A method and system for evaluating adjustable potential of an electrical load

Abstract

The present application belongs to the technical field of power system electricity utilization, and discloses a kind of electricity utilization load adjustable potential evaluation method and system, including obtaining the operation state data formed in the process of grid-connected operation and regulation of electricity utilization load, and time alignment and state organization are carried out to operation state data, and the time sequence state data set representing the regulation behavior of electricity utilization load is constructed;Based on the time sequence state data set, the power change process of electricity utilization load after receiving the regulation instruction is analyzed, the key time sequence characteristics of load power entering the regulation target allowable interval are identified, and the corresponding regulation response state segment is extracted;After the load power reaches the regulation target allowable interval, the power maintaining state of electricity utilization load is continuously monitored according to the regulation response state segment, the effective response time interval that the load power continuously maintains in the preset target allowable deviation range is determined, and the corresponding persistence evaluation index is generated;The accuracy and stability of the regulation potential evaluation result to the actual regulation behavior are improved.

Description

Technical Field

[0001] This invention relates to the field of power system electricity technology, and more specifically, to a method and system for assessing the adjustability potential of electricity load. Background Technology

[0002] Existing methods and systems for assessing the adjustability potential of electricity load have the following main problems:

[0003] With the increasing proportion of renewable energy connected to the power system and the gradual promotion of applications such as demand response and load-side regulation, the importance of electricity load as a flexible adjustment resource of the power system is becoming increasingly prominent. How to accurately assess the adjustability potential of electricity load under grid-connected operation conditions has become a key technical issue in grid dispatching, load aggregation, and demand response control.

[0004] Existing methods and systems for assessing the adjustability potential of electrical loads largely rely on fixed dead zone ratios or standardized test specifications to determine whether the load can reach a preset target power. These methods typically focus on the static assessment of adjustment results, making it difficult to accurately depict the actual dynamic response process of the load after receiving adjustment commands. Key dynamic characteristics exhibited during load response, such as response delay and power change rate, lack systematic and quantifiable calculation methods, resulting in inaccurate assessment results reflecting the actual load adjustment capability. Furthermore, existing technologies often neglect important characteristics such as overshoot, steady-state deviation, and the magnitude of dynamic power changes during power changes, particularly lacking the ability to identify the time it takes for the load to first enter the allowable adjustment target range, leading to a coarse-grained analysis of load response speed and adjustment capability.

[0005] Furthermore, existing technologies typically only determine whether the load has reached the target power or is in a stable state, failing to quantify the duration for which the load power is maintained within the target allowable range, making it difficult to accurately evaluate the continued availability after load regulation. In practical applications, there is a significant difference in dispatch value between instantaneously reaching the target power and maintaining the target power stably over a long period, but traditional methods often conflate the two. Existing methods mostly rely on empirical judgment or fixed thresholds for stability analysis, lacking a systematic scanning mechanism for the load power change over time, making it difficult to distinguish between short-term target achievement and sustained stability. Simultaneously, existing technologies usually only focus on the power change itself, ignoring changes in electrical parameters such as load-side voltage, current, power factor, and grid frequency during the regulation process, failing to form a comprehensive evaluation index reflecting the sustainability of load regulation and the impact on grid-connected operation, resulting in somewhat biased evaluation results.

[0006] Existing methods for assessing regulation accuracy typically calculate the deviation between the actual output power and the target power of the load at a fixed moment or a few sampling points. This is easily affected by instantaneous fluctuations, measurement noise, or short-term disturbances, leading to significant randomness in the assessment results and making it difficult to accurately reflect the load's accuracy level throughout the entire regulation execution phase. Furthermore, some methods fail to conduct accuracy assessments after the load has completed its regulation response and entered a stable operating phase, easily incorporating transient deviations during the regulation process into the accuracy analysis, thus affecting the accuracy of the assessment results. In addition, existing technologies often ignore the cumulative effect of power deviations over time, failing to reflect the load's overall performance throughout the entire stable regulation time interval, which is detrimental to judging the reliability and actual availability of the load's regulation capabilities.

[0007] In view of this, the present invention proposes a method for assessing the adjustable potential of electrical load to solve the above problems. Summary of the Invention

[0008] To overcome the aforementioned deficiencies of the prior art and to achieve the above objectives, the present invention provides the following technical solution: a method for assessing the adjustable potential of electrical load, comprising:

[0009] S1. Obtain the operating status data of the power load during grid-connected operation and regulation, and perform time alignment and state organization on the operating status data to construct a time-series state dataset that characterizes the regulation behavior of the power load.

[0010] S2. Based on the time-series state dataset, analyze the power change process of the electrical load after receiving the regulation command, identify the key time-series features of the load power entering the allowable range of the regulation target, and extract the corresponding regulation response state segments.

[0011] S3. After the load power reaches the allowable range of the adjustment target, continuously monitor the power maintenance status of the power load according to the adjustment response state segment, determine the effective response time interval for the load power to be continuously maintained within the preset target allowable deviation range, and generate the corresponding continuous evaluation index.

[0012] S4. Within the effective response time interval, calculate the degree of deviation between the actual output power and the corresponding target power of the power load during the adjustment process, and construct a relative deviation evaluation index that reflects the accuracy of load adjustment.

[0013] S5. Based on the regulation response state segments and relative deviation evaluation indicators, analyze the regulation capability of the power load under the preset regulation scenario while meeting the grid connection operation constraints, and generate the corresponding adjustable potential evaluation results.

[0014] Preferably, the method for acquiring the operating status data includes:

[0015] During the operation of the power system, the electrical load is connected to the distribution network or the main power grid through the access point and is in a grid-connected operation state that is monitored and regulated by the power system. During the process of issuing and executing adjustment commands by the grid dispatch terminal, load aggregation platform or user-side load control terminal, the operation status data formed by the electrical load in the grid-connected operation state and in the process of executing adjustment commands are obtained through the operation monitoring interface set on the load side, aggregation side or grid side.

[0016] The operating status data includes the actual output power data of the electrical load and the corresponding time stamp information, as well as the initial operating status data obtained before the regulation command is issued, the power change status data obtained during the execution of the regulation command, the stable operating status data obtained during the period when the load reaches the regulation target and maintains the regulation status, and the recovery status data of the load recovery operation phase obtained after the regulation ends or the regulation is withdrawn.

[0017] Preferably, the method for obtaining the time-series state dataset includes:

[0018] By synchronously collecting timestamps or interpolating asynchronously collected data, the initial operating status data, power change status data, stable operating status data, and recovery status data in the operating status data are time-aligned according to their respective time identifiers to unify the time base.

[0019] The time-aligned operational status data is organized into status categories, and each type of data is logically classified according to the order of load adjustment. Each type of status data is assigned a status type, start time, end time, and duration.

[0020] The time-aligned operational status data is transformed into corresponding structured status data through state organization. After completing time alignment and state organization, the structured status data is combined in chronological order and subjected to missing value imputation, outlier removal, and noise smoothing to construct a time-series status dataset that characterizes the power load regulation behavior.

[0021] Preferably, the method for identifying the key temporal features includes:

[0022] Based on the time-series state dataset, the power change process of the electrical load after receiving the adjustment command is analyzed to determine the trigger time of the adjustment command. The target power and the allowable deviation of the target power corresponding to the adjustment command are preset. According to the target power and the allowable deviation of the target power corresponding to the adjustment command, the allowable range of the adjustment target is defined as the range in which the difference between the load power and the target power is within the allowable deviation range.

[0023] Identify the time when the load first enters the allowable range of the regulation target from the time-series state dataset, and obtain the average regulation rate of the load regulation process based on the change of load power before and after entering the allowable range of the regulation target for the first time;

[0024] The load response speed under the regulation command is quantified by the average regulation rate. The load response speed is characterized by the time when the load first reaches the allowable range of the regulation target. Key timing features for identifying the load power entering the allowable range of the regulation target are extracted. Key timing features include power change amplitude, power change rate, response delay, overshoot, and steady-state deviation.

[0025] Preferably, the method for extracting the corresponding adjustment response state segment includes:

[0026] The structured time-series data from the moment the regulation command is triggered until the load first reaches the allowable range of the regulation target is defined as regulation response state segments. Each regulation response state segment includes the start time, end time, load power at each time point, and related electrical parameter information.

[0027] Preferably, the method for generating the corresponding sustainability evaluation index includes:

[0028] After the load power reaches the allowable range of the regulation target, the starting time when the load reaches the target allowable range is determined. The load power within the allowable deviation range is considered to be maintained within the allowable range of the regulation target. The data of load power change over time recorded in the regulation response state segment are scanned to identify the time interval in which the load is continuously maintained within the allowable range of the regulation target, and this time interval is defined as the effective response time interval.

[0029] By using the set supremum method, the longest time that the load power is maintained within the effective response time interval is obtained, thus forming a response duration index. Within the effective response time interval, the load power and related electrical parameter information are continuously monitored, and the power deviation range, power fluctuation and electrical parameter changes are statistically analyzed, thereby generating a continuous evaluation index to characterize the load regulation continuous performance.

[0030] Preferably, the method for obtaining the relative deviation evaluation index includes:

[0031] After determining that the load power is continuously maintained within the allowable range of the regulation target and an effective response time range is formed, the effective response time range is used as the evaluation time range for regulation accuracy. Within this evaluation time range, the actual output power of the electrical load at each moment is continuously acquired, and the target power at the corresponding moment is acquired simultaneously.

[0032] Based on the power data within the observation time interval, the deviation between the actual output power of the power load and the corresponding target power at each moment is calculated, and the deviation is normalized relative to the corresponding adjustment target power to obtain the normalized power deviation.

[0033] The normalized power deviation at each moment within the observation time interval is accumulated over time and averaged according to the length of the observation time interval to obtain a relative deviation evaluation index characterizing the adjustment execution accuracy of the power load throughout the entire effective response time interval.

[0034] Preferably, the method for generating the corresponding adjustable potential assessment result includes:

[0035] After obtaining the regulation response state segments and corresponding relative deviation evaluation indicators formed by the power load under the preset regulation scenario, the regulation response state segments are used as the basic data carrier to characterize the state evolution of the entire load regulation process.

[0036] Within the time range corresponding to the regulation response state segment, grid-connected operation constraints are introduced to perform constraint consistency analysis on the power changes, electrical parameter changes and operating state changes involved in the regulation process of the power load, so as to determine whether the regulation response process meets the grid-connected safety and stability requirements.

[0037] Under the premise of satisfying grid-connected operation constraints, key feature parameters for characterizing the regulation capability are extracted for each regulation response state segment. The key feature parameters include the regulation entry time of the load from the issuance of the regulation command to the entry into the target regulation state and the regulation duration of the load in maintaining the regulation state under the premise of satisfying grid-connected operation constraints.

[0038] The adjustment capability of the power load under the preset adjustment scenario is analyzed. The adjustment entry time, adjustment duration and relative deviation evaluation index are processed with unified dimensions and correlated according to the preset fusion rules to generate the corresponding adjustment potential evaluation results.

[0039] Preferably, the grid-connected operation constraints include maintaining the voltage within a preset allowable voltage range during power regulation, and being less than a preset upper voltage threshold and greater than or equal to a preset lower voltage threshold; the deviation of the grid's operating frequency relative to the grid's nominal frequency at the load connection point being less than a preset deviation threshold; and the load's power factor satisfying a preset power factor threshold during regulation.

