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Congratulations to SBS lab member Julia Ho on becoming the first Penn State student selected for the U.S. Department of Energy (DOE) Innovation in Buildings (IBUILD) Graduate Research Fellowship. Julia’s research focuses improving modeling and design of low-carbon heating and cooling systems. She will use this fellowship to evaluate the feasibility of low-carbon heating and cooling for rural communities using advanced modeling tools such as Modelica. More information can be found here.
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Congratulations to SBS lab member Rosina Adhikari on passing her Ph.D. comprehensive exam. Her research is focused on addressing challenges in climate resilience and building decarbonization with specific emphasis on low-income communities. She has worked on multiple U.S. Department of Energy (DOE) and National Science Foundation (NSF) projects. She has also published several conference papers. Rosina joins several of our lab members who have recently passed their Ph.D, comprehensive exams.
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SBS lab has been working on the DOE Grid-Interactive Efficient District (GED) energy system project for 3 years. Team meetings have been conducted weekly via zoom, but today the team held their first in-person meeting in Boulder. They received an amazing tour of the University of Colorado Boulder’s Energy Plant by Ken Morse. It was a great experience to see the energy plant and actually meet with the team in-person after all these years! We look forward to our continued collaborations and research.
The GED project focuses on the coordination of thermal-electrical-control networks. Which is essential for the optimal design of grid-interactive efficient district (GED) energy systems, particularly when renewable energy sources are integrated. This joint research is to create a holistic open-source modeling and optimization platform for the optimal design and retrofit of GED energy systems. The project includes teams from Pennsylvania State University, University of Colorado Boulder, Rensselaer Polytechnic Institute, University of Texas Austin, Lawrence Berkeley National Lab, National Renewable Energy Lab, and Amzur Technologies.
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We are excited to have Saranya Anbarasu present her poster on “Optimization Operational Costs in Combined Heat and Power Integrated District Heating Systems: A Reinforcement Learning Approach.” This poster shows the application of cutting-edge AI technology to complex district energy systems. This is the outcome of our DOE project “Optimal Co-Design of Integrated Thermal-Electrical Networks and Control Systems for Grid-Interactive Efficient District (GED) Energy Systems.” This research was co-authored with current lab members Rosina Adhikari, Katy Hinkelman, Zhanwei Hu, and former lab members Ardeshir Moftakhari and Tanmay Ambadkar.
We are so excited to see our lab members presenting their work. To see a summary of the presentation and details for where it will be held follow this link.
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We are excited to have Zhanwei He present “Computationally Efficient and Accurate Modeling of Combined Heating and Power Systems for District Energy Applications” at SimBuild 2024 in Technical session 8: Grid Interactions and Distributed Energy Resources. The presentation introduces Modelica-based simplified combined heat and power (CHP) models that achieve computational efficiency and high accuracy. This is the outcome of our DOE project “Optimal Co-Design of Integrated Thermal-Electrical Networks and Control Systems for Grid-Interactive Efficient District (GED) Energy Systems.” Zhanwei is working with current lab members Saranya Anbarasu, Katy Hinkelman, lab alumni Ardi Moftakhari, and Lawrence Berkley National Lab’s Jianjun Hu to release these models in the Modelica Buildings Library.
We are so excited to see our lab members presenting their work. To see a summary of the presentation and details for where it will be held follow this link.
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Congratulations to SBS lab member Saranya Anbarasu on receiving the Marlene & Joseph Borda Architectural Engineering Graduates Travel Fellowship. This fellowship is supporting her to present her paper “Optimizing Operational Costs in Combined Heat and Power Integrated District Heating Systems: A Reinforcement Learning Approach” at IBPSA-USA SimBuild 2024 Conference in Denver, Colorado. We appreciate all the generous donors for supporting the lab members to have these experiences.
Saranya’s paper is joint research of Tanmay Ambadkar, Rosina Adhikari, Kathryn Hinkleman, Zhanwei He, and Ardeshir Moftakhari from our DOE project.
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SBS lab member Jake Castellini’s paper, titled “Quantifying Spatiotemporal Variability in Occupant Exposure to an Indoor Airborne Contaminant with an Uncertain Source Location,” was published in the journal Building Simulation this month. He worked with fellow lab member Cary Faulkner and Michael Sohn of Lawrence Berkeley National Lab to complete this project, which was sