Heating, ventilating and air-conditioning (HVAC) operation strategies can greatly affect energy consumption, energy cost and peak electrical demand. This paper demonstrates the optimal operation effect of a hybrid energy source system introduced into a mid-size office building. The system is composed of an electric screw heat pump chiller/heater and a gas-fired absorption chiller/heater with a thermal stratified chilled/hot water storage tank. The effects of the optimization (primary energy consumption minimum, demand charge minimum and peak electrical demand minimum) are calculated by the HVAC system simulation using measured weather data and building thermal load data. The optimized control variables are outlet water temperature and water flow rate of the heat source equipment, water flow rate of the thermal storage tank and cooling water/air flow rate of the cooling tower. The purpose of this study is to quantitatively clarify that the strategic operation of the HVAC system is more useful for energy conservation or energy cost saving than the conventional operation.
In certain previous studies on the optimization of HVAC operations, Dynamic Programming (DP) has been used as the optimization technique. DP can globally search for the optimal solution, but has a practical difficulty that the number of calculations by DP increases explosively as the number of control and state variables increase. Namely, the optimization effects are examined under the primitive HVAC system and limited number of variables, not under the high level (practical) HVAC system and multi-variables. However, the optimization is more important for just the high level HVAC system. The main point in this paper is that the Hill Climbing method (HC) is used as the optimization technique, and is applied to the practical HVAC system. The optimal solution by HC is apt to be local, but HC can calculate the optimal multi-variables without the problem of dimensionality. The result of the simulation for the optimal operation effects is that the optimization brings about 300`500 GJ primary energy conservation, an energy cost saving of between 700,000 and 1,000,000 yen or 40-70% peak electrical demand reducing during three months in summer season. In addition, the sensitivities of the control variables toward these effects are analyzed. The result of the sensitivity analysis can reveal useful information about preferential order of the HVAC system control variables.
This paper is mainly divided into the following seven sections: (1) introduction, (2) HVAC system model for simulation, (3) comparison of calculated energy consumption with measured one, (4) merits and demerits of optimization technique HC, (5) important assumptions used in the system simulation, (6) optimization effects of the practical HVAC system operation and sensitivities of the control variables, and (7) conclusions. This paper shows the potential of the energy conservation or the energy cost saving which the optimal control strategies of the HVAC system can bring about.