For their research,  Localized Distributed Power Generation: Economically Robust, Demand-Optimized Placement of Urban Energy Production Systems, mechanical engineering professor Eric Pardyjak, assistant professor Amanda Smith and associate professor Rob Stoll received a three-year grant from the National Science Foundation of $309,911.

Over the past decade there has been renewed and growing interest in implementing distributed power generation in the U.S. and abroad. Distributed generation includes a wide range of sources, such as: solar energy, wind energy, small-scale fossil fuel combustion, etc. as well as combinations of these systems. Compared to centralized power plants, distributed generation has a number of advantages and trade-offs, however placement of these systems within complex urban environments has not been well studied. Urban areas are ideally positioned to take advantage of the close proximity between demand and supply that distributed generation provides. Most decisions on distributed generation implementation made with existing modeling tools are based on reasonable knowledge of regional climate data, but limited knowledge of the site-specific microclimate. Hence, the existing tools may be sufficient for making policy level decisions, but may fail in providing useful place-based strategies. That is, strategies that will work best at a specific site within a city surrounded by a real built environment. One of the reasons that this has yet to be explored is that tools needed to run the required simulations down to the meter-scale are too computationally demanding to be practical, and have not been integrated with building simulations.

There is a critical need for decision makers to have a place-based framework (tools and system) that allows them to understand the complex interactions and trade offs between demand, moderating urban form options, and distributed power generation opportunities. We hypothesize that a site-specific optimal mix of distributed power generation and microscale building demand reduction strategies exists that can minimize both internal and external costs resulting in more sustainable cities.

Through the research performed during this project, we will address the following questions:

  1. Are building and vegetation resolving micrometeorological tools that include detailed physics of the built environment surrounding a building necessary to realize demand side optimization, compared to simpler modeling systems?
  2. How do optimal mixtures of demand reduction and power generation change with regional and local climate?
  3. How does including (and valuing) ecosystem services alter the optimum mixture of green infrastructure (e.g. green landscaping) and distributed energy generation?

Learn more about this and related research in the area at Thermal Fluids & Energy Systems.