Power plant flexibility reforming method, device, equipment and medium based on energy end

Abstract

The application provides a method and device for flexible transformation of thermal power based on energy consumption end, equipment and medium, relates to the technical field of thermal power climbing optimization, and comprises the following steps: obtaining load monitoring data of the energy consumption end in a T-1 time period to form a time-measured load curve; obtaining load planning data of the energy consumption end in a T time period to form a time-planning load curve; obtaining climbing auxiliary demand evaluation parameters according to measured climbing data of the energy consumption end in the T-1 time period and planning climbing data in the T time period based on the time-measured load curve and the time-planning load curve; determining total auxiliary climbing energy storage called in climbing planning in the T time period according to the climbing auxiliary demand evaluation parameters; and obtaining a climbing strategy in the T time period based on monitoring values of a temperature sensor, the time-planning load curve and the called total auxiliary climbing energy storage. The application has the advantages of considering the reliability of thermal power climbing under the assistance of an energy storage system and the loss of the energy storage system.

Description

Technical Field

[0001] This invention relates to the field of thermal power plant ramp-up optimization technology, and more specifically, to methods, apparatus, equipment, and media for the flexible transformation of thermal power plants based on energy consumption. Background Technology

[0002] In recent years, the pressure on power systems to regulate peak loads and frequencies has increased significantly, and thermal power units are an important component of the power grid.

[0003] Existing methods for improving the flexibility of thermal power plants mainly focus on boiler combustion optimization, turbine regulation modification, and unit start-up and shutdown process optimization. While these methods can improve the ramp-up speed and flexibility of the units to some extent, they lack a dynamic adjustment and control mechanism that integrates with the actual characteristics of the energy-consuming side, making it difficult to balance the amount of energy storage used. For example, insufficient energy storage usage may lead to delayed unit response and inability to meet system regulation needs. However, excessive use of energy storage increases the number of charge-discharge cycles and losses, reducing its service life. It may also result in insufficient available capacity for subsequent larger load fluctuations due to excessive single-time usage.

[0004] Therefore, existing technologies urgently need to be optimized for thermal power plant retrofitting based on the load characteristics of the energy consumption end, so as to balance the reliability of thermal power plant ramp-up with the assistance of energy storage system and the loss of energy storage system. Summary of the Invention

[0005] The purpose of this invention is to provide a method, apparatus, equipment and medium for the flexible transformation of thermal power plants based on the energy consumption end, which can take into account both the reliability of thermal power plant ramping with the assistance of energy storage system and the loss of energy storage system.

[0006] This invention is achieved through the following technical solution:

[0007] The method for adapting thermal power plants to their energy consumption side includes the following steps:

[0008] Obtain load monitoring data from the energy-consuming end during the T-1 time period to form a time-measured load curve;

[0009] Obtain the load planning data of the energy consumption end in the Tth time period to form a time-planned load curve;

[0010] Based on the time-measured load curve and the time-planned load curve, the climbing auxiliary demand evaluation parameters are obtained according to the measured ramping data of the energy consumption end in the T-1 time period and the planned ramping data in the T time period. The ramping auxiliary demand evaluation parameters are used to quantify the demand for total auxiliary ramping energy storage.

[0011] The total auxiliary climbing energy storage to be used in the climbing planning of the T-th time period is determined based on the climbing auxiliary demand evaluation parameters.

[0012] Temperature sensors are installed at multiple points in the thermal power system. The ramping strategy for the T-time period is obtained based on the monitoring values ​​of the temperature sensors, the time-planned load curve, and the total auxiliary ramping energy storage called up.

[0013] Preferably, the method for obtaining the climbing assistance demand evaluation parameters is as follows:

[0014] Based on the time-measured load curve, obtain the actual load ramp number N of the energy-consuming end in the T-1 time period and the total power difference of the nth ramp. , ;

[0015] Based on the time-planned load curve, obtain the number of planned load ramp-ups M at the energy consumption end in the T-time period, and the total power difference of the m-th ramp-up. , ;

[0016] Based on M and The magnitude of the value, and the degree of increase of M relative to N, and relatively The degree of increase determines the climbing assistance demand evaluation parameter. The larger the value and the greater the degree of increase, the higher the climbing assistance demand evaluation parameter, and the more total auxiliary climbing energy is called up.

