Unit operation scheduling method and system considering in-plant equipment operation state

Abstract

The invention provides a unit operation scheduling method and system considering the operation state of equipment in a plant, and belongs to the technical field of load scheduling, and the method specifically comprises the steps: determining the load output range of a unit in different time periods in a day based on the load prediction data of the unit in the plant, the method comprises the steps of determining operation fault data of different devices under different peak regulation depths according to a load output range, determining peak regulation reliability coefficients under the different peak regulation depths based on the operation fault data of the different devices under the different peak regulation depths, and determining that the abnormal peak regulation depth is responded when the peak regulation reliability coefficients are used for determining that the abnormal peak regulation depth is responded. On the basis of the distribution data responding to the abnormal peak regulation depth in the time period and the peak regulation reliability coefficient, when it is determined that the peak regulation reliability degree of the time period does not meet the requirement, load data of an adjacent time period in the time period are obtained, and the load scheduling strategy of the time period is determined in combination with the electric load peak regulation data of the time period; therefore, the safety and reliability of peak regulation processing are improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of load scheduling, and particularly relates to a unit operation scheduling method and system considering the operation status of in-plant equipment. Background Art

[0002] During the operation scheduling process of a unit, it often involves various equipment, such as coal mills, fans, boilers, steam turbines, generators, coal feeders, feed water pumps, condensate pumps, high and low pressure heaters. The operation status of different equipment has a great impact on the flexibility of the unit in responding to peak load regulation. If the operation status of different equipment cannot be comprehensively considered during the peak load regulation process, it is impossible to ensure the operation reliability of different equipment in the plant on the basis of ensuring the flexibility of peak load regulation.

[0003] In view of the above technical problems, specifically, the present application provides a unit operation scheduling method and system considering the operation status of in-plant equipment. Summary of the Invention

[0004] To achieve the object of the present invention, the present invention adopts the following technical solutions: A unit operation scheduling method considering the operation status of in-plant equipment specifically includes: S1 Based on the operation data of different types of equipment in the plant, determine the operation failure data and response deviation data of different types of equipment in the plant when responding to electric load peak regulation. When it is determined that there is no equipment with an unsatisfactory operation status based on the operation failure data and response deviation data, proceed to the next step; S2 Based on the load prediction data of the unit in the plant, determine the load output range of the unit at different time periods within a day. According to the load output range, determine the operation failure data of different equipment at different peak regulation depths. Based on the operation failure data of different equipment at different peak regulation depths, determine the peak regulation reliability coefficient at different peak regulation depths. When it is determined that there is an abnormal response peak regulation depth using the peak regulation reliability coefficient, proceed to the next step; S3 When it is determined that the peak regulation reliability degree of the time period does not meet the requirements based on the distribution data of the abnormal response peak regulation depth and the peak regulation reliability coefficient in the time period, obtain the load data of adjacent time periods in the time period, and combine the electric load peak regulation data of the time period to determine the load scheduling strategy of the time period.

[0005] The beneficial effects of the present invention are as follows: Based on the operation failure data of different devices at different peak shaving depths, the peak shaving reliability coefficient and the response abnormal peak shaving depth at different peak shaving depths are determined, so as to realize the determination of the peak shaving reliability at different peak shaving depths according to the operation failure conditions at different peak shaving depths, thus avoiding the technical problem of insufficient reliability of peak shaving processing caused by the operation failure of the device at the peak shaving depth, and improving the reliability of peak shaving processing.

[0006] Using the load data of adjacent time periods in a time period and the electric load peak shaving data of the time period to determine the load scheduling strategy of the time period, not only considering the peak shaving processing requirements of the current time period, making the load scheduling strategy of the current time period able to meet the historical peak shaving requirements as much as possible, but also further combining the load data of adjacent time periods, so that the load fluctuation between the current time period and adjacent time periods is controlled, ensuring the reliability of unit peak shaving processing and the stability of operation.

[0007] A further technical solution is that the device includes a coal mill, a blower, a boiler, a steam turbine, a generator, a coal feeder, a feed water pump, a condensate pump, high and low pressure heaters.

[0008] A further technical solution is that the operation failure data includes the number of peak shaving times with fault alarm data and the fault alarm type when the device responds to electric load peak shaving processing.

[0009] A further technical solution is that the response deviation data includes the number of peak shaving times and the response duration when the device has a response deviation when responding to electric load peak shaving processing.

