Energy storage adjusting method and system of thermoelectric unit based on hybrid energy storage device

Abstract

The invention provides an energy storage adjusting method and system for a thermoelectric unit based on a hybrid energy storage device, and belongs to the technical field of thermoelectric units, and the method specifically comprises the steps: obtaining an energy storage space of a short-time energy storage device when historical adjustment data in a preset adjustment depth interval meets requirements, and in combination with historical adjustment data in different adjustment depth intervals, when it is determined that the adjustment flexibility of the short-time energy storage device meets the requirement, the short-time energy storage device is used for carrying out load adjustment processing. And the input processing strategy of the long-time energy storage device is determined according to the deviation condition of the short-time energy storage device and the preset energy storage space and the fluctuation condition of the adjustment rate of the short-time energy storage device during load adjustment processing, so that the flexibility of energy storage adjustment is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of thermoelectric generator sets, and in particular relates to an energy storage regulation method and system for thermoelectric generator sets based on a hybrid energy storage device. Background Art

[0002] Energy storage devices can be divided into long-term energy storage devices and short-term energy storage devices based on their different energy storage characteristics. Existing technical solutions often use a single long-term energy storage device or a single short-term energy storage device to carry out load scheduling of thermal power units. These technical solutions cannot meet the flexibility requirements of load scheduling of thermal power units in the face of increasingly severe load fluctuations. On the one hand, this will have a certain degree of impact on the equipment operation reliability of the thermal power units. On the other hand, it will also make the thermal power units face severe frequency regulation and peak regulation assessment pressure.

[0003] The existing technical solution provides a technical solution for unit regulation using long-term energy storage devices and short-term energy storage devices. Specifically, in CN202411237895.0 "A wide-time domain multi-hybrid energy storage system and charging and discharging method", in the peak-shaving direction to cope with higher discharge time requirements, the battery module can first store excess power, and then the power of the battery module or the excess power of the power grid can be used to lift the battery module in turn, converting the excess power into gravitational potential energy and storing it for a long time.

[0004] When coordinating the scheduling of long-term and short-term energy storage devices, the response rate of the energy storage regulation of the long-term energy storage device is often lower than that of the short-term energy storage device due to its energy storage characteristics. Therefore, how to ensure the response rate of the short-term energy storage device and the reliability of the unit's regulation during the regulation process has become a technical problem that needs to be solved urgently.

[0005] In response to the above technical problems, the present application specifically provides an energy storage regulation method and system for a thermoelectric generator set based on a hybrid energy storage device. Summary of the Invention

[0006] To achieve the purpose of the present invention, the present invention adopts the following technical solutions: In a first aspect, the present application provides an energy storage regulation method for a thermoelectric generator set based on a hybrid energy storage device, specifically comprising: S1 obtains the load forecast data of the thermal power unit at different time periods on the current date, and uses the changes in the load forecast data between different time periods to determine that the fluctuation of the load forecast data does not meet the requirements, and then proceeds to the next step; S2 determines weather data of the region where the thermal power unit is located on different dates within a future preset period, and uses the weather data to determine historical regulation data of the thermal power unit within different regulation depth intervals; S3: When the historical adjustment data within the preset adjustment depth interval meets the requirements, the energy storage capacity of the short-term energy storage device is obtained, and the adjustment flexibility of the short-term energy storage device is determined to meet the requirements by combining the historical adjustment data within different adjustment depth intervals, and then the process proceeds to the next step; S4 utilizes the short-term energy storage device to perform load regulation processing, and determines the input processing strategy of the long-term energy storage device based on the deviation between the short-term energy storage device and the preset energy storage space and the fluctuation of the regulation rate of the short-term energy storage device during the load regulation processing.

[0007] The beneficial effects of the present invention are: By utilizing the changes in the load forecast data between different time periods, it is determined whether the fluctuation of the load forecast data meets the requirements, thereby realizing the screening of the load fluctuation of the current date based on the changes in the load forecast data between different time periods on the current date, and realizing the screening of dates with more severe load fluctuations. This not only avoids the impact of using a long-term energy storage device to perform load regulation on dates with more severe load fluctuations on the service life of the long-term energy storage device, but also avoids the impact of using a single short-term energy storage device on the regulation flexibility of the short-term energy storage device. On the basis of ensuring load regulation flexibility, the operating reliability of the hybrid energy storage device is improved.

