Evolutionary synthesis of HVAC system configurations : algorithm development (RP-1049)

This paper describes the development of a model-based optimization procedure for the synthesis of novel heating, ventilating, and air-conditioning system configurations. The optimization problem can be considered as having three suboptimization problems: the choice of a component set; the design of the topological connections between the components; and the design of a system operating strategy. In an attempt to limit the computational effort required to obtain a design solution, the approach adopted in this research is to solve all three subproblems simultaneously. The computational effort has been further limited by implementing simplified component models and including the system performance evaluation as part of the optimization problem (there being no need, in this respect, to simulate the system performance). The optimization problem has been solved using a Genetic Algorithm (GA) that has data structures and search operators specifically developed for the solution of HVAC system optimization problems. The performance of the algorithm and various search operators has been examined for a two-zone optimization problem, the objective of the optimization being to find a system design that minimizes system energy use. In particular, the performance of the algorithm in finding feasible system designs has been examined. It was concluded that the search was unreliable when the component set was optimized, but if the component set was fixed as a boundary condition on the search, then the algorithm had an 81% probability of finding a feasible system design. The optimality of the solutions is not examined in this paper but is described in an associated publication (Wright and Zhang 2008). It was concluded that, given a candidate set of system components, the algorithm described here provides an effective tool for exploring the design of novel HVAC systems.