Thermal power generating unit deep peak regulation control method and system

Abstract

The invention discloses a deep peak regulation control method and system for a thermal power generating unit, and the method comprises the steps: 1, obtaining the operation data of the thermal power generating unit, and enabling the operation data to comprise the fuel consumption of the thermal power generating unit, the consumption characteristic coefficient of the thermal power generating unit, and the output power of the thermal power generating unit; 2, inputting the operation data into a thermal power generating unit fuel consumption cost calculation formula, and obtaining a calculation result; 3, inputting a calculation result in the step 2 into a calculation formula of deep peak regulation of the thermal power generating unit, and calculating a state score of the deep peak regulation of the thermal power generating unit at the current moment; 4, establishing a multi-interval sub-prediction model of a primary frequency modulation controlled object in a deep peak regulation state of the thermal power generating unit, generating a corresponding sub-prediction function controller, and obtaining the state prediction of the deep peak regulation of the thermal power generating unit at the current moment or a certain moment in the future; according to the scheme, the problem of performance condition constraints of various machines in the prior art is solved, the high efficiency and accuracy of deep peak regulation of the thermal power generating unit are improved, and the peak regulation requirement is finally met.

Description

Technical Field

[0001] The present invention belongs to the technical field of deep peak regulation of thermal power units, and in particular relates to a deep peak regulation control method and system for thermal power units. Background Art

[0002] Thermal power units, also known as thermal power units or thermal power units, are one of the important power generation equipment in the power industry. They use coal, oil or combustible gas as fuel, generate heat energy through combustion, and then convert it into mechanical energy and finally into electrical energy.

[0003] The existing technology studies the basic logic of the unit, boiler low-load stable combustion control, variable load rate, denitrification emission full process control and auxiliary steam source pressure that affect the deep peak regulation of thermal power units, and analyzes the characteristics of the unit's CCS coordinated control system, low-load stable combustion, auxiliary steam system and other control systems. These parameters are likely to affect the efficiency of deep peak regulation: the impact of coal powder mass concentration and air distribution on boiler low-load stable combustion, the impact of air distribution control and ammonia injection control of low-nitrogen combustion on denitrification emission control, the impact of primary frequency regulation on the main process control loop, and the nonlinear characteristics of a large number of objects such as steam-driven feedwater pumps and regulating valves that change with the operating range. Equipment modification and control parameter optimization are carried out to achieve load reduction peak regulation of thermal power units. During the deep peak regulation process, the operating cost of thermal power units will also change significantly due to the significant reduction in unit output. The peak regulation cost mainly includes coal consumption cost, equipment loss cost and possible penalty cost, etc.; and then subject to the performance conditions of various machines, it is difficult to optimize the controller to an ideal state.

[0004] Therefore, the present invention provides a deep peak regulation control method and system for a thermal power unit to solve the problems raised by the above-mentioned background technology. Summary of the invention

[0005] In view of the problems raised by the above background technology, the purpose of the present invention is to provide a deep peak-shaving control method and system for thermal power units, which can improve the efficiency and accuracy of deep peak-shaving of thermal power units and meet peak-shaving needs.

[0006] In order to achieve the above technical objectives, the technical solution adopted by the present invention is as follows:

[0007] A method and system for controlling deep peak load regulation of a thermal power unit, the control method comprising the following steps:

[0008] Step 1: Acquire the operation data of the thermal power unit, wherein the operation data includes the fuel consumption of the thermal power unit, the consumption characteristic coefficient of the thermal power unit and the output power of the thermal power unit;

[0009] Step 2: Input the operating data in step 1 into the calculation formula of the fuel consumption cost of the thermal power unit and obtain the calculation result;

[0010] Step 3: Input the calculation result of step 2 into the calculation formula of deep peak regulation of thermal power generation unit, and calculate the state score of deep peak regulation of thermal power generation unit at the current moment;

[0011] Step 4: Establish a multi-interval sub-prediction model of the next frequency regulation controlled object under the deep peak regulation state of the thermal power unit, and generate the corresponding sub-prediction function controller to obtain the state prediction of the deep peak regulation of the thermal power unit at the current moment or at a certain moment in the future;

[0012] Step 5: Determine the optimal control amount of deep peak regulation of thermal power units by predicting the state of deep peak regulation of thermal power units at multiple moments.

