CN110334878B - Photo-thermal energy storage power station power generation amount optimization method based on typical static model - Google Patents

Photo-thermal energy storage power station power generation amount optimization method based on typical static model Download PDF

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CN110334878B
CN110334878B CN201910624118.4A CN201910624118A CN110334878B CN 110334878 B CN110334878 B CN 110334878B CN 201910624118 A CN201910624118 A CN 201910624118A CN 110334878 B CN110334878 B CN 110334878B
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宋汶秦
吕金历
陆军
妥建军
李锦键
陈英普
王海亮
徐建委
汪静
张海生
张中丹
曹喆
王兴贵
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State Grid Corp of China SGCC
State Grid Gansu Electric Power Co Ltd
Lanzhou University of Technology
Economic and Technological Research Institute of State Grid Gansu Electric Power Co Ltd
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State Grid Gansu Electric Power Co Ltd
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Abstract

一种基于静态模型的光热电站发电量优化方法，首先对静态模型中影响电站发电量的可控部分进行分析；其次以发电量最大为目标函数，静态模型的约束条件，建立优化数学模型，提出一种优化方法；最后，引入Smith预估补偿机制，以降低控制系统中出现的大滞后环节对系统稳定性与准确性的影响。本优化方法能有效地提升光热储能电站的发电量与运行效率。

Figure 201910624118

A method for optimizing the power generation of a CSP station based on a static model. First, the controllable part of the static model that affects the power generation of the power station is analyzed; secondly, the maximum power generation is used as the objective function and the constraints of the static model to establish an optimization mathematical model. An optimization method is proposed; finally, the Smith prediction compensation mechanism is introduced to reduce the influence of the large lag in the control system on the stability and accuracy of the system. The optimization method can effectively improve the power generation and operation efficiency of the solar thermal energy storage power station.

Figure 201910624118

Description

一种基于典型静态模型的光热储能电站发电量优化方法An optimization method for power generation of solar thermal energy storage power station based on typical static model

技术领域technical field

本发明涉及基于光热储能电站静态模型的发电量优化方法。The invention relates to a power generation optimization method based on a static model of a solar thermal energy storage power station.

背景技术Background technique

近年来，光热储能发电(Concentrating Solar Power,CSP)方式凭借着其可快速调节出力的优势，已成为解决新能源发电及电网波动性与随机性的重要发电方式。现有关于提升光热储能电站发电量的方式主要有改进储热介质，优化储热方式以及基于热力学动态模型的控制方法，但以上方法都不适用于光热储能电站长时间尺度上的优化。其中，基于热力学动态模型的控制方法中需要检测的量过多，检测元件工作的环境较为恶劣，不适用于长期工作。In recent years, Concentrating Solar Power (CSP) has become an important power generation method to solve the fluctuation and randomness of new energy power generation and power grid due to its advantages of rapid output adjustment. The existing methods for increasing the power generation of CSP stations mainly include improving heat storage medium, optimizing heat storage methods, and control methods based on thermodynamic dynamic models. optimization. Among them, the control method based on the thermodynamic dynamic model requires too much detection, and the working environment of the detection element is relatively harsh, which is not suitable for long-term work.

本发明在CSP电站典型静态模型的基础上，通过优化储热系统充放热能量流的方式，并结合Smith预估补偿机制以消除大滞后环节对控制系统的影响，从而达到提升CSP电站发电量与运行效率的目的。Based on the typical static model of the CSP power station, the present invention improves the power generation of the CSP power station by optimizing the way of charging and discharging the heat energy flow of the heat storage system, and combining with the Smith prediction compensation mechanism to eliminate the influence of the large lag link on the control system. with the purpose of operating efficiency.

发明内容SUMMARY OF THE INVENTION

为了实现CSP电站发电量最大的优化运行，本发明提供一种基于典型静态模型的CSP电站发电量优化方法，主要包括以下步骤：In order to realize the optimal operation of the maximum power generation capacity of the CSP power station, the present invention provides a method for optimizing the power generation capacity of the CSP power station based on a typical static model, which mainly includes the following steps:

步骤1：综合分析CSP电站的典型静态模型与运行模式，得出可以通过优化热能存储子系统(Thermal Storage Subsystem,TSS)的充热功率Pt S-T与放热功率Pt T-P的方法，达到优化CSP电站发电量的目的。引入充热功率系数α∈[0,1]与放热功率系数β∈[0,1]之后的充放热能量流可以表示为：Step 1: Comprehensively analyze the typical static model and operating mode of the CSP power station, and obtain the optimization method that can be achieved by optimizing the thermal energy storage subsystem (Thermal Storage Subsystem, TSS) charging power P t ST and heat releasing power P t TP . The purpose of the power generation of the CSP power station. After introducing the charging and heating power coefficient α∈[0,1] and the exothermic power coefficient β∈[0,1], the charging and discharging energy flow can be expressed as:

Figure BDA0002125940220000011
Figure BDA0002125940220000011

Figure BDA0002125940220000012
Figure BDA0002125940220000012

式中，Pt solar为聚光集热子系统(Solar Field Subsystem,SFS)t时刻收集到能量的功率；ΔPf为能量传递时的损失；Pt S-P为SFS向汽轮机发电子系统(PowerblockSubsystem,PS)提供能量的功率；

Figure BDA0002125940220000013
为SFS向TSS提供能量的功率，即充热功率；
Figure BDA0002125940220000014
为TSS向PS提供能量的功率，即放热功率；γ∈{0,1}为PS工作的状态变量；ut为t时刻启动汽轮发电机组的数量；PSU为启动汽轮发电机组所需的最小能量。In the formula, P t solar is the power of the energy collected by the solar field subsystem (Solar Field Subsystem, SFS) at time t; ΔP f is the loss during energy transfer; P t SP is the SFS to the steam turbine power generation subsystem (Powerblock Subsystem, PS) power to provide energy;
Figure BDA0002125940220000013
The power that provides energy for the SFS to the TSS, that is, the charging power;
Figure BDA0002125940220000014
The power that provides energy for the TSS to the PS, that is, the exothermic power; γ∈ {0,1} is the state variable of the PS operation; u t is the number of starting turbo-generator units at time t; minimum energy required.

步骤2：将CSP电站发电量最大作为优化的目标函数，在输入至系统的能量一定时，通过优化TSS的充放热控制策略，使电站的发电量达到最大。相应的优化约束条件为引入控制变量α与β的CSP电站的静态能量流数学模型。Step 2: The maximum power generation of the CSP power station is taken as the optimization objective function. When the energy input to the system is constant, the power generation of the power station can be maximized by optimizing the charge and release heat control strategy of the TSS. The corresponding optimization constraints are the static energy flow mathematical model of the CSP power plant with the introduction of control variables α and β.

步骤3：在上述优化数学模型的基础上，优化策略的主要方法是：通过检测各子系统自身的能量流及各子系统之间的能量流，得出所对应的具体优化方式，以提高CSP电站的发电量与整体的运行效率。Step 3: On the basis of the above optimization mathematical model, the main method of the optimization strategy is to obtain the corresponding specific optimization method by detecting the energy flow of each subsystem itself and the energy flow between the subsystems, so as to improve the CSP power station. power generation and overall operating efficiency.

为保证CSP电站在光照直接辐射强度(DNI)持续较低的天气情况下仍能发出电能，本优化策略做如下设定：在持续

Figure BDA0002125940220000015
条件下，若TSS充热至
Figure BDA0002125940220000016
时，启动PS，由TSS与SFS共同向PS提供满足要求的能量。具体的优化策略框图如图1所示。In order to ensure that the CSP power station can still generate electricity under the weather conditions with continuously low direct radiation intensity (DNI), the optimization strategy is set as follows:
Figure BDA0002125940220000015
condition, if the TSS is heated to
Figure BDA0002125940220000016
When , the PS is started, and the TSS and SFS jointly provide the PS with the energy that meets the requirements. The specific optimization strategy block diagram is shown in Figure 1.

步骤4：在本优化策略中，充热功率优化控制策略的核心思想为：令

Figure BDA0002125940220000021
作为给定值，通过反馈调节器对充热功率系数α进行调整，使由SFS收集到的能量全部送入TSS存储，或除去PS所需的最小能量后全部送入TSS存储，以减少对能量的浪费。针对控制过程中产生的大时滞环节，引入Smith预估补偿器，以减轻对控制系统的影响。具体的充热功率控制策略框图如图2所示。Step 4: In this optimization strategy, the core idea of the charging power optimization control strategy is:
Figure BDA0002125940220000021
As a given value, the charging power coefficient α is adjusted by the feedback regulator, so that all the energy collected by the SFS is sent to the TSS storage, or the minimum energy required by the PS is removed and all sent to the TSS storage to reduce the energy consumption. of waste. For the large time-delay link in the control process, a Smith predictor compensator is introduced to reduce the impact on the control system. The specific charging power control strategy block diagram is shown in Figure 2.

