Intelligent thermal power plant unit performance multi-dimensional optimization management and control system

Abstract

The invention discloses an intelligent thermal power plant unit performance multi-dimensional optimization management and control system, relates to the technical field of thermal power plant units, and solves the problems that the energy consumption states of a plurality of units are not balanced and a thermal power plant does not have an optimal adjustment standard, resulting in large errors of adjusted related parameters. According to the method, the historical operation data of the thermal power plant unit is analyzed, and the power parameters associated with the thermal power plant unit are subsequently adjusted based on the actual analysis result, so that the subsequently adjusted specific parameters are applied to the actual operation state, and the operation optimization effect of the corresponding thermal power plant unit is guaranteed; and the overall operation effect of the thermal power plant unit is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of thermal power plant units, and in particular to an intelligent thermal power plant unit performance multi-dimensional optimization control system. Background Art

[0002] The thermal power plant unit is the core equipment for realizing energy conversion in a thermal power plant. It converts the chemical energy of fuel (mainly coal, natural gas, etc.) into electrical energy.

[0003] The application with the publication number CN118466183A discloses a thermal power plant optimization control system and method based on model prediction, including a data acquisition module for acquiring the operation index of the thermal power plant, and calculating the weight value of the key equipment operation parameter according to the operation index of the thermal power plant; a prediction range setting module for calculating the operation index disturbance value according to the weight value of the key equipment operation parameter, and determining the prediction range according to the operation index disturbance value; a model prediction module for establishing a thermal power plant operation parameter prediction model, and determining the key equipment operation parameters within the prediction range according to the thermal power plant operation parameter prediction model; a control range setting module for setting the control range according to the prediction range; and a parameter control module for optimizing and controlling each thermal power plant equipment within the control range according to the prediction results of the thermal power plant operation parameter prediction model. The unit can respond to the disturbance in time, and the control accuracy of the model prediction control is improved.

[0004] During the multi-dimensional optimization process, its intelligent thermal power plant generally performs adaptive adjustments on the internal units of the thermal power plant based on specific operating parameters to keep the units in a better operating state. However, during actual operation, there is no optimal adjustment standard for its thermal power plant, resulting in large errors in the adjusted related parameters. At the same time, the energy consumption states of individual units in the thermal power plant are inconsistent. Since the energy consumption states of multiple units are not balanced, the unit energy consumption generated by the thermal power plant is too large, and the overall operating effect of the thermal power plant cannot be fully guaranteed. Summary of the invention