[0040] A system for assessing the adjustable potential of electrical load, comprising:

[0041] The regulation status sensing module is used to acquire the operation status data of the power load during grid-connected operation and regulation, and to perform time alignment and status organization on the operation status data to construct a time-series status dataset that characterizes the regulation behavior of the power load.

[0042] The load regulation response module is used to analyze the power change process of the electrical load after receiving the regulation command based on the time-series state dataset, identify the key time-series features of the load power entering the allowable range of the regulation target, and extract the corresponding regulation response state segments.

[0043] The load regulation assessment module is used to continuously monitor the power maintenance status of the electrical load based on the regulation response state segment after the load power reaches the allowable range of the regulation target, determine the effective response time interval for the load power to be continuously maintained within the preset target allowable deviation range, and generate the corresponding continuous assessment index.

[0044] The adjustment deviation assessment module is used to calculate the degree of deviation between the actual output power and the corresponding target power of the power load during the adjustment process within the effective response time interval, and to construct a relative deviation assessment index that reflects the accuracy of load adjustment.

[0045] The adjustable potential assessment module is used to analyze the adjustment capability of the power load under preset adjustment scenarios based on the adjustment response state segments and relative deviation assessment indicators, while meeting the grid-connected operation constraints, and generate corresponding adjustable potential assessment results.

[0046] Compared with the prior art, the present invention has the following beneficial effects:

[0047] This invention accurately characterizes the dynamic response speed of a load after receiving a regulation command by using the average regulation rate and the time to first enter the target allowable range, without relying on a fixed dead zone ratio or specific test specifications. It systematically identifies key timing characteristics such as power change amplitude, power change rate, response delay, overshoot, and steady-state deviation, making load regulation behavior quantifiable and comparable. It comprehensively reflects the dynamic characteristics of the load during the regulation process, providing more refined data support for regulation capability assessment.

[0048] By utilizing the effective response time interval and supremacy calculation, a load response duration index is obtained, upgrading the duration from an empirical description to a calculable quantitative indicator. This clearly characterizes the continuous maintenance capability of load power after initially reaching the target range, improving assessment accuracy. By combining the time of first entering the target allowable range with the response duration, the completion time of load regulation and stability maintenance capability are clearly defined, solving the problem of unclear availability despite response completion in existing technologies. Continuous monitoring of power and related electrical parameters, statistical analysis of power deviation, power fluctuation, and changes in electrical parameters, generates a comprehensive sustainability assessment index, achieving a comprehensive quantification of load regulation stability and sustainability. Through system scanning and continuous monitoring, the influence of instantaneous fluctuations and anomalies is eliminated, making the sustainability assessment index more accurate and reliable. This provides a scientific data foundation for load regulation potential analysis and adjustability assessment, supporting the optimization of power system dispatch and load management.

[0049] By using the effective response time interval as the evaluation time interval for regulation accuracy, assessments are only conducted during the stable phase when the load power continuously remains within the allowable range of the regulation target, making the evaluation of regulation accuracy more reasonable and objective. By accumulating and averaging the normalized power deviation at each moment within the evaluation time interval, a holistic evaluation of the entire regulation execution process is achieved, avoiding unreasonable amplification of regulation accuracy results by single-point deviations or short-term fluctuations. By normalizing the power deviation relative to the corresponding target power, the relative deviation evaluation index is independent of the absolute power level of the load, thus supporting horizontal comparisons and unified evaluations between different capacities and types of electrical loads. Attached Figure Description

[0050] Figure 1 This is a schematic diagram of a method for assessing the adjustable potential of electrical load according to the present invention.

[0051] Figure 2 This is a schematic diagram of the structure of an adjustable power load potential assessment system according to the present invention. Detailed Implementation

[0052] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0053] Example 1:

[0054] Please see Figure 1 As shown, this embodiment provides a method for assessing the adjustability potential of electrical load, specifically including the following steps:

[0055] S1. Obtain the operating status data of the power load during grid-connected operation and regulation, and perform time alignment and state organization on the operating status data to construct a time-series state dataset that characterizes the regulation behavior of the power load.

[0056] S2. Based on the time-series state dataset, analyze the power change process of the electrical load after receiving the regulation command, identify the key time-series features of the load power entering the allowable range of the regulation target, and extract the corresponding regulation response state segments.

[0057] S3. After the load power reaches the allowable range of the adjustment target, continuously monitor the power maintenance status of the power load according to the adjustment response state segment, determine the effective response time interval for the load power to be continuously maintained within the preset target allowable deviation range, and generate the corresponding continuous evaluation index.

[0058] S4. Within the effective response time interval, calculate the degree of deviation between the actual output power and the corresponding target power of the power load during the adjustment process, and construct a relative deviation evaluation index that reflects the accuracy of load adjustment.

[0059] S5. Based on the regulation response state segments and relative deviation evaluation indicators, analyze the regulation capability of the power load under the preset regulation scenario while meeting the grid connection operation constraints, and generate the corresponding adjustable potential evaluation results.

[0060] Methods for obtaining runtime status data include:

[0061] During the operation of the power system, the electrical load is connected to the distribution network or the main power grid through the access point and is in a grid-connected operation state that is monitored and regulated by the power system. During the process of issuing and executing adjustment commands by the grid dispatch terminal, load aggregation platform or user-side load control terminal, the operation status data formed by the electrical load in the grid-connected operation state and in the process of executing adjustment commands are obtained through the operation monitoring interface set on the load side, aggregation side or grid side.

[0062] The operating status data includes the actual output power data of the electrical load and the corresponding time stamp information, as well as the initial operating status data obtained before the regulation command is issued, the power change status data obtained during the execution of the regulation command, the stable operating status data obtained during the period when the load reaches the regulation target and maintains the regulation status, and the recovery status data of the load recovery operation phase obtained after the regulation ends or the regulation is withdrawn.

