Power distribution area compatibility optimization method considering energy storage device

Abstract

The invention provides a power distribution area compatibility optimization method considering an energy storage device, and belongs to the technical field of optimization management, and the method specifically comprises the steps: determining a load fluctuation user of an energy storage adjustment influence user based on the load fluctuation conditions of the energy storage adjustment influence user in different historical dates, determining distribution data of load fluctuation users in the energy storage adjustment influence users, and combining with overlapped data of load fluctuation time periods of the load fluctuation users in different historical dates to determine whether compatibility optimization processing needs to be carried out in an associated power transmission line between the load fluctuation users and an energy storage device or not; according to the method, a power consumer with multiple power transmission lines serves as an optimization target, compatibility optimization strategies of different optimization targets are determined according to power loads and historical operation fault data of different power transmission lines of different optimization targets, and the reliability of adjustment processing of the energy storage device is improved.

Description

Technical Field

[0001] This invention belongs to the field of optimization management technology, and in particular relates to a method for optimizing the compatibility of distribution areas of energy storage devices. Background Technology

[0002] With the increasing number of distributed energy systems connected to distribution substations, the load fluctuation situation within these substations is becoming increasingly severe. Therefore, existing technical solutions often employ energy storage devices to stabilize the load in distribution substations. At the same time, how to optimize the compatibility of distribution substations, avoid the impact of energy storage devices on the power distribution network after they are put into use, and ensure the reliability of power supply in distribution substations has become an urgent technical problem.

[0003] To achieve compatibility optimization for distribution substations, the invention patent application CN202110973270.0, "A Control Method and System for Distribution Substations Containing Energy Storage Devices and Interruptible Loads," employs a genetic algorithm to solve this problem, deriving the optimal control curve for the energy storage device voltage. This approach mitigates the voltage surge in the substation during interrupted load switching and reduces line losses during this process, making it suitable for distribution substations with both energy storage devices and interruptible loads. However, it still presents the following technical problems: When energy storage devices are put into use, fixed lines and power distribution equipment are often required to regulate the load fluctuations of the distribution area. However, if the operating load of the aforementioned related lines or power distribution equipment is too large, when the energy storage device needs to be regulated, it may prevent the energy storage device from being put into use. On the other hand, it may require secondary regulation of the load of the related lines, thus preventing the energy storage device from being put into use in a timely and effective manner.

[0004] To address the aforementioned technical problems, this application provides a method for optimizing distribution area compatibility considering energy storage devices. Summary of the Invention

[0005] To achieve the objectives of this invention, the following technical solution is adopted: Specifically, this application provides a method for optimizing distribution area compatibility considering energy storage devices, which includes: S1 uses the associated transmission lines of the energy storage device in the distribution area and the load data at different times to determine the impact of the energy storage device on the user during energy storage regulation. S2 determines the users whose load fluctuations are affected by the energy storage regulation based on the load fluctuations of the users on different historical dates. S3 determines the distribution data of load fluctuation users among the users affected by the energy storage regulation, and combines the overlapping data of the load fluctuation periods of the load fluctuation users in different historical dates to determine when compatibility optimization processing is required, and then proceeds to the next step. S4 takes power users with multiple transmission lines in the associated transmission lines between the load fluctuating users and the energy storage device as optimization targets, and determines the compatibility optimization strategy for different optimization targets based on the power load of different transmission lines and historical operation fault data of different optimization targets.

[0006] The beneficial effects of this invention are as follows: By using the distribution data of load fluctuation users affected by energy storage regulation and the overlapping data of load fluctuation periods of these users on different historical dates, it is determined whether compatibility optimization processing is required. This approach not only considers the differences in the number of users affected by energy storage regulation and the differences in the number of load fluctuation users, but also the differences in the compatibility optimization requirements due to the differences in overlapping data of load fluctuation periods. This enables the evaluation of compatibility optimization processing from multiple perspectives and lays the foundation for ensuring the reliability and timeliness of energy storage regulation processing.