[0005] In view of the deficiencies in the prior art, the present invention provides an intelligent multi-dimensional optimization control system for the performance of thermal power plant units, which solves the problem that the energy consumption states of multiple units are not balanced and there is no optimal adjustment standard for thermal power plants, resulting in large errors in the adjusted related parameters.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: an intelligent thermal power plant unit performance multi-dimensional optimization control system, comprising: The unit parameter acquisition terminal obtains the historical operation data generated by the unit of this thermal power plant from the cloud data; The parameter comprehensive processing end confirms a set of periodic data based on several sets of historical operation data confirmed by the thermal power plant unit, and then confirms the numerical performance of different output power and energy consumption parameters associated with different times from the periodic data, and selects the optimal output power range associated with the thermal power plant unit. The best way is: Based on several groups of historical operation data confirmed by the thermal power plant units, a group of traceability cycles are confirmed with the current time as the calibration time, and the traceability cycle is the preset cycle; Confirm different output powers and energy consumption parameters associated with different moments in the traceability cycle from historical operation data, generate output power change curves and energy consumption parameter change curves, and simultaneously place the output power change curves and energy consumption parameter change curves in the same two-dimensional coordinate system, where the horizontal axis of the two-dimensional coordinate system is the timeline and the vertical axis is the power parameter; Based on the constructed two-dimensional coordinate system, two sets of standard lines perpendicular to the horizontal coordinate axis are constructed, and the two sets of standard lines are aligned with the initial moment and the final moment of the two sets of change curves, and the standard line associated with the initial moment is recorded as the initial standard line, and the standard line associated with the final moment is recorded as the final standard line; Execute several groups of processing processes and record the processing characteristics associated with the corresponding processing processes, specifically in the following way: S1. Execute the first set of processing processes: record the time length Cd between the initial standard line and the terminal standard line, where Cd = terminal time - initial time, then record the area covered by the initial standard line, terminal standard line, output power change curve and energy consumption parameter change curve, confirm the area parameter M of the area, and use: M÷Cd=Tz to confirm the processing feature Tz associated with this processing process; S2, move the initial standard line back a group of unit time, execute a group of processing processes, and adopt the same processing method as the above processing processes to lock the processing features associated with the processing processes. Each time the initial standard line moves a group of unit time and executes a group of processing processes, synchronously confirm the processing features associated with the corresponding processing processes. When the initial standard line moves to the moment before the terminal standard line, stop moving; S3, move the initial standard line back to the initial time, move the terminal standard line forward by one unit time, and then execute steps S1-S2 to confirm different processing features associated with different processing processes, and so on. When the initial standard line and the terminal standard line of the subsequent processing process are separated by only one unit time, move the terminal standard line forward by one unit time again, and so on, to confirm different processing features associated with several different processing processes; From the different processing characteristics Tz associated with different processing processes k In the kmaxThe associated processing process is recorded as a standard process, the regional range associated with the standard process is confirmed, and the partial curve of the output power change curve located within the regional range is confirmed, and the minimum output power value and the maximum output power value are selected from the partial curve to generate the optimal output power interval associated with the unit of this thermal power plant, where k represents different processing processes; The real-time adjustment and optimization end analyzes the energy consumption parameters of a single unit in real time based on the numerical state of the energy consumption parameters monitored in real time by the thermal power plant unit, selects the unit with abnormal energy consumption from multiple units, and adjusts the energy consumption of the selected unit with abnormal energy consumption, so that the thermal power plant unit is in the optimal operating state at the current output power. The specific method is as follows: Based on the different energy consumption parameters associated with different units in the thermal power plant in real time, the different energy consumption parameters associated in real time are averaged and the average energy consumption J is confirmed in real time. i , where i represents different moments, and the different energy consumption parameters associated with different units are calibrated as N q , where q represents different individual units, and the corresponding time is evaluated to see whether: (N q -J i )≥Y1, where Y1 is the preset value. If it exists, the corresponding single unit will be marked as an abnormal energy consumption unit. If it does not exist, it will be continuously monitored. Based on the calibrated abnormal energy consumption unit, the output power associated with the abnormal energy consumption unit is adjusted downward, and the power value Gz adjusted downward in unit time is recorded, and one unit time is 1 minute; The output power Gz adjusted downward in real time is distributed to other units. Based on the total number Z of other units, Gz÷Z=Dz is used to confirm the single-unit power Dz that can be distributed to a single unit, and the output power of other units is controlled to be increased in real time, and the increased power value is Dz; After the output power of other units is increased, the energy consumption parameters generated at the time of increase are recorded, and the recorded energy consumption parameters are processed by ratio to confirm the energy consumption ratio, and the energy consumption ratios are sorted from small to large to confirm the energy consumption ratio sequence; After the power value Gz associated with the next unit time is determined, Gz is evenly divided according to the energy consumption ratio within the energy consumption ratio sequence, the power value evenly divided sequence is confirmed, and the energy consumption ratio within the energy consumption ratio sequence is matched with the average value within the power value evenly divided sequence. The matching method is: the energy consumption ratio is matched from small to large in sequence with the average value within the power value evenly divided sequence from large to small, the average value matched by the energy consumption ratio is matched with a single unit, and the single unit is controlled to increase power; By analogy, the energy consumption parameters associated with the abnormal energy consumption unit meet the following conditions: (N q -J i )<Y1, stop adjusting; The main control center, based on the optimal output power range stored in the storage database and the current output power of the thermal power plant unit, confirms the control signal after numerical comparison and outputs it. Then, external personnel confirm whether it is necessary to control the thermal power plant unit to change the power, and transmit the control signal to the real-time adjustment optimization terminal. The specific method is as follows: Based on the current output power DG of the thermal power plant units and the confirmed optimal output power range: If DG∉optimal output power range, a signal to be controlled is generated and displayed on the display screen. Relevant personnel confirm the control signal or do not perform any processing based on the generated signal to be controlled; If DG∈optimal output power interval, no processing is performed; The main control center transmits the confirmed control signal to the real-time adjustment and optimization terminal, and the real-time adjustment and optimization terminal adjusts the output power of the thermal power plant unit to the optimal output power range.

[0007] Preferably, the historical operation data includes output power and energy consumption parameters associated with the units of the thermal power plant.

[0008] Preferably, it also includes: The storage database stores the optimal output power range associated with the thermal power plant units and provides the main control center with numerical extraction; The unit real-time monitoring terminal monitors the energy consumption parameters of a single unit in a thermal power plant in real time, and transmits the energy consumption parameters of a single unit monitored in real time to the real-time adjustment and optimization terminal.

[0009] The present invention provides an intelligent thermal power plant unit performance multi-dimensional optimization control system. Compared with the prior art, it has the following beneficial effects: The present invention analyzes the historical operation data of the thermal power plant units, and based on the actual analysis results, subsequently adjusts the power parameters associated with the thermal power plant units, so that the subsequently adjusted specific parameters are applied to the actual operation state, thereby ensuring the operation optimization effect of the corresponding thermal power plant units and improving the overall operation effect of the thermal power plant units; Subsequently, during the actual operation, the energy consumption status of a single unit within the unit is confirmed, the related unit with a single energy consumption abnormality is locked, and then power is allocated to other units, so that the energy consumption parameters of multiple units within the thermal power plant are in a relatively balanced state, achieving better multi-dimensional optimization control effects and improving the operating results of thermal power plant units during operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] Figure 1 It is a schematic diagram of the principle framework of the present invention; Figure 2 It is a schematic diagram of the area range determined between the change curves of the present invention. DETAILED DESCRIPTION

[0011] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0012] First embodiment See also Figure 1 , the present application provides an intelligent thermal power plant unit performance multi-dimensional optimization management and control system, including a unit parameter acquisition terminal, a parameter comprehensive processing terminal, a storage database, a unit real-time monitoring terminal, a real-time adjustment optimization terminal and a main control center; The unit parameter acquisition terminal, the parameter comprehensive processing terminal, the storage database and the main control center are electrically connected from the output node to the input node in sequence, and the unit real-time monitoring terminal is electrically connected to the input node of the real-time adjustment and optimization terminal, and the real-time adjustment and optimization terminal is bidirectionally connected to the main control center; Among them, the unit parameter acquisition end obtains the historical operation data generated by the thermal power plant unit from the cloud data, and transmits the obtained historical operation data to the parameter comprehensive processing end. Specifically, the obtained historical operation data is the output power and energy consumption parameters associated with the thermal power plant unit. Different output powers correspond to different energy consumption parameters. Among them, the parameter comprehensive processing end confirms a set of periodic data based on several sets of historical operation data confirmed by the thermal power plant unit, and then confirms different output power and energy consumption parameters associated with different times from the periodic data. Based on the numerical performance of different output power and energy consumption parameters, the optimal output power range associated with the thermal power plant unit is selected. Specifically, after locking the optimal output power range, it can ensure that the thermal power plant unit is in the best operating state, so that the thermal power plant unit can be in the best operating state in the later period, so that the thermal power plant unit can achieve better operation processing effect. The best way to select the optimal output power range is: Based on several groups of historical operation data confirmed by the thermal power plant units, with the current time as the calibration time, a group of traceability cycles are confirmed in the past. The traceability cycle is a preset cycle, which is prepared in advance by relevant personnel based on experience. The general value is 72h. The traceability cycle can be understood as follows: when the current time is 14:00, tracing back 72h, then tracing back 72h on the basis of the current time to lock the traceability cycle; Confirm different output powers and energy consumption parameters associated with different moments in the traceability period from historical operation data (the numerical units of the output power and energy consumption parameters are the same), generate output power change curves and energy consumption parameter change curves, and simultaneously place the output power change curves and energy consumption parameter change curves in the same two-dimensional coordinate system, where the horizontal axis of the two-dimensional coordinate system is the timeline and the vertical axis is the power parameter (the power parameter is associated with the output power or energy consumption parameter); Based on the constructed two-dimensional coordinate system, two sets of standard lines perpendicular to the horizontal coordinate axis are constructed, and the two sets of standard lines are aligned with the initial moment and the terminal moment of the two sets of change curves. The standard line associated with the initial moment is recorded as the initial standard line, and the standard line associated with the terminal moment is recorded as the terminal standard line. Specifically, the standard line is perpendicular to the horizontal coordinate axis, that is, the associated parameter is the corresponding time parameter, thereby corresponding to different moments; Execute several groups of processes and record the processing characteristics associated with the corresponding processes: S1. Execute the first set of processing processes: record the time length Cd between the initial standard line and the terminal standard line, where Cd = terminal moment - initial moment, and then record the area covered by the initial standard line, terminal standard line, output power change curve and energy consumption parameter change curve, confirm the area parameter M of the area, and use: M÷Cd=Tz to confirm the processing feature Tz associated with this processing process, Tz represents the density relationship between the output power and the energy consumption parameter per unit time, and the unit is kg / MWh; S2, move the initial standard line back a group of unit time, execute a group of processing processes, and adopt the same processing method as the above processing processes to lock the processing features associated with this processing process. Each time the initial standard line moves a group of unit time and executes a group of processing processes, synchronously confirm the processing features associated with the corresponding processing processes. When the initial standard line moves to the moment before the terminal standard line, stop moving. One unit time is 1 minute. S3, move the initial standard line back to the initial time, move the terminal standard line forward by one unit time, and then execute steps S1-S2 to confirm different processing features associated with different processing processes, and so on. When the initial standard line and the terminal standard line of the subsequent processing process are separated by only one unit time, move the terminal standard line forward by one unit time again, and so on, to confirm different processing features associated with several different processing processes; From the different processing characteristics Tz associated with different processing processes k In the kmaxThe associated processing process is recorded as the standard process, the regional range associated with the standard process is confirmed, and the partial curve of the output power change curve within the regional range is confirmed, and the minimum output power value and the maximum output power value are selected from the partial curve to generate the optimal output power interval associated with the unit of this thermal power plant, where k represents different processing processes. The larger the area of ​​the regional range, the shorter the corresponding interval time, which means that the difference in the related values ​​associated within the unit time is larger, that is, the difference between the output power and the energy consumption parameter is larger. Then this kind of situation belongs to the situation with better numerical performance, and the optimal processing process can be selected from it to carry out the specific selection of the optimal output power interval; Specifically, during the actual operation of the thermal power plant units, different energy consumption values ​​will be associated with different power output states. Therefore, based on the specific difference between the corresponding power and energy consumption values, the area with the maximum difference can be selected, that is, the area associated with the maximum value of the corresponding processing feature. The larger the processing feature value, the greater the value density represented, and the optimal value state can be selected to complete the optimal selection of the corresponding value, thereby achieving a better value selection effect. Combination Figure 2 In the constructed two-dimensional coordinate system, according to the change of output power and energy consumption parameters over time, the output power change curve or energy consumption parameter change curve is confirmed, and then based on the associated previous and next moments, the initial standard line and the terminal standard line associated with the corresponding moment are confirmed, and along with the movement of the initial standard line and the terminal standard line, the area range generated between the corresponding standard line and the corresponding change curve is confirmed, so that the relevant density involved in the corresponding area range can be determined based on the time difference between the two sets of standard lines and the area parameter of the area range, and the confirmed relevant density is the processing feature associated with the corresponding processing process; The process of calculating the area of ​​the regional range includes: assuming that the initial standard line is at time 0, the terminal standard line is at time 4, and the output powers corresponding to the output power curve at time 0-4 are 100, 105, 110, 115 and 120 respectively, and the energy consumption parameters are 70, 80, 85, 90, 95 respectively; according to step S1, the area parameter M of the regional range is calculated: The time length between the initial standard line and the final standard line is Cd=4-0=4min.

