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首页> 外文期刊>International Journal of Innovative Computing Information and Control >ENERGY CONSERVATION AND COMFORT MANAGEMENT IN BUILDING ENVIRONMENT
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ENERGY CONSERVATION AND COMFORT MANAGEMENT IN BUILDING ENVIRONMENT

机译：建筑环境节能与舒适管理

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摘要

Today energy conservation in building sector is a major subject of interest to the research community. A number of applications proposed and exist in the literature, but the trade-off between users comfort index and energy consumption is still a major challenge to the researchers. In this paper we propose energy conservations and comfort management model in building environment using Multi-Island Genetic Algorithm (MIGA) and Genetic Algorithm (GA). The focus of our paper is to increase occupants comfort index and minimize energy consumption simultaneously. The input of the fuzzy logic is the error difference between real environment and user set parameters. To minimize the required output power of the fuzzy, we need to minimize the error difference. To do this, the input parameters of the fuzzy are optimized using MIGA/GA. After optimization, the error difference between MIGA/GA optimal parameters and environmental parameters becomes small as compare with the error difference between without-MIGA/GA parameters (without optimization) and environmental parameters. This small error consequently minimizes the required power with respect to the occupant's comfort index and available power. The results show the effectiveness of the proposed model in increasing the occupant's comfort index and minimizing energy consumption.
机译：如今，建筑行业的节能已成为研究界关注的主要课题。文献中提出并存在许多应用，但是用户舒适度指数和能耗之间的权衡仍然是研究人员面临的主要挑战。本文提出了利用多岛遗传算法（MIGA）和遗传算法（GA）的建筑环境节能和舒适管理模型。本文的重点是提高乘员的舒适指数并同时最大程度地减少能耗。模糊逻辑的输入是真实环境和用户设置参数之间的误差差。为了最小化所需的模糊输出功率，我们需要最小化误差差异。为此，使用MIGA / GA优化模糊的输入参数。优化后，与不使用MIGA / GA参数（不优化）和环境参数之间的误差相比，MIGA / GA最佳参数和环境参数之间的误差将变小。因此，该小误差使关于乘员的舒适指数和可用功率的所需功率最小化。结果表明，该模型在提高乘员的舒适度指标和最小化能耗方面是有效的。

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