吹灰是清除受热面积灰结渣的一种有效手段。目前电厂吹灰的频率和时机通常是依靠经验判断，效率低且经济成本高。为改善吹灰方式，以新疆准东地区某台660 MW超超临界燃煤电站锅炉为研究对象，基于电厂分布式控制系统(DCS)中的运行数据、受热面管束排布方式及入炉煤的煤质特性，运用热平衡法求出受热面上的灰污系数，并构建在线监测模型，利用该模型优化原有的吹灰系统。结果表明：优化后1天内吹灰频率减少4次，可为电厂节省约76.26 t煤，说明此优化模型经济效益十分明显。

Soot blowing is a very effective means to remove ash and slag from heating surface. At present, the frequency and timing of soot blowing in power plants are mostly judged by experience, which is low in efficiency and high in economic cost. To improve the way of blowing blindly, this paper takes a 660 MW ultrasupercritical coalfired utility boiler in Xinjiang Zhundong region as the research object, based on the operation data of distributed control system (DCS) of power plant, heating surface tube bundle arrangement way, medium characteristics of coal in furnace, the fouling coefficient of heating surface is calculated by using heat balance method, and online monitoring model is built to optimize the original soot blowing system. Results show that after the optimization, the soot blowing frequency is reduced 4 times in one day, which can save about 76.26 ton of coal for the power plant, indicating that the economic benefit of the optimization model is very obvious.

TK221

积灰结渣；热平衡法；在线监测；灰污系数；吹灰时长