[0013] The area M of the region can be obtained by integration or approximate calculation. Assuming that the trapezoidal method is used for calculation, the area of ​​the region is: M=(70+95)÷2×4=330 kg / MWh.min; Treatment characteristics Tz = M ÷ Cd = 1280 ÷ 4 = 320 {kg / MWh}; Related examples of the constructed standard lines: the initial standard line and the terminal standard line are determined based on the preset traceability period (such as 72 hours); the initial standard line is usually set to the starting time of the traceability period, and the terminal standard line is set to the end time of the traceability period. For example, if the current time is 14:00 and the traceability period is 72 hours, the initial standard line is 14:00 72 hours ago, and the terminal standard line is the current time 14:00. The initial standard line and the terminal standard line can be moved forward or backward by one unit time (such as 1 minute) respectively to execute different processing processes; after each movement of the standard line, the area parameter M and processing characteristics Tz of the regional range are recalculated.

[0014] Among them, the storage database stores the optimal output power range associated with the thermal power plant units and provides the main control center with numerical extraction.

[0015] Second embodiment In the specific implementation process of this embodiment, compared with the above embodiment, this embodiment mainly adjusts the parameters associated with the unit in real time to make the unit reach the state with the lowest energy consumption value; Among them, the unit real-time monitoring end monitors the energy consumption parameters of a single unit in the thermal power plant in real time, and transmits the energy consumption parameters of a single unit monitored in real time to the real-time adjustment optimization end. The thermal power plant unit is composed of several units, so each unit has different energy consumption losses, but the output power of each unit is in an overall evenly distributed state. If the energy consumption balance is too different, it is necessary to adjust the relevant energy consumption of a single unit. Based on the specific situation of real-time adjustment, the optimal energy consumption processing state can be achieved to put the unit in the optimal operating state; Among them, the real-time adjustment optimization end, based on the energy consumption parameter numerical state of a single unit monitored in real time in the thermal power plant, performs real-time analysis on the energy consumption parameters of a single unit, selects a unit with abnormal energy consumption from multiple units, and adjusts the energy consumption of the selected unit with abnormal energy consumption, so that the thermal power plant unit is in the optimal operating state at the current output power. The specific method of energy consumption adjustment is: Based on the different energy consumption parameters associated with different units in the thermal power plant in real time, the different energy consumption parameters associated in real time are averaged and the average energy consumption J is confirmed in real time. i , where i represents different moments, and the different energy consumption parameters associated with different units are calibrated as N q , where q represents different individual units, and the corresponding time is evaluated to see whether: (N q -J i)≥Y1, where Y1 is a preset value, and its specific value is determined by the operator based on experience. If it exists, the corresponding single unit will be marked as an abnormal energy consumption unit. If it does not exist, it will be continuously monitored. For the value Y1, the energy consumption parameter data of each unit in the thermal power plant at different times in the past year are collected first, and a total of n data points are obtained. The average value of all energy consumption parameters is calculated first, and then the absolute value of the difference between each data point and the average value is calculated, and these differences are sorted; then, we can select a suitable percentage position according to actual needs and experience, such as selecting the 80th percentile difference as the value of Y1; this means that among all the energy consumption parameter data, 80% of the data points have an absolute value less than Y1 in difference with the average value, and only 20% of the data points have an absolute value greater than or equal to Y1 in difference with the average value. The units corresponding to these data points with larger differences may be abnormal energy consumption units. The proposed confirmed Y1 value