步骤5：在本优化策略中，放热功率优化控制策略的核心思想为：令

Figure BDA0002125940220000022
作为给定值，通过反馈调节器对放热功率系数β进行调整，使TSS与SFS共同向PS提供满足正常工作要求的能量，以保证CSP电站的正常工作。针对控制过程中产生的大时滞环节，引入Smith预估补偿器，以减轻对控制系统的影响。具体的放热功率控制策略框图如图3所示。Step 5: In this optimization strategy, the core idea of the optimal control strategy for exothermic power is:
Figure BDA0002125940220000022
As a given value, the exothermic power coefficient β is adjusted through the feedback regulator, so that the TSS and SFS jointly provide the PS with energy that meets the normal working requirements, so as to ensure the normal operation of the CSP power station. For the large time-delay link in the control process, a Smith predictor compensator is introduced to reduce the impact on the control system. The specific exothermic power control strategy block diagram is shown in Figure 3.

本发明的有益之处在于：提出了一种基于静态模型的CSP电站发电量优化模型，解决了动态优化策略中检测元件工作环境苛刻等问题。同时，基于静态模型的优化策略可以为今后CSP电站并网之后的优化调度提供一种方法。其次，采用Smith预估补偿器，解决了大时滞环节对控制系统的影响。The advantages of the present invention lie in that a static model-based power generation optimization model of the CSP power station is proposed, which solves the problems of harsh working environment of the detection element in the dynamic optimization strategy. At the same time, the optimization strategy based on the static model can provide a method for the optimal scheduling of CSP power plants after grid connection in the future. Secondly, the Smith predictor compensator is used to solve the influence of the large time-delay link on the control system.

附图说明Description of drawings

图1是优化策略流程框图，图2是充热控制策略框图，图3是放热控制策略框图。Figure 1 is a block diagram of an optimization strategy flow, Figure 2 is a block diagram of a charging control strategy, and Figure 3 is a block diagram of a heat release control strategy.

具体实施方式Detailed ways

本发明是一种基于CSP电站静态模型的发电量最大优化方法。如图1所示，可以通过优化CSP电站内部TSS的充放热控制策略，以达到提升CSP发电量与整体运行效率的目的。针对控制过程中存在的大滞后环节，采用Smith预估补偿器予以补偿，具体的发明步骤为：The invention is a maximum power generation optimization method based on a static model of a CSP power station. As shown in Figure 1, the charge and discharge heat control strategy of the TSS inside the CSP power station can be optimized to achieve the purpose of improving the CSP power generation and overall operating efficiency. Aiming at the large lag link in the control process, the Smith predictor compensator is used to compensate. The specific steps of the invention are as follows:

步骤1：综合分析CSP电站的典型静态模型与运行模式，得出可以通过优化热能存储子系统(Thermal Storage Subsystem,TSS)的充热功率Pt S-T与放热功率Pt T-P的方法，达到优化CSP电站发电量的目的。引入充热功率系数α∈[0,1]与放热功率系数β∈[0,1]之后的充放热能量流可以表示为：Step 1: Comprehensively analyze the typical static model and operating mode of the CSP power station, and obtain the optimization method that can be achieved by optimizing the thermal energy storage subsystem (Thermal Storage Subsystem, TSS) charging power P t ST and heat releasing power P t TP . The purpose of the power generation of the CSP power station. After introducing the charging and heating power coefficient α∈[0,1] and the exothermic power coefficient β∈[0,1], the charging and discharging energy flow can be expressed as:

Figure BDA0002125940220000023
Figure BDA0002125940220000023

Figure BDA0002125940220000024
Figure BDA0002125940220000024

式中，Pt solar为聚光集热子系统(Solar Field Subsystem,SFS)t时刻收集到能量的功率；ΔPf为能量传递时的损失；Pt S-P为SFS向汽轮机发电子系统(PowerblockSubsystem,PS)提供能量的功率；