[0010] A further technical solution is that the method for determining the load scheduling strategy of the time period is as follows: Using the load data of adjacent time periods of the time period and the load prediction data of the time period, determine the load fluctuation amount with adjacent time periods under different load regulation amounts, and use the load fluctuation amount with adjacent time periods to determine the load fluctuation coefficient under different load regulation amounts; Based on the electric load peak shaving data of the time period, determine the number of peak shaving times at different peak shaving depths in the time period, and combine the matching situation between different load regulation amounts and peak shaving depths to determine the load regulation matching coefficient under different load regulation amounts; According to the load fluctuation coefficient and the load regulation matching coefficient, determine the load regulation priority coefficient under different load regulation amounts, and use the load regulation priority coefficient to determine the load regulation amount of the time period, and perform the load scheduling processing of the time period according to the load regulation amount and the load prediction data.

[0011] A further technical solution lies in that the load fluctuation amount is the deviation amount between the sum of the load adjustment amount and the load prediction data and the load data in the adjacent time period.

[0012] A further technical solution lies in that the load adjustment matching coefficient is determined according to the proportion of the number of peak shaving times that the load adjustment amount can meet the peak shaving depth.

[0013] On the other hand, an embodiment of the present application provides a computer system, on which a computer program is stored. When the computer program is executed on a computer, the computer is made to execute the above-mentioned unit operation scheduling method considering the operation state of in-plant equipment.

[0014] On the other hand, an embodiment of the present application provides a computer program product, characterized in that the computer program product stores instructions, and when the instructions are executed by a computer, the computer is made to implement the above-mentioned unit operation scheduling method considering the operation state of in-plant equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] By referring to the drawings and describing in detail its exemplary embodiments, the above and other features and advantages of the present invention will become more obvious.

[0016] Figure 1 is a flowchart of a unit operation scheduling method considering the operation state of in-plant equipment according to Embodiment 1.

[0017] Figure 2 is a flowchart for judging whether the operation state of the equipment meets the requirements; Figure 3 is a flowchart of a method for determining the peak shaving reliability coefficient under the peak shaving depth. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0018] Now, exemplary embodiments will be described more fully with reference to the accompanying drawings. However, the exemplary embodiments can be implemented in various ways and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that the present invention will be thorough and complete, and will fully convey the concept of the exemplary embodiments to those skilled in the art. The same reference numerals in the drawings denote the same or similar structures, and thus their detailed descriptions will be omitted.

[0019] The terms "a", "an", "the", and "said" are used to denote the presence of one or more elements / components / etc.; the terms "comprising" and "having" are used to denote an open inclusion meaning and mean that there may be additional elements / components / etc. in addition to the listed elements / components / etc.

[0020] Embodiment 1 To solve the above problems, according to one aspect of the present invention, asFigure 1 As shown in the figure, a unit operation scheduling method considering the operation status of in-plant equipment is provided, specifically including: S1 Based on the operation data of different types of equipment in the plant, determine the operation failure data and response deviation data of different types of equipment in the plant when responding to electric load peak shaving processing. When it is determined that there is no equipment with an unsatisfactory operation status based on the operation failure data and response deviation data, proceed to the next step; S2 Based on the load prediction data of the unit in the plant, determine the load output range of the unit at different time periods within a day. According to the load output range, determine the operation failure data of different equipment at different peak shaving depths. Based on the operation failure data of different equipment at different peak shaving depths, determine the peak shaving reliability coefficient at different peak shaving depths. When it is determined that there is an abnormal response peak shaving depth using the peak shaving reliability coefficient, proceed to the next step; S3 When it is determined that the peak shaving reliability degree of the time period does not meet the requirements based on the distribution data of the abnormal response peak shaving depth and the peak shaving reliability coefficient in the time period, obtain the load data of adjacent time periods in the time period, and combine the electric load peak shaving data of the time period to determine the load scheduling strategy of the time period.

[0021] Further, the equipment includes coal mills, fans, boilers, steam turbines, generators, coal feeders, feed water pumps, condensate pumps, high and low pressure heaters.

[0022] Specifically, the operation failure data includes the number of peak shaving times with fault alarm data and the type of fault alarm when the equipment responds to electric load peak shaving processing.

[0023] It should be noted that the response deviation data includes the number of peak shaving times with response deviation and the response duration when the equipment responds to electric load peak shaving processing.

