Optimum balcony design for maximum solar energy generation and indoor visual comfort?

PROJECT INFORMATION

Submitted by:  Hoang

Firm Name: Transsolar

ASHRAE Climate Zone: 5B

Building/Space Type: Residential

Who performed the simulation analysis?  External Energy Consultant

What tools were used for the simulation analysis? 

  • Grasshopper Ladybug

  • Grasshopper Honeybee

  • TRNSYS

  • Python

What tools did you use to create the graphic?

  • Grasshopper Ladybug

  • Grasshopper Honeybee

  • D3.js

What phase of the project was analysis conducted?  Schematic Design

What are the primary inputs of the analysis?  Balcony Geometry

What are the primary outputs of the analysis?  Total solar energy generated per balcony, indoor visual comfort quality

PROCESS

List the investigations questions that drove your analysis process.

What would be the most optimum shape for a balcony in order to gain as much PV power as possible while ensuring the indoor visual comfort?

How was simulation integrated into the overall design process?

The simulation is carried on side-by-side with the evolution of architecture design, allowing crosschecking and providing feedback to each iteration of architecture design. An interactive html graphic was created allowing the team to "view and play" with it at the same time, understanding how each parameter can have an impact to the final design goal.

How did you set up the simulation analysis and workflow?

A dynamic Grasshopper model of the architecture design was set up in order to perform fast and reliable simulations as the floor-plan evolve through each iteration. The simulation model evaluates different balcony geometries through different criteria, including: PV power generated on the facade, solar exposure on the window, indoor visual comfort. After having the simulation results, a Python script was used to generate an interactive parallel-coordinate graph, visualizes all variants together as a part of a multi-objective study. This allows the architect to select the optimum geometry as well as understand how each parameter can impact the final goals of the design.

How did you visualize the results to the design team? What was successful about the graphics that you used to communicate the data?

The final graphic is html file (parallel coordinate, generate by Python plotly package) which can be easily opened by anyone via internet browser. In addition, the graphic is interactive, therefore the design team can "play" with the graphic to not only pick out the most optimum solution for a multi-objective study but also to understand the impact of each parameter to the design goals.

Most importantly, what did you learn from the investigation?  How did simulation and its outputs influence the design of the project?

The investigation is a great opportunity to know the complexity of the building and understand the depth of involvement required to make accurate building model. Also this process allows us to apply our current knowledge to test the feasibility of design strategies.

What is the impact of toplighting on daylight and energy performance in a hot climate?

PROJECT INFORMATION

Submitted by:  Elliot J Glassman, Associate

Firm Name: WSP Built Ecology

ASHRAE Climate Zone: 1A

Building/Space Type: Office

Who performed the simulation analysis?  External Energy Consultant

What tools were used for the simulation analysis? 

  • Grasshopper Honeybee

  • DIVA for Grasshopper

What tools did you use to create the graphic?

  • Excel

  • Adobe InDesign

What phase of the project was analysis conducted?  Design Development

What are the primary inputs of the analysis?  Material reflectance and thermal properties, various toplighting options, internal loads

What are the primary outputs of the analysis?  sDA, ASE, DGP, EUI

PROCESS

List the investigations questions that drove your analysis process.

Can we bring top lighting to a below grade office space while managing the climate’s high angle sun and strong solar radiation? What are the different possible design directions that would work for both daylight and energy performance? What is the impact of different alternatives on daylight, visual comfort, and energy? Are there trade-offs or synergies between daylight and energy performance?

How was simulation integrated into the overall design process?

This study was conducted on the project during early design development. The design team had wanted to bring daylight to a below grade office space through a lightwell and toplighting. The initial proposal for the toplighting was a large, centralized horizontal skylight. Our building performance team expressed concern that this would introduce a great deal of direct sun to the space because of the high sun angles in the climate, imposing unwanted solar loads and greatly increasing the risk of glare.

Simulation was brought into the process to illustrate the concerns as well as propose alternative toplighting approaches that could successfully daylight the space while reducing solar loads and glare. The goal was not to restrict the design but demonstrate a variety of alternatives that would work, giving the design team the flexibility to choose the approach that they felt was compatible with their design intent.

A reference case was created with no toplighting that would have only the lightwell to provide daylight but would perform well in terms of energy relative to the toplit alternatives. In addition to the horizontal toplight design, we proposed alternative design approaches such as a louvered shading system over the toplight to diffuse sunlight, a north facing monitor, and smaller monitors distributed across the space. Within each design direction, we look at three different parameters which varied by scheme such as the VLT of the glass for the unprotected skylight, louver angle for the shaded skylight, or the area of glass for the monitors.

How did you set up the simulation analysis and workflow?

We utilized the power of Grasshopper to perform the simulation analysis on all the alternatives. Each of the toplight schemes were preprogrammed into the script along with the parameterized variable we wanted to explore within each scheme.

The simulation was set up to run daylight, glare, and energy analysis for each alternative and output images of the results with unique file names referenced to the scheme. The simulations were connected so that the daylight analysis would inform the lighting schedule used in the energy simulation.