is 10. When the corresponding moment exists (N q -J i ) ≥ 10, the abnormal energy consumption unit is calibrated, otherwise, the energy consumption monitoring is continued, where J i represents the mean energy consumption in kg / MWh, and Y1 is the preset energy consumption difference threshold in kg / MWh; Based on the calibrated abnormal energy consumption unit, the output power associated with the abnormal energy consumption unit is adjusted downward, and the power value Gz adjusted downward in unit time is recorded, and one unit time is 1 minute; The output power Gz adjusted downward in real time is distributed to other units. Based on the total number Z of other units, Gz÷Z=Dz is used to confirm the single power Dz that can be allocated to a single unit, and the output power of other units is controlled to be increased in real time. The increased power value is Dz. Gz represents the power value adjusted downward by the unit with abnormal energy consumption per unit time, in MW, and Dz represents the single power that can be allocated to a single unit, in MW. After the output power of other units is increased, the energy consumption parameters generated at the time of increase are recorded, and the recorded energy consumption parameters are processed by ratio to confirm the energy consumption ratio, and the energy consumption ratios are sorted from small to large to confirm the energy consumption ratio sequence; After the power value Gz associated with the next unit time is determined, Gz is evenly divided according to the energy consumption ratio within this energy consumption ratio sequence, the power value evenly divided sequence is confirmed, and the energy consumption ratio within the energy consumption ratio sequence is matched with the average value within the power value evenly divided sequence. The matching method is: the energy consumption ratio matches the average value from large to small in the power value evenly divided sequence in sequence from small to large, the average value matched by the energy consumption ratio is matched with a single unit, and the single unit is controlled to increase power. Specifically, the proposed confirmed power value Gz is 60, and the associated energy consumption ratio is processed, and the generated energy consumption ratio sequence is A: B: C = 1: 2: 3, then A accounts for (1 / 6), B accounts for (1 / 3), and C accounts for (1 / 2). Based on the confirmed power value of 60, according to the specific ratio of this energy consumption ratio sequence, the adjusted value distribution sequence is 10:20:30, that is, according to the processing method of "matching the average values ​​from large to small in the power value distribution sequence with the energy consumption ratio from small to large", the power value matched by (1 / 6) A is 30, the power value matched by (1 / 3) B is 20, and the power value matched by (1 / 2) C is 10. Therefore, this processing method can fully complete the value distribution processing and achieve a better value distribution processing effect; By analogy, the energy consumption parameters associated with the abnormal energy consumption unit meet the following conditions: (N q -J i )<Y1, stop adjusting, Nq represents the energy consumption parameter of a single unit, the unit is kg / MWh.

[0016] Among them, the main control center, based on the optimal output power range stored in the storage database and the current output power of the thermal power plant unit, confirms the control signal after numerical comparison and outputs it, and then external personnel confirm whether it is necessary to control the thermal power plant unit to change the power, and transmits the control signal to the real-time adjustment optimization terminal. The specific way of actual control and adjustment is as follows: Based on the current output power DG of the thermal power plant units and the confirmed optimal output power range: If DG∈optimal output power interval, no processing is performed; If DG∉optimal output power range, a signal to be controlled is generated and displayed on the display screen. Based on the generated signal to be controlled, the relevant personnel confirm the control signal or do not perform any processing. The control signal means that the external personnel want to adjust the output power of the unit to the optimal output power range; The main control center transmits the confirmed control signal to the real-time adjustment and optimization terminal, and the real-time adjustment and optimization terminal adjusts the output power of the thermal power plant unit to the optimal output power range to ensure that the operating status of the thermal power plant unit is in the best state.