[0024] It can be understood that as Figure 2 shown in the figure, determining whether the operation status of the equipment meets the requirements specifically includes: Using the operation failure data of the equipment, determine the number of peak shaving times with fault alarm data when the equipment responds to electric load peak shaving processing, and use it as the number of fault peak shaving times. Based on the proportion of the number of times of the fault peak shaving times, determine the proportion of the number of fault times of the equipment; According to the response deviation data of the equipment, determine the number of peak shaving times with response deviation when the equipment responds to electric load peak shaving processing, and use it as the number of response deviation peak shaving times. Based on the proportion of the number of times of the response deviation peak shaving times, determine the proportion of the number of response deviation times of the equipment; Determine the abnormal state coefficient of the device based on the average of the proportion of response deviation times and the proportion of failure times of the device, and use the abnormal state coefficient to determine whether the operating state of the device meets the requirements.

[0025] Further, when the abnormal state coefficient of the device is greater than the preset abnormal coefficient threshold, it is determined that the operating state of the device does not meet the requirements.

[0026] In addition, it can be understood that when there is a device whose operating state does not meet the requirements, the load scheduling strategy for different time periods is determined according to the load output range and historical electric load peak shaving data for different time periods.

[0027] In one of the embodiments, determining the load scheduling strategy for different time periods according to the load output range and historical electric load peak shaving data for different time periods specifically includes: Determine the proportion of historical peak shaving times corresponding to the peak shaving depth interval based on the historical electric load peak shaving data for different time periods, and use the peak shaving depth interval with the proportion of historical peak shaving times greater than the preset proportion as the selected peak shaving interval; Determine the load output demand range for different time periods based on the maximum peak shaving depth corresponding to the selected peak shaving interval and the load output range, and use the load output demand range to determine the load scheduling strategy for the time period.

[0028] In another possible embodiment, determining whether the operating state of the device meets the requirements specifically includes: Using the operating failure data of the device, determine the number of peak shaving times with fault alarm data when the device responds to the electric load peak shaving process, and use it as the fault peak shaving times. When the fault peak shaving times do not meet the requirements, it is determined that the operating state of the device does not meet the requirements; When the fault peak shaving times meet the requirements: Based on the proportion of the number of times of the fault peak shaving times, determine the proportion of the number of failures of the device. When the proportion of the number of failures of the device does not meet the requirements, it is determined that the operating state of the device does not meet the requirements; When the proportion of the number of failures of the device meets the requirements: According to the response deviation data of the device, determine the number of peak shaving times with response deviation when the device responds to the electric load peak shaving process, and use it as the response deviation peak shaving times. When the response deviation peak shaving times of the device do not meet the requirements, it is determined that the operating state of the device does not meet the requirements; When the response deviation times of the device meet the requirements: Determine the proportion of the number of response deviation peak shaving times of the device based on the proportion of the number of times of the response deviation peak shaving times. When the proportion of the number of response deviation times of the device does not meet the requirements, it is determined that the operating state of the device does not meet the requirements; When the proportion of the number of response deviation times of the device meets the requirements: Determine the fault peak shaving coefficient of the device based on the number of fault peak shaving times and the proportion of the number of fault times of the device. When the fault peak shaving coefficient of the device does not meet the requirements, it is determined that the operating state of the device does not meet the requirements; When the fault peak shaving coefficient of the device meets the requirements: Determine the response deviation peak shaving coefficient of the device based on the number of response deviation peak shaving times and the proportion of the number of response deviation times of the device. When the response deviation peak shaving coefficient of the device does not meet the requirements, it is determined that the operating state of the device does not meet the requirements; When the response deviation peak shaving coefficient of the device meets the requirements: Determine the comprehensive abnormal peak shaving coefficient of the device based on the average value of the fault peak shaving coefficient and the response deviation peak shaving coefficient of the device, and use the comprehensive abnormal peak shaving coefficient to determine whether the operating state of the device meets the requirements.

[0029] Further, the load output range of the time period is determined according to the load prediction data of the time period. Specifically, it is determined by constructing a load output range based on the load prediction values at different times in the time period.

[0030] Specifically, as Figure 3 shown, the method for determining the peak shaving reliability coefficient at the peak shaving depth is: Determine the operation fault data of different devices at the peak shaving depth under the load processing range based on the operation fault data of different devices at the peak shaving depth; Take the devices with operation fault data at the peak shaving depth under the load processing range as the screened fault devices; Determine the peak shaving reliability coefficient at the peak shaving depth based on the proportion of the number of the screened fault devices in the devices.

