging pile cluster in the specified area. The two-dimensional response state point set of the charging pile represents the charging pile load reduction amount during the response period and the charging pile load rebound amount during the non-response period. The third determining module is used to determine the comprehensive two-dimensional response state point set of the air conditioning cluster and the charging pile cluster based on the convex hull data of the air conditioning two-dimensional response state point set and the charging pile two-dimensional response state point set, respectively. A first extraction module is configured to extract at least one target state point from the integrated two-dimensional response state point set, wherein the target state point indicates an integrated load reduction amount greater than a preset reduction amount threshold and an integrated load rebound amount less than a preset rebound amount threshold; and The first adjustment module is used to adjust the flexible control strategy of the air conditioning cluster and charging pile cluster in the specified area based on the air conditioning data and charging pile data indicated by the at least one target state point.

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