In traditional modelling approaches, you may need to coordinate inputs across multiple models to make sure you are getting an apples to apples comparison of alternatives. In our workflow, the geometry was parametric so we had one model where our inputs for material properties, thermal constructions, and internal loads were entered once and remained constant through each iteration. The only thing that varied was the lighting schedule which was automatically generated by the daylight performance.

How did you visualize the results to the design team? What was successful about the graphics that you used to communicate the data?

Looking at multiple alternatives can produce a great deal of outputs. We wanted to balance being able to understand the relative performance of each alternative at a glance with the ability to dig deeper into the metrics if desired.

We conceived of the result visualization as a matrix for each of the metrics. Each cell of the matrix contained the visual output of the simulation and the border of each cell was color coded based on the result to give a quick indication of the performance. Grasshopper helped us assign the colors based on gradients so that we could look at the performance of the alternatives both relative to each other and against fixed performance thresholds.

Based on the color coding, it was clear that while the unprotected toplight appeared to be well daylit, it was actually letting in too much direct sun, negatively impacting visual comfort and energy.

Most importantly, what did you learn from the investigation?  How did simulation and its outputs influence the design of the project?

The interesting conclusion illustrated by the study was that there were a number of schemes that performed better in terms of energy than the reference case without a toplight since the daylight reduced the lighting load and subsequently the cooling load as well.

This meant that there was not a trade off we needed to make between providing daylight or good energy performance. Rather, by sensibly managing the way that daylight entered the building, we could provide a well daylit and comfortable indoor environment for the occupants while reducing energy consumption.

There were a number of different alternatives that performed well giving us some flexibility to choose based on aesthetic or constructability criteria.

What is the impact of Architectural and MEP Systems on Energy and Construction Costs?

PROJECT INFORMATION

Submitted by: Amir Rezaei

Firm Name: CannonDesign

ASHRAE Climate Zone: 5A

Building/Space Type: Office

Who performed the simulation analysis?  High Performance Building Analyst

What tools were used for the simulation analysis? 

  • EnergyPlus

  • jEplus+EA + PowerBI

What tools did you use to create the graphic?

  • OpenStudio

  • PowerBI

What phase of the project was analysis conducted?  Conceptual Design, Schematic Design

What are the primary inputs of the analysis?  Envelope thermal properties, window-wall ratios, zone HVAC type, AHU coil types, boiler/chiller sizes

What are the primary outputs of the analysis?  EUI, Energy cost, Construction cost

PROCESS

List the investigations questions that drove your analysis process.

Designing an office in a specific climate (Buffalo, NY), I want to know what are most economical energy conservation measures either architecturally or mechanically? What are the impact of different WWRs on different facades on the mechanical system sizes? How does the envelope thermal properties affect the overall building energy use and construction costs? How much energy savings can I achieve using a more efficient HVAC system for my building? I only need ballpark numbers for early stages of design! Should I spend more money on more insulation or upgrade to a more efficient HVAC system?

How was simulation integrated into the overall design process?

A fully parametrized shoebox model was created in Energyplus with EPMacro capabilities and connected to the optimization engine JEPlus+EA. A large number of architectural and mechanical equipment were modeled and the goal was to look at the combination of different variables that land the project on the intersection of low energy/cost and construction cost.

The visualized results were used at the onset of the project to come up with the ballpark WWR and envelope properties that the architect took responsibility to design to. The results were also used to quantify the ballpark range of EUI and energy cost associated with different AHU and zone HVAC systems, i.e. the impact of having a plant loop versus gas/DX/electrical solutions. The inputs to the simulations also has construction cost associated with all the design variables including amount and type of insulation, glazing properties, HVAC system type, chiller/boiler size, etc. so that the energy implications of design decisions can be looked at in conjunction with the building construction cost implications.

How did you set up the simulation analysis and workflow?

1) Fully parametrized a shoebox model that can look at multiple combination of different design inputs. 2) Connected that parametrized model to JEPlus+EA 3) Simulated overnight for a few thousand simulations 4) Collected the data from simulations and post-processed the data in PowerBi to make the data interactive and digestible

How did you visualize the results to the design team? What was successful about the graphics that you used to communicate the data?

Using PowerBi. Interactive nature of data was successful. The interactive data started conversations among team members on what strategies were most economical depending on other elements of design. The results showed how each design elements's performance is truly dependent on the previous one. For example, the optimized WWR conversation and how that impacts the size of central plant equipment that in turn drives the overall cost of the HVAC solutions and how those two are interdependent based on the thermal performance of glazing and other envelope properties...

Most importantly, what did you learn from the investigation?  How did simulation and its outputs influence the design of the project?

1. Learnt that building science concepts are best discussed with data when multiple stakeholders at the table.

2. The large datasets can be confusing but with the expert at the table to navigate the data the design direction can significantly be influenced and maybe changed!

3. Not everyone is ready for large data shock and it takes time to get used to this way of approaching design.

4. Was able to demonstrate how even with a traditional mechanical system it is possible to deliver high performance office projects with more investment in the envelope solutions.

