• 대한설비공학회:학술대회논문집
• /
• 대한설비공학회 2007년도 동계학술발표대회 논문집
• /
• pp.352-357
• /
• 2007

The objective of this study is to find the optimal set-point of a hybrid Plant, which is combined by renewable energy plant of the GSHP(Ground Source Heat Pump) and the conventional plant(chiller, boiler). The work presented in this study was carried out by using the EnergyPlus(Version 2.0). In order to validate the simulation model, field data were measured from a building. The GSHP was used as a base plant and the conventional plant as the assistant plant. Various temperatures were controlled (zone summer set-point, zone winter set-point, chilled water temperature, hot water temperature) to find the optimal set-point temperature of the system. The influence of the various set-points were analyzed seasonally.

• 한국멀티미디어학회논문지
• /
• 제23권2호
• /
• pp.155-165
• /
• 2020

In this paper, we propose a smart thermostat temperature set-point control method based on machine learning and rule engine, which controls thermostat's temperature set-point so that it can achieve energy savings as much as possible without sacrifice of occupants' comfort while users' preference usage pattern is respected. First, the proposed method periodically mines data about how user likes for heating (winter)/cooling (summer) his or her home by learning his or her usage pattern of setting temperature set-point of the thermostat during the past several weeks. Then, from this learning, the proposed method establishes a weekly schedule about temperature setting. Next, by referring to thermal comfort chart by ASHRAE, it makes rules about how to adjust temperature set-points as much as low (winter) or high (summer) while the newly adjusted temperature set-point satisfies thermal comfort zone for predicted humidity. In order to make rules work on time or events, we adopt rule engine so that it can achieve energy savings properly without sacrifice of occupants' comfort. Through experiments, it is shown that the proposed smart thermostat temperature set-point control method can achieve better energy savings while keeping human comfort compared to other conventional thermostat.