气候变化领域集成服务门户(CCPortal): Model predictive control and rainfall Uncertainties: Performance and risk analysis for drainage systems

CCPortal

DOI	10.1016/j.jhydrol.2024.130779
	Model predictive control and rainfall Uncertainties: Performance and risk analysis for drainage systems
	Chen, Yang; Wang, Chao; Yang, Qiu; Lei, Xiaohui; Wang, Hao; Jiang, Shuanglin; Wang, Ziyuan
发表日期	2024
ISSN	0022-1694
EISSN	1879-2707
起始页码	630
卷号	630
英文摘要	Urban flooding resulting from severe rainstorms is an increasing challenge for cities worldwide due to climate change and rapid urbanization. Model predictive control (MPC) has emerged as a promising approach for realtime management of urban drainage systems to mitigate flooding impacts. However, existing MPC research often relies on idealized rainfall forecasts without adequately accounting for forecast uncertainty, which can compromise the effectiveness of MPC strategies. This study aims to address this critical research gap by developing a framework to evaluate the impacts of forecast uncertainty on MPC performance for urban drainage management. The framework consists of 3 components, (1) martingale model of forecast evolution based on Langevin dynamics for generating rainfall data under different uncertainty conditions (2) MPC, which accepts the rainfall inputs and obtains the real-time control results under different uncertainty conditions and (3) the Scheduling Performance Indicator module, which performs a systematic evaluation of the real-time control system. Using a case study of the Doumen region in Fuzhou City, the results reveal two key findings: First, MPC performance remains close to optimal when forecast uncertainty levels are between 0.1 and 0.3, but deteriorates significantly at uncertainty levels from 0.3 to 0.5. Second, while the MPC error feedback module can occasionally degrade performance for individual events, its overall impact is beneficial in reducing performance deviation risks.
英文关键词	Model predictive control; Uncertainty evolution; Langevin dynamics; Rainfall forecast uncertainty; Urban drainage systems; Real-time control
语种	英语
WOS研究方向	Engineering ; Geology ; Water Resources
WOS类目	Engineering, Civil ; Geosciences, Multidisciplinary ; Water Resources
WOS记录号	WOS:001176152700001
来源期刊	JOURNAL OF HYDROLOGY
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/297502
作者单位	Northeastern University - China; China Institute of Water Resources & Hydropower Research; Xiamen University; Jiangsu University; Hohai University
推荐引用方式 GB/T 7714	Chen, Yang,Wang, Chao,Yang, Qiu,et al. Model predictive control and rainfall Uncertainties: Performance and risk analysis for drainage systems[J],2024,630.
APA	Chen, Yang.,Wang, Chao.,Yang, Qiu.,Lei, Xiaohui.,Wang, Hao.,...&Wang, Ziyuan.(2024).Model predictive control and rainfall Uncertainties: Performance and risk analysis for drainage systems.JOURNAL OF HYDROLOGY,630.
MLA	Chen, Yang,et al."Model predictive control and rainfall Uncertainties: Performance and risk analysis for drainage systems".JOURNAL OF HYDROLOGY 630(2024).