[0017] Some of the data in the above formulas are dimensionless and numerically calculated. Meanwhile, the contents not described in detail in this specification belong to the prior art known to those skilled in the art.

[0018] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. Intelligent thermal power plant unit performance multi-dimensional optimization control system, characterized by: include: The unit parameter acquisition terminal obtains the historical operation data generated by the unit of this thermal power plant from the cloud data; The parameter comprehensive processing end determines a set of periodic data based on several sets of historical operation data confirmed by the thermal power plant unit, and then determines the numerical performance of different output power and energy consumption parameters associated with different times from the periodic data, and selects the optimal output power range associated with the thermal power plant unit; The real-time adjustment and optimization end analyzes the energy consumption parameters of a single unit in real time based on the numerical status of the energy consumption parameters monitored in real time by the thermal power plant unit, selects the unit with abnormal energy consumption from multiple units, and adjusts the energy consumption of the selected unit with abnormal energy consumption, so that the thermal power plant unit is in the optimal operating state at the current output power; The main control center, based on the optimal output power range stored in the storage database and the current output power of the thermal power plant unit, confirms the control signal after numerical comparison and outputs it. External personnel then confirm whether it is necessary to control the thermal power plant unit to change power, and transmit the control signal to the real-time adjustment and optimization terminal.

2. According to claim 1, the intelligent thermal power plant unit performance multi-dimensional optimization control system is characterized in that: The historical operation data includes output power and energy consumption parameters associated with the thermal power plant units.

3. The intelligent thermal power plant unit performance multi-dimensional optimization control system according to claim 1 is characterized in that: Also includes: The storage database stores the optimal output power range associated with the thermal power plant units and provides the main control center with numerical extraction; The unit real-time monitoring terminal monitors the energy consumption parameters of a single unit in a thermal power plant in real time, and transmits the energy consumption parameters of a single unit monitored in real time to the real-time adjustment and optimization terminal.

4. The intelligent thermal power plant unit performance multi-dimensional optimization control system according to claim 1 is characterized in that: The best way for the parameter comprehensive processing end to select the optimal output power range is: Based on several groups of historical operation data confirmed by the thermal power plant units, a group of traceability cycles are confirmed with the current time as the calibration time, and the traceability cycle is the preset cycle; Confirm different output powers and energy consumption parameters associated with different moments in the traceability cycle from historical operation data, generate output power change curves and energy consumption parameter change curves, and simultaneously place the output power change curves and energy consumption parameter change curves in the same two-dimensional coordinate system, where the horizontal axis of the two-dimensional coordinate system is the timeline and the vertical axis is the power parameter; Based on the constructed two-dimensional coordinate system, two sets of standard lines perpendicular to the horizontal coordinate axis are constructed, and the two sets of standard lines are aligned with the initial moment and the final moment of the two sets of change curves, and the standard line associated with the initial moment is recorded as the initial standard line, and the standard line associated with the final moment is recorded as the final standard line; Execute several groups of processing processes and record processing characteristics associated with the corresponding processing processes; From the different processing characteristics Tz associated with different processing processes k In the kmax The associated processing process is recorded as the standard process, the regional range associated with the standard process is confirmed, and the partial curve of the output power change curve within the regional range is confirmed, the minimum output power value and the maximum output power value are selected from the partial curve to generate the optimal output power range associated with the unit of this thermal power plant, where k represents different processing processes.