[0063] Initial operating status data includes the actual output power of the load, operating voltage, current, frequency, power factor, load type identifier, and corresponding timestamp, which are used to characterize the load's baseline operating condition before regulation; power change status data includes power change amplitude, change rate, response delay, step response characteristics, and corresponding timestamp, which are used to characterize the load's response process to regulation commands.

[0064] Stable operating status data includes short-term fluctuation range of load power, power deviation, output power continuity, frequency stability and duration information, which are used to assess the load's ability to regulate and maintain its position within the target range; recovery status data includes information on the process of load power returning to the baseline state, power recovery curve, recovery time and load operating parameter stability, which are used to assess the recovery characteristics after load regulation and the impact of system backoff.

[0065] It should be noted that the step response characteristic is used to describe the transient process of load power transitioning from an initial value to a target value. It includes indicators such as rise time, overshoot, settling time, and delay time, which can be extracted by continuously acquiring output power and analyzing the power-time curve. Recording power change state data can be used to characterize the load's response speed and accuracy to regulation commands.

[0066] Output power continuity measures the smoothness of the load while maintaining the target power, and can be obtained by calculating the rate of change or standard deviation of continuously sampled power values. Frequency stability characterizes the load's ability to maintain power stability under grid frequency disturbances, and is obtained by synchronously collecting grid frequency and load power and analyzing their correlation. Stable operating state data can assess the load's ability to regulate and maintain power within the target range and its impact on grid stability.

[0067] Load operation parameter stability describes the smoothness with which parameters such as power, voltage, current, and power factor return to baseline values ​​during the recovery process. This can be achieved by continuously collecting data on each parameter and analyzing their time-varying curves to extract recovery time, maximum deviation, and fluctuations. Recovery status data can be used to evaluate performance regression and system reliability after load adjustment.

[0068] Methods for obtaining time-series state datasets include:

[0069] By synchronously collecting timestamps or interpolating asynchronously collected data, the initial operating status data, power change status data, stable operating status data, and recovery status data in the operating status data are time-aligned according to their respective time identifiers to unify the time base.

[0070] The time-aligned operational status data is organized into status categories, and each type of data is logically classified according to the order of load adjustment. Each type of status data is assigned a status type, start time, end time, and duration.

[0071] The time-aligned operational status data is transformed into corresponding structured status data through state organization. After completing time alignment and state organization, the structured status data is combined in chronological order and subjected to missing value imputation, outlier removal, and noise smoothing to construct a time-series status dataset that characterizes the power load regulation behavior.

[0072] Methods for identifying key temporal features include:

[0073] Based on the time-series state dataset, the power change process of the electrical load after receiving the adjustment command is analyzed to determine the trigger time of the adjustment command. The target power and the allowable deviation of the target power corresponding to the adjustment command are preset. According to the target power and the allowable deviation of the target power corresponding to the adjustment command, the allowable range of the adjustment target is defined as the range in which the difference between the load power and the target power is within the allowable deviation range.

[0074] Adjust the target allowable range: ;in, Indicates the load at time. The actual output power; This indicates the target power corresponding to the adjustment command, which is the power value that the load hopes to achieve; This indicates the allowable deviation from the target power, meaning the load power can be within a certain range. Fluctuations within a certain range are still considered to have achieved the target. This represents the absolute deviation between the load power and the target power. An index representing a time point;

[0075] Identify the time when the load first enters the allowable range of the regulation target from the time-series state dataset. The time when the load first enters the allowable range of the regulation target is: ;in, This indicates the time when the load first enters the target allowable range, i.e., when the power first meets the requirement. The moment; This indicates the time when the control command is triggered, which is the moment when the load begins to respond to the control command; This indicates the time value at which the minimum value in the set is taken, i.e., the time when the condition is first met.

[0076] The average regulation rate during the load regulation process is obtained based on the change in load power before and after it first enters the allowable range of the regulation target; the average regulation rate is: ;in, This represents the average adjustment rate, used to quantify the rate of change of load power from its initial value to the allowable range of the adjustment target. This indicates the power value at the moment when the load first reaches the allowable range of the control target; This indicates the power value of the load at the moment the regulation command is triggered; This indicates the time interval from the triggering of the control command to the first entry of the load into the allowable range of the control target; Indicates the absolute magnitude of the power change;

[0077] The load response speed under the regulation command is quantified by the average regulation rate. The load response speed is characterized by the time to first reach the allowable range of the regulation target. Key time-series features for identifying the load power entering the allowable range of the regulation target are extracted. Key time-series features include power change amplitude, power change rate, response delay, overshoot, and steady-state deviation.

[0078] It should be noted that the following terms are used: power change magnitude, which is the total change in load power within the allowable time range of the regulation target; power change rate, which is the average rate of change of power per unit time; response delay, which is the time difference between the start of a significant change in load power and the command triggering time; overshoot, which is the maximum extent by which power exceeds the target power when reaching the allowable range of the regulation target; and steady-state deviation, which is the average deviation or short-term fluctuation range of power after entering the allowable range of the regulation target. By progressively analyzing the power change curve over time and calculating the values ​​of each characteristic, a quantitative description of the dynamic response behavior of the load can be achieved.

[0079] This solution addresses the following technical problems of existing technologies: Traditional methods typically rely on fixed dead-zone ratios or standard test specifications, making it difficult to accurately characterize the true dynamic response characteristics of the load after receiving a regulation command. Key indicators such as response delay and power change rate lack systematic calculation methods, leading to significant biases in evaluation results. Existing technologies often only focus on whether the load reaches the target power or maintains a stable state, neglecting important characteristics such as overshoot, steady-state deviation, and the magnitude of dynamic power changes during power changes. The lack of identification of the time when the load first enters the target allowable range results in insufficient precision in the analysis of response speed and regulation capability.