[0008] By utilizing the energy storage capacity of the short-term energy storage device and historical adjustment data within different adjustment depth intervals, it is determined whether the adjustment flexibility of the short-term energy storage device meets the requirements. This avoids the technical problem of low flexibility of the short-term energy storage device in future energy storage adjustment processes caused by the use of long-term energy storage devices for energy storage adjustment. This ensures the flexibility of the energy storage adjustment of the short-term energy storage device while also ensuring the safety and reliability of the unit operation.

[0009] A further technical solution is that the load forecast data is determined according to weather data of different time periods. Specifically, based on the weather data, a preset mapping model is constructed to determine the load forecast data.

[0010] A further technical solution is that the change in the load forecast data between the time periods includes the change amount of the load forecast data between different time periods.

[0011] A further technical solution is to determine whether the fluctuation of the load forecast data meets the requirements, specifically including: Based on the changes in load forecast data between different time periods, determine the proportion of time periods within different load ranges; Determining a clustering interval in the load interval according to the proportion of the number of time periods; It is determined whether the fluctuation of the load forecast data meets the requirement based on the number of the aggregation intervals.

[0012] A further technical solution is that, when the number of the aggregation intervals is greater than a preset number of aggregation intervals, it is determined that the fluctuation of the load forecast data does not meet the requirements.

[0013] A further technical solution is that the method for determining the input processing strategy of the long-term energy storage device is: According to the deviation between the short-term energy storage device and the preset energy storage space, determine the deviation between the short-term energy storage device and the lower limit node of the preset energy storage space, and use it as the energy storage space deviation; Based on the fluctuation of the regulation rate of the short-term energy storage device during load regulation processing, determining the variation of the regulation rate of the load regulation demand between different moments, determining the load regulation fluctuation moment based on the variation of the regulation rate at adjacent moments, and determining the rate fluctuation coefficient based on the proportion of the load regulation fluctuation moment in the total number of moments in the load regulation process; The investment processing strategy of the long-term energy storage device is determined based on the energy storage space deviation and the rate fluctuation coefficient.

[0014] A further technical solution is to determine the input processing strategy of the long-term energy storage device based on the energy storage space deviation and the rate fluctuation coefficient, specifically including: When the energy storage space deviation is less than a preset energy storage space deviation threshold or the energy storage capacity of the short-term energy storage device is not within the preset energy storage space, the long-term energy storage device is controlled to be put into processing and the short-term energy storage device is maintained at the preset energy storage capacity; When the energy storage space deviation is not less than a preset energy storage space deviation threshold and the energy storage capacity of the short-term energy storage device is within the preset energy storage space: it is determined whether the rate fluctuation coefficient is greater than the preset fluctuation coefficient threshold. If so, the long-term energy storage device is controlled to be put into operation, and there is no need to charge the energy storage capacity of the short-term energy storage device. If not, there is no need to control the long-term energy storage device to be put into operation.

[0015] A further technical solution is that when the rate fluctuation coefficient is greater than a preset fluctuation coefficient value, the long-term energy storage device is controlled to be put into processing, and the short-term energy storage device is maintained at a preset energy storage capacity.

[0016] A further technical solution is that the preset value of the fluctuation coefficient is greater than a preset fluctuation coefficient threshold.

[0017] On the other hand, an embodiment of the present application provides a computer system having a computer program stored thereon. When the computer program is executed in a computer, the computer is caused to execute the above-mentioned energy storage regulation method of a thermoelectric generator set based on a hybrid energy storage device. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The above and other features and advantages of the present invention will become more apparent by describing in detail exemplary embodiments thereof with reference to the accompanying drawings.

[0019] Figure 1 This is a flow chart of an energy storage regulation method for a thermoelectric generator set based on a hybrid energy storage device according to Example 1.

[0020] Figure 2 It is a flow chart to determine whether the fluctuation of load forecast data meets the requirements; Figure 3 It is a flow chart for determining whether the historical adjustment data within the preset adjustment depth range meets the requirements. DETAILED DESCRIPTION

[0021] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in many ways and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete and will fully convey the concepts of the example embodiments to those skilled in the art. Like reference numerals in the figures represent like or similar structures, and thus their detailed description will be omitted.

[0022] The terms "a", "an", "the", and "said" are used to indicate the presence of one or more elements / components / etc.; the terms "including" and "having" are used to express an open-ended inclusive meaning and mean that additional elements / components / etc. may be present in addition to the listed elements / components / etc.

