空调
电
计算机科学
调度(生产过程)
碳足迹
温室气体
环境科学
汽车工程
模拟
数学优化
工程类
运营管理
电气工程
机械工程
生态学
数学
生物
作者
Xipeng Shen,Jiahao Li,Yitong Yin,Jianlin Tang,Bin Qian,Xiaoming Liu,Zongyi Wang
标识
DOI:10.3389/fenrg.2024.1360573
摘要
As global temperatures rise and climate change becomes more severely. People realize that air conditioning systems as a controllable resource and play an increasingly important role in reducing carbon emissions. In the past, the operation optimization of air conditioning systems was mainly oriented to user comfort and electricity costs ignoring the long-term impact on the environment. This article aims to establish a multi-objective model of air-conditioning load to ensure user temperature comfort performance and reduce the total cost (i.e., electricity cost and carbon emission cost) simultaneously. Multi Sand Cat Swarm Optimization (MSCSO) algorithm combined with gray target decision-making (GTD) is used to explore optimal solution. Meanwhile four competitive strategies are applied to validate the effectiveness of the proposed method, i.e., genetic algorithm (GA), MSCSO-comfort objective, MSCSO-total electricity cost objective and unoptimization. The simulation results show that the MSCSO-GTD based objective method can significantly reduce total costs while taking into account appropriate indoor temperature comfort.
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