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  • Multi-objective optimal design of a near net zero energy solar house

    Resource Type:
    Conference Proceeding
    Creator:
    Bucking, Scott, Zmeureanu, Radu, and Athienitis, Andreas
    Abstract:
    This paper presents a multi-objective redesign case study of an archetype solar house based on a near net zero energy (NZE) demonstration home located in Eastman, Quebec. Using optimization techniques, pathways are identified from the original design to both cost and energy optimal designs. An evolutionary algorithm is used to optimize trade-offs between passive solar gains and active solar generation, using two objective functions: net-energy consumption and life-cycle cost over a thirty-year life cycle. In addition, this paper explores different pathways to net zero energy based on economic incentives, such as feed-in tariffs for on-site electricity production from renewables. The main objective is to identify pathways to net zero energy that will facilitate the future systematic design of similar homes based on the concept of the archetype that combines passive solar design; energy-efficiency measures, including a geothermal heat pump; and a building-integrated photovoltaic system. Results from this paper can be utilized as follows: (1) systematic design improvements and applications of lessons learned from a proven NZE home design concept, (2) use of a methodology to understand pathways to cost and energy optimal building designs, and (3) to aid in policy development on economic incentives that can positively influence optimized home design.
    Date Created:
    2014-01-01

  • An information driven hybrid evolutionary algorithm for optimal design of a Net Zero Energy House

    Resource Type:
    Article
    Creator:
    Bucking, Scott, Zmeureanu, Radu, and Athienitis, Andreas
    Abstract:
    Building Performance Simulation (BPS) is a powerful tool to estimate and reduce building energy consumption at the design stage. However, the true potential of BPS remains unrealized if trial and error simulation methods are practiced to identify combinations of parameters to reduce energy use of design alternatives. Optimization algorithms coupled with BPS is a process-orientated tool which identifies optimal building configurations using conflicting performance indicators. However, the application of optimization approaches to building design is not common practice due to time and computation requirements. This paper proposes a hybrid evolutionary algorithm which uses information gained during previous simulations to expedite and improve algorithm convergence using targeted deterministic searches. This technique is applied to a net-zero energy home case study to optimize trade-offs in passive solar gains and active solar generation using a cost constraint.
    Date Created:
    2013-08-27