Assessing gaps and needs for integrating building performance optimization tools in net zero energy buildings design

This paper summarizes a study undertaken to reveal potential challenges and opportunities for integrating optimization tools in net zero energy buildings (NZEB) design. The paper reviews current trends in simulation-based building performance optimization (BPO) and outlines major criteria for optimization tools selection and evaluation. This is based on analyzing user's needs for tools capabilities and requirement specifications. The review is carried out by means of a literature review of 165 publications and interviews with 28 optimization experts. The findings are based on an inter-group comparison between experts. The aim is to assess the gaps and needs for integrating BPO tools in NZEB design. The findings indicate a breakthrough in using evolutionary algorithms in solving highly constrained envelope, HVAC and renewable optimization problems. Simple genetic algorithm solved many design and operation problems and allowed measuring the improvement in the optimality of a solution against a base case. Evolutionary algorithms are also easily adapted to enable them to solve a particular optimization problem more effectively. However, existing limitations including model uncertainty, computation time, difficulty of use and steep learning curve. Some future directions anticipated or needed for improvement of current tools are presented.Peer reviewe

Energy Optimization in Residential Spaces Using BEopt

The residential sector in the United states accounts for 22 percent of the total energy consumption according to the reports from U.S. Energy Information Administration (EIA) (2013). 31 percent of the house holds are reported facing challenges in paying their energy bills for heating or cooling their homes in 2015 according to the Residential energy consumption survey (RECS). To promote green buildings and to reduce the carbon footprints. The US Green building council has developed LEED certification to evaluate energy performance of a building. To achieve this level of energy efficiency software's such as BEopt, Equest are used. These software's help evaluate building design and identify cost optimal efficiency to save energy. This research project compares results of the software and average energy costs per household to determine housing design adjustments to minimize energy usage for different geographic regions in the Northern US. Data are taken from government website such as EIA and census.gov These results can be used to inform housing design and retrofit and remodeling actives

Numerical optimisation in spot detector design

Spots are image details resulting from objects, the projections of which are so small that the inner structure of these objects cannot be resolved from their image. Spot detectors are image operators aiming at the detection and localisation of spots in the image. Most spot detectors can be tuned with parameters. This paper addresses the problem of how to select the parameters. We propose to use carefully designed test images, a performance measure, and numerical optimisation techniques to solve this problem. Several optimisation methods are compared, and their adequacy for spot detector design is tested

Optimization as a design strategy. Considerations based on building simulation-assisted experiments about problem decomposition

In this article the most fundamental decomposition-based optimization method - block coordinate search, based on the sequential decomposition of problems in subproblems - and building performance simulation programs are used to reason about a building design process at micro-urban scale and strategies are defined to make the search more efficient. Cyclic overlapping block coordinate search is here considered in its double nature of optimization method and surrogate model (and metaphore) of a sequential design process. Heuristic indicators apt to support the design of search structures suited to that method are developed from building-simulation-assisted computational experiments, aimed to choose the form and position of a small building in a plot. Those indicators link the sharing of structure between subspaces ("commonality") to recursive recombination, measured as freshness of the search wake and novelty of the search moves. The aim of these indicators is to measure the relative effectiveness of decomposition-based design moves and create efficient block searches. Implications of a possible use of these indicators in genetic algorithms are also highlighted.Comment: 48 pages. 12 figures, 3 table

Effect of geometric factors on the energy performance of high-rise office towers in Tianjin, China

To improve energy efficiency of office buildings in Tianjin, we select a prototypical high-rise office tower as an example and focus on the effect of geometric factors on building energy performance. These factors include the orientation, plane shape, floor area, plane shape factor (the ratio of the plane length to the plane width, only as regards to a rectangle-shaped plane), floor height, floor number and window-to-wall ratio. The simulation is performed in DesignBuilder, which integrates artificial lighting with instantaneous daylight during the energy simulation process. The geometric factors of the defined prototype are examined in both single-parameter and multi-parameter evaluations. As to the multi-parameter results, the energy saving rate can vary by up to 18.9%, and reducing the floor height is observed to be the most effective means of reducing annual total end-use energy consumption, followed by increasing the plane shape factor and reducing the floor area. The results can serve as a reference for passive design strategies related to geometric factors in the early design stage