[0013] It is further defined that the calculation formula for the fuel consumption cost of the thermal power unit in step 2 includes C coal represents the fuel consumption cost of the thermal power unit, a, b and c all represent the consumption characteristic coefficients of the thermal power unit, and P represents the output power of the thermal power unit. The calculation formula is:

[0014] C coal =aP 2 +bP+c

[0015] Also includes P min and P max , P min is the minimum output power of the thermal power unit, P max is the maximum output power of the thermal power unit, the P min <P<P max .

[0016] It is further defined that the calculation formula for the deep peak regulation of the thermal power unit in step 3 is:

[0017] Q i =(A i ·B i ·C i ·D i )÷P

[0018] Among them, i represents the thermal power unit, Q i represents the deep peak load regulation state score of thermal power unit i, A i represents the network blocking factor, B i Denitrification factor, C i Denotes dust removal factor and D i represents the desulfurization factor.

[0019] It is further defined that the calculation formula of the sub-prediction function controller in step 4 is:

[0020] x k+1∣k =Ex k∣k +Fuk∣k

[0021] where x k+1∣k represents the prediction of the state of the thermal power unit at time k+1 at time k, x k∣k and u k∣k They represent the estimation and control input of the state at time K at time k respectively, and E and F represent the system matrices.

[0022] It is further limited to also include total operating costs, which include fuel consumption costs, equipment loss costs and penalty costs of thermal power units. The equipment smoothness cost is the loss caused by frequent actions of auxiliary equipment to cooperate with changes in the operating conditions of the unit. The penalty cost is the penalty cost received by the thermal power unit when completing deep peak-shaving tasks.

[0023] Further defined, the step 4 specifically includes the following steps:

[0024] S10: Model building, building a discrete time state space model;

[0025] S11: Predict future dynamics. Using the model established by S11, the system state changes in the future are predicted based on the current system state and control input.

[0026] S12: Solve the optimization problem, substitute the control input based on the predicted future state into the sub-predictive function controller, and calculate the optimal control input.

[0027] A deep peak-shaving control system for a thermal power unit, the control system comprising: a thermal power unit operation data acquisition module, a thermal power unit fuel consumption cost calculation module, a thermal power unit deep peak-shaving state score calculation module and a thermal power unit control amount determination module;

[0028] The thermal power unit operation data acquisition module is used to input current operation data into the thermal power unit fuel consumption cost calculation module for cost calculation, wherein the operation data includes the fuel consumption of the thermal power unit, the consumption characteristic coefficient of the thermal power unit and the output power of the thermal power unit;

[0029] The thermal power unit fuel consumption cost calculation module is used to calculate the fuel consumption cost of the thermal power unit, and input the calculation result into the state score calculation module of the deep peak regulation of the thermal power unit;

[0030] The state score calculation module for deep peak regulation of the thermal power unit is used to calculate the state score of deep peak regulation of the thermal power unit at the current moment;

[0031] The thermal power unit control quantity determination module is used to determine the optimal control quantity for deep peak regulation of the thermal power unit.

[0032] It is further defined that it also includes an analysis module, which sets a comprehensive score threshold for the state score of the deep peak regulation of the thermal power unit. When the comprehensive score threshold is exceeded, it is a high-efficiency configuration; if it does not exceed the comprehensive score threshold, it is a normal configuration.

[0033] Beneficial effects of the present invention:

[0034] The present solution provides a method and system for controlling deep peak regulation of thermal power units, which comprises setting a thermal power unit operation data acquisition module, a thermal power unit fuel consumption cost calculation module, a thermal power unit deep peak regulation state score calculation module and a thermal power unit control quantity determination module; obtaining the operation data of the current thermal power unit, calculating the fuel consumption cost of the thermal power unit through the thermal power unit fuel consumption cost calculation module, and then calculating the state score of the deep peak regulation of the thermal power unit at the current moment through the thermal power unit deep peak regulation state score calculation module, and finally generating a sub-prediction function controller through the thermal power unit control quantity determination module based on a multi-interval sub-prediction model to determine the optimal control quantity of the deep peak regulation of the thermal power unit; thereby solving the problem of performance condition constraints of various machines existing in the prior art, which makes it difficult for the controller to be optimized to an ideal state, improving the efficiency and accuracy of the deep peak regulation of the thermal power unit, and finally meeting the peak regulation demand. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] The present invention can be further illustrated by the non-limiting examples given in the accompanying drawings;

[0036] Figure 1 A flowchart of a method and system for controlling deep peak load of a thermal power unit according to the present invention;

[0037] Figure 2 The present invention is a system module diagram of a method and system embodiment of deep peak regulation control of a thermal power unit. DETAILED DESCRIPTION

[0038] In order to enable those skilled in the art to better understand the present invention, the technical solution of the present invention is further described below in conjunction with the accompanying drawings and embodiments. The technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings 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 the field without creative work are within the scope of protection of the present invention.

