DesignBuilder Team wins the "Best innovative workflow" award's how we did it!

View a recordingof our Webinar to learn more about the 3 step process used in the DesignBuilder Team competition entry.



在20个新ASHRAE这样能源建模会议15 was the LowDown Showdown modelling challenge sponsored by the US Department of Energy and the National Renewable Energy Laboratory. The competition showcased the work of eight mainstream modelling software packages competing to design and model a net-zero or below building.

The challenge set by ASHRAE was for a 53,600 sq ft 3-storey office building with specified requirements such as occupancy density, internal gains and set points. Criteria such as the building location, orientation, form, fabric, glazing, HVAC and lighting systems were left open to competitors.

DesignBuilder team and approach


The team was coached by Dave Cocking and Andy Tindale from DesignBuilder and comprised of participants from Arup, Carnegie Mellon University, Atelier Ten, Building Performance Team, Revitaliza Consultores and Sumac:

  • David Polson, Holly Stevenson, Arup
  • Michael Tillou, Atelier Ten
  • Khee Poh Lam, Omer Tugrul Karaguzel, Weili Xu, Adrian Chong, Carnegie Mellon University
  • Ignacio家具,Revitaliza Consultores
  • Gonzalo Lema, Dante Garcia, Billy Condor, Sumac
  • Mitchell Gleason, Building Performance Team
  • Christian Stalberg, DesignBuilder USA

The first team meeting focused on the general approach and we agreed that we wanted to work on the kind of problem routinely faced by design teams. The location was selected as Pittsburgh (ASHRAE climate zone 5A) which meant that mechanical heating and cooling would be required during the year and that the building could not rely on passive design techniques alone.

We were fortunate that some team members already had detailed data for a development area in Pittsburgh so we were able to site design work in a "real" location. The selected location presented realistic challenges such as a relatively restricted site footprint (meaning we weren't able to simply select any ideal building form for net-zero) and tall surrounding buildings resulting in shading of both glazing and photovoltaic (PV) devices.


The "real" development site in Pittsburgh.

The project architect also introduced the requirement for mixed-mode (hybrid) conditioning reflecting a typical brief from a client with high sustainability aspirations in Pittsburgh.

The final element of the approach agreed at the outset was that the team would use DesignBuilder's optimisation tools enabling us to ensure that the design would be good value for money through an advanced approach to cost-benefit analysis. Although costed solutions were not required as part of the competition they are required for real projects so we felt that it was important to be able to illustrate cost-optimal solutions in addition to those which would easily achieve net-zero and beyond. Costs were included for all materials and systems used at each stage of the design.

Early-stage design - load reduction optimisation



The 7 different building forms optimised to identify minimum loads.

Much of the early work involved setting up the model with the correct ASHRAE 90.1 data including schedules. The competition set challenging requirements for some of the internal gains and we were able to draw on the experience of the Carnegie Mellon University group to produce schedules for gains like elevators and plug loads based on calibrated data from their recent award-winning net-zero project. The basic model data used in each building form was identical.


Various permutations of model data such as orientation, insulation type and thickness, glazing type and size, external shading and thermal mass were included as design variables. The optimisation objectives were to minimise net site energy and capital expenditure (Capex) and we added a maximum 50 hours discomfort constraint using the ASHRAE 55 80% adaptive comfort metric.

DesignBuilder的优化工具使用遗传算法有效地搜索设计变量的最佳组合,从而使其能够比传统的参数或系统方法更快地找到最佳解决方案。Energy Plus模拟是由优化器分批运行的,以确保最佳的解决方案被延续到未来的迭代中……该过程使用“优胜最佳生存”的原理模仿自然进化。使用遗传算法的优化使得可以快速有效地搜索整个解决方案空间,从而使设计团队和客户端具有额外的信心,即确定了所有可行的解决方案。

The first optimisations were run using fast simulation servers in the DesignBuilder and Arup offices. The outcome of the first optimisation run was a set of results for each building form similar to that shown below. This shows a range of viable solutions from high-cost low-energy at the top left to low-cost high energy at the bottom right. The red Pareto-optimal points at the leading edge show those designs which pass the comfort constraint and cannot be beaten in terms of the design objectives set. The two main clusters relate to those solutions with Building integrated PV (higher-cost lower net site energy consumption) and those without. All building form options tested included a consistent number of roof PV panels.


The results for each building form were then analysed and overlaid on one plot to identify which yielded the best overall solution.



The series of solutions sets formed the basis of a design team discussion on the preferred options to carry forward to the detailed design stage. It is clear from the overlay graph that there is no outright "winner" in terms of building form which is likely to be at least partly due to the site constraints. This enabled the architect (with the notional client) to choose a form which also satisfied other "soft" requirements. The rectangle + courtyard form was selected so that the architect could create a pleasing sheltered exterior space in the courtyard for the benefit of the office occupants.

Optimal design variables identified from the selected building form consistent with a net-zero building were:

  • Orientation at 0 degrees rotation (it was already optimal for the site). To maintain consistency with adjacent buildings there would be limited scope for significant rotation anyway so this was fortunate!
  • Window to wall ratio 30% (also the minimum allowed by the competition rules).
  • Double-glazing preferred to triple and quadruple (cooling-dominated building).
  • High thermal mass generally preferred.
  • The maximum amount of PV allowable.