[0031] Further, the method for determining the peak shaving reliability coefficient at the peak shaving depth is: Take the difference between the preset value and the proportion of the number of the screened fault devices in the devices as the peak shaving reliability coefficient at the peak shaving depth.

[0032] Optionally, the value range of the peak shaving reliability coefficient at the peak shaving depth is between 0 and 1. When the peak shaving reliability coefficient at the peak shaving depth is not greater than the preset reliability coefficient, it is determined that the peak shaving depth is the response abnormal peak shaving depth.

[0033] In another embodiment, the method for determining the peak shaving reliability coefficient at the peak shaving depth is as follows: Based on the operation failure data of different devices at the peak shaving depth, determine the operation failure data of different devices at the peak shaving depth within the load processing range. When there is no operation failure data for different devices at the peak shaving depth within the load output range, it is determined that the peak shaving depth does not belong to the response abnormal peak shaving depth; When there are devices with operation failure data at the peak shaving depth within the load output range: Obtain the number of operation failures at the peak shaving depth within the load output range. When the number of operation failures at the peak shaving depth within the load output range meets the requirements, it is determined that the peak shaving depth does not belong to the response abnormal peak shaving depth; When the number of operation failures at the peak shaving depth within the load output range does not meet the requirements, use the devices with operation failure data at the peak shaving depth within the load output range as the screened failure devices. When the number of the screened failure devices meets the requirements: Based on the operation failure data of different screened failure devices at the peak shaving depth within the load output range, determine the number of failures of different screened failure devices at the peak shaving depth within the load output range, and determine the total number of failures. When the total number of failures meets the requirements, it is determined that the peak shaving depth does not belong to the response abnormal peak shaving depth; When the total number of failures does not meet the requirements: Based on the number of failures of different screened failure devices at the peak shaving depth within the load output range, determine the failure abnormal coefficient of different screened failure devices. When there are no screened failure devices with a failure abnormal coefficient not meeting the requirements, it is determined that the peak shaving depth does not belong to the response abnormal peak shaving depth; When the number of the screened failure devices does not meet the requirements or there are screened failure devices with a failure abnormal coefficient not meeting the requirements: Determine the comprehensive abnormal coefficient based on the sum of the failure abnormal coefficients of different screened failure devices, and use the difference between the preset value and the comprehensive abnormal coefficient to determine the peak shaving reliability coefficient at the peak shaving depth.

[0034] Furthermore, the determination that the peak shaving reliability degree of the time period does not meet the requirements specifically includes: Based on the distribution data of the response abnormal peak shaving depth in the time period, determine the number of the response abnormal peak shaving depth in the time period; Based on the number of the response abnormal peak shaving depth and the peak shaving reliability coefficient of different response abnormal peak shaving depths, determine the peak shaving deviation coefficient in the time period; Determine whether the peak shaving reliability of the time period meets the requirements according to the peak shaving deviation coefficient.

[0035] Optionally, the method for determining the peak shaving deviation coefficient in the time period is as follows: Determine the preset deviation coefficient corresponding to the time period based on the number of abnormal response peak shaving depths in the time period; Determine the peak shaving deviation coefficient in the time period according to the ratio of the preset deviation coefficient to the average value of the peak shaving reliability coefficients of different abnormal response peak shaving depths.

[0036] Further, when the peak shaving deviation coefficient of the time period is greater than the preset deviation coefficient, it is determined that the peak shaving reliability of the time period does not meet the requirements.