[0039] It should be noted that all directional indications in the embodiments of the present invention (such as up, down, left, right, front, back, etc.) are only used to explain the relative position relationship, movement status, etc. between the components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly.

[0040] In addition, the descriptions of "first", "second", etc. in the present invention are only used for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In addition, the technical solutions between the various embodiments can be combined with each other, but it must be based on the ability of ordinary technicians in the field to implement. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such a combination of technical solutions does not exist and is not within the scope of protection required by the present invention. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0041] Embodiment 1: Figure 1 As shown, a method and system for controlling deep peak load regulation of a thermal power unit according to the present invention, the control method comprises the following steps:

[0042] Step 1: Acquire the operation data of the thermal power unit, wherein the operation data includes the fuel consumption of the thermal power unit, the consumption characteristic coefficient of the thermal power unit and the output power of the thermal power unit;

[0043] Step 2: Input the operating data in step 1 into the calculation formula of the fuel consumption cost of the thermal power unit and obtain the calculation result;

[0044] Step 3: Input the calculation result of step 2 into the calculation formula of deep peak regulation of thermal power generation unit, and calculate the state score of deep peak regulation of thermal power generation unit at the current moment;

[0045] Step 4: Establish a multi-interval sub-prediction model of the next frequency regulation controlled object under the deep peak regulation state of the thermal power unit, and generate the corresponding sub-prediction function controller to obtain the state prediction of the deep peak regulation of the thermal power unit at the current moment or at a certain moment in the future;

[0046] Step 5: Determine the optimal control amount of deep peak regulation of thermal power units by predicting the state of deep peak regulation of thermal power units at multiple moments.

[0047] Preferably, the calculation formula for the fuel consumption cost of the thermal power unit in step 2 includes C coal represents the fuel consumption cost of the thermal power unit, a, b and c all represent the consumption characteristic coefficients of the thermal power unit, and P represents the output power of the thermal power unit. The calculation formula is:

[0048] C coal =aP 2 +bP+c

[0049] Also includes P min and P max , P minis the minimum output power of the thermal power unit, P max is the maximum output power of the thermal power unit, the P min <P<P max .

[0050] Preferably, the calculation formula for deep peak regulation of the thermal power unit in step three is:

[0051] Q i =(A i ·B i ·C i ·D i )÷P

[0052] Among them, i represents the thermal power unit, Q i represents the deep peak load regulation state score of thermal power unit i, A i represents the network blocking factor, B i Denitrification factor, C i Denotes dust removal factor and D i represents the desulfurization factor.

[0053] Preferably, the calculation formula of the sub-prediction function controller in step 4 is:

[0054] x k+1∣k =Ex k∣k +Fu k∣k

[0055] where x k+1∣k represents the prediction of the state of the thermal power unit at time k+1 at time k, x k∣k and u k∣k They represent the estimation and control input of the state at time K at time k respectively, and E and F represent the system matrices.

[0056] Preferably, it also includes total operating costs, which include fuel consumption costs, equipment loss costs and penalty costs of the thermal power units. The equipment smoothness cost is the loss caused by the frequent actions of auxiliary equipment to cooperate with changes in the operating conditions of the units. The penalty cost is the penalty cost received by the thermal power units when completing deep peak-shaving tasks.

[0057] Specifically, during the deep peak load regulation process, thermal power units need to be adjusted according to the dispatching instructions of the power grid. This usually involves multiple aspects such as load distribution, combustion adjustment, and operation control of steam turbines. In addition, the deep peak load regulation of thermal power units also needs to consider the impact of network constraints. Network constraints mainly include transmission capacity limitations of transmission lines, grid stability limitations, and trading rules of the power market.