[0017] Preferably, the method for determining the climbing assistance demand evaluation parameters is as follows:

[0018] ;

[0019] ;

[0020] ;

[0021] in, Here, A and B are the parameters for evaluating the climbing auxiliary demand, and max is the function for finding the maximum value. This is a tolerance value for the number of climbs within a time period, set based on experience. This is an empirically set power tolerance value for a single climb within a time period. For the The average value, For the The average value.

[0022] Preferably, the method for determining the total auxiliary climbing energy storage to be used in the climbing plan for time period T is as follows:

[0023] The proportion of total auxiliary climbing energy storage is determined based on the climbing auxiliary demand evaluation parameters. ;

[0024] Calculate the total auxiliary climbing energy storage :

[0025] ;

[0026] in, This represents the total power difference during the m-th ramp in the planned load ramping process of the energy-consuming end in the T-th time period.

[0027] Preferably, the proportion of the total auxiliary climbing energy storage is determined. The method is as follows:

[0028] Mapping the climbing auxiliary demand evaluation parameters to [0,1] yields... This achieves normalization.

[0029] Obtain the percentage :

[0030] ;

[0031] Where exp represents the natural exponential function, and k is a coefficient controlling the steepness of the function. To control the proportion corresponding to 0.5 Numerical parameters.

[0032] Preferably, the method for obtaining the climbing strategy for the Tth time period is to solve the climbing strategy for each time period through iterative optimization, as follows:

[0033] Initialize the climbing sequence number m=1, and initialize the remaining auxiliary climbing energy storage of the climbing. Energy storage for the total auxiliary climbing. ;

[0034] Perform the following steps until you obtain the strategy for all the climbs:

[0035] Temperatures at various points were collected at the first and second time points, respectively, representing the time remaining from the start of the m-th climb. Seconds and At the second;

[0036] The maximum local fatigue increment of the thermal power unit during the m-th uphill climb is calculated based on the temperature at each location. ;

[0037] Based on the local maximum fatigue increment during the m-th climb. Remaining auxiliary climbing energy storage, and the total power difference of the m-th climb in the T-th time period. The prescribed climbing time and the maximum gradeability of thermal power units Establish the optimization function:

[0038] Establish an objective function, which is to minimize the value of J:

[0039] ;

[0040] ;

[0041] ;

[0042] Establish constraints:

[0043] ;

[0044] ;

[0045] in, and These represent the ramp-up costs of energy storage and thermal power units, respectively, with exp representing the natural exponential function. The actual climbing rate of the thermal power unit during the m-th climb is given. For the m-th climb, according to The time spent climbing the hill. For based on The calculated auxiliary climbing energy storage for the m-th climb is used. To control the coefficient of steepness, For a control ratio of 0.5, the corresponding Numerical parameters;

[0046] Solving based on optimization function ;

[0047] Update m to the current value plus 1, update Subtract from the current value .

[0048] Preferably, the calculation of the local maximum fatigue increment of the m-th ramp of the thermal power unit is... The method is as follows:

[0049] Based on the mapping relationship between thermal stress and temperature, the maximum thermal stress at the second moment is obtained. and maximum thermal stress The corresponding point at the first moment of thermal stress :

[0050] ;

[0051] ;

[0052] in, Let h be the temperature at the second time point. , and These represent the elastic modulus, coefficient of linear expansion, and Poisson's ratio of the material at the corresponding points. For reference temperature, To achieve maximum thermal stress The temperature at the point at the first moment, To find the maximum value based on the change of h;

[0053] Calculate the local maximum fatigue increment :

[0054] ;

[0055] in, and These are the weights for the influence of stable thermal stress and the weights for the influence of transient thermal stress, respectively. This represents the power value of the corresponding material fatigue life curve.