[0023] Example 1 To solve the above problems, according to one aspect of the present invention, Figure 1 As shown, a method for regulating energy storage of a thermoelectric generator set based on a hybrid energy storage device is provided, which specifically includes: S1 obtains the load forecast data of the thermal power unit at different time periods on the current date, and uses the changes in the load forecast data between different time periods to determine that the fluctuation of the load forecast data does not meet the requirements, and then proceeds to the next step; S2 determines weather data of the region where the thermal power unit is located on different dates within a future preset period, and uses the weather data to determine historical regulation data of the thermal power unit within different regulation depth intervals; S3: When the historical adjustment data within the preset adjustment depth interval meets the requirements, the energy storage capacity of the short-term energy storage device is obtained, and the adjustment flexibility of the short-term energy storage device is determined to meet the requirements by combining the historical adjustment data within different adjustment depth intervals, and then the process proceeds to the next step; S4 utilizes the short-term energy storage device to perform load regulation processing, and determines the input processing strategy of the long-term energy storage device based on the deviation between the short-term energy storage device and the preset energy storage space and the fluctuation of the regulation rate of the short-term energy storage device during the load regulation processing.

[0024] Furthermore, the load forecast data is determined according to weather data of different time periods. Specifically, based on the weather data, a preset mapping model is constructed to determine the load forecast data.

[0025] Specifically, the change of the load forecast data between the time periods includes the change amount of the load forecast data between different time periods.

[0026] It should be noted that if Figure 2 As shown, determining that the fluctuation of the load forecast data meets the requirements specifically includes: Based on the changes in load forecast data between different time periods, determine the proportion of time periods within different load ranges; Determining a clustering interval in the load interval according to the proportion of the number of time periods; It is determined whether the fluctuation of the load forecast data meets the requirement based on the number of the aggregation intervals.

[0027] Further, when the number of the aggregation intervals is greater than the preset number of aggregation intervals, it is determined that the fluctuation of the load forecast data does not meet the requirements.

[0028] Optionally, determining whether the fluctuation of the load forecast data meets the requirements specifically includes: Based on the changes in the load forecast data between different time periods, the proportion of the number of time periods in different load intervals is determined. When there is a load interval with a time period proportion greater than a preset time period proportion, the load interval with a time period proportion greater than the preset time period proportion is used as an aggregation interval. When the number of the aggregation intervals is greater than the preset number of aggregation intervals, it is determined that the fluctuation of the load forecast data does not meet the requirements; When the number of the aggregation intervals is not greater than the preset number of aggregation intervals: Obtaining the number of aggregation intervals, and determining a basic fluctuation coefficient of the load forecast data based on the proportion of the number of time periods of different aggregation intervals, and determining that the fluctuation of the load forecast data does not meet the requirements when the basic fluctuation coefficient does not meet the requirements; When there is no load interval with a time period ratio greater than the preset time period ratio or the basic fluctuation coefficient meets the requirements: Determine the variation of the load forecast data between different adjacent time periods according to the variation of the load forecast data between different adjacent time periods; when the variation of the load forecast data between different adjacent time periods is within a preset variation range, determine that the fluctuation of the load forecast data meets the requirements; When there is a period where the change is not within the preset change range: The period in which the variation is not within the preset variation range is regarded as a load variation period, and when the number of the load variation periods does not meet the requirement, it is determined that the fluctuation of the load forecast data does not meet the requirement; When the number of load change periods meets the requirements: Obtaining the load variation amounts in different load variation periods, and determining the load variation coefficient using the load variation amounts in different load variation periods, and when the load variation coefficient does not meet the requirements, determining that the fluctuation of the load forecast data does not meet the requirements; When the load variation coefficient meets the requirements: A comprehensive fluctuation coefficient is determined based on an average value of the basic fluctuation coefficient and the load variation coefficient, and the comprehensive fluctuation coefficient is used to determine whether the fluctuation of the load forecast data meets the requirements.

[0029] It is understandable that when the fluctuation of the load forecast data meets the requirements, the short-term energy storage device is used to perform energy storage regulation processing of the thermal power unit.

[0030] Specifically, the preset period is determined based on the rated capacity of the short-time energy storage device, wherein the smaller the rated capacity of the short-time energy storage device is, the shorter the preset period is.

