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Evolutionary Synthesis of HVAC System Configurations: Algorithm Development.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

  • Jonathan A. Wright
  • Yi Zhang
  • Plamen Angelov
  • Victor I. Hanby
  • Richard A. Buswell
<mark>Journal publication date</mark>01/2008
<mark>Journal</mark>HVAC and R Research
Issue number1
Number of pages23
Pages (from-to)33-55
Publication StatusPublished
<mark>Original language</mark>English


This paper describes the development of an optimization procedure for the synthesis of novel heating, ventilating, and air-conditioning (HVAC) system configurations. Novel HVAC system designs can be synthesized using model-based optimization methods. The optimization problem can be considered as having three sub-optimization 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 sub-problems simultaneously. Further, the computational effort has been 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 simulation the system performance). The optimization problem has been solved using a Genetic Algorithm (GA), with data structures and search operators that are specifically developed for the solution of HVAC system optimization problems (in some instances, certain of the novel operators may also be used in other topological 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 the 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. It was concluded that, given a candidate set of system components, the algorithm described here provides an effective tool for exploring the novel design of HVAC systems. (c) HVAC & R journal

Bibliographic note

© 2008. American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc. (www.ashrae.org). Reprinted by permission from HVAC&R Research 2008, Vol. 14 (1). Additional reproduction, distribution, or transmission in either print or digital form is not permitted without ASHRAE’s prior written permission.