[0037] In one possible embodiment, determining that the peak shaving reliability of the time period does not meet the requirements specifically includes: Determine the number of abnormal response peak shaving depths in the time period based on the distribution data of the abnormal response peak shaving depths in the time period. When the number of abnormal response peak shaving depths in the time period does not meet the requirements, it is determined that the peak shaving reliability of the time period does not meet the requirements; When the number of abnormal response peak shaving depths in the time period meets the requirements: Based on the peak shaving reliability coefficients of the abnormal response peak shaving depths in the time period, when it is determined that there is an abnormal response peak shaving depth with a peak shaving reliability coefficient less than the preset reliability threshold, it is determined that the peak shaving reliability of the time period does not meet the requirements; When there is no abnormal response peak shaving depth with a peak shaving reliability coefficient not less than the preset reliability threshold: When the number of abnormal response peak shaving depths in the time period is within the preset peak shaving depth quantity range: Obtain the average value of the peak shaving reliability coefficients of different response peak shaving depths. When the average value of the peak shaving reliability coefficients of different response peak shaving depths does not meet the requirements, it is determined that the peak shaving reliability of the time period does not meet the requirements; When the number of abnormal response peak shaving depths in the time period is not within the preset peak shaving depth quantity range or the average value of the peak shaving reliability coefficients of different response peak shaving depths meets the requirements: Determine the distribution dispersion coefficient of the abnormal response peak shaving depths in the time period based on the interval distance between the abnormal response peak shaving depths in the time period. When the distribution dispersion coefficient of the abnormal response peak shaving depths in the time period does not meet the requirements, it is determined that the peak shaving reliability of the time period does not meet the requirements; When the distribution dispersion coefficient of the abnormal response peak shaving depths in the time period meets the requirements: Determine the peak - shaving deviation coefficient in the time period based on the quantity of the response abnormal peak - shaving depth and the peak - shaving reliability coefficients of different response abnormal peak - shaving depths; Determine the comprehensive deviation coefficient according to the product of the peak - shaving deviation coefficient and the distribution dispersion coefficient, and use the comprehensive deviation coefficient to determine whether the peak - shaving reliability degree in the time period meets the requirements.

[0038] Furthermore, the method for determining the load scheduling strategy in the time period is as follows: Based on the load data of the adjacent time period of the time period and the load prediction data of the time period, determine the load fluctuation quantity with the adjacent time period under different load regulation amounts, and use the load fluctuation quantity with the adjacent time period to determine the load fluctuation coefficient under different load regulation amounts; Based on the electric load peak - shaving data of the time period, determine the peak - shaving times of different peak - shaving depths in the time period, and combine the matching situation between different load regulation amounts and the peak - shaving depth to determine the load regulation matching coefficient under different load regulation amounts; According to the load fluctuation coefficient and the load regulation matching coefficient, determine the load regulation priority coefficient under different load regulation amounts, and use the load regulation priority coefficient to determine the load regulation amount in the time period, and perform load scheduling processing for the time period according to the load regulation amount and the load prediction data.

[0039] Specifically, the load fluctuation quantity is the deviation quantity between the sum of the load regulation amount and the load prediction data and the load data of the adjacent time period.

[0040] It should be noted that the load regulation matching coefficient is determined according to the proportion of the peak - shaving times that the load regulation amount can meet the peak - shaving depth.

[0041] Embodiment 2 On the other hand, an embodiment of the present application provides a computer system, on which a computer program is stored. When the computer program is executed on a computer, the computer is made to execute the above - mentioned unit operation scheduling method considering the operation state of in - plant equipment.

[0042] Embodiment 3 On the other hand, an embodiment of the present application provides a computer program product, characterized in that the computer program product stores instructions, and when the instructions are executed by a computer, the computer is made to implement the above - mentioned unit operation scheduling method considering the operation state of in - plant equipment.

[0043] In the embodiments of the present invention, the term "a plurality of" refers to two or more, unless otherwise clearly defined. Terms such as "mounted", "connected", "fixed", etc. should be understood in a broad sense. For example, "connected" can be a fixed connection, a detachable connection, or an integral connection. For those of ordinary skill in the art, the specific meanings of the above terms in the embodiments of the present invention can be understood according to specific circumstances.

[0044] In the description of the embodiments of the present invention, it should be understood that the orientation or positional relationship indicated by terms such as "upper", "lower", etc. is based on the orientation or positional relationship shown in the drawings. It is 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 orientation. Therefore, it should not be construed as a limitation to the embodiments of the present invention.

[0045] In the description of this specification, the description of terms such as "an embodiment", "a preferred embodiment", etc. means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the embodiments of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or instance. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0046] The above are only the preferred embodiments of the embodiments of the present invention and are not used to limit the embodiments of the present invention. For those skilled in the art, various changes and modifications can be made to the embodiments of the present invention. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the embodiments of the present invention shall be included within the protection scope of the embodiments of the present invention.

