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针对机组直接监测数据无法准确反映空预器内部堵塞情况的现状,本节首先基于流体力学基本原理,结合机组负荷及空预器进出口压差等实测数据,构建了空预器实时阻力系数计算方法;进一步针对该计算结果随机误差较大的问题,引入近期内历史数据进行拟合修正,以获得基于不同运行周期的堵塞演化模型。
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空预器阻力系数是反映其内部堵塞状态的无量纲参数,其计算公式如式(1)所示[16]。
$$ K=2 \dfrac{\Delta P}{\overline{\rho}_{{\mathrm{f}}}\left(Q_{\mathrm{z}} / A_{\mathrm{ph}}\right)^{2}} $$ (1) 式中:
Δp ——空预器进出口压力差(Pa);
$ \bar{\rho}_{{\mathrm{f}}} $ ——流经空预器的烟气的平均密度(kg/m3);
Qv ——流经空预器的烟气的体积流量(折算至烟气平均温度状态下,m3/s);
Aph ——空预器烟气侧的流通截面积(m2)。
在实际应用中,烟气压差主要依靠空预器进出口处布置的压力测点的实测数据计算得到;由于烟气的温度和压力波动范围通常较小,烟气平均密度通常视为定值;而烟气流量则是该计算方法的主要难点。电厂SIS系统(厂级信息监控系统)的烟气流量通常是标准状态下(0 ℃,101.325 kPa)、干基(即不含水蒸气)的测量数据,使得该参数参与计算时存在严重滞后;此外,由于难以保证烟道截面内的流速均匀,测量数据可能存在较大随机误差。一种改进方案是引入机组负荷W和过量空气系数α代替式(1)中的烟气流量,获得“修正”的阻力系数如式(2)所示。
$$ K^{\prime}=\Delta p /(W \alpha)^{2} $$ (2) 如图2所示,空预器压差与负荷存在明显的线性相关性(Pearson相关系数0.92,R2为0.84),无法直接反映其内部堵塞状态。而如图3所示,由式(2)所得的阻力系数在机组满负荷运行段相对稳定,可一定程度反映空预器阻力变化。
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机组实际运行中,空预器的阻力系数应只与其内部结构及实时堵塞状态相关:即阻力系数K应在锅炉变负荷过程中保持相对稳定。但图3所示阻力系数即使在堵塞未发生明显变化的时段内,也可能存在大幅波动。这可能由压力传感器的测量系统误差和随机误差导致,也可能是因为测点在截面上的布置位置单一,使得逐时刻计算结果不具有代表性。
为解决该问题,提出引入多项式K(t; k1…ki)的方式对阻力系数K进行拟合与修正:
$$ \Delta p=K\left(t ; k_{1}, k_{2} \cdots k_{i}\right)[W(t) \alpha(t)]^{2}+b $$ (3) 式中:
W(t) ——机组负荷(MW);
α(t) ——过量空气系数;
ki、b ——拟合参数。
其中K的具体拟合形式需依据不同规律变化期(例如:吹灰、停炉冲洗)进行选取,以获取适用于不同时间尺度的堵塞因子演化模型。
经测试,短期内(即通常小于单个吹灰周期),采取二次多项式对阻力系数变化趋势进行拟合可取得较好效果:
$$ K=k_{1} t^{2}+k_{2} t+k_{3} $$ (4) $$ \Delta p(t)=\left(k_{1} t^{2}+k_{2} t+k_{3}\right) W(t)^{2}+b $$ (5) 式中:
k1、k2、k3 ——待定系数。
图4(a)展示了机组A(600 MW)在一次持续约48 h的吹灰周期内的阻力系数拟合效果(R2 = 0.9168)。可见,在该时间区间内,阻力系数呈缓慢上升趋势,与工程实际相符。且如图4(a)所示,利用此拟合多项式计算得到的压差拟合曲线可在消除实际压差的波动的同时,较好地吻合其变化趋势,证明了该拟合结果的可靠性。取机组B(350 MW)一次持续约14 h的吹灰周期数据进行类似拟合验证,得到了如图4(b)及图5(b)所示的拟合效果(R2 = 0.8158),验证了该拟合模型在不同容量机组的适用性。
对于机组更长时间跨度内的堵塞状态演化趋势,简单的二次函数形式通常无法满足压差拟合需求。为处理周期性短期吹灰对空预器长期积灰状态的演化影响,在二次多项式拟合的基础上进一步引入包含吹灰周期T的拟合函数形式:
$$ K=k_1 t^2+k_2 t+k_3\left|\sin \left(\dfrac{{\text{π}}}{T} t\right)\right|+k_4 t+k_5 $$ (6) 式中:
k1~k5 ——待定系数;
T ——吹灰周期。
如图6(a)所示,该拟合多项式下的机组B(350 MW)空预器中长期阻力系数变化规律与实际堵塞状态变化规律相符,且拟合压差可较好地反映实际压差的变化趋势(见图6(b))。此外,图6(a)所示拟合曲线呈现出一定的周期波动趋势,反映了短期的、周期性的吹灰对空预器长期堵塞演化的影响。
图 6 (a) 350 MW机组空预器长期阻力系数演化;(b) 拟合压差
Figure 6. (a) Long-term evolution of resistance coefficient of the air preheater for the 350 MW unit; (b) fitted pressure difference
为获取空预器处于不同调峰状态下吹灰周期内的堵塞增长情况,本节所提的短期空预期阻力系数演化模型通常设置吹灰周期T作为模型数据拟合周期。由此,火电机组可依据周期T内的压差涨幅的变化,为未来机组运行策略调整提供参考依据。此外,本节所提的中长期堵塞规律演化模型是一种对包含多个吹灰周期的空预器长期堵塞状态评估,可显示展示机组在经历长时间灵活变负荷运行后的空预器安全状态,增强火电机组灵活运行能力。
Flexibility-Oriented Safety Assessment Strategy for Air Preheater in Thermal Power Units Adapting to the Advanced Power System
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摘要:
目的 “双碳”目标下新型电力系统建设要求存量火电转向调峰运行,因此火电机组灵活运行下的安全性成为提升电力系统整体稳定性不可或缺的一环。其中,空气预热器是影响火电机组宽负荷运行能力的关键辅机设备,针对其由烟温波动与过量喷氨诱发的堵塞与腐蚀问题,开发回转式空气预热器积灰堵塞实时评估及安全状态监测模型至关重要。 方法 依托我国中部地区某600 MW和350 MW机组宽负荷运行监测大数据,建立了一种基于阻力系数的不同时间尺度逼近的空预器堵塞评估模型;进一步,以空预器出口烟气温度及冷端工作温度为监测指标,统计其在机组多个负荷段的参数超限比例。 结果 结果表明,机组处于39%调峰负荷下监测温度约有20%的超限概率;独立计算两指标下的堵塞风险相较以联合分布计算会一定程度低估其折损率。此外,通过两台机组数据的验证,堵塞评估模型可实现量化机组在空预器吹灰周期内(短期)和中长期的堵塞状态演化趋势。 结论 所提评估策略可应用于SCR脱硝系统、磨煤机等其他火电机组设备及系统,可量化机组调峰运行安全风险,指导火电机组高效、稳定地配合新型电力系统调度。 Abstract:Introduction The realization of dual carbon goals in the construction of a new power system necessitates the transformation of existing thermal power plants to accommodate peak load operations. The safety of thermal power units during flexible operation is a critical element for enhancing the overall stability of the power system. Air preheater is the key auxiliary equipment that affects the wide-load operation capacity of thermal power units. This paper addresses the challenges associated with flue gas temperature fluctuations and blockage and corrosion induced by excessive ammonia injection. It is very important to develop a real-time assessment and safety status monitoring model for dust and blockage of rotary air preheaters. Method Based on the big data of wide-load operation monitoring of 600 MW and 350 MW units in central China, the paper developed a model for air preheater blockage assessment based on approximation of the resistance coefficients in the case of various time scales. Furthermore, the flue gas temperature at the outlet of the air preheater and the cold end working temperature were used as monitoring indicators to count the proportion of parameters exceeding the limit in multiple load sections of the unit. Result The results show that, at a peak regulation load of 39%, there is approximately a 20% probability of temperature exceedance. In addition, the independent calculation of the blockage risk based on the two indicators may result in a certain degree of underestimation of its degradation rate compared to the calculation based on a joint distribution. Besides, with the verification of data from the two units, the method can quantify the short-term (within the soot-blowing cycle) and mid-and-long term evolution of the air preheater blockage. Conclusion This assessment strategy applies to other equipment and systems in thermal power plants, such as SCR denitrification systems and coal mills, providing a quantitative assessment of safety risks during peak load operation. It guides thermal power units to efficiently and stably cooperate with the new power system in dispatching. -
Key words:
- thermal power /
- flexibility /
- air preheater /
- blockage /
- condition assessment
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