[0080] The advantages over existing technologies include: accurately characterizing the dynamic response speed of the load after receiving a regulation command by using the average adjustment rate and the time to first enter the target allowable range, without relying on a fixed dead zone ratio or specific test specifications. It systematically identifies key timing characteristics such as power change amplitude, power change rate, response delay, overshoot, and steady-state deviation, making load regulation behavior quantifiable and comparable. It can comprehensively reflect the dynamic characteristics of the load during the regulation process, providing more refined data support for regulation capacity assessment.

[0081] Methods for extracting the corresponding regulation response state fragments include:

[0082] The structured time-series data from the moment the regulation command is triggered until the load first reaches the allowable range of the regulation target is defined as regulation response state segments. Each regulation response state segment includes the start time, end time, load power at each time point, and related electrical parameter information.

[0083] The relevant electrical parameter information includes instantaneous voltage, instantaneous current, power factor, grid frequency on the grid side or at the load end, load type identification, and status stage identification information, which are collected and recorded synchronously to form a complete data sequence.

[0084] Methods for generating corresponding sustainability assessment indicators include:

[0085] After the load power reaches the allowable range of the regulation target, the starting time when the load reaches the target allowable range is determined. The load power within the allowable deviation range is considered to be maintained within the allowable range of the regulation target. The data of load power change over time recorded in the regulation response state segment are scanned to identify the time interval in which the load is continuously maintained within the allowable range of the regulation target, and this time interval is defined as the effective response time interval.

[0086] The longest duration for which the load maintains power within the effective response time interval is obtained by using the set supremum method, thus forming the response duration index. Response duration index: ;in, This indicates the load response duration, which is the longest period of time that the power is continuously maintained within the target allowable range from the moment the load first enters the target allowable range. The supremum operation of a set finds the maximum time value of all time points where the power is within the allowable deviation range, i.e., the longest continuous duration.

[0087] Within the effective response time interval, load power and related electrical parameters are continuously monitored, and the range of power deviation, power fluctuation, and changes in electrical parameters are statistically analyzed to generate a continuous evaluation index characterizing the load regulation performance. The continuous evaluation index may include response duration, steady-state power deviation, power fluctuation amplitude, frequency stability, and power factor change.

[0088] This solution addresses the following technical problems of existing technologies: Traditional methods typically only determine whether the load has reached the target power, but cannot quantify the duration for which the load power is maintained within the target range. They cannot accurately evaluate the continued availability after load regulation, leading to confusion between response completion and sustained stability. Existing technologies largely rely on experience or fixed thresholds for judgment, lacking methods for systematically scanning load power changes over time, and cannot distinguish between instantaneous achievement of the target and long-term stable maintenance. Existing methods usually only focus on power values, ignoring the impact of changes in electrical parameters such as load-side voltage, current, power factor, and grid frequency on sustainability assessment. They cannot form comprehensive sustainability assessment indicators, resulting in biased assessment results that are difficult to support accurate regulation potential analysis.

[0089] Compared to existing technologies, the advantages are as follows: By utilizing the effective response time interval and supremacy calculation, a load response duration index is obtained, upgrading the duration from an empirical description to a calculable quantitative indicator; it clearly characterizes the continuous maintenance capability of load power after first reaching the target range, improving assessment accuracy. By combining the time of first entering the target allowable range with the response duration, the completion time of load regulation and stability maintenance capability are clearly defined, solving the problem of unclear availability after response completion in existing technologies. Continuous monitoring of power and related electrical parameter information, statistical analysis of power deviation, power fluctuation, and changes in electrical parameters, generates a comprehensive sustainability assessment index, achieving a comprehensive quantification of load regulation stability and sustainability. Through system scanning and continuous monitoring, the influence of instantaneous fluctuations and anomalies is eliminated, making the sustainability assessment index more accurate and reliable, providing a scientific data foundation for load regulation potential analysis and adjustability assessment, and supporting the optimization of power system dispatch and load management.

[0090] Methods for obtaining relative deviation evaluation indicators include:

[0091] After determining that the load power is continuously maintained within the allowable range of the regulation target and an effective response time range is formed, the effective response time range is used as the evaluation time range for regulation accuracy. Within this evaluation time range, the actual output power of the electrical load at each moment is continuously acquired, and the target power at the corresponding moment is acquired simultaneously.

[0092] Based on the power data within the observation time interval, the deviation between the actual output power of the power load and the corresponding target power at each moment is calculated, and the deviation is normalized relative to the corresponding adjustment target power to obtain the normalized power deviation.

[0093] The normalized power deviation at each moment within the observation time interval is accumulated over time and averaged according to the length of the observation time interval to obtain a relative deviation evaluation index characterizing the adjustment execution accuracy of the power load throughout the entire effective response time interval.

[0094] The relative deviation evaluation index is: ;in, It represents the regulation deviation rate, which characterizes the average relative deviation of the actual output power of the electrical load from the regulation target power within the effective response time interval; This indicates the last moment when the load is continuously maintained within the allowable range of the adjustment target during the adjustment process. That is, before this moment, the load power continuously meets the target allowable deviation condition, and after this moment, the load power no longer continuously meets the condition. This moment corresponds to the end time of the effective response time interval. This indicates the length of the effective response time interval, used for time averaging of adjustment deviations. Indicates the load at time. The absolute deviation between the actual output power and the target power; Indicates time Adjust the target power corresponding to the command;

[0095] This solution addresses the following technical problems of existing technologies: Existing technologies typically calculate the deviation between load power and target power at a fixed time or a few sampling points, making them susceptible to instantaneous fluctuations, measurement noise, or short-term disturbances. This results in significant randomness in the evaluation results, failing to accurately reflect the load's accuracy level throughout the entire regulation execution phase. Existing methods fail to perform accuracy assessments after the load has completed its response and entered a stable operating phase, easily incorporating transient deviations during the response process into the regulation accuracy analysis, thus affecting the evaluation accuracy. Existing regulation accuracy assessment methods typically ignore the cumulative effect of power deviations over time, failing to reflect the load's overall performance throughout the entire stable regulation period, which is detrimental to assessing the reliability and availability of load regulation capabilities.

