Air Conditioning Consumption Optimization Based on CO2 Concentration Level

Mahsa Khorram, Modar Zheiry, P. Faria, Z. Vale
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引用次数: 2

Abstract

Nowadays, energy consumption increasing is a big concern for many countries around the world. Disadvantages and consequences of fossil fuels for the environment caused a lot of efforts to invest in renewable energy resources and programs to optimize energy consumption. All types of buildings are the major consumers of electric power. Therefore, buildings can be considered as good options for implementing optimization algorithms, assuming that they are equipped to required infrastructures. Air conditioners are flexible loads that can be directly controlled by optimization programs. This paper presents a particle swarm optimization algorithm to minimize the power consumption of the air conditioners based on the carbon dioxide concentration level. The algorithm considers the thermal comfort of users with defining restrictions. The case study of the paper proposes two scenarios with real monitored data of a building. The result of the paper shows the obtained results of the algorithm and makes the comparison of two scenarios.
基于CO2浓度水平的空调能耗优化
如今,能源消耗的增加是世界上许多国家关注的一个大问题。化石燃料对环境的缺点和后果导致了许多努力投资于可再生能源资源和优化能源消耗的计划。所有类型的建筑物都是电力的主要消费者。因此,如果建筑物配备了所需的基础设施,则可以将其视为实施优化算法的良好选择。空调是柔性负荷,可通过优化程序直接控制。提出了一种基于二氧化碳浓度水平的粒子群优化算法,以实现空调功耗的最小化。该算法考虑了用户的热舒适性,并定义了限制条件。本文的案例研究提出了两种具有建筑物真实监控数据的场景。论文的结果展示了算法得到的结果,并对两种场景进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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