Figure BDA0002125940220000025
为SFS向TSS提供能量的功率，即充热功率；
Figure BDA0002125940220000026
为TSS向PS提供能量的功率，即放热功率；γ∈{0,1}为PS工作的状态变量；ut为t时刻启动汽轮发电机组的数量；PSU为启动汽轮发电机组所需的最小能量。In the formula, P t solar is the power of the energy collected by the solar field subsystem (Solar Field Subsystem, SFS) at time t; ΔP f is the loss during energy transfer; P t SP is the SFS to the steam turbine power generation subsystem (Powerblock Subsystem, PS) power to provide energy;
Figure BDA0002125940220000025
The power that provides energy for the SFS to the TSS, that is, the charging power;
Figure BDA0002125940220000026
The power that provides energy for the TSS to the PS, that is, the exothermic power; γ∈ {0,1} is the state variable of the PS operation; u t is the number of starting turbo-generator units at time t; minimum energy required.

步骤2：将CSP电站发电量最大作为优化的目标函数，在输入至系统的能量一定时，通过优化TSS的充放热控制策略，使电站的发电量达到最大，则对应的目标函数为：Step 2: The maximum power generation of the CSP power station is taken as the objective function of optimization. When the energy input to the system is constant, the power generation of the power station can be maximized by optimizing the charging and discharging control strategy of the TSS. The corresponding objective function is:

max et·T (公式五)max e t ·T (Formula 5)

式中，et为t时刻CSP电站的输出电功率；T为CSP电站的发电时长。In the formula, e t is the output electric power of the CSP power station at time t; T is the power generation time of the CSP power station.

相应的优化约束条件为引入控制变量α与β的CSP电站的静态能量流数学模型。The corresponding optimization constraints are the static energy flow mathematical model of the CSP power plant with the introduction of control variables α and β.

步骤3：在上述优化数学模型的基础上，优化策略的主要方法是：通过检测各子系统自身的能量流及各子系统之间的能量流，得出所对应的具体优化方式，以提高CSP电站的发电量与整体的运行效率。具体表现为：①当阳光不充足，且PS停止工作时，由SFS收集到的能量全部存储到TSS中；当PS正在工作时，由TSS与SFS共同向PS提供满足工作要求的能量；②当阳光充足时，将PS无法利用的多余能量尽可能全部储存到TSS中；③当无阳光时，为保证CSP系统的正常工作，TSS以最大功率进行放热，为PS提供满足要求的能量。Step 3: On the basis of the above optimization mathematical model, the main method of the optimization strategy is to obtain the corresponding specific optimization method by detecting the energy flow of each subsystem itself and the energy flow between the subsystems, so as to improve the CSP power station. power generation and overall operating efficiency. The specific performance is as follows: ①When the sunlight is insufficient and the PS stops working, all the energy collected by the SFS is stored in the TSS; when the PS is working, the TSS and the SFS jointly provide the PS with energy that meets the working requirements; ②When the PS is working When the sunlight is sufficient, the excess energy that cannot be used by the PS is stored in the TSS as much as possible; ③ When there is no sunlight, in order to ensure the normal operation of the CSP system, the TSS releases heat at the maximum power to provide the PS with energy that meets the requirements.

为保证CSP电站在光照直接辐射强度(DNI)持续较低的天气情况下仍能发出电能，本优化策略做如下设定：在持续

Figure BDA0002125940220000031
条件下，若TSS充热至
Figure BDA0002125940220000032
时，启动PS，由TSS与SFS共同向PS提供满足要求的能量。具体的优化策略框图如图1所示。In order to ensure that the CSP power station can still generate electricity under the weather conditions with continuously low direct radiation intensity (DNI), the optimization strategy is set as follows:
Figure BDA0002125940220000031
condition, if the TSS is heated to
Figure BDA0002125940220000032
When , the PS is started, and the TSS and SFS jointly provide the PS with the energy that meets the requirements. The specific optimization strategy block diagram is shown in Figure 1.