[0058] Therefore, when calculating the specific effect of deep peak regulation of thermal power units, the calculation formula for the fuel consumption cost of thermal power units in step two is used, and then the calculation formula for deep peak regulation of thermal power units in step three is used. This formula will comprehensively consider multiple factors such as the unit's coal consumption cost, network congestion factor, denitrification factor, dust removal factor, desulfurization factor and network constraints.

[0059] Preferably, the step 4 specifically includes the following steps:

[0060] S10: Model building, building a discrete time state space model;

[0061] S11: Predict future dynamics. Using the model established by S11, the system state changes in the future are predicted based on the current system state and control input.

[0062] S12: Solve the optimization problem, substitute the control input based on the predicted future state into the sub-predictive function controller, and calculate the optimal control input.

[0063] A deep peak-shaving control system for a thermal power unit, the control system comprising: a thermal power unit operation data acquisition module, a thermal power unit fuel consumption cost calculation module, a thermal power unit deep peak-shaving state score calculation module and a thermal power unit control amount determination module;

[0064] The thermal power unit operation data acquisition module is used to input current operation data into the thermal power unit fuel consumption cost calculation module for cost calculation, wherein the operation data includes the fuel consumption of the thermal power unit, the consumption characteristic coefficient of the thermal power unit and the output power of the thermal power unit;

[0065] The thermal power unit fuel consumption cost calculation module is used to calculate the fuel consumption cost of the thermal power unit, and input the calculation result into the state score calculation module of the deep peak regulation of the thermal power unit;

[0066] The state score calculation module for deep peak regulation of the thermal power unit is used to calculate the state score of deep peak regulation of the thermal power unit at the current moment;

[0067] The thermal power unit control quantity determination module is used to determine the optimal control quantity for deep peak regulation of the thermal power unit.

[0068] Preferably, it also includes an analysis module, which sets a comprehensive score threshold for the state score of the deep peak regulation of the thermal power unit. When the comprehensive score threshold is exceeded, it is a high-efficiency configuration, and if it does not exceed the comprehensive score threshold, it is a normal configuration.

[0069] The working principle of the first embodiment is:

[0070] By setting a thermal power unit operation data acquisition module, a thermal power unit fuel consumption cost calculation module, a thermal power unit deep peak regulation state score calculation module and a thermal power unit control quantity determination module; the operation data of the current thermal power unit is obtained, the fuel consumption cost of the thermal power unit is calculated by the thermal power unit fuel consumption cost calculation module, and then the state score of the thermal power unit deep peak regulation at the current moment is calculated by the thermal power unit deep peak regulation state score calculation module, and finally a sub-prediction function controller is generated by the thermal power unit control quantity determination module based on a multi-interval sub-prediction model to determine the optimal control quantity of the thermal power unit deep peak regulation; thereby solving the performance condition constraints of various machines in the prior art, which makes it difficult for the controller to be optimized to an ideal state, improving the efficiency and accuracy of the deep peak regulation of the thermal power unit, and ultimately meeting the peak regulation demand.

[0071] Embodiment 2:

[0072] The similarities between this embodiment and the first embodiment are not repeated here, and the differences are as follows:

[0073] Embodiment 2 provides a computer, including a memory, a processor and a cloud server, wherein the memory is used to store computer programs, formulas and calculation methods, etc., the processor is used to run the computer program and enable the computer to execute the deep peak-shaving control method of the thermal power unit of the embodiment, and run the deep peak-shaving control system of the thermal power unit, and the cloud server is used to store and back up all programs, formulas and calculation methods of the computer, and record and archive each operation status and deep peak-shaving status score of the thermal power unit of Embodiment 1, so as to facilitate subsequent improvement of the thermal power unit.

[0074] The above embodiments are merely illustrative of the principles and effects of the present invention, and are not intended to limit the present invention. Anyone familiar with the technology may modify or change the above embodiments without violating the spirit and scope of the present invention. Therefore, all equivalent modifications or changes made by those with ordinary knowledge in the technical field without departing from the spirit and technical ideas disclosed by the present invention should still be covered by the claims of the present invention.