[0007] Based on the power load of different transmission lines and historical operational fault data for different optimization objectives, compatibility optimization strategies for different optimization objectives are determined, thereby enabling the switching of power load for the optimization objectives, reducing the load on associated transmission lines, and further ensuring the operational reliability of the optimization objectives after the switching is completed by combining the power load of the transmission lines and historical operational fault data.

[0008] A further technical solution is that the associated transmission line is the transmission line between the energy storage device and the power user.

[0009] A further technical solution is that the load data includes the load rate and remaining load capacity of different associated transmission lines at different times.

[0010] A further technical solution is that the method for determining the impact of energy storage regulation on users is as follows: Based on the load data of the associated transmission lines at different times, the load rate of the different associated transmission lines between the energy storage device and the power user at different times is determined. Associated transmission lines with load rates greater than a preset load rate threshold are considered high-load lines. The high-load time is determined by the proportion of high-load lines among the associated transmission lines at different times. Based on the percentage of high-load moments within a preset time period, it is determined whether the power user is affected by energy storage regulation.

[0011] A further technical solution is that the high load time is the time when the proportion of high load lines in the associated transmission lines is greater than the preset proportion of high load lines.

[0012] A further technical solution is that when the proportion of high-load moments within a preset time period is greater than the proportion of preset load moments, the power user is determined to be a user affected by energy storage regulation.

[0013] A further technical solution is that when there is no energy storage regulation affecting users, there is no need to perform compatibility optimization processing for distribution radio stations.

[0014] A further technical solution is that the method for determining the compatibility optimization strategy of the optimization target is as follows: Based on the power load of the transmission lines, determine the average load rate of different transmission lines at different times; Based on the historical operational fault data of the transmission lines, determine the number of historical operational faults for different transmission lines; The transmission lines that belong to the associated transmission lines are designated as target transmission lines. Based on the average load rate of the other transmission lines excluding the target transmission lines and the number of historical operational failures, a compatibility optimization strategy for the optimization target is determined.

[0015] A further technical solution is that when the average load rate and the number of historical operational faults of other transmission lines besides the target transmission line are both within a preset range, it is determined to switch the power load of the optimized target to other transmission lines.

[0016] Other features and advantages will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention are realized and obtained through the structures particularly pointed out in the description and the drawings.

[0017] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0018] The above and other features and advantages of the present invention will become more apparent from a detailed description of exemplary embodiments thereof with reference to the accompanying drawings.

[0019] Figure 1 This is a flowchart of a method for optimizing the distribution area compatibility of energy storage devices. Figure 2 This is a flowchart illustrating the methods for determining how energy storage regulation affects users; Figure 3This is a flowchart illustrating the method for determining the user's load fluctuations caused by energy storage regulation; Figure 4 This is a flowchart for determining which compatibility optimizations are needed. Detailed Implementation

[0020] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the embodiments set forth herein; rather, they are provided so that the invention will be thorough and complete, and the concept of the exemplary embodiments will be fully conveyed to those skilled in the art. The same reference numerals in the drawings denote the same or similar structures, and therefore their detailed description will be omitted.

[0021] The terms “a,” “one,” “the,” and “the” are used to indicate the existence of one or more elements / components / etc.; the terms “including” and “having” are used to indicate an open-ended meaning of inclusion and that other elements / components / etc. may exist in addition to the listed elements / components / etc.

[0022] To solve the above problems, according to one aspect of the present invention, such as Figure 1 As shown, a method for optimizing distribution area compatibility considering energy storage devices is provided, specifically including: S1 uses the associated transmission lines of the energy storage device in the distribution area and the load data at different times to determine the impact of the energy storage device on the user during energy storage regulation. S2 determines the users whose load fluctuations are affected by the energy storage regulation based on the load fluctuations of the users on different historical dates. S3 determines the distribution data of load fluctuation users among the users affected by the energy storage regulation, and combines the overlapping data of the load fluctuation periods of the load fluctuation users in different historical dates to determine when compatibility optimization processing is required, and then proceeds to the next step. S4 takes power users with multiple transmission lines in the associated transmission lines between the load fluctuating users and the energy storage device as optimization targets, and determines the compatibility optimization strategy for different optimization targets based on the power load of different transmission lines and historical operation fault data of different optimization targets.