[0056] This invention also provides a device for the flexible retrofitting of thermal power plants based on the energy consumption end, applied to the above-mentioned method for the flexible retrofitting of thermal power plants based on the energy consumption end, comprising:

[0057] The first data acquisition module is used to acquire load monitoring data from the energy consumption end during the T-1 time period and form a time-measured load curve.

[0058] The second data acquisition module is used to acquire the load planning data of the energy consumption end in the T-time period and form a time-planned load curve;

[0059] The ramp-up auxiliary demand evaluation parameter calculation module is used to obtain ramp-up auxiliary demand evaluation parameters based on the time-measured load curve and the time-planned load curve, according to the measured ramp-up data of the energy-consuming end in the T-1 time period and the planned ramp-up data in the T time period. The ramp-up auxiliary demand evaluation parameters are used to quantify the degree of demand for total auxiliary ramp-up energy storage.

[0060] The total auxiliary climbing energy storage acquisition module is used to determine the total auxiliary climbing energy storage to be called in the climbing planning of the T-th time period based on the climbing auxiliary demand evaluation parameters.

[0061] The ramping strategy acquisition module is used to set up temperature sensors at multiple points in the thermal power system and acquire the ramping strategy for the T-th time period based on the monitoring values ​​of the temperature sensors, the time-planned load curve, and the total auxiliary ramping energy storage called.

[0062] The present invention also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor is used to execute the computer program to implement the above-described method for the flexible transformation of thermal power plants based on energy consumption.

[0063] The present invention also provides a readable storage medium storing a computer program, which, when executed by a processor, implements the above-described method for the flexible transformation of thermal power plants based on energy consumption.

[0064] The technical solution of the present invention has at least the following advantages and beneficial effects:

[0065] This method is based on the measured load and planned load curves of the energy-consuming end, combined with historical and current ramp-up data, to quantitatively obtain ramp-up auxiliary demand evaluation parameters, thereby reasonably determining the energy storage call amount in the T-time period, avoiding excessive or insufficient call caused by setting the proportion or amount of energy storage call based on experience in traditional methods.

[0066] By quantitatively calculating the climbing assistance demand and formulating climbing strategies, this invention can prevent the energy release of energy storage from exceeding the actual demand, avoid the problems of decreased energy utilization and reduced operating cost-effectiveness, reduce ineffective charging and discharging operations of energy storage equipment, reduce the number of cycles, extend the service life of energy storage system, and retain sufficient energy margin to cope with subsequent larger-scale load fluctuations.

[0067] This invention comprehensively considers the energy storage call-up amount and the temperature monitoring results of key parts of the unit in the ramp-up strategy, which can effectively reduce the impact of thermal stress during the ramp-up stage, reduce the risk of equipment wear, and extend the service life of the unit.

[0068] This invention is reasonably designed, easy to implement, and can be applied to various energy sources to optimize energy control strategies, making it easy to promote and implement. Attached Figure Description

[0069] Figure 1 This is a flowchart illustrating the method for the flexible retrofitting of thermal power plants based on the energy consumption end, as provided in Embodiment 1 of the present invention.

[0070] Figure 2 This is a schematic diagram of the structure of the thermal power plant flexibility modification device based on the energy consumption end provided in Embodiment 2 of the present invention. Detailed Implementation

[0071] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0072] Example 1

[0073] This embodiment provides a method for the flexible retrofitting of thermal power plants based on energy consumption. (See also...) Figure 1 This includes the following steps:

[0074] Step S1: Obtain load monitoring data of the energy-consuming end in the T-1 time period to form a time-measured load curve;

[0075] Obtain the load planning data of the energy consumption end in the Tth time period to form a time-planned load curve.

[0076] Step S2: Based on the time-measured load curve and the time-planned load curve, obtain the climbing auxiliary demand evaluation parameters according to the measured ramping data of the energy consumption end in the T-1 time period and the planned ramping data in the T time period. The ramp auxiliary demand evaluation parameters are used to quantify the demand for total auxiliary ramping energy storage.