步骤4：在本优化策略中，充热功率优化控制策略的核心思想为：令

Figure BDA0002125940220000033
作为给定值，通过反馈调节器对充热功率系数α进行调整，使由SFS收集到的能量全部送入TSS存储，或除去PS所需的最小能量后全部送入TSS存储，以减少对能量的浪费。对充热能量流进一步分析，有：Step 4: In this optimization strategy, the core idea of the charging power optimization control strategy is:
Figure BDA0002125940220000033
As a given value, the charging power coefficient α is adjusted by the feedback regulator, so that all the energy collected by the SFS is sent to the TSS storage, or the minimum energy required by the PS is removed and all sent to the TSS storage to reduce the energy consumption. of waste. Further analysis of the charging energy flow, there are:

Figure BDA0002125940220000034
Figure BDA0002125940220000034

可解得：Solved:

Figure BDA0002125940220000035
Figure BDA0002125940220000035

将关于时间t的一次函数变换到频域，有：Transform the linear function of time t to the frequency domain, we have:

Figure BDA0002125940220000036
Figure BDA0002125940220000036

故可以得出：充热功率系数α与主要变化量(DNI)呈正相关。针对控制过程中产生的大时滞环节，引入Smith预估补偿器，以减轻对控制系统的影响。此外，考虑到克服系统较大惯性及消除偏差等目的，采用PID调节器以实现控制目标。具体的充热控制策略框图如图2所示。Therefore, it can be concluded that the charging power coefficient α is positively correlated with the main variation (DNI). For the large time-delay link in the control process, a Smith predictor compensator is introduced to reduce the impact on the control system. In addition, considering the purpose of overcoming the large inertia of the system and eliminating the deviation, a PID regulator is used to achieve the control objective. The specific charging control strategy block diagram is shown in Figure 2.

步骤5：在本优化策略中，放热功率优化控制策略的核心思想为：令

Figure BDA0002125940220000037
作为给定值，通过反馈调节器对放热功率系数β进行调整，使TSS与SFS共同向PS提供满足正常工作要求的能量，以保证CSP电站的正常工作。对放热能量流进一步分析，有：Step 5: In this optimization strategy, the core idea of the optimal control strategy for exothermic power is:
Figure BDA0002125940220000037
As a given value, the exothermic power coefficient β is adjusted through the feedback regulator, so that the TSS and SFS jointly provide the PS with energy that meets the normal working requirements, so as to ensure the normal operation of the CSP power station. Further analysis of the exothermic energy flow, there are:

Figure BDA0002125940220000038
Figure BDA0002125940220000038

因为当TSS处于放热状态时，CSP发电系统处于正常运行，故(公式四)中的ΔPf可近似忽略，且γ＝1，ut＝0，Pt solar≈Pt S-P，此时将(公式四)带入上式可解得：Because when the TSS is in the exothermic state, the CSP power generation system is in normal operation, so the ΔP f in (Formula 4) can be approximately ignored, and γ=1, u t =0, P t solar ≈P t SP , then the (Formula 4) is brought into the above formula to get:

Figure BDA0002125940220000039
Figure BDA0002125940220000039

同理将上式变换到频域。有：In the same way, the above equation is transformed to the frequency domain. Have:

Figure BDA00021259402200000310
Figure BDA00021259402200000310

可以得出：放热功率系数β与主要变化量(DNI)呈负相关。同样的，针对控制过程中产生的大时滞环节，引入Smith预估补偿器，以减轻对控制系统的影响。此外，考虑到克服系统较大惯性及消除偏差等目的，采用PID调节器以实现控制目标。具体的放热控制策略框图如图3所示。It can be concluded that the exothermic power coefficient β is negatively correlated with the main variation (DNI). Similarly, for the large time-delay link in the control process, a Smith prediction compensator is introduced to reduce the impact on the control system. In addition, considering the purpose of overcoming the large inertia of the system and eliminating the deviation, a PID regulator is used to achieve the control objective. The specific heat release control strategy block diagram is shown in Figure 3.

以上是本发明的实施方法之一，对于本领域内的一般技术员而言，在不花费创造性劳动的情况下，可对上述实施例进行多种变化，同样能够实现本发明的目的。但是很明显，这种变化应该包含在本发明权利要求书的保护范围内。The above is one of the implementation methods of the present invention. For those skilled in the art, various changes can be made to the above-mentioned embodiments without creative work, and the object of the present invention can also be achieved. However, it is obvious that such changes should be included within the protection scope of the claims of the present invention.

