SketchUp: NHS Western Isles Hospital

 

GreenspaceLive is a software and consultancy shop based on the Isle of Lewis in Scotland. The company was founded in 2008 as a spin-out from the Greenspace Research, a low-carbon building and renewable energy research program at Lews Castle College, University of the Highlands and Islands. This case study about gModeller, the company’s SketchUp energy analysis plugin based on gbXML, comes to us from Donald Macaskill, Technical Manager and Energy Engineer at GreenspaceLive.

Making hospitals more energy efficient

Hospitals have unique energy consumption demands. Not only do a hospitals require lighting and heating 24 hours a day, but they also require ventilation, sterilization, laundry, food preparation and important medical equipment to be powered as well. Therefore, any improvements made to the building could drastically reduce the bills, freeing up money to be spent elsewhere.

The NHS Western Isles Trust are very proactive in trying to reduce their energy costs and carbon footprint. To determine their baseline energy consumption and carbon emissions and then to simulate a number of fabric and technology improvements to their largest building, they turned to GreenspaceLive. A hospital model and energy analysis workflow was created in Google SketchUp Pro with GreenspaceLive’s gTools suite.

 

Completed model for gModeller 

 

Project Methodology

To start, existing 2D CAD models and scanned paper drawings were shared via gWorkspace. These floor plans were then imported into Google SketchUp Pro. Once the floor plans had been imported, each floor was extruded to the correct height and dimensions. A detailed model is not required for the gModeller plugin, so the model could be simplified to single faces for walls, floors and roofs.

Once completed, attributes were added to the model using the gModeller’s customised materials, located within the Paint Bucket tool in SketchUp. Next, spaces were identified using the manual Space tool, which allowed the model to have zone specific information, such as heating, lighting and ventilation for different areas.

 

The completed gbXmL model 

 

The gbXML building information model generated by gModeller was now ready to be exported to an energy analysis engine. In this case, gEnergy was used, however, exported models can also be imported into Green Building Studio, Ecotect, Trace, DesignBuilder and others. gEnergy was initially run using the Hospital’s existing fabric and technologies to establish a baseline Energy Performance rating, subsequent analysis runs were then carried out with simulated improvements to the building, including proposed refurbishment changes, to determine the impact they would have on performance of the building.

Once gEnergy runs were completed, the model was exported to Google Earth and presented to the clients, showing gDashboard energy results on screen while touring their model.

 

The model in Google Earth with energy data 

 

Using the gWorkspace cloud platform, the modeling team was able to share and collaborate with the client throughout the process. Team members and client representatives were able to view, download and share files from the project, as well as view all energy runs that were undertaken.

The Results

Armed with the tools and the data, NHS Western Isles Hospital were able to model different scenarios and view the impact these changes would have. The results were dramatic – making a number of changes to the heating system, the team was able to demonstrate that the most effective change would result in over 50% energy savings, while reducing the CO2 emissions by almost 80%.

Dave Tierney, part of the Energy Team at NHS Western Isles Hospital said, “Using gTools, senior executives and staff received an overview of our carbon emissions, energy consumption and the impact changes in technology and fabric will have on our building. We can clearly see the differences in low carbon technology investment options. The results will help shape our plans for tackling carbon emissions and energy consumption in the future.”

Solar Permit AppEngine Examples

It was a milestone that took over 50 years, and at last solar panel manufacturers can produce their modules for less than $1/Watt. Now, the renewable energy community is faced with the dilemma that the permitting and interconnection costs, i.e. the paperwork, is a significant fraction of the cost of a rooftop installation. To deploy gigaWatts of solar energy in the United States these costs need to drop. In response, the Department of Energy has made permitting part of its Sun Shot Initiative and SolarTech has launched its Solar Permitting Challenge. And now Google is pleased to announce Solar Permitting Code Examples to make it faster for software developers to be productive using AppEngine.
A small team of Googlers (Alex Martelli, Arjun Satyapal, Clay Murphy, Luke Stone, Ross Koningstein and Dave Fork) pooled their 20% time to help out. We tried to make the task of building a web based permitting application easier by providing examples of essential tasks in AppEngine including login, creating new permit requests, uploading files, and gathering statistics. Two different versions, one in Python and one in Java, were created.
We were inspired to create this code example by the work that SolarTech has done to promote faster permitting through its Solar Permitting Challenge, and by the Solar ABCs efforts to produce a simple, uniform process for solar permitting. The user login screen for the Python code example appears below.
Navigant consulting estimates that there are 700 gigaWatts of solar power generation resource on rooftops in the United States. Overall, we believe that efforts to streamline the workflow connected with rooftop solar installations could reduce the costs of installations by 50 cents/Watt. Please help us help the industry make this a reality.

Aurelius on Objectivity and Focus

“The first rule is, to keep an untroubled spirit. The second is to look things in the face and know them for what they are.”

–Marcus Aurelius (121–180)
Roman emperor and philosopher

Prune. Not the fruit. The verb.

To prune a tree is to remove the branches and shoots that don’t serve its growth and vigor. But it goes a step further.

A diseased branch or low performing shoot not only doesn’t serve the tree – it drains the energy that can be used elsewhere – the energy that can produce more fruit, more flowers, and stronger branches.

When did you last evaluate your sales day activities against what’s most important to you succeeding (e.g., getting new customers, retaining current customers, driving profitable revenue)?

212 thought: Removing just two diversions from your sales efforts each week eliminates more than 100 distractions throughout your sales year.