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城市空气质量目标约束下冬季污染减排最优控制策略研究

陈晓红1,2,周明辉1,唐湘博1   

  1. 1. 湖南工商大学
    2. 中南大学商学院
  • 收稿日期:2022-01-24 修回日期:2022-09-12 发布日期:2022-09-13
  • 通讯作者: 唐湘博
  • 基金资助:
    知识扩散视角下的智能网联汽车产业开放协同创新研究;北京市 社会科学基金项目;中央高校基本科研业务费精品文科项目;中央高校基本科研业务费精品文科项目

Research on the Optimal Control Strategy for Pollution Reduction in Winter under the Constraints of Urban Air Quality Targets

  • Received:2022-01-24 Revised:2022-09-12 Published:2022-09-13

摘要： 本文提出城市空气质量达标约束的污染减排最优控制系统，以空气质量模型（WRF-CMAQ）为基础，搭建“本地化”空气质量模拟平台，构建空气质量达标评估模型和减排成本优化模型，并通过遗传算法求解某城市冬季拟定空气质量目标约束下污染减排最优控制策略。结果表明，在保持臭氧浓度不变的情形下，当PM2.5目标浓度值分别拟定为55?g/m3、60?g/m3、65?g/m3时，可得到相应的污染减排最优控制方案。空气质量PM2.5目标值分别改进30.4%、24.1%、17.8%，对应减排总成本分别为16.6×106、6.36×106、1.46×106元。本文构建的城市污染减排最优控制系统及其模型求解方法，不仅可为制定城市冬季重污染天气应对方案提供有效科技支撑，也可为城市制定“一市一策”空气质量达标战略规划提供理论指导与决策方法。

关键词: 冬季典型月份, 空气质量目标, 遗传算法, 污染减排, 最优控制策略

Abstract: This paper proposes an optimal control system for pollution reduction constrained by urban air quality compliance. Based on the air quality model (WRF-CMAQ), a “localized” air quality simulation platform is built, and an air quality compliance assessment model and emission reduction cost optimization model are constructed. The genetic algorithm is used to solve the optimal control strategy of pollution reduction of a city under the constraint of air quality target in winter. The results show that under the condition of keeping the ozone concentration unchanged, when the PM2.5 target concentration values are set as 55?g/m3, 60?g/m3, and 65?g/m3, respectively, the corresponding optimal control scheme of pollution reduction can be obtained. The PM2.5 target concentration values were improved by 30.4%, 24.1%, and 17.8%, and the corresponding total emission reduction costs were 16.6×106, 6.36×106, and 1.46×106 yuan, respectively. The optimal control system for urban pollution reduction and its model solving method constructed in this paper can not only provide effective scientific and technological support for the formulation of the urban heavy pollution weather response plan in winter, but also provide theoretical guidance and decision-making method for the development of “one city, one policy” urban air quality compliance strategic planning.

Key words: typical months of winter, air quality target, genetic algorithm, pollution reduction, optimal control strategy

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