[0031] Furthermore, the weather data includes humidity, temperature, wind speed and sunlight.

[0032] It should be noted that the adjustment depth intervals are divided into adjustment depth intervals based on preset adjustment amounts.

[0033] Furthermore, the historical adjustment data is determined based on historical energy storage adjustment data of dates with similar weather conditions on different dates, specifically including the number of historical adjustments and energy storage adjustment amounts for different historical adjustment times.

[0034] Specifically, the similar weather date is a historical date whose deviation from the weather data of the date is within a preset deviation range.

[0035] It should be noted that the energy storage methods of the long-term energy storage device and the short-term energy storage device are different.

[0036] Furthermore, the preset adjustment depth interval is an adjustment depth interval corresponding to the energy storage adjustment amount in the preset adjustment amount interval.

[0037] It is understandable that if Figure 3 As shown, it is determined that the historical adjustment data within the preset adjustment depth range meets the requirements, specifically including: Based on the historical adjustment data within the preset adjustment depth range, determine the historical adjustment times for similar weather dates corresponding to different dates; Determining a frequently adjusted date among the dates based on an average of the number of historical adjustments on dates with similar weather conditions corresponding to different dates; Based on the proportion of the number of the frequently adjusted dates in a future preset period, it is determined whether the historical adjustment data within the preset adjustment depth range meets the requirements.

[0038] Optionally, when the proportion of the number of the frequently adjusted dates in a future preset period is greater than the preset proportion, it is determined that the historical adjustment data within the preset adjustment depth interval does not meet the requirements.

[0039] Furthermore, when the historical adjustment data within the preset adjustment depth range does not meet the requirements, the long-term energy storage device and the short-term energy storage device are simultaneously enabled to perform energy storage adjustment processing on the thermal power unit, and the long-term energy storage device is used to charge the short-term energy storage device so that the short-term energy storage device is maintained at the preset energy storage space.

[0040] Optionally, determining whether historical adjustment data within a preset adjustment depth range meets the requirements specifically includes: S11 determines the number of historical adjustments on dates with similar weather conditions corresponding to different dates based on historical adjustment data within a preset adjustment depth range, and determines the most frequently adjusted dates among the dates based on an average of the number of historical adjustments on dates with similar weather conditions corresponding to different dates; S12 obtains the average value of the historical adjustment times of similar weather dates corresponding to different frequent adjustment dates, and determines the adjustment frequency coefficient of the different frequent adjustment dates in the preset adjustment depth interval in combination with the average value of the historical adjustment times of the corresponding similar weather dates in the adjacent adjustment depth interval of the preset adjustment depth interval; S13 obtains the proportion of the number of frequent adjustment dates in the future preset period, and determines the adjustment frequency value based on the adjustment frequency coefficient of different frequent adjustment dates in the preset adjustment depth range, and determines whether the historical adjustment data in the preset adjustment depth range meets the requirements based on the adjustment frequency value.

[0041] Furthermore, the adjustment frequency value ranges from 0 to 1, and when the adjustment frequency value is greater than a preset frequency threshold, it is determined that the historical adjustment data within the preset adjustment depth interval does not meet the requirements.

[0042] Optionally, the above step S11 includes the following contents: S111 is based on the historical adjustment data within the preset adjustment depth interval. When it is determined that there is no historical adjustment number within the preset adjustment depth interval for similar weather dates corresponding to different dates, it is determined that the historical adjustment data within the preset adjustment depth interval meets the requirements. When there is a date with a historical adjustment number within the preset adjustment depth interval for the corresponding similar weather date, the process proceeds to step S112. S112 selects dates with similar weather conditions and a number of historical adjustments within a preset adjustment depth range as screening dates. When the number of screening dates is less than a preset screening date number threshold, the process proceeds to step S113. When the number of screening dates is not less than the preset screening date number threshold, the process proceeds to step S114. S113: When the historical adjustment times within the preset adjustment depth interval on the similar weather dates corresponding to different screening dates are all within the preset adjustment times interval, it is determined that the historical adjustment data within the preset adjustment depth interval meets the requirements; when there is a screening date on which the historical adjustment times within the preset adjustment depth interval on the corresponding similar weather date are not within the preset adjustment times interval, the process proceeds to step S114; S114 determines the frequently adjusted dates among the dates based on the average value of the number of historical adjustments of similar weather dates corresponding to different dates. When the proportion of the number of frequently adjusted dates is greater than the preset proportion, it is determined that the historical adjustment data within the preset adjustment depth range does not meet the requirements. When the proportion of the number of frequently adjusted dates is not greater than the preset proportion, it goes to step S12.

