期刊论文

Ji, Dongxu(jidongxu@cuhk.edu.cn)

英文

Applied Thermal Engineering

1359-4311

2023

227

120386

10.1016/j.applthermaleng.2023.120386

This work is supported by the National Natural Science Foundation of China (grant no. 62173050), the Energy Conservation and Emission Reduction Hunan University Student Innovation and Entrepreneurship Education Center (grant no. 2020-19), Changsha University of Science and Technology's "The Double First Class University Plan" International Cooperation and Development Project in Scientific Research in 2018 (grant no. 2018IC14), the Hunan Provincial Department of Transportation's 2018 Science and Technology Progress and Innovation Plan Project (grant no. 201843), General Projects of Hunan University Students' Innovation and Entrepreneurship Training Program in 2022 (grant no. 2565), the Graduate Scientific Research Innovation Project of Changsha University of Science and Technology (grant no. CXCLY2022094), National Natural Science Foundation of China (grant no. 52206279), Shenzhen Science and Technology Innovation Commission (grant no. KCXFZ20211020165004006).

本校为第一机构

Aiming at the problem of considerable economic losses caused by the large fluctuation range of response load and Automatic Generation Control (AGC) commanded load of ultra-supercritical thermal power units, an inadequate load output diagnosis model of multi-label random forest with multi-improved whale optimization algorithm (MIWOA-MLRF) is proposed. Thermal power units are a kind of high-dimensional, nonlinear, and complex industrial complex, which brings difficulty for conventional mechanistic models in comprehensively analyzing the inadequat...