[0096] The advantages over existing technologies are as follows: By using the effective response time interval as the evaluation time interval for regulation accuracy, assessment is only conducted during the stable phase when the load power continuously remains within the allowable range of the regulation target, making the evaluation of regulation accuracy more reasonable and objective. By accumulating and averaging the normalized power deviation at each moment within the evaluation time interval, a holistic evaluation of the entire regulation execution process is achieved, avoiding unreasonable amplification of regulation accuracy results by single-point deviations or short-term fluctuations. By normalizing the power deviation relative to the corresponding target power, the relative deviation evaluation index does not depend on the absolute power level of the load, thus supporting horizontal comparison and unified evaluation between different capacities and types of electrical loads.

[0097] Methods for generating corresponding adjustability potential assessment results include:

[0098] After obtaining the regulation response state segments and corresponding relative deviation evaluation indicators formed by the power load under the preset regulation scenario, the regulation response state segments are used as the basic data carrier to characterize the state evolution of the entire load regulation process.

[0099] Within the time range corresponding to the regulation response state segment, grid-connected operation constraints are introduced to perform constraint consistency analysis on the power changes, electrical parameter changes and operating state changes involved in the regulation process of the power load, so as to determine whether the regulation response process meets the grid-connected safety and stability requirements.

[0100] It should be noted that the constraint consistency analysis includes comparing the load power, voltage, frequency, power factor and operating status information recorded at each moment in the regulation response state segment with the corresponding grid-connected operation constraint thresholds on a time-by-time or interval-by-interval basis to determine whether the load regulation response process continuously meets the grid-connected safety and stability requirements throughout the entire regulation time series.

[0101] Under the premise of satisfying grid-connected operation constraints, key feature parameters for characterizing the regulation capability are extracted for each regulation response state segment. The key feature parameters include the regulation entry time of the load from the issuance of the regulation command to the entry into the target regulation state and the regulation duration of the load in maintaining the regulation state under the premise of satisfying grid-connected operation constraints.

[0102] The regulation capacity of electricity load under preset regulation scenarios is analyzed. Regulation entry time, regulation duration, and relative deviation evaluation indicators are standardized in terms of dimensions and correlated according to preset fusion rules to generate corresponding regulation potential assessment results. These results characterize the regulation capacity level of electricity load that can be actually utilized by the power system under preset regulation scenarios, provided that grid-connected operation constraints are met.

[0103] It should be noted that the preset fusion rules include correlation modeling of each characteristic parameter after unified dimensional processing, based on a preset regulation capacity evaluation logic. The correlation modeling uses the regulation entry time to reflect the load's response speed characteristics, the regulation duration to reflect the load's sustainable regulation capacity, and the relative deviation evaluation index to reflect the load's execution accuracy of the regulation target. By fusing the above characteristic parameters according to preset weights or correlation functions, a regulation capacity evaluation function is constructed to comprehensively characterize the power load regulation capacity.

[0104] During the fusion process, when the adjustment entry time is short, the adjustment duration is long, and the relative deviation assessment index is small, the corresponding adjustment capability evaluation result takes a higher value; conversely, when any characteristic parameter reflects that the adjustment response is lagging, the sustainability is insufficient, or the execution deviation is large, the corresponding adjustment capability evaluation result is reduced accordingly, thus reflecting the degree of influence of different adjustment behaviors on the overall adjustment capability in the fusion result.

[0105] Furthermore, the evaluation results of the regulation capacity of multiple regulation response state segments obtained under the same preset regulation scenario are summarized and analyzed. Based on the distribution of each state segment in the time dimension and the effective duration ratio, a comprehensive evaluation result reflecting the overall regulation capacity level of the power load under the regulation scenario is generated.

[0106] Grid-connected operation constraints include maintaining the voltage within the preset allowable voltage range during power regulation, and being less than the preset upper voltage threshold and greater than or equal to the preset lower voltage threshold; the deviation of the grid's operating frequency relative to the grid's nominal frequency at the load connection point being less than the preset deviation threshold; and the load's power factor meeting the preset power factor threshold during regulation.

[0107] The preset offset threshold is set by staff based on historical data analysis results. This historical analysis process includes the system collecting multiple offsets and calculating their average value as a reference to obtain the preset offset threshold. Similarly, the preset upper voltage threshold, preset lower voltage threshold, and preset power factor threshold are also set by staff based on the system's historical operating data and specific application scenario requirements. These can be adjusted by staff during system operation according to actual conditions.

[0108] This embodiment accurately characterizes the dynamic response speed of the load after receiving a regulation command by using the average adjustment rate and the time to first enter the target allowable range, without relying on a fixed dead zone ratio or specific test specifications. It systematically identifies key timing characteristics such as power change amplitude, power change rate, response delay, overshoot, and steady-state deviation, making load regulation behavior quantifiable and comparable. It comprehensively reflects the dynamic characteristics of the load during the regulation process, providing more refined data support for regulation capability assessment.

[0109] By utilizing the effective response time interval and supremacy calculation, a load response duration index is obtained, upgrading the duration from an empirical description to a calculable quantitative indicator. This clearly characterizes the continuous maintenance capability of load power after initially reaching the target range, improving assessment accuracy. By combining the time of first entering the target allowable range with the response duration, the completion time of load regulation and stability maintenance capability are clearly defined, solving the problem of unclear availability despite response completion in existing technologies. Continuous monitoring of power and related electrical parameters, statistical analysis of power deviation, power fluctuation, and changes in electrical parameters, generates a comprehensive sustainability assessment index, achieving a comprehensive quantification of load regulation stability and sustainability. Through system scanning and continuous monitoring, the influence of instantaneous fluctuations and anomalies is eliminated, making the sustainability assessment index more accurate and reliable. This provides a scientific data foundation for load regulation potential analysis and adjustability assessment, supporting the optimization of power system dispatch and load management.