[0043] Optionally, the above step S12 includes the following contents: S121: obtaining an average value of the number of historical adjustments on similar weather dates corresponding to different frequent adjustment dates, and determining an adjustment frequency coefficient for each of the different frequent adjustment dates in the preset adjustment depth interval in combination with the average value of the number of historical adjustments on the corresponding similar weather dates in adjacent adjustment depth intervals within the preset adjustment depth interval; S122: When there is a frequent adjustment date whose adjustment frequency coefficient does not meet the requirement, it is determined that the historical adjustment data within the preset adjustment depth interval does not meet the requirement; when there is no frequent adjustment date whose adjustment frequency coefficient does not meet the requirement, the process proceeds to step S123; S123: When the average value of the frequency coefficients of the different frequency adjustment dates in the preset depth adjustment interval is within the preset frequency coefficient interval, the process proceeds to step S124; when the average value of the frequency coefficients of the different frequency adjustment dates in the preset depth adjustment interval is not within the preset frequency coefficient interval, the process proceeds to step S13; S124: When the number of frequently adjusted dates is within the preset frequent date number range, it is determined that the historical adjustment data within the preset adjustment depth range does not meet the requirements; when the number of frequently adjusted dates is not within the preset frequent date number range, proceed to step S13.

[0044] Furthermore, when the historical adjustment data within the preset adjustment depth interval does not meet the requirements, the short-term energy storage device is used to perform energy storage adjustment processing on the thermal power unit.

[0045] Specifically, determining whether the adjustment flexibility of the short-term energy storage device meets the requirements specifically includes: Based on the historical adjustment data within different adjustment depth intervals, determine the average value of the historical adjustment times within different adjustment depth intervals for similar weather dates corresponding to different dates; Determine the predicted number of adjustments within different adjustment depth intervals on different dates based on the average of the number of historical adjustments within different adjustment depth intervals on similar weather dates corresponding to different dates; Based on the energy storage space of the short-term energy storage device and the predicted number of adjustments within different adjustment depth intervals on different dates, determining the date on which the energy storage space cannot meet the energy storage adjustment requirement, and using the date as the energy storage adjustment deviation date; Whether the regulation flexibility of the short-term energy storage device meets the requirement is determined according to the proportion of the number of the energy storage regulation deviation dates.

[0046] Furthermore, when the proportion of the number of energy storage adjustment deviation dates does not meet the requirement, it is determined that the adjustment flexibility of the short-term energy storage device does not meet the requirement.

[0047] It should also be noted that when the adjustment flexibility of the short-term energy storage device does not meet the requirements, the long-term energy storage device and the short-term energy storage device are simultaneously activated to perform energy storage adjustment processing of the thermal power unit, and the long-term energy storage device is used to charge the short-term energy storage device so that the short-term energy storage device is maintained at the preset energy storage space.

[0048] Optionally, determining whether the adjustment flexibility of the short-term energy storage device meets the requirements specifically includes: Based on the historical adjustment data within different adjustment depth intervals, determine the average value of the historical adjustment times of similar weather dates corresponding to different dates within different adjustment depth intervals; and determine the predicted adjustment times of different dates within different adjustment depth intervals based on the average value of the historical adjustment times of similar weather dates corresponding to different dates within different adjustment depth intervals; Based on the energy storage space of the short-term energy storage device and the predicted number of adjustments within different adjustment depth intervals on different dates, if it is determined that there is no date on which the energy storage space cannot meet the energy storage adjustment requirements, then it is determined that the adjustment flexibility of the short-term energy storage device meets the requirements; When there is a date when the energy storage space cannot meet the energy storage regulation requirements: The date on which the energy storage space cannot meet the energy storage regulation requirement is used as the energy storage regulation deviation date. When the proportion of the number of energy storage regulation deviation dates does not meet the requirement, it is determined that the regulation flexibility of the short-term energy storage device does not meet the requirement. When the percentage of the energy storage regulation deviation dates meets the requirements: Determining energy storage space deviations for different energy storage adjustment deviation dates based on the energy storage space of the short-term energy storage device and the predicted number of adjustments within different adjustment depth intervals for different energy storage adjustment deviation dates; if there is an energy storage adjustment deviation date where the energy storage space deviation does not meet the requirements, determining that the adjustment flexibility of the short-term energy storage device does not meet the requirements; When there is no energy storage space deviation that does not meet the energy storage adjustment deviation date: The distribution data of different energy storage adjustment deviation dates are determined, and the energy storage adjustment deviation coefficient is determined in combination with the energy storage space deviation amount of different energy storage adjustment deviation dates, and the energy storage adjustment deviation coefficient is used to determine whether the adjustment flexibility of the short-term energy storage device meets the requirements.

