Abstract:

Cracking furnace is the key equipment in petrochemical industry. Optimization of cracking furnace status is very important to enhance benefits of ethylene plant. Since pyrolysis reaction mechanism is complex, the model of cracking furnace is difficult to obtain and the cracking furnace has frequent disturbances, and thus it is difficult to optimize the cracking furnace status with traditional optimal methods. In order to solve the problem that the model of cracking furnace is needed in its optimization and the traditional optimal methods lack adaptivity and anti-interference, the correlation integral optimal method is proposed in this paper. First, the operating parameters affecting the benefits of cracking furnace are analyzed, the appropriate operating variables are selected and the optimal objective function is constructed. Then, the historical database is established via the data of operating variables and optimal objective function. Finally, the cracking furnace status is optimized based on the iteration of correlation integral optimal method. The simulation results verify the effectiveness of the correlation integral optimal methods in cracking furnace optimization.

Key words: algorithm, cracking furnace, model, operating variable, measurement, optimal objective function

摘要：

裂解炉是石油化工产业中重要设备,优化裂解炉运行状态对提升乙烯装置绩效至关重要。由于裂解反应机理复杂,裂解炉模型难以确定且扰动频繁,运用传统优化方法难以解决裂解炉运行优化问题。提出将相关积分优化方法应用于裂解炉运行优化,以解决裂解炉优化需要裂解炉具体模型、传统优化方法的自适应性与抗干扰性不满足裂解炉优化需求的两大问题。首先,分析影响裂解炉运行的主要操作参数,选取合适的操作变量,并构建优化目标函数;然后,采集操作变量与优化目标函数数据,建立裂解炉历史数据库。最后,基于相关积分优化方法,利用历史数据进行迭代计算以对裂解炉进行优化。仿真结果验证了相关积分优化方法在裂解炉优化中的有效性。

关键词: 算法, 裂解炉, 模型, 操作变量, 测量, 目标函数