学習効率を考慮したキャンパスエネルギーマネジメントシステムの提案と実証

抄録

Many studies dealing with energy saving have been conducted from the viewpoint of mitigating global warming. However, most of them only consider energy saving and ignore total environmental impact toward human life. It is necessary to provide a comfortable workspace using efficient and optimized energy control, because excessive demand control may have a negative impact on a living environment. Excessive demand control also brings impact on efficiency of working and learning. In order to provide a comfortable indoor environment, some environmental indexes are necessary, including not only temperature, humidity, luminance, wind speed, but also CO₂ concentration. In this paper, we propose a novel method to allocate power optimally by using learning efficiency, which contains both PMV and CO₂ concentration as its index. We constructed experiments at real place with developed BEMS that enables both monitoring environmental indexes and controlling HVAC systems.