[0023] Furthermore, the associated transmission line is the transmission line between the energy storage device and the power user.

[0024] Specifically, the load data includes the load rate and remaining load capacity of different associated transmission lines at different times.

[0025] Specifically, such as Figure 2As shown, the method for determining the impact of energy storage regulation on users is as follows: Based on the load data of the associated transmission lines at different times, the load rate of the different associated transmission lines between the energy storage device and the power user at different times is determined. Associated transmission lines with load rates greater than a preset load rate threshold are considered high-load lines. The high-load time is determined by the proportion of high-load lines among the associated transmission lines at different times. Based on the percentage of high-load moments within a preset time period, it is determined whether the power user is affected by energy storage regulation.

[0026] It should be noted that the high load time is the time when the proportion of high load lines in the associated transmission lines is greater than the preset proportion of high load lines, that is, when it is greater than 0.3.

[0027] It is understandable that when the proportion of high-load moments within a preset time period is greater than the proportion of preset load moments, in one possible embodiment, when the proportion of high-load moments within the most recent week is greater than 0.6, the power user is determined to be a user affected by energy storage regulation.

[0028] Furthermore, when there is no energy storage regulation affecting users, there is no need to perform compatibility optimization processing for distribution radio stations.

[0029] In another possible embodiment, the method for determining the impact of energy storage regulation on users is as follows: S11 uses the load data of the associated transmission lines at different times to determine the load rate of the different associated transmission lines between the energy storage device and the power user at different times. S12 obtains the load rate of different associated transmission lines at different times, and determines the abnormal load values ​​of transmission lines at different times based on the load rate at different times. S13 determines the comprehensive abnormal value based on the abnormal load values ​​of the transmission line at different times within a preset time period, and uses the comprehensive abnormal value to determine whether the power user is a user affected by energy storage regulation.

[0030] Furthermore, when the overall abnormal value is greater than a preset abnormal value threshold, the power user is determined to be a user affected by energy storage regulation.

[0031] Furthermore, the impact of energy storage regulation on user load fluctuations on different historical dates is determined based on the changes in user electricity load during corresponding time periods on different historical dates.

[0032] Specifically, such as Figure 3As shown, the method for determining users whose load fluctuations are affected by energy storage regulation is as follows: Based on the electricity load of the target period on different historical dates, the average value of the electricity load of the target period on different historical dates is determined and used as the reference electricity load; Based on the deviation between the electricity load and the reference electricity load in different historical dates during the target period, the historical dates with a deviation greater than a preset deviation threshold are determined and used as the load deviation dates. Based on the proportion of days with load deviations during different target periods, it is determined whether the users affected by the energy storage regulation are users with load fluctuations.

[0033] It should be noted that when the preset deviation threshold is the ratio of the absolute value of the deviation between the power load and the reference power load to the reference power load, it is determined as the load deviation date.

[0034] Furthermore, when the percentage of days with load deviations for users affected by the energy storage regulation is greater than the target period for the percentage of days with load deviations (i.e., greater than the target period of 0.2), the users affected by the energy storage regulation are determined to be users with load fluctuations.

[0035] It should be noted that when there are no users with load fluctuations among the users affected by the energy storage regulation, there is no need to perform compatibility optimization processing for the distribution radio area.

[0036] In another possible embodiment, the method for determining the user whose load fluctuations are affected by the energy storage regulation is as follows: Based on the electricity load of the target period on different historical dates, the average value of the electricity load of the target period on different historical dates is determined and used as the reference electricity load; Based on the deviation between the electricity load and the reference electricity load in different historical dates during the target period, the historical dates with a deviation greater than a preset deviation threshold are determined and used as the load deviation dates. Based on the average percentage of the number of load deviation dates for different target periods, the percentage of load deviation dates is determined, and the percentage of load deviation dates is used to determine whether the users affected by the energy storage regulation are load fluctuation users.

