SIEMENS

The screen shows a satellite picture of the U.S. Dr. Bernd Wachmann, head of the “Sustainable Cities” project at Siemens Corporate Technology (CT), zooms in on a meadow just outside Princeton, New Jersey. With a few clicks, he inserts two office buildings into the image. He plots the ground plan, adds a parking lot and access roads — and the complex has taken shape in the virtual realm. As Wachmann does all this, a bar under the images he generates delivers data, such as the buildings’ energy consumption at different times of the day and year, how photovoltaic systems could improve their energy balance, how many people could work in the buildings, how their activity would impact traffic flows and the power grid, the amount of waste and air pollution they would produce, and what the expected operating costs would be. “Those are just a few of the parameters we simulate,” Wachmann explains. “The list can be expanded to include things like pedestrian-friendliness, the effects of electric vehicles on a project’s energy balance, and even quality of life. All of these aspects can be quantified and therefore modeled.”

The software platform Wachmann uses for this is part of the City Life Management (CLM) project developed by CT scientists. The CLM platform comes from Princeton and Munich, city data is evaluated in Berlin and Vienna, and Munich is responsible for infrastructure expertise. The project develops and offers solutions for viewing cities holistically, simulating the long-term impact of changes, and formulating appropriate responses. CLM offers urban planners a simple way to see the potential consequences of their decisions. It also allows the easy development of alternative “what if…” scenarios such as changing a two-way street into a one-way street, making a building taller, or using photovoltaic facilities to improve a neighborhood’s energy balance. This opens up new possibilities for addressing complex urban planning issues in a simple and intuitive manner.

The interrelationships between a city’s economic, environmental, and social goals are often extremely complex. For example, which is better: promoting the use of electric vehicles or expanding the public transport network? If you choose the former option, you won’t reduce traffic congestion but you will lower carbon dioxide emissions — but even that is only true if the power grid supplying the electric vehicles delivers energy from renewable sources. This, in turn, requires a high-performance grid, which in some cases first has to be built and must include battery-charging stations. If, on the other hand, you choose the public transport option, you have to be sure there are enough incentives for people to use it. All of this is too complex for any one person — or even many city governments — to evaluate. But it is no problem for the CLM platform. “Although our models don’t offer exact predictions,” says Wachmann. “They are 80 percent accurate. This enables them to provide a solid foundation for decision-making for a range of organizations, such as municipal agencies, politicians, citizens’ initiatives, and local residents.”

There are no quick fixes for entities as complex as cities, and areas of friction are sure to arise. As soon as plans for a new industrial park or a new urban district are announced, government agencies and citizens begin addressing the potential impact. After initial plans are drawn up, they pass through many — building departments, utility companies, economic and environmental management offices, architectural bureaus, and energy suppliers. The plans are also usually made available for public viewing at government agencies. An online platform such as CLM can save project planners a lot of trouble — particularly if a project is contentious. Under such circumstances, appropriate citizen participation plays a key role.

Digitally Modeling Cities. CLM was modeled on industrial solutions for product lifecycle management (PLM), which centrally manages all data on product development, production, warehousing, and sales. This approach not only increases transparency but also makes the entire value creation process much more efficient. Use of this innovative technology has led to extensive cost savings, shorter development and production times, and greater productivity in the automotive industry (Pictures of the Future. However, until recently, it had not been used very much in urban planning applications. Still, Thomas Gruenewald, Project Manager for the CLM Platform at Siemens CT in Princeton, believes that a skillfully programmed platform for planning major infrastructure projects could result in similar successes and would also make it possible to promote sustainability in cities.

At the moment, CT experts are focusing on the planning phase for urban infrastructure, an area where there’s plenty of room for improvement. According to Dr. George Lo, Senior Principal at CT in Princeton, 75 percent of the decisions that determine the lifecycle costs of a building are made before detailed plans become available. Moreover, a study conducted by the University of Texas in Austin found that 57 percent of the time invested in most construction projects is wasted because initial drafts often need to be altered. In other words, those who wish to design sustainable urban construction projects that meet budget and schedule targets should make their decisions during the drafting phase.

The development of the CLM Platform was helped by the fact that the company has many years of experience in planning, building, and operating water, wastewater, and energy supply systems, as well as transportation infrastructures. “We can deal with such great complexity because we know how to mathematically model the physical behavior of these systems,” says modeling expert Tim Schenk from Siemens CT in Munich. In addition, Schenk and others are examining data now being made available by more and more cities about their demographic structures and development, energy consumption, and transport requirements. The results can then be combined with CLM to create realistic models that give participants a look into realistic future scenarios.

All of this amounts to a paradigm shift, as planners can now see almost in real time how their decisions in one area — for instance, the height of a building — can impact things such as local traffic or the energy balance in a neighborhood.

The CLM working group is now negotiating with representatives from two major projects in China and central Europe that plan to utilize this technology for the first time.

Simulating Quality of Life. “But that’s just the beginning,” says Wachmann. “At the moment, we’re also working on using key performance indicators (KPIs) such as energy consumption, traffic and transport volume, and carbon dioxide generation to derive socioeconomic indicators as well.” The socioeconomic indicators Wachmann is referring to enable an assessment of quality of life, economic development, and more. To this end, Siemens researchers are developing an estimation model based on expert opinions and statistical studies. Quality of life assessments depend heavily on factors such as wages, public safety, and living conditions, but cultural conditions are also taken into account.

Local factors such as building ordinances and energy efficiency stipulations will also be more precisely incorporated into the simulations, as will factors that extend beyond local boundaries. These might include global climate trends, for example, since future energy consumption in buildings will of course also be impacted by climate change. Demographic developments will be considered as well. After all, if a neighborhood ages, this will increase the need for things like sidewalks with wheelchair-friendly ramps and disabled-only parking. “As long as the factors remain quantifiable, we’ll be able to model them,” says Wachmann.

The potential offered by CLM doesn’t end with virtual planning. Not only can it be used to conceive new neighborhoods and redesign cities for the decades to come, but it can also help to manage buildings and neighborhoods after they’re completed. A few mouse clicks will then be all it takes for planners and citizen groups to determine, for instance, how a neighborhood’s demand for electric vehicle parking and charging will change if a streetcar line is added.