Affiliation:
1. Department of Industrial and System Engineering, Aoyama Gakuin University, Japan
Abstract
Air-conditioning systems must save energy while maintaining an appropriate room environment. In heat management, there is a tradeoff between the requirement to save energy during heat production and individual heat consumption for maintaining comfort. Heat consumption is dependent on environmental conditions in a given room, including the thermal load of the room and ambient weather. To predict thermal load, regression models can be built using weather forecast data, and the heat level necessary to avoid heat stroke while maintaining comfort can be calculated. In this study, we propose a decision-making process model of heat resource allocation for facility managers, known as a dynamic air-conditioning operation plan. The heat level allocated may change, considering the gap between planned and actual heat usage on a daily and monthly basis, and the resource is then distributed according to the thermal load. If the actual heat usage is expected to exceed the monthly target by the middle of the month, the plan is then revised to use the heat resource allocated for the following month, ahead of schedule. To demonstrate effectiveness of the model, sensitivity analysis was performed based on measured data.