Conference Paper

An "ageing" operator and its use in the highly constrained topological optimization of HVAC system design.

DOI: 10.1145/1068009.1068353 Conference: Genetic and Evolutionary Computation Conference, GECCO 2005, Proceedings, Washington DC, USA, June 25-29, 2005
Source: DBLP

ABSTRACT The synthesis of novel heating, ventilating, and air-conditioning (HVAC), system configurations is a mixed-integer, non-linear, highly constrained, multi-modal, optimization problem, with many of the constraints being subject to time-varying boundary conditions on the system operation. It was observed that the highly constrained nature of the problem resulted in the dominance of the search by a single topology. This paper, introduces an new evolutionary algorithm operator that prevents topology dominance by penalizing solutions that have a dominant topology.The operator results in a range of dynamic behavior for the rates of growth in topology dominance. Similarly, the application of the ageing penalty can result in the attenuation of topology dominance, or more severely, the complete removal of a topology from the search. It was also observed that following the penalization of a dominant topology, the search was dynamically re-seeded with both new and previously evaluated topologies. It is concluded that the operator prevents topology dominance and increases the exploratory power of the algorithm.The application of an evolutionary algorithm with ageing to the synthesis of HVAC system configurations resulted in a novel design solution having a 15% lower energy use than the best of conventional system designs.

  • Source
  • [Show abstract] [Hide abstract]
    ABSTRACT: Air conditioning is responsible for around 60% of energy use in commercial buildings and is rapidly increasing in the residential sector. Although each system is individually small, the proliferation of air conditioning and the correlation of energy use with temperature is driving peak demand and the need for electricity distribution network upgrades. Energy retailers are now looking for ways to reduce this aggregate peak demand, leading to a tradeoff between peak demand, energy cost and the thermal comfort of building occupants. This paper presents a multi-objective evolutionary algorithm (MOEA) to quantify trade-offs amongst these three competing goals. We study a scenario with 8 air conditioners (ACs) and compare our findings against the case of having all ACs working independently, irrespective of global goals. The results show that, with statistically significant certainty, any run of the MOEA outperforms any scenario where the ACs function independently to keep a given level of comfort on a typical hot day.
    Evolutionary Computation (CEC), 2010 IEEE Congress on; 08/2010
  • [Show abstract] [Hide abstract]
    ABSTRACT: Poor indoor air quality (IAQ) may appear due to wrong choice of building materials, insufficient levels of ventilation, air filtering, and inadequate management of contaminant sources. The problems start with the lack of a decision mechanism besides the local or national standards when choosing a specific IAQ management option. Building industry is not thoroughly aware of the consequences of different IAQ management methods and decisions, yet they lack the resources to identify the "best" solutions to IAQ problems. These consequences may result in soft costs such as lost productivity as well as hard costs such as the conditioning of the incoming outdoor air. This paper proposes to combine these costs towards true costs and introduces a modeling methodology for optimizing IAQ in commercial buildings by mathematical programming. These analyses also explore the contradictions among IAQ and energy efficiency. This paper explores alternative IAQ control options in terms of improved ventilation and air cleaning and presents alternatives for decision variables, as well as the possible technical, financial, and legal constraints. Significance of the paper derives from introducing the idea of applying "Operations Research" to construction management and providing the conceptual background for formulating the optimization of IAQ in commercial buildings. (5931 Words)


Available from