[0077] In this embodiment, the method for obtaining the climbing assistance demand evaluation parameters is as follows:

[0078] Based on the time-measured load curve, obtain the actual load ramp number N of the energy-consuming end in the T-1 time period and the total power difference of the nth ramp. , ;

[0079] Based on the time-planned load curve, obtain the number of planned load ramp-ups M at the energy consumption end in the T-time period, and the total power difference of the m-th ramp-up. , ;

[0080] Based on M and The magnitude of the value, and the degree of increase of M relative to N, and relatively The degree of increase determines the climbing assistance demand evaluation parameter. The larger the value and the greater the degree of increase, the higher the climbing assistance demand evaluation parameter, and the more total auxiliary climbing energy is called up.

[0081] It should be noted that there are two scenarios for climbing: ascending and descending. The total power difference for climbing in the above schemes refers to the absolute value of the climbing power.

[0082] Based on this, the method for determining the evaluation parameters of the climbing assistance demand is as follows:

[0083] ;

[0084] ;

[0085] ;

[0086] in, Here, A and B are the parameters for evaluating the climbing auxiliary demand, and max is the function for finding the maximum value. This is an empirically set tolerance value for the number of climbs within a time period, used to control the normal fluctuation range. This is an empirically set power tolerance value for a single climb within a time period. For the The average value, For the The average value.

[0087] Based on the above design, when the planned number of climbs M increases too much relative to N, or the average value of the power difference of a single climb in the T-th time period to be planned... The historical average value relative to the previous period, time period T-1. Adding too much, or just M and When the values ​​are too large, it indicates that the load fluctuations in the T-time period are intensified. An excessive number of ramp-up cycles means that load increases or decreases occur more frequently within a time period. Since thermal power units have inertia in their output adjustments, frequent adjustments not only test the adjustment speed but also increase the thermal and mechanical stresses on key components such as turbines and boilers. Furthermore, an excessively large average value of the power difference per ramp indicates a larger amplitude of each load change. Excessive load changes may exceed the safe adjustment speed of the thermal power unit, causing response lag or even operational risks. A significant increase in both the number of ramp-up cycles and the average value of the power difference per ramp compared to the previous period means that the stable operating rhythm of the thermal power unit will be more disrupted. For example, boiler combustion relies on continuous and stable pulverized coal supply and air ratio. When the ramp-up plan of the thermal power unit changes too drastically in a short period, combustion adjustments cannot match in time, easily causing furnace pressure fluctuations, decreased combustion efficiency, and even risks such as flameout and slagging. and This allows for the quantification of the dramatic changes in the average number of climbs and the average climb power compared to the previous period. Increasing the denominator by 1 avoids a denominator of 0, and the max function prevents errors when the evaluated values ​​are all within the normal range. Negative values ​​appear. and This allows for the quantification of the magnitude of the number of climbs and the average climbing power.

[0088] Therefore, if the load on thermal power units is greater, the demand for energy storage auxiliary power will be higher. Thus, the climbing auxiliary demand evaluation parameters in this embodiment... This will increase accordingly. Using the above method, a quantitative evaluation parameter for the climbing assistance requirement can be obtained. The larger the value, the more auxiliary climbing energy storage needs to be called up in the Tth time period, thus providing a reliable basis for the formulation of subsequent climbing strategies.

[0089] Step S3: Determine the total auxiliary climbing energy storage to be used in the climbing planning of the T-th time period based on the climbing auxiliary demand evaluation parameters.

[0090] As a preferred embodiment, the method for determining the total auxiliary climbing energy storage to be used in the climbing plan for time period T is as follows:

[0091] The proportion of total auxiliary climbing energy storage is determined based on the climbing auxiliary demand evaluation parameters. ;

[0092] Calculate the total auxiliary climbing energy storage :

[0093] ;

[0094] in, This represents the total power difference during the m-th ramp in the planned load ramping process of the energy-consuming end in the T-th time period.

[0095] As a further optimization scheme, the proportion of the total auxiliary climbing energy storage is determined. The preferred method is:

[0096] Mapping the climbing auxiliary demand evaluation parameters to [0,1] yields... This achieves normalization.