[0110] By using the effective response time interval as the evaluation time interval for regulation accuracy, assessments are only conducted during the stable phase when the load power continuously remains within the allowable range of the regulation target, making the evaluation of regulation accuracy more reasonable and objective. By accumulating and averaging the normalized power deviation at each moment within the evaluation time interval, a holistic evaluation of the entire regulation execution process is achieved, avoiding unreasonable amplification of regulation accuracy results by single-point deviations or short-term fluctuations. By normalizing the power deviation relative to the corresponding target power, the relative deviation evaluation index is independent of the absolute power level of the load, thus supporting horizontal comparisons and unified evaluations between different capacities and types of electrical loads.

[0111] Example 2:

[0112] Please see Figure 2 As shown, for parts not described in detail in this embodiment, please refer to the description in Embodiment 1. A system for assessing the adjustable potential of electrical load is provided, including:

[0113] The regulation status sensing module is used to acquire the operation status data of the power load during grid-connected operation and regulation, and to perform time alignment and status organization on the operation status data to construct a time-series status dataset that characterizes the regulation behavior of the power load.

[0114] The load regulation response module is used to analyze the power change process of the electrical load after receiving the regulation command based on the time-series state dataset, identify the key time-series features of the load power entering the allowable range of the regulation target, and extract the corresponding regulation response state segments.

[0115] The load regulation assessment module is used to continuously monitor the power maintenance status of the electrical load based on the regulation response state segment after the load power reaches the allowable range of the regulation target, determine the effective response time interval for the load power to be continuously maintained within the preset target allowable deviation range, and generate the corresponding continuous assessment index.

[0116] The adjustment deviation assessment module is used to calculate the degree of deviation between the actual output power and the corresponding target power of the power load during the adjustment process within the effective response time interval, and to construct a relative deviation assessment index that reflects the accuracy of load adjustment.

[0117] The adjustable potential assessment module is used to analyze the adjustment capability of the power load under preset adjustment scenarios based on the adjustment response state segments and relative deviation assessment indicators, while meeting the grid-connected operation constraints, and generate corresponding adjustable potential assessment results.

[0118] Since the electronic device described in this embodiment is the one used in implementing the power load adjustable potential assessment method and system described in this application, those skilled in the art can understand the specific implementation and various variations of the electronic device in this embodiment based on the power load adjustable potential assessment method and system described in this application. Therefore, how the electronic device implements the method in this application will not be described in detail here. Any electronic device used by those skilled in the art in implementing the power load adjustable potential assessment method and system described in this application falls within the scope of protection of this application.

[0119] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters and thresholds in the formulas are set by those skilled in the art according to the actual situation.

[0120] The above description is merely a preferred embodiment of the present invention. The scope of protection of the present invention is not limited to the above embodiments. All technical solutions falling within the scope of the present invention's concept are within the scope of protection of the present invention. It should be noted that for those skilled in the art, any improvements and modifications made without departing from the principles of the present invention should also be considered within the scope of protection of the present invention.

Claims

1. A method for assessing the adjustability potential of electrical load, characterized in that, include: S1. Obtain the operating status data of the power load during grid-connected operation and regulation, and perform time alignment and state organization on the operating status data to construct a time-series state dataset that characterizes the regulation behavior of the power load. S2. Based on the time-series state dataset, analyze the power change process of the electrical load after receiving the regulation command, identify the key time-series features of the load power entering the allowable range of the regulation target, and extract the corresponding regulation response state segments. The method for identifying the key temporal features includes: Based on the time-series state dataset, the power change process of the electrical load after receiving the adjustment command is analyzed to determine the trigger time of the adjustment command. The target power and the allowable deviation of the target power corresponding to the adjustment command are preset. According to the target power and the allowable deviation of the target power corresponding to the adjustment command, the allowable range of the adjustment target is defined as the range in which the difference between the load power and the target power is within the allowable deviation range. Identify the time when the load first enters the allowable range of the regulation target from the time-series state dataset, and obtain the average regulation rate of the load regulation process based on the change of load power before and after entering the allowable range of the regulation target for the first time; The load response speed under the regulation command is quantified by the average regulation rate. The load response speed is characterized by the time to first reach the allowable range of the regulation target. Key time-series features for identifying the load power entering the allowable range of the regulation target are extracted. Key time-series features include power change amplitude, power change rate, response delay, overshoot, and steady-state deviation. The method for extracting the corresponding regulation response state fragment includes: The structured time-series data from the moment the regulation command is triggered until the load first reaches the allowable range of the regulation target is defined as a regulation response state segment. Each regulation response state segment includes the start time, end time, load power at each time point, and related electrical parameter information. S3. After the load power reaches the allowable range of the adjustment target, continuously monitor the power maintenance status of the power load according to the adjustment response state segment, determine the effective response time interval for the load power to be continuously maintained within the preset target allowable deviation range, and generate the corresponding continuous evaluation index. The method for generating the corresponding continuous evaluation indicators includes: After the load power reaches the allowable range of the regulation target, the starting time when the load reaches the target allowable range is determined. The load power within the allowable deviation range is considered to be maintained within the allowable range of the regulation target. The data of load power change over time recorded in the regulation response state segment are scanned to identify the time interval in which the load is continuously maintained within the allowable range of the regulation target, and this time interval is defined as the effective response time interval. The longest duration for which the load power is sustained within the effective response time interval is obtained by using the set supremum method, thus forming a response duration index. Within the effective response time interval, the load power and related electrical parameters are continuously monitored, and the power deviation range, power fluctuation and electrical parameter changes are statistically analyzed, thereby generating a continuous evaluation index to characterize the load regulation continuous performance. S4. Within the effective response time interval, calculate the degree of deviation between the actual output power and the corresponding target power of the power load during the adjustment process, and construct a relative deviation evaluation index that reflects the accuracy of load adjustment. S5. Based on the regulation response state segments and relative deviation evaluation indicators, analyze the regulation capability of the power load under the preset regulation scenario while meeting the grid connection operation constraints, and generate the corresponding adjustable potential evaluation results.