Once the building form was confirmed via optimisation the architect exported the DesignBuilder model geometry to Revit to enable work on the detailed architectural design.


Detailed design - "systems" optimisation

Having confirmed the optimal fabric characteristics to minimise heating and cooling loads the design team set to work on the systems required to meet those loads in the most cost-effective way, with the aim being to minimise site energy consumption then to match any residual consumption with renewable energy generation such as PV.

The variables considered in the second optimisation were:

  • 4个不同的HVAC系统:可变空气量(VAV);风扇线圈单元(FCU);地面源热泵(GSHP);从地面环(VRF)的水流变化剂流动。
  • 3个不同的照明系统,每个照明系统都有和没有日光控制:LED;T5;CFL。
  • PV options: Roof-mounted panels; Building-integrated PV; Shading devices (overhangs).
  • 再次包括绝缘,热质量和外部阴影,以确保与HVAC系统特征一起完全考虑其效果。

The initial load reduction optimisation results indicated no shading (louvers only) suggesting that we should also consider less drastic shading devices such as overhangs to ensure we identified the optimum trade-off between the conflicting need for cooling and daylighting. Otherwise the objectives and constraint applied were as the load reduction optimisation and the results showed a large spread of cost and performance as shown in the graph below:


Herein lies one of the major benefits offered by optimisation. No longer do you have to discuss 1, 2 or 3 options with the client...using the optimisation results you can have a fully-informed discussion to identify where the client wishes to be on the cost-performance spectrum. Do they want maximum performance at high cost? Or the opposite? Or do they want to explore the region closer to the origin where the best "trade-off" between cost and performance often lies? The competition brief was to achieve net-zero so we focused on the Pareto-optimal solutions around the zero net site energy consumption line. The cost-optimal solutions identified from the systems optimisation were:

  • LED lighting with daylight control.
  • 除了东立面以外的所有人都首选使用0.5m深的悬垂的阴影。由于早晨太阳增益的总体好处,在东立面上首选的阴影深度降低了0.3m。
  • The maximum number of roof-mounted PV panels plus BIPV on the South façade only. The more BIPV added to the design, the more the building becomes a net energy contributor, but at increased construction cost.
  • 0。5m deep PV shading devices used as overhangs only on the South façade, the remainder being standard shading.
  • VRF(带接地循环)在成本和性能之间提供了最佳平衡。虽然带有加热地板和冷梁的GSHP系统提供了最好的理论性能,但与混合模式策略相结合,它并不理想。


Selected Ground Water Cooled VRF system with Condenser Heat Recovery Preheating DHW

Fine-tuning the design

With the main building systems selected the final stage in the process was to fine-tune the HVAC control settings to further improve comfort and minimise energy consumption and unmet load hours. As an innovative extension of the HVAC design, the heating and cooling setback and the natural ventilation setpoint temperatures were optimised as below. To achieve this unmet load hours were used as one of the optimisation objectives:







Heating = 17

Cooling setback


Cooling = 0




DesignBuilder's integrated CFD and daylighting analysis tools were used to confirm that the design met good practise requirements. The same model geometry and basic data was used for all analyses eliminating the need to import and export between different programs.

该团队在一开始就意识到,鉴于气候区和现场限制,很可能需要进行可再生能源供款,我们很幸运能够在我们的团队中拥有一些重要的PV设计专业知识。DesignBuilder模型被导出到优化PV构型的犀牛和蚱hopper。最终设计证实了最佳面板间距为24m,斜率角度为26度,以最大程度地减少相邻面板的过度阴影,并考虑到相邻建筑物的阴影最大化。详细的PV设计导致PV容量为216 kWP,使PV能够满足剩余的能耗,产生产能的过量非常小。


DesignBuilder is able to export EnergyPlus simulation results as the boundary conditions for a CFD analysis which proved to be very useful when analysing natural and mechanical ventilation performance during operation.


团队也能够运行的空气改变有效ness (ACE) calculations using DesignBuilder CFD to ensure that there was suitable mixing of zone air from mechanical ventilation supply diffuser.

Radiance and Daysim calculations were used to check building daylight performance including illuminance under design conditions and daylight autonomy (sDA300/50%):



The competition required the teams to present results in different ways. The main output was the comparison between the ASHRAE 90.1 baseline building and our proposed building (the competition entry). The EUI of the baseline building (created from the proposed building using our new baseline generator tool) was around 47 kBTU/ft2.year whereas the EUI of our proposed building was 17 kBTU/ft2.year, a 64% reduction on the baseline.


These results were selected for one possible design permutation from the Pareto front of optimal designs. We could equally have selected a design with a much greater net energy contribution but at significantly greater construction cost

所以...您想走多么低以及以多少成本... DesignBuilder为团队提供了高级成本效益分析工具,以便能够进行评估。


DesignBuilder would like to express our thanks for the hard work, expertise and enthusiasm of the team members that made this such a rewarding process for all involved.


For more details on the competition see:

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