[0097] Obtain the percentage :

[0098] ;

[0099] Where exp represents the natural exponential function, and k is a coefficient controlling the steepness of the function. To control the proportion corresponding to 0.5 Numerical parameters.

[0100] In calculating the proportion In the sigmoid function, k controls the sensitivity. Control center point. That is, the larger k is, the greater the proportion. In the function, and The steeper the numerical relationship curve, the flatter it is. The purpose of the value is to, for When It is 0.5, which is It can be used to control when to start large-scale energy storage.

[0101] As a case study, in setting When prioritizing the use of generator units over energy storage, the value of k can be set to 0.65–0.8. For a more aggressive approach that prioritizes energy storage, the value can be set to 0.25–0.4. A more coordinated strategy can be implemented with a value of around 0.5. For a smoother response, the value of k can be set to 3–6. For high sensitivity, it can be set to 10. In other cases, a value of 6–10 can be considered.

[0102] Step S4: Install temperature sensors at multiple points in the thermal power system. Based on the temperature sensor readings, the time-planned load curve, and the total auxiliary ramp-up energy storage, obtain the ramp-up strategy for time period T. Temperature measurement points may include superheater pipes, steam valves, and boiler water-cooled wall tubes, etc.

[0103] As a preferred embodiment, the method for obtaining the climbing strategy for the Tth time period is to solve the climbing strategy for each time period through iterative optimization, as follows:

[0104] Step S401: Initialize the climbing sequence number m=1, and initialize the remaining auxiliary climbing energy storage of the climbing. Energy storage for the total auxiliary climbing. ;

[0105] Perform the following steps S402-S406: until the strategy for all climbs is obtained:

[0106] Step S402: Collect the temperature at each point at the first and second time points, where the first and second time points are respectively the time points from the start of the m-th climb. Seconds and At the second;

[0107] Step S403: Calculate the local maximum fatigue increment of the thermal power unit during the m-th ramp based on the temperature at each location. The calculation of the local maximum fatigue increment of the m-th ramp of the thermal power unit. The method is as follows:

[0108] Based on the mapping relationship between thermal stress and temperature, the maximum thermal stress at the second moment is obtained. and maximum thermal stress The corresponding point at the first moment of thermal stress :

[0109] ;

[0110] ;

[0111] in, Let h be the temperature at the second time point. , and These represent the elastic modulus, coefficient of linear expansion, and Poisson's ratio of the material at the corresponding points. For reference temperature, To achieve maximum thermal stress The temperature at the point at the first moment, To find the maximum value based on the change of h;

[0112] Calculate the local maximum fatigue increment :

[0113] ;

[0114] in, and These are the weights for the influence of stable thermal stress and the weights for the influence of transient thermal stress, respectively. This represents the power value of the corresponding material fatigue life curve.

[0115] During rapid ascent, critical components not only bear the stress amplitude but also the impact from the rate of stress change, thus resulting in a localized maximum fatigue increment. The effects of thermal stress at this temperature were taken into account. The impact of transient changes compared to thermal stress at the previous moment Among them This is derived from the material fatigue life curve, where life damage is in a power relationship with stress amplitude.

[0116] Step S404: Based on the local maximum fatigue increment of the m-th climb. Remaining auxiliary climbing energy storage, and the total power difference of the m-th climb in the T-th time period. The prescribed climbing time and the maximum gradeability of thermal power units Establish the optimization function:

[0117] Establish an objective function, which is to minimize the value of J:

[0118] ;

[0119] ;

[0120] ;

[0121] Establish constraints:

[0122] ;

[0123] ;

[0124] in, and These represent the ramp-up costs of energy storage and thermal power units, respectively, with exp representing the natural exponential function. The actual climbing rate of the thermal power unit during the m-th climb is given. For the m-th climb, according to The time spent climbing the hill. For based on The calculated auxiliary climbing energy storage for the m-th climb is used. To control the coefficient of steepness, For a control ratio of 0.5, the corresponding Numerical parameters; it should be noted that here... and The setting principle and the previous text and The setup principle is the same.