Claims (1)

1. A method for optimizing the generated energy of a photo-thermal energy storage power station based on a typical static model is characterized by comprising the following steps:
step 1: comprehensively analyzing a typical static model and an operation mode of the photo-thermal energy storage power station to obtain the heat charging and discharging power P capable of optimizing the heat energy storage subsystemt S-PWith heat release power Pt T-PThe method optimizes the generating capacity of the photo-thermal energy storage power station; introducing a heat charging power coefficient alpha epsilon [0,1 ∈ ]]With heat release power coefficient beta ∈ [0,1 ]]The subsequent charge and discharge energy flow can be expressed as:
Figure FDA0003537516850000011
in the formula, Pt solarCollecting the power of the energy for the light-gathering and heat-collecting subsystem at the moment t;
ΔPfloss in energy transfer;
Pt S-Pproviding power of energy for the light-gathering and heat-collecting subsystem to the steam turbine power generation subsystem;
Figure FDA0003537516850000012
providing energy power, namely heat charging power, for the light and heat gathering subsystem to the heat energy storage subsystem;
Figure FDA0003537516850000013
providing power, namely heat release power, for the thermal energy storage subsystem to the steam turbine power generation subsystem;
gamma belongs to {0,1} is a working state variable of the steam turbine power generation subsystem;
utstarting the number of the turbo generator units at the time t;
PSUminimum energy required for starting the turbo generator set;
step 2: the maximum generated energy of the photo-thermal energy storage power station is used as an optimized objective function, and when the energy input into the system is constant, the generated energy of the power station is maximized by optimizing a charging and discharging control method of the thermal energy storage subsystem; the corresponding optimization constraint condition is a static energy flow mathematical model of the photo-thermal energy storage power station with control variables alpha and beta introduced;
And step 3: on the basis of the optimization model, the implementation way of the optimization method is as follows: the corresponding specific control mode is obtained by detecting the energy flow of each subsystem and the energy flow among the subsystems, so that the generated energy and the overall operating efficiency of the photo-thermal energy storage power station are improved; in order to ensure that the photo-thermal energy storage power station can still generate electric energy under the weather condition that the direct illumination radiation intensity-DNI (deep ultraviolet) is continuously low, the optimization method is set as follows:
in the process of persistence
Figure FDA0003537516850000014
Under the condition, if the thermal energy storage subsystem is charged to
Figure FDA0003537516850000015
When the system is started, the steam turbine power generation subsystem is started, and the heat energy storage subsystem and the light-gathering and heat-collecting subsystem provide energy meeting requirements for the steam turbine power generation subsystem together;
and 4, step 4: in the optimization method, the realization approach of the heat charging power optimization control method is as follows: order to
Figure FDA0003537516850000016
As a given value, adjusting the heat charging power coefficient alpha through a feedback regulator; when the steam turbine power generation subsystem does not work, all the energy collected by the light and heat collection subsystem is sent to the heat energy storage subsystem for storage; when the steam turbine power generation subsystem works for power generation, the energy collected by the light-gathering and heat-collecting subsystem is completely sent to the heat energy storage subsystem for storage after the minimum energy required by the steam turbine power generation subsystem is removed; the heat charging energy flow is further analyzed, and the following steps are included:
Figure FDA0003537516850000021
Can be solved as follows:
Figure FDA0003537516850000022
transforming the linear function with respect to time t into the frequency domain, there are:
Figure FDA0003537516850000023
therefore, it can be obtained that: the heat charging power coefficient alpha is in positive correlation with the main variable quantity, and a Smith pre-estimation compensator and a PI regulator are introduced to adjust the heat charging power coefficient alpha;
and 5: in the optimization method, the heat release power optimization control method is realized by the following steps: order to
Figure FDA0003537516850000024
As a given value, adjusting the heat release power coefficient beta through a feedback regulator to enable the heat energy storage subsystem and the light gathering and heat collecting subsystem to provide energy meeting normal working requirements for the steam turbine power generation subsystem together; the exothermic power was further analyzed to be:
Figure FDA0003537516850000025
when the thermal energy storage subsystem is in a heat release state, the photo-thermal energy storage power generation system is in normal operation, and delta PfCan be ignored, and gamma is 1, ut＝0，Pt solar≈Pt S-PAt this time, the following can be solved:
Figure FDA0003537516850000026
the same way transforms the above equation to the frequency domain, with:
Figure FDA0003537516850000027
therefore, it can be obtained that: the heat release power coefficient beta is inversely related to the main variation; and a Smith pre-estimation compensator and a PI regulator are introduced to adjust the Smith pre-estimation compensator and the PI regulator.
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