抄録
高性能化の技術的手法の一つであるインバータターボ冷凍機は,遠心式圧縮機の特性に着目し低温側の冷水と高温側の冷却水の広い温度域に高い成績係数で追従することが可能である.この特性は民生業務用空調熱源システムの大幅な省エネルギーの可能性を示唆しており新たな設計手法や運転法の提とする.まず本報ではその入力となるインバータターボ冷凍機の性能特性について熱力学的理論サイクル性能と比較をおこない不確かさと共に明らかとする.
A variable speed control of the compressor is known as a key technology of high performance heat pumps. In recent years, the inverter control technology for centrifugal chillers has been improving spectacularly. The inverter centrifugal chiller is a heat pump which can be used in a wide range of temperature at a high efficiency of performance. This is an advantage of the aerodynamic characteristics of the centrifugal compressor. This characteristic suggests there is a good chance of high energy saving of a heat source system for air-conditioning, so we are going to report new design techniques and the control method for an appropriate air-conditioning heat source system for business use. Therefore, it is necessary to carry out highly accurate simulations with the performance prediction model of the inverter centrifugal chiller and the performance prediction model of the cooling tower. The purpose of this first report is to clarify the performance of the inverter centrifugal chiller using actual measured data taking into account uncertainness of each value. Not only the rating point performance but also partial load points performance are evaluated. Each efficiency calculated from measured values was fairly satisfactory in large area within comparison to thermodynamic theoretical efficiencies. Furthermore, by using characteristic of the aerodynamics machine of the centrifugal compressor, we have been able to identify the performance characteristic of the inverter centrifugal chiller in a domain measured values closed to theoretical efficiencies. Especially, an improving cooling tower performance suggests a big energy saving potential of the heat source system. For air-conditioning system use, seasonal performances were fundamental to the evaluation of energy saving. But the consideration of uncertainness of seasonal performance is not enough, so by using measured data which evaluate uncertainness, we can describe appropriate observations about the seasonal performance.