[0125] Under the above objective function and constraint design, the balance point between energy storage utilization and the self-climbing of the thermal power unit is sought through the objective function to minimize costs. Two constraints are established: the first is a thermal fatigue constraint, which is applied at the maximum ramp rate of the thermal power unit. The first constraint is based on the degree of thermal fatigue, and the attenuation rate is used as the upper limit of the ramp rate of the thermal power unit. The second constraint is the energy storage allocation constraint, which can avoid excessive consumption of energy storage in each ramp, resulting in insufficient energy storage for subsequent ramps.

[0126] Step S405: Solve based on the optimization function ;

[0127] Step S406: Update m to the current value plus 1, update Subtract from the current value .

[0128] Through the above steps, the local fatigue level of the thermal power unit can be dynamically calculated before each ramp. Combined with the remaining energy storage resources and the planned ramp power difference, the ramp strategy that meets the safety and system regulation requirements of the thermal power unit can be iteratively optimized, thereby realizing the coordinated scheduling of energy storage and thermal power unit.

[0129] In summary, based on the technical solution of this embodiment, a dynamic optimization scheduling mechanism can be established between thermal power units and energy storage, realizing the optimization between energy demand, thermal power unit capacity and energy storage resources. This not only improves the overall ramp-up adjustment capability of the thermal power grid, ensuring that ramp-up demand is met, but also optimizes the energy storage scheduling scheme, thereby optimizing the economy and lifespan of the energy storage system.

[0130] Example 2

[0131] This embodiment provides a thermal power plant flexibility retrofit device based on the energy-consuming end, applied to the thermal power plant flexibility retrofit method based on the energy-consuming end in Embodiment 1. (See reference...) Figure 2 ,include:

[0132] The first data acquisition module is used to acquire load monitoring data from the energy consumption end during the T-1 time period and form a time-measured load curve.

[0133] The second data acquisition module is used to acquire the load planning data of the energy consumption end in the T-time period and form a time-planned load curve;

[0134] The ramp-up auxiliary demand evaluation parameter calculation module is used to obtain ramp-up auxiliary demand evaluation parameters based on the time-measured load curve and the time-planned load curve, according to the measured ramp-up data of the energy-consuming end in the T-1 time period and the planned ramp-up data in the T time period. The ramp-up auxiliary demand evaluation parameters are used to quantify the degree of demand for total auxiliary ramp-up energy storage.

[0135] The total auxiliary climbing energy storage acquisition module is used to determine the total auxiliary climbing energy storage to be called in the climbing planning of the T-th time period based on the climbing auxiliary demand evaluation parameters.

[0136] The ramping strategy acquisition module is used to set up temperature sensors at multiple points in the thermal power system and acquire the ramping strategy for the T-th time period based on the monitoring values ​​of the temperature sensors, the time-planned load curve, and the total auxiliary ramping energy storage called.

[0137] Example 3

[0138] This embodiment provides a computer device, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the thermal power plant flexibility transformation method based on the energy consumption end of Embodiment 1. The computer device can be a desktop computer, laptop computer, or other similar device. Users can interact with the computer using external devices such as a keyboard and mouse to perform operations such as reading, storing, and running programs, as well as storing and retrieving data.

[0139] This embodiment also provides a readable storage medium storing a computer program. When executed by a processor, the computer program implements the thermal power plant flexibility transformation method based on the energy-consuming end of Embodiment 1. The readable storage medium stores a computer program, which, when executed by a processor, implements the thermal power plant flexibility transformation method based on the energy-consuming end. Furthermore, the storage medium in this embodiment can be a computer's built-in memory or an external storage device, such as a portable hard drive or a USB flash drive. The storage medium can store the computer program used to execute the aforementioned thermal power plant flexibility transformation method based on the energy-consuming end, as well as all input data, output data, and intermediate cache data involved in the processing of the thermal power plant flexibility transformation method based on the energy-consuming end.

