分类
通风(建筑)
多目标优化
数学优化
帕累托原理
计算机科学
能源消耗
功率(物理)
算法
混合算法(约束满足)
工程类
数学
随机规划
物理
电气工程
约束规划
约束逻辑程序设计
机械工程
量子力学
作者
Bao-cai Yu,Liang-Shan Shao
出处
期刊:Energy Reports
[Elsevier]
日期:2022-11-01
卷期号:8: 11003-11021
被引量:4
标识
DOI:10.1016/j.egyr.2022.08.228
摘要
With the increase of mining years, the mine ventilation system becomes more and more complex, causing serious energy waste. The traditional single-objective optimization model cannot accurately describe the complex mine ventilation system. In order to solve this problem, this paper establishes a multi-objective optimization model for mine ventilation systems considering ventilation energy consumption, fan shaft power, and fan efficiency. Furthermore, we proposed an R2 index hybrid multi-objective equilibrium optimization algorithm(R2HMEOA). Firstly, We use R2 index to improve the sorting rules of the Pareto solution. Secondly, improve the reference point strategy, and propose an elite archiving strategy based on R2 index. We use classical test functions to test the proposed algorithm. The results show that the algorithm has obvious advantages. Furthermore, we apply the algorithm to the ventilation system optimization of Wangjialing mine of Zhongmei Huajin Energy Co. Ltd. The results show that the algorithm can effectively reduce the ventilation power consumption and improve the shaft power and efficiency of the fan, which proves the practicability of the proposed algorithm.
科研通智能强力驱动
Strongly Powered by AbleSci AI