Claims

1. A deep peak regulation control method for a thermal power unit, characterized in that: The control method comprises the following steps: Step 1: Acquire the operation data of the thermal power unit, wherein the operation data includes the fuel consumption of the thermal power unit, the consumption characteristic coefficient of the thermal power unit and the output power of the thermal power unit; Step 2: Input the operating data in step 1 into the calculation formula of the fuel consumption cost of the thermal power unit and obtain the calculation result; Step 3: Input the calculation result of step 2 into the calculation formula of deep peak regulation of thermal power generation unit, and calculate the state score of deep peak regulation of thermal power generation unit at the current moment; Step 4: Establish a multi-interval sub-prediction model of the next frequency regulation controlled object under the deep peak regulation state of the thermal power unit, and generate the corresponding sub-prediction function controller to obtain the state prediction of the deep peak regulation of the thermal power unit at the current moment or at a certain moment in the future; Step 5: Determine the optimal control amount of deep peak regulation of thermal power units by predicting the state of deep peak regulation of thermal power units at multiple moments.

2. A method for deep peak regulation control of a thermal power unit according to claim 1, characterized in that: The calculation formula for the fuel consumption cost of the thermal power unit in step 2 includes C coal represents the fuel consumption cost of the thermal power unit, a, b and c all represent the consumption characteristic coefficients of the thermal power unit, and P represents the output power of the thermal power unit. The calculation formula is: C coal =aP 2 +bP+c Also includes P min and P max , P min is the minimum output power of the thermal power unit, P max is the maximum output power of the thermal power unit, the P min <P<P max .

3. A method for deep peak regulation control of a thermal power unit according to claim 1, characterized in that: The calculation formula for the deep peak regulation of the thermal power unit in step 3 is: Q i =(A i ·B i ·C i ·D i )÷P Among them, i represents the thermal power unit, Q i represents the deep peak load regulation state score of thermal power unit i, A i represents the network blocking factor, B i Denitrification factor, C i Denotes dust removal factor and D i represents the desulfurization factor.

4. A method for deep peak regulation control of a thermal power unit according to claim 1, characterized in that: The calculation formula of the sub-prediction function controller in step 4 is: x k+1∣k =Ex k∣k +Fu k∣k where x k+1∣k represents the prediction of the state of the thermal power unit at time k+1 at time k, x k∣k and u k∣k They represent the estimation and control input of the state at time K at time k respectively, and E and F represent the system matrices.

5. A method for deep peak regulation control of a thermal power unit according to claim 1, characterized in that: It also includes total operating costs, which include fuel consumption costs, equipment loss costs and penalty costs of thermal power units. The equipment smoothing cost is the loss caused by frequent actions of auxiliary equipment to coordinate with changes in the operating conditions of the units. The penalty cost is the penalty cost received by the thermal power units when completing deep peak-shaving tasks.

6. A method for deep peak regulation control of a thermal power unit according to claim 1, characterized in that: The step 4 specifically includes the following steps: S10: Model building, building a discrete time state space model; S11: Predict future dynamics. Using the model established by S11, the system state changes in the future are predicted based on the current system state and control input. S12: Solve the optimization problem, substitute the control input based on the predicted future state into the sub-predictive function controller, and calculate the optimal control input.

7. A deep peak regulation control system for thermal power units, characterized in that: The control system comprises: a thermal power unit operation data acquisition module, a thermal power unit fuel consumption cost calculation module, a thermal power unit deep peak regulation state score calculation module and a thermal power unit control quantity determination module; The thermal power unit operation data acquisition module is used to input current operation data into the thermal power unit fuel consumption cost calculation module for cost calculation, wherein the operation data includes the fuel consumption of the thermal power unit, the consumption characteristic coefficient of the thermal power unit and the output power of the thermal power unit; The thermal power unit fuel consumption cost calculation module is used to calculate the fuel consumption cost of the thermal power unit, and input the calculation result into the state score calculation module of the deep peak regulation of the thermal power unit; The state score calculation module for deep peak regulation of the thermal power unit is used to calculate the state score of deep peak regulation of the thermal power unit at the current moment; The thermal power unit control quantity determination module is used to determine the optimal control quantity for deep peak regulation of the thermal power unit.

8. A deep peak regulation control system for thermal power units according to claim 7, characterized in that: It also includes an analysis module, which sets a comprehensive score threshold for the state score of the deep peak regulation of the thermal power unit. When the comprehensive score threshold is exceeded, it is a high-efficiency configuration, and if it does not exceed the comprehensive score threshold, it is a normal configuration.

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