[0140] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for the flexible retrofitting of thermal power plants based on energy consumption, characterized in that: Includes the following steps: Obtain load monitoring data from the energy-consuming end during the T-1 time period to form a time-measured load curve; Obtain the load planning data of the energy consumption end in the Tth time period to form a time-planned load curve; Based on the time-measured load curve and the time-planned load curve, the climbing auxiliary demand evaluation parameters are obtained according to the measured ramping data of the energy consumption end in the T-1 time period and the planned ramping data in the T time period. The ramping auxiliary demand evaluation parameters are used to quantify the demand for total auxiliary ramping energy storage. The total auxiliary climbing energy storage to be used in the climbing planning of the T-th time period is determined based on the climbing auxiliary demand evaluation parameters. Temperature sensors are installed at multiple points in the thermal power system. The ramping strategy for the T-time period is obtained based on the monitoring values ​​of the temperature sensors, the time-planned load curve, and the total auxiliary ramping energy storage called up. The method for obtaining the climbing-assisted demand evaluation parameters is as follows: Based on the time-measured load curve, obtain the actual load ramp number N of the energy-consuming end in the T-1 time period and the total power difference of the nth ramp. , ; Based on the time-planned load curve, obtain the number of planned load ramp-ups M at the energy consumption end in the T-time period, and the total power difference of the m-th ramp-up. , ; Based on M and The magnitude of the value, and the degree of increase of M relative to N, and relatively The degree of increase determines the climbing assistance demand evaluation parameter. The larger the value and the greater the degree of increase, the higher the climbing assistance demand evaluation parameter, and the more total climbing assistance storage energy is called up. The method for determining the climbing assistance demand evaluation parameters is as follows: ； ； ； in, Here, A and B are the parameters for evaluating the climbing auxiliary demand, and max is the function for finding the maximum value. This is a tolerance value for the number of climbs within a time period, set based on experience. This is an empirically set power tolerance value for a single climb within a time period. For the The average value, For the The average value.

2. The method for adapting thermal power plants to their flexibility based on the energy consumption end, as described in claim 1, is characterized in that... The method for determining the total auxiliary climbing energy storage to be used in the climbing plan for time period T is as follows: The proportion of total auxiliary climbing energy storage is determined based on the climbing auxiliary demand evaluation parameters. ; Calculate the total auxiliary climbing energy storage : ； in, This represents the total power difference during the m-th ramp in the planned load ramping process of the energy-consuming end in the T-th time period.

3. The method for adapting thermal power plants to their flexibility based on the energy consumption end, as described in claim 2, is characterized in that... Determine the proportion of the total auxiliary climbing energy storage. The method is as follows: Mapping the climbing auxiliary demand evaluation parameters to [0,1] yields... This achieves normalization. Obtain the percentage : ； Where exp represents the natural exponential function, and k is a coefficient controlling the steepness of the function. To control the proportion corresponding to 0.5 Numerical parameters.

4. The method for adapting thermal power plants to their flexibility based on the energy consumption end, as described in claim 1, is characterized in that... The method for obtaining the climbing strategy for the Tth time period is to iteratively optimize and solve for the climbing strategy for each time period. The method is as follows: Initialize the climbing sequence number m=1, and initialize the remaining auxiliary climbing energy storage of the climbing. Energy storage for the total auxiliary climbing. ; Perform the following steps until you obtain the strategy for all the climbs: Temperatures at various points were collected at the first and second time points, respectively, representing the time remaining from the start of the m-th climb. Seconds and At the second; The maximum local fatigue increment of the thermal power unit during the m-th uphill climb is calculated based on the temperature at each location. ; Based on the local maximum fatigue increment during the m-th climb. The remaining auxiliary climbing energy storage, and the total power difference of the m-th climb in the T-th time period obtained from the time-planned load curve. The prescribed climbing time and the maximum gradeability of thermal power units Establish the optimization function: Establish an objective function, which is to minimize the value of J: ； ； ； Establish constraints: ； ； in, and These represent the ramp-up costs of energy storage and thermal power units, respectively, with exp representing the natural exponential function. The actual climbing rate of the thermal power unit during the m-th climb is given. For the m-th climb, according to The time spent climbing the hill. Based on The calculated auxiliary climbing energy storage for the m-th climb is used. To control the coefficient of steepness, For a control ratio of 0.5, the corresponding Numerical parameters; Solving based on optimization function ; Update m to the current value plus 1, update Subtract from the current value .