[0049] Furthermore, the preset energy storage space is determined according to the product of the rated energy storage space of the short-term energy storage device and the long-term energy storage device and a preset proportional factor.

[0050] Specifically, the method for determining the input processing strategy of the long-term energy storage device is: According to the deviation between the short-term energy storage device and the preset energy storage space, determine the deviation between the short-term energy storage device and the lower limit node of the preset energy storage space, and use it as the energy storage space deviation; Based on the fluctuation of the regulation rate of the short-term energy storage device during load regulation processing, determining the variation of the regulation rate of the load regulation demand between different moments, determining the load regulation fluctuation moment based on the variation of the regulation rate at adjacent moments, and determining the rate fluctuation coefficient based on the proportion of the load regulation fluctuation moment in the total number of moments in the load regulation process; The investment processing strategy of the long-term energy storage device is determined based on the energy storage space deviation and the rate fluctuation coefficient.

[0051] Furthermore, determining the input processing strategy of the long-term energy storage device based on the energy storage space deviation and the rate fluctuation coefficient specifically includes: When the energy storage space deviation is less than a preset energy storage space deviation threshold or the energy storage capacity of the short-term energy storage device is not within the preset energy storage space, the long-term energy storage device is controlled to be put into processing and the short-term energy storage device is maintained at the preset energy storage capacity; When the energy storage space deviation is not less than a preset energy storage space deviation threshold and the energy storage capacity of the short-term energy storage device is within the preset energy storage space: it is determined whether the rate fluctuation coefficient is greater than the preset fluctuation coefficient threshold. If so, the long-term energy storage device is controlled to be put into operation, and there is no need to charge the energy storage capacity of the short-term energy storage device. If not, there is no need to control the long-term energy storage device to be put into operation.

[0052] Furthermore, when the rate fluctuation coefficient is greater than a preset fluctuation coefficient value, the long-term energy storage device is controlled to be put into processing, and the short-term energy storage device is maintained at a preset energy storage capacity.

[0053] It should be noted that the preset value of the fluctuation coefficient is greater than the preset fluctuation coefficient threshold.

[0054] Example 2 On the other hand, an embodiment of the present application provides a computer system having a computer program stored thereon. When the computer program is executed in a computer, the computer is caused to execute the above-mentioned energy storage regulation method of a thermoelectric generator set based on a hybrid energy storage device.

[0055] In the embodiments of the present invention, the term "plurality" refers to two or more, unless otherwise specified. Terms such as "installed," "connected," and "fixed" should be interpreted broadly. For example, "connected" can refer to a fixed connection, a detachable connection, or an integral connection. Those skilled in the art will understand the specific meanings of these terms in the embodiments of the present invention based on specific circumstances.

[0056] In the description of the embodiments of the present invention, it should be understood that the terms "upper" and "lower" and the like indicate directions or positional relationships based on the directions or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the embodiments of the present invention and simplifying the description, rather than indicating or implying that the device or unit referred to must have a specific direction, be constructed and operated in a specific direction. Therefore, they cannot be understood as limitations on the embodiments of the present invention.

[0057] Throughout this specification, terms such as "one embodiment" and "a preferred embodiment" mean that the specific features, structures, materials, or characteristics described in conjunction with that embodiment or example are included in at least one embodiment or example of the present invention. In this specification, schematic representations of these terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

[0058] The above is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations are possible in the present invention. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention are intended to be within the scope of protection of the present invention.

