重庆理工大学学报2024，Vol.38Issue(1)：160-168,9.DOI:10.3969/j.issn.1674-8425(z).2024.01.018
空压机负荷预测与智能调度算法研究
Research on air compressor load prediction and intelligent scheduling algorithm
摘要
Abstract
The air compressor system consists of multiple units,and the optimization of unit combination is a nonlinear and large-scale task of multiple objectives and constraints.To address such problems as high energy consumption and serious waste of resources in air compressor scheduling,this paper studies the quantity scheduling problem of air compressors based on the characteristics of air compressor combination.A multi-strategy improved Harris Hawk Optimization Algorithm(MHHO)combined with Deep Echo State Network(DESN)is proposed to predict the load of the air compressor.After obtaining the load required for 24 hours a day,the MHHO algorithm is employed for unit combination scheduling and gas consumption allocation.Our experimental results show the prediction model achieves a higher prediction accuracy,and thus is highly applicable for air compressor load prediction.Intelligent scheduling improves the unit operation efficiency and reduces the system's energy consumption.关键词
空压机负荷预测/改进的哈里斯鹰优化算法/深度回声状态网络/超参数/智能调度Key words
air compressor load prediction/improved Harris Hawk optimization algorithm/deep echo state network/hyperparameters/intelligent scheduling分类
信息技术与安全科学引用本文复制引用
王华秋,张燕..空压机负荷预测与智能调度算法研究[J].重庆理工大学学报,2024,38(1):160-168,9.基金项目
国家科技部重点研发计划项目(2018YFB1700803) （2018YFB1700803）
重庆市科委一般自然基金项目(cstc2019jcyj-msxmX0500) （cstc2019jcyj-msxmX0500）