5. The intelligent multi-dimensional optimization control system for thermal power plant unit performance according to claim 4 is characterized in that: The specific way to execute several groups of processing processes is as follows: S1. Execute the first set of processing processes: record the time length Cd between the initial standard line and the terminal standard line, where Cd = terminal time - initial time, then record the area covered by the initial standard line, terminal standard line, output power change curve and energy consumption parameter change curve, confirm the area parameter M of the area, and use: M÷Cd=Tz to confirm the processing feature Tz associated with this processing process; S2, move the initial standard line back a group of unit time, execute a group of processing processes, and adopt the same processing method as the above processing processes to lock the processing features associated with the processing processes. Each time the initial standard line moves a group of unit time and executes a group of processing processes, synchronously confirm the processing features associated with the corresponding processing processes. When the initial standard line moves to the moment before the terminal standard line, stop moving; S3. Move the initial standard line back to the initial moment, move the terminal standard line forward by one unit moment, and then execute steps S1-S2 to confirm the different processing features associated with different processing processes. Similarly, when the initial standard line and the terminal standard line of the subsequent processing process are separated by only one unit moment, move the terminal standard line forward by one unit moment again, and so on to confirm the different processing features associated with several different processing processes.

6. The intelligent thermal power plant unit performance multi-dimensional optimization control system according to claim 1 is characterized in that: The specific method of the real-time adjustment optimization end for adjusting the energy consumption of the selected abnormal energy consumption unit is: Based on the different energy consumption parameters associated with different units in the thermal power plant in real time, the different energy consumption parameters associated in real time are averaged and the average energy consumption J is confirmed in real time. i , where i represents different moments, and the different energy consumption parameters associated with different units are calibrated as N q , where q represents different individual units, and the corresponding time is evaluated to see whether: (N q -J i )≥Y1, where Y1 is the preset value. If it exists, the corresponding single unit will be marked as an abnormal energy consumption unit. If it does not exist, it will be continuously monitored; Based on the calibrated abnormal energy consumption unit, the output power associated with the abnormal energy consumption unit is adjusted downward, and the power value Gz adjusted downward in unit time is recorded, and one unit time is 1 minute; The output power Gz adjusted downward in real time is distributed to other units. Based on the total number Z of other units, Gz÷Z=Dz is used to confirm the single-unit power Dz that can be distributed to a single unit, and the output power of other units is controlled to be increased in real time, and the increased power value is Dz; After the output power of other units is increased, the energy consumption parameters generated at the time of increase are recorded, and the recorded energy consumption parameters are processed by ratio to confirm the energy consumption ratio, and the energy consumption ratios are sorted from small to large to confirm the energy consumption ratio sequence; After the power value Gz associated with the next unit time is determined, Gz is evenly divided according to the energy consumption ratio within the energy consumption ratio sequence, the power value evenly divided sequence is confirmed, and the energy consumption ratio within the energy consumption ratio sequence is matched with the average value within the power value evenly divided sequence. The matching method is: the energy consumption ratio is matched from small to large in sequence with the average value within the power value evenly divided sequence from large to small, the average value matched by the energy consumption ratio is matched with a single unit, and the single unit is controlled to increase power; By analogy, the energy consumption parameters associated with the abnormal energy consumption unit meet the following conditions: (N q -J i )<Y1, stop adjusting.

7. The intelligent thermal power plant unit performance multi-dimensional optimization control system according to claim 6 is characterized in that: The specific method for the main control center to determine whether it is necessary to re-control the thermal power plant units is as follows: Based on the current output power DG of the thermal power plant units and the confirmed optimal output power range: If DG∉optimal output power range, a signal to be controlled is generated and displayed on the display screen. Relevant personnel confirm the control signal or do not perform any processing based on the generated signal to be controlled; The main control center transmits the confirmed control signal to the real-time adjustment and optimization terminal, and the real-time adjustment and optimization terminal adjusts the output power of the thermal power plant unit to the optimal output power range.

8. The intelligent multi-dimensional optimization control system for thermal power plant unit performance according to claim 7 is characterized in that: If DG∈optimal output power interval, no processing is performed.

Images