5. The method for adapting thermal power plants to their flexibility based on the energy consumption end, as described in claim 4, is characterized in that... The calculation of the local maximum fatigue increment of the thermal power unit during the m-th climb is described. The method is as follows: Based on the mapping relationship between thermal stress and temperature, the maximum thermal stress at the second moment is obtained. and maximum thermal stress The corresponding point at the first moment of thermal stress : ； ； in, Let h be the temperature at the second time. , and These represent the elastic modulus, coefficient of linear expansion, and Poisson's ratio of the material at the corresponding points. For reference temperature, To achieve maximum thermal stress The temperature at the point at the first moment, To find the maximum value based on the change of h; Calculate the local maximum fatigue increment : ； in, and These are the weights for the influence of steady thermal stress and the weights for the influence of transient thermal stress, respectively. This represents the power value of the corresponding material fatigue life curve.

6. A thermal power plant flexibility retrofit device based on the energy consumption end, applied to the thermal power plant flexibility retrofit method based on the energy consumption end as described in any one of claims 1-5, characterized in that, include: The first data acquisition module is used to acquire load monitoring data from the energy consumption end during the T-1 time period and form a time-measured load curve. The second data acquisition module is used to acquire the load planning data of the energy consumption end in the T-time period and form a time-planned load curve; The ramp-up auxiliary demand evaluation parameter calculation module is used to obtain ramp-up auxiliary demand evaluation parameters based on the time-measured load curve and the time-planned load curve, according to the measured ramp-up data of the energy-consuming end in the T-1 time period and the planned ramp-up data in the T time period. The ramp-up auxiliary demand evaluation parameters are used to quantify the degree of demand for total auxiliary ramp-up energy storage. The total auxiliary climbing energy storage acquisition module is used to determine the total auxiliary climbing energy storage to be called in the climbing planning of the T-th time period based on the climbing auxiliary demand evaluation parameters. The ramping strategy acquisition module is used to set up temperature sensors at multiple points in the thermal power system and acquire the ramping strategy for the T-th time period based on the monitoring values ​​of the temperature sensors, the time-planned load curve, and the total auxiliary ramping energy storage called. The method for obtaining the climbing-assisted demand evaluation parameters is as follows: Based on the time-measured load curve, obtain the actual load ramp number N of the energy-consuming end in the T-1 time period and the total power difference of the nth ramp. , ; Based on the time-planned load curve, obtain the number of planned load ramp-ups M at the energy consumption end in the T-time period, and the total power difference of the m-th ramp-up. , ; Based on M and The magnitude of the value, and the degree of increase of M relative to N, and relatively The degree of increase determines the climbing assistance demand evaluation parameter. The larger the value and the greater the degree of increase, the higher the climbing assistance demand evaluation parameter, and the more total climbing assistance storage energy is called up. The method for determining the climbing assistance demand evaluation parameters is as follows: ； ； ； in, Here, A and B are the parameters for evaluating the climbing auxiliary demand, and max is the function for finding the maximum value. This is a tolerance value for the number of climbs within a time period, set based on experience. This is an empirically set power tolerance value for a single climb within a time period. For the The average value, For the The average value.

7. A computer device, characterized in that, It includes a memory and a processor, wherein the memory stores a computer program, and the processor is used to execute the computer program to implement the thermal power plant flexibility transformation method based on the energy consumption end as described in any one of claims 1-5.

8. A readable storage medium, characterized in that, The readable storage medium stores a computer program, which, when executed by a processor, implements the thermal power plant flexibility transformation method based on the energy consumption end as described in any one of claims 1-5.

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