Claims

1. A unit operation scheduling method considering the operating status of equipment in a plant, characterized in that: Specifically include: Based on the operation data of different types of equipment in the factory, determine the operation fault data and response deviation data of the different types of equipment in the factory when responding to the electric load peak regulation process, and when it is determined based on the operation fault data and the response deviation data that there is no equipment whose operation status does not meet the requirements, proceed to the next step; Based on the load forecast data of the units in the plant, determine the load output range of the units in different time periods within the day, determine the operation fault data of different equipment at different peak-shaving depths according to the load output range, determine the peak-shaving reliability coefficient at different peak-shaving depths based on the operation fault data of different equipment at different peak-shaving depths, and when it is determined by using the peak-shaving reliability coefficient that there is a peak-shaving depth with abnormal response, proceed to the next step; Based on the distribution data of the abnormal peak-shaving depth in response to the time period and the peak-shaving reliability coefficient, when it is determined that the peak-shaving reliability of the time period does not meet the requirements, the load data of the adjacent time periods in the time period are obtained, and the load scheduling strategy of the time period is determined in combination with the electric load peak-shaving data of the time period.

2. The unit operation scheduling method considering the operating status of the equipment in the plant as claimed in claim 1 is characterized in that: The equipment includes a coal mill, a fan, a boiler, a steam turbine, a generator, a coal feeder, a feed water pump, a condensate pump, and high and low pressure heaters.

3. The unit operation scheduling method considering the operating status of the equipment in the plant as claimed in claim 1 is characterized in that: The operation fault data includes the peak load times and fault alarm types of the fault alarm data when the device responds to the peak load load processing.

4. The unit operation scheduling method considering the operating status of the equipment in the plant as claimed in claim 1 is characterized in that: The response deviation data includes the number of peak-shaving times and the response duration when the device has a response deviation when responding to the peak-shaving process of the electric load.

5. The unit operation scheduling method considering the operation status of the equipment in the plant as claimed in claim 1 is characterized in that: Determining whether the operating status of the device meets the requirements specifically includes: Using the operation fault data of the device, determine the peak load times of the device in response to the peak load load regulation process when there is a fault alarm data, and use it as the fault peak load times, and determine the fault times ratio of the device based on the times ratio of the fault peak load times; According to the response deviation data of the device, the number of peak-shaving times when the device responds to the peak-shaving process of the electric load with response deviation is determined, and the number is used as the number of peak-shaving times of the response deviation, and the proportion of the number of peak-shaving times of the response deviation is determined based on the proportion of the number of peak-shaving times of the response deviation; Based on the average value of the proportion of response deviation times and the proportion of failure times of the device, the abnormal state coefficient of the device is determined, and the abnormal state coefficient is used to determine whether the operating state of the device meets the requirements.

6. The unit operation scheduling method considering the operation status of the equipment in the plant as claimed in claim 5, characterized in that: When there is equipment whose operating status does not meet the requirements, the load dispatching strategy for different time periods is determined based on the load output range in different time periods and the historical power load peak regulation data.

7. The method for dispatching unit operation considering the operating status of the equipment in the plant as claimed in claim 5, characterized in that: Determine the load dispatching strategy for different periods of time based on the load output range and historical load peak load data in different periods of time, including: Determine the proportion of historical peak-shaving times corresponding to the peak-shaving depth interval based on the historical electricity load peak-shaving data of different periods, and use the peak-shaving depth interval with a historical peak-shaving times proportion greater than the preset proportion as the screening peak-shaving interval; The maximum peak-shaving depth corresponding to the screened peak-shaving interval and the load output range are used to determine the load output demand range of different time periods, and the load dispatching strategy of the time period is determined using the load output demand range.

8. The unit operation scheduling method considering the operation status of the equipment in the plant as claimed in claim 1, characterized in that: The method for determining the load dispatching strategy for the period is: Determine the load fluctuation amount of the adjacent time period under different load adjustment amounts by using the load data of the adjacent time period and the load forecast data of the time period, and determine the load fluctuation coefficient under different load adjustment amounts by using the load fluctuation amount of the adjacent time period; Based on the peak load regulation data of the time period, determine the peak regulation times of different peak regulation depths in the time period, and determine the load regulation matching coefficients under different load regulation amounts in combination with the matching conditions of the peak regulation depths under different load regulation amounts; According to the load fluctuation coefficient and the load regulation matching coefficient, the load regulation priority coefficient under different load regulation amounts is determined, and the load regulation amount of the time period is determined using the load regulation priority coefficient, and the load scheduling processing of the time period is performed according to the load regulation amount and load forecast data.

9. The method for dispatching unit operation considering the operating status of the equipment in the plant according to claim 8, characterized in that: The load fluctuation amount is the sum of the load adjustment amount and the load forecast data, and the deviation from the load data in the adjacent time period.

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 a unit operation scheduling method taking into account the operating status of equipment within a plant as described in any one of claims 1 to 9.

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