| The purpose of computer-based building energy analysis programs is to assist heating, ventilation, and air conditioning (HVAC) engineers in the design process and to help researchers develop more effective and efficient methods of controlling a building's environment. One such program is BLAST (Building Loads Analysis and System Thermodynamics) that is heat balance based and can model a building's thermal performance for an entire year. However, the component simulations: zones, fan systems, and central plants, are simulated separately and no feedback occurs. In this work a computational engine was developed to model building thermal processes and have all the elements of the simulation interact. This new program IBLAST will, as a result, be able to simulate many of the fan systems and building thermal interactions that can not be modeled by BLAST.; An additional development of this work was the implementation of methods to optimally schedule both conventional and thermal storage plant equipment in IBLAST. Optimal schedules, in this case, had minimum energy cost when variations in cost by: energy type, time of day, and peak energy demand, were taken into account. A limited search of the possible equipment operating schedules was used that both ensures a global minimum, and reduces the number of schedules calculated to a computationally feasible number. Results are presented for optimization problems involving cool thermal storage systems and various combinations of conventional chilling equipment. As energy cost parameters were modified, the optimal equipment operating schedule changed accordingly. In the case of thermal storage, increases in on-peak energy cost resulted in greater use of storage to meet the cooling loads. In conventional systems, high demand charges resulted in fewer changes in equipment operating state from one time step to the next. If the conventional plant used more than one type of energy, relative changes in the costs of each energy source resulted in greater utilization of equipment powered by the cheapest energy. Results obtained from these methods are valuable in making cost-based comparisons between several plant equipment design options or evaluating the operating strategy of an in-service plant. |