2. The method for assessing the adjustable potential of electrical load according to claim 1, characterized in that, The method for obtaining the operating status data includes: During the operation of the power system, the electrical load is connected to the distribution network or the main power grid through the access point and is in a grid-connected operation state that is monitored and regulated by the power system. During the process of issuing and executing adjustment commands by the grid dispatch terminal, load aggregation platform or user-side load control terminal, the operation status data formed by the electrical load in the grid-connected operation state and in the process of executing adjustment commands are obtained through the operation monitoring interface set on the load side, aggregation side or grid side. The operating status data includes the actual output power data of the electrical load and the corresponding time stamp information, as well as the initial operating status data obtained before the regulation command is issued, the power change status data obtained during the execution of the regulation command, the stable operating status data obtained during the period when the load reaches the regulation target and maintains the regulation status, and the recovery status data of the load recovery operation phase obtained after the regulation ends or the regulation is withdrawn.

3. The method for assessing the adjustable potential of electrical load according to claim 2, characterized in that, The method for obtaining the time-series state dataset includes: By synchronously collecting timestamps or interpolating asynchronously collected data, the initial operating status data, power change status data, stable operating status data, and recovery status data in the operating status data are time-aligned according to their respective time identifiers to unify the time base. The time-aligned operational status data is organized into status categories, and each type of data is logically classified according to the order of load adjustment. Each type of status data is assigned a status type, start time, end time, and duration. The time-aligned operational status data is transformed into corresponding structured status data through state organization. After completing time alignment and state organization, the structured status data is combined in chronological order and subjected to missing value imputation, outlier removal, and noise smoothing to construct a time-series status dataset that characterizes the power load regulation behavior.

4. The method for assessing the adjustable potential of electrical load according to claim 3, characterized in that, The method for obtaining the relative deviation evaluation index includes: After determining that the load power is continuously maintained within the allowable range of the regulation target and an effective response time range is formed, the effective response time range is used as the evaluation time range for regulation accuracy. Within this evaluation time range, the actual output power of the electrical load at each moment is continuously acquired, and the target power at the corresponding moment is acquired simultaneously. Based on the power data within the observation time interval, the deviation between the actual output power of the power load and the corresponding target power at each moment is calculated, and the deviation is normalized relative to the corresponding adjustment target power to obtain the normalized power deviation. The normalized power deviation at each moment within the observation time interval is accumulated over time and averaged according to the length of the observation time interval to obtain a relative deviation evaluation index characterizing the adjustment execution accuracy of the power load throughout the entire effective response time interval.

5. The method for assessing the adjustable potential of electrical load according to claim 4, characterized in that, The method for generating the corresponding adjustable potential assessment results includes: After obtaining the regulation response state segments and corresponding relative deviation evaluation indicators formed by the power load under the preset regulation scenario, the regulation response state segments are used as the basic data carrier to characterize the state evolution of the entire load regulation process. Within the time range corresponding to the regulation response state segment, grid-connected operation constraints are introduced to perform constraint consistency analysis on the power changes, electrical parameter changes and operating state changes involved in the regulation process of the power load, so as to determine whether the regulation response process meets the grid-connected safety and stability requirements. Under the premise of satisfying grid-connected operation constraints, key feature parameters for characterizing the regulation capability are extracted for each regulation response state segment. The key feature parameters include the regulation entry time of the load from the issuance of the regulation command to the entry into the target regulation state and the regulation duration of the load in maintaining the regulation state under the premise of satisfying grid-connected operation constraints. The adjustment capability of the power load under the preset adjustment scenario is analyzed. The adjustment entry time, adjustment duration and relative deviation evaluation index are processed with unified dimensions and correlated according to the preset fusion rules to generate the corresponding adjustment potential evaluation results.

6. The method for assessing the adjustable potential of electrical load according to claim 5, characterized in that, The grid-connected operation constraints include maintaining the voltage within a preset allowable voltage range during the power regulation process, and being less than a preset upper voltage threshold and greater than or equal to a preset lower voltage threshold. The deviation of the operating frequency of the power grid at the load connection point from the nominal frequency of the power grid is less than a preset deviation threshold. During the adjustment process, the power factor of the load meets the preset power factor threshold.

7. A system for assessing the adjustable potential of electrical load, used to implement the method for assessing the adjustable potential of electrical load according to any one of claims 1 to 6, characterized in that, include: The regulation status sensing module is used to acquire the operation status data of the power load during grid-connected operation and regulation, and to perform time alignment and status organization on the operation status data to construct a time-series status dataset that characterizes the regulation behavior of the power load. The load regulation response module is used to analyze the power change process of the electrical load after receiving the regulation command based on the time-series state dataset, identify the key time-series features of the load power entering the allowable range of the regulation target, and extract the corresponding regulation response state segments. The load regulation assessment module is used to continuously monitor the power maintenance status of the electrical load based on the regulation response state segment after the load power reaches the allowable range of the regulation target, determine the effective response time interval for the load power to be continuously maintained within the preset target allowable deviation range, and generate the corresponding continuous assessment index. The adjustment deviation assessment module is used to calculate the degree of deviation between the actual output power and the corresponding target power of the power load during the adjustment process within the effective response time interval, and to construct a relative deviation assessment index that reflects the accuracy of load adjustment. The adjustable potential assessment module is used to analyze the adjustment capability of the power load under preset adjustment scenarios based on the adjustment response state segments and relative deviation assessment indicators, while meeting the grid-connected operation constraints, and generate corresponding adjustable potential assessment results.

Images