Claims

1. A method for regulating energy storage of a thermoelectric generator set based on a hybrid energy storage device, characterized in that: Specifically include: Obtaining load forecast data of the thermal power unit at different time periods on the current date, and using the changes in the load forecast data between different time periods to determine that the fluctuation of the load forecast data does not meet the requirements, proceeding to the next step; Determining weather data for different dates in a future preset period in the area where the thermal power unit is located, and using the weather data to determine historical regulation data of the thermal power unit in different regulation depth intervals; When the historical adjustment data within the preset adjustment depth interval meets the requirements, the energy storage capacity of the short-term energy storage device is obtained, and the adjustment flexibility of the short-term energy storage device is determined to meet the requirements by combining the historical adjustment data within different adjustment depth intervals, and then the process proceeds to the next step; A short-term energy storage device is used to adjust the load, and the input processing strategy of the long-term energy storage device is determined based on the deviation between the short-term energy storage device and the preset energy storage space and the fluctuation of the adjustment rate of the short-term energy storage device during the load adjustment process.

2. The energy storage regulation method of a thermoelectric generator set based on a hybrid energy storage device according to claim 1, characterized in that: The load forecast data is determined according to weather data of different time periods. Specifically, based on the weather data, a preset mapping model is constructed to determine the load forecast data.

3. The energy storage regulation method for a thermoelectric generator set based on a hybrid energy storage device according to claim 1, characterized in that: The change of the load forecast data between the time periods includes the change amount of the load forecast data between different time periods.

4. The energy storage regulation method for a thermoelectric generator set based on a hybrid energy storage device according to claim 1, characterized in that: Determining that the fluctuation of the load forecast data meets the requirements includes: Based on the changes in load forecast data between different time periods, determine the proportion of time periods within different load ranges; Determining a clustering interval in the load interval according to the proportion of the number of time periods; It is determined whether the fluctuation of the load forecast data meets the requirement based on the number of the aggregation intervals.

5. The energy storage regulation method for a thermoelectric generator set based on a hybrid energy storage device according to claim 4, characterized in that: When the number of the aggregation intervals is greater than the preset number of aggregation intervals, it is determined that the fluctuation of the load forecast data does not meet the requirements.

6. The energy storage regulation method for a thermoelectric generator set based on a hybrid energy storage device according to claim 1, characterized in that: When the fluctuation of the load forecast data meets the requirements, the short-term energy storage device is used to perform energy storage regulation processing on the thermal power unit.

7. The energy storage regulation method for a thermoelectric generator set based on a hybrid energy storage device according to claim 1, characterized in that: The preset period is determined by the rated capacity of the short-time energy storage device, wherein the smaller the rated capacity of the short-time energy storage device is, the shorter the preset period is.

8. The energy storage regulation method for a thermoelectric generator set based on a hybrid energy storage device according to claim 1, characterized in that: The method for determining the input processing strategy of the long-term energy storage device is: According to the deviation between the short-term energy storage device and the preset energy storage space, determine the deviation between the short-term energy storage device and the lower limit node of the preset energy storage space, and use it as the energy storage space deviation; Based on the fluctuation of the regulation rate of the short-term energy storage device during load regulation processing, determining the variation of the regulation rate of the load regulation demand between different moments, determining the load regulation fluctuation moment based on the variation of the regulation rate at adjacent moments, and determining the rate fluctuation coefficient based on the proportion of the load regulation fluctuation moment in the total number of moments in the load regulation process; The investment processing strategy of the long-term energy storage device is determined based on the energy storage space deviation and the rate fluctuation coefficient.

9. The energy storage regulation method for a thermoelectric generator set based on a hybrid energy storage device according to claim 8, characterized in that: Determining a strategy for processing the long-term energy storage device based on the energy storage space deviation and the rate fluctuation coefficient specifically includes: When the energy storage space deviation is less than a preset energy storage space deviation threshold or the energy storage capacity of the short-term energy storage device is not within the preset energy storage space, the long-term energy storage device is controlled to be put into processing and the short-term energy storage device is maintained at the preset energy storage capacity; When the energy storage space deviation is not less than a preset energy storage space deviation threshold and the energy storage capacity of the short-term energy storage device is within the preset energy storage space: it is determined whether the rate fluctuation coefficient is greater than the preset fluctuation coefficient threshold. If so, the long-term energy storage device is controlled to be put into operation, and there is no need to charge the energy storage capacity of the short-term energy storage device. If not, there is no need to control the long-term energy storage device to be put into operation.

10. A computer system having a computer program stored thereon, characterized in that: When the computer program is executed in a computer, the computer is caused to execute the energy storage regulation method of a thermoelectric generator set based on a hybrid energy storage device according to any one of claims 1 to 9.

Images