5. Users could click on different points (hold SHIFT to select multiple design points) or filter the parallel coordinate graphs to compare the results early in the design process. This was done as a case study for office spaces with Buffalo, NY climatic data and the plan is to perform similar simulations for different climatic conditions and building typologies to have the EUI and energy cost numbers ready for every project we design in major climates we design for!

What is the impact of facade WWR and U-Value on whole-building EUI

PROJECT INFORMATION

Submitted by: Ajit Naik

Firm Name: Baumann Consulting

Other contributors or acknowledgements: Kreuck + Sexton Architects, Thomas Phifer and Partners, Yuna Zhang & Oliver Baumann - Baumann Consulting

ASHRAE Climate Zone: 5A

Building/Space Type: Mixed Use (Retail)

Who performed the simulation analysis?  External Energy Consultant

What tools were used for the simulation analysis? 

  • Design Builder + Eplus

  • BuildSimHub

What tools did you use to create the graphic?

  • Excel

  • Adobe InDesign

What phase of the project was analysis conducted?  Conceptual Design

What are the primary inputs of the analysis?  WWR, U-Value

What are the primary outputs of the analysis?  Whole-Building (Site) EUI

PROCESS

List the investigations questions that drove your analysis process.

What is the required glazing thermal performance to ensure energy code compliance for different high-rise curtainwall window to wall ratios?

How was simulation integrated into the overall design process?

 

Prospective tenant requests for panoramic views prompted the high-rise project development team to prioritize a high window-to-wall ratio (WWR) of 80%. The current Chicago Energy Conservation Code, which references 2015 IECC (and so ASHRAE 90.1-2013) requires high-WWR projects to demonstrate energy performance better than a baseline with prescribed 40% WWR, U-0.42 window assembly U-Value, SHGC-0.40 window solar heat gain coefficient, and U-0.055 wall U-Value . To meet this goal, high-WWR projects must employ envelope or system performance improvements to offset increased glazing heat loss relative to the baseline.

The design team recognized that code compliance through demand reduction via envelope improvements could be more cost-effective than through subsequent consumption reduction via HVAC efficient systems, and wanted to understand the aesthetic façade design implications. Having selecting an aggressive SHGC-0.26 target at project outset to reduce required cooling equipment capacity, the project team integrated simulation to establish a feasible combined WWR and curtainwall assembly U-value target.

The study parametrically analyzed combinations of WWR and U-value ranging from 35-85% and U-0.22 – U-0.42. The study identified code baseline performance and WWR-U-Value pairs resulting in code-compliant performance without system efficiency improvements; this information informed preliminary façade cost estimation prior to MEP systems design. By testing and presenting a wide range of possibilities in response to a design query about specific design concepts, integrated simulation offered the design team feedback on future potential concepts in addition to those under consideration.

How did you set up the simulation analysis and workflow?

The simulation team set up a simplified core-perimeter energy model in DesignBuilder with all WWR, envelope (except SHGC-0.26 glazing), HVAC, lighting, and domestic hot water performance parameters set at code baseline efficiencies for systems described in the preliminary concept package. The team exported the IDF file from DesignBuilder and uploaded to BuildSimHub for cloud-based batch manipulation and execution. BuildSimHub functions created IDF files, executed simulations, and reported whole-building energy usage intensity (EUI) for each possible combinations of WWR and U-value spanning 35-85% at 5% intervals and U-0.22 – U-0.42 at U-0.02 intervals, respectively. Site energy performance was selected as the single simulation output for comparative analysis to understand the cost of meeting energy code via improved façade U-value alone.

How did you visualize the results to the design team? What was successful about the graphics that you used to communicate the data?

The preliminary strategy involved a simple table to list the curtainwall assembly U-value meeting code baseline energy performance for each WWR option tested. Though this method indicated maximum allowable insulation levels, it provided solely static value targets. The design team wanted to visualize the full range of compliant combinations with aesthetic context, and so employed a graphic-based strategy. An excel graph with curves depicting EUI vs WWR for multiple glazing assembly U-values allowed the design team to identify code baseline EUI and draw a horizontal line representing the cutoff for compliant (below the line) and non-compliant (above the line) WWR-U-Value combinations. Simultaneously, the original table was represented visually as colored overlays representing required U-Value on several of the team’s façade concepts. This dual strategy targeted both data-focused and experiential-focused design team members.

Most importantly, what did you learn from the investigation?  How did simulation and its outputs influence the design of the project?

The combined visualization scheme proved to be an effective strategy for achieving an energy code compliant façade. Rather than developing and modeling efficiency packages to accommodate a given façade, parametrically analyzing the full set of façade design options maximized simulation impact and minimized design workflow and timeline interruptions. Visualizing the entire dataset together with colored façade options afforded the design team flexibility and the ability to quickly predict code compliance for preliminary concept modifications without waiting for further analysis results. The design team ultimately selected a façade option with 68% WWR that featured sections of floor-to-ceiling glass, ensuring high-quality views, and a feasible U-0.26 glazing assembly, ensuring energy code compliance prior to inclusion of high-efficiency MEP systems.