[0037] Furthermore, when the percentage of the load deviation date does not meet the requirements, i.e., it is greater than 0.2, the user affected by the energy storage regulation is determined to be a user with load fluctuation.

[0038] Specifically, the load fluctuation period of the load fluctuation user is the period in which the deviation from the average electricity load on different historical dates of the specified period is greater than a preset deviation threshold.

[0039] It should be noted that the distribution data of the load fluctuation users includes the number and proportion of load fluctuation users among the users affected by energy storage regulation.

[0040] Furthermore, the overlapping data of load fluctuation periods of the load fluctuation users in different historical dates includes the overlap of load fluctuation periods of different load fluctuation users on the same date.

[0041] Specifically, such as Figure 4 As shown, compatibility optimization is required, specifically including: Based on the distribution data of load fluctuation users among the users affected by energy storage regulation, determine the proportion of load fluctuation users among the users affected by energy storage regulation, and use it as the proportion of fluctuation users. Based on the overlap data of load fluctuation periods of the load fluctuation users in different historical dates, the dates on which the load fluctuation periods of different load fluctuation users all overlap are determined and used as the load fluctuation overlap dates. Based on the percentage of overlapping dates of load fluctuations and the percentage of fluctuating users, load fluctuation anomalies are determined, and based on the load fluctuation anomalies, it is determined whether compatibility optimization is required.

[0042] Furthermore, the load fluctuation anomaly value is the average of the percentage of overlapping load fluctuation dates and the percentage of fluctuating users.

[0043] It should be noted that when the load fluctuation anomaly value is greater than the preset fluctuation anomaly threshold, in one possible embodiment it is greater than 0.3, then it is determined that compatibility optimization processing is required.

[0044] Furthermore, the method for determining the compatibility optimization strategy of the optimization target is as follows: Based on the power load of the transmission lines, determine the average load rate of different transmission lines at different times; Based on the historical operational fault data of the transmission lines, determine the number of historical operational faults for different transmission lines; The transmission lines that belong to the associated transmission lines are designated as target transmission lines. Based on the average load rate of the other transmission lines excluding the target transmission lines and the number of historical operational failures, a compatibility optimization strategy for the optimization target is determined.

[0045] Specifically, when the average load rate and the number of historical operational faults of other transmission lines besides the target transmission line are both within a preset range, that is, when the average load rate of other transmission lines is less than 0.8 and the daily average number of historical operational faults is less than 0.05, it is determined that the power load of the optimized target will be switched to other transmission lines.

[0046] In another embodiment, the method for determining the compatibility optimization strategy of the optimization target is as follows: The transmission line of the optimization target belongs to the associated transmission line as the target transmission line. When the average load rate of the target transmission line at different times within a preset time period is greater than the preset load rate threshold, it is determined to switch the power load of the optimization target to other transmission lines. Additionally, it should be noted that when the average load rate of the target transmission line at different times within a preset time period is not greater than a preset load rate threshold: the number of power fluctuation users associated with the target transmission line and the number of users affected by energy storage regulation are obtained; when either the number of power fluctuation users associated with the target transmission line or the number of users affected by energy storage regulation is greater than a preset user number setting value, it is determined that the power load of the optimized target will be switched to other transmission lines. Furthermore, it is understood that when the number of power fluctuation users associated with the target transmission line and the number of users affected by energy storage regulation are both not greater than the preset user number setting value: the switching demand value of the target transmission line is determined by the number of power fluctuation users associated with the target transmission line and the number of users affected by energy storage regulation, combined with the average load rate of the target transmission line at different times within a preset period. When the switching demand value is greater than the preset switching demand value threshold, it is determined that the power load of the optimized target will be switched to other transmission lines. Furthermore, when the switching demand value is not greater than the preset switching demand value threshold, based on the power load of the transmission line, the average load rate of different transmission lines at different times is determined. Based on the historical operation fault data of the transmission line, the number of historical operation faults of different transmission lines is determined. The transmission line belonging to the associated transmission line is taken as the target transmission line. Based on the average load rate and the number of historical operation faults of the other transmission lines excluding the target transmission line, the compatibility optimization strategy of the optimization target is determined.

[0047] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the embodiments of apparatus, devices, and non-volatile computer storage media are basically similar to the method embodiments, so the descriptions are relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0048] The foregoing has described specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0049] The above description is merely one or more embodiments of this specification and is not intended to limit this specification. Various modifications and variations can be made to the one or more embodiments of this specification by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principle of one or more embodiments of this specification should be included within the scope of the claims of this specification.

Claims

1. A method for optimizing distribution area compatibility considering energy storage devices, characterized in that, Specifically, it includes: Using the load data of the associated transmission lines of the energy storage device in the distribution substation at different times, the impact of the energy storage regulation on users during the energy storage regulation process of the energy storage device is determined. Based on the load fluctuations of users affected by the energy storage regulation on different historical dates, identify the users whose load fluctuations are affected by the energy storage regulation. Determine the distribution data of load fluctuation users among the users affected by the energy storage regulation, and combine the overlapping data of the load fluctuation periods of the load fluctuation users in different historical dates. If compatibility optimization processing is required, proceed to the next step. Among the power transmission lines associated with the load fluctuation users and energy storage devices, power users with multiple transmission lines are taken as optimization targets. Based on the power load of different transmission lines and historical operational fault data of different optimization targets, compatibility optimization strategies for different optimization targets are determined.

2. The method for optimizing distribution area compatibility considering energy storage devices as described in claim 1, characterized in that, The associated transmission line is the transmission line between the energy storage device and the power user.

3. The method for optimizing distribution area compatibility considering energy storage devices as described in claim 1, characterized in that, The load data includes the load rate and remaining load capacity of different associated transmission lines at different times.

4. The method for optimizing distribution area compatibility considering energy storage devices as described in claim 1, characterized in that, The method for determining the impact of energy storage regulation on users is as follows: Based on the load data of the associated transmission lines at different times, the load rate of the different associated transmission lines between the energy storage device and the power user at different times is determined. Associated transmission lines with load rates greater than a preset load rate threshold are considered high-load lines. The high-load time is determined by the proportion of high-load lines among the associated transmission lines at different times. Based on the percentage of high-load moments within a preset time period, it is determined whether the power user is affected by energy storage regulation.

5. The method for optimizing distribution area compatibility considering energy storage devices as described in claim 4, characterized in that, The high-load moment is the moment when the proportion of high-load lines in the associated transmission lines is greater than the preset proportion of high-load lines.

6. The method for optimizing distribution area compatibility considering energy storage devices as described in claim 4, characterized in that, When the proportion of high-load moments within a preset time period is greater than the proportion of preset load moments, the power user is determined to be a user affected by energy storage regulation.

7. The method for optimizing distribution area compatibility considering energy storage devices as described in claim 1, characterized in that, If there is no energy storage regulation affecting users, then there is no need to perform compatibility optimization for the distribution radio area.

8. The method for optimizing distribution area compatibility considering energy storage devices as described in claim 1, characterized in that, The impact of energy storage regulation on user load fluctuations on different historical dates is determined based on the changes in user electricity load during corresponding time periods on different historical dates.

9. The method for optimizing distribution area compatibility considering energy storage devices as described in claim 1, characterized in that, The method for determining the compatibility optimization strategy of the optimization objective is as follows: Based on the power load of the transmission lines, determine the average load rate of different transmission lines at different times; Based on the historical operational fault data of the transmission lines, determine the number of historical operational faults for different transmission lines; The transmission lines that belong to the associated transmission lines are designated as target transmission lines. Based on the average load rate of the other transmission lines excluding the target transmission lines and the number of historical operational failures, a compatibility optimization strategy for the optimization target is determined.

10. The method for optimizing distribution area compatibility considering energy storage devices as described in claim 9, characterized in that, When the average load rate and the number of historical operational faults of other transmission lines besides the target transmission line are both within a preset range, it is determined that the power load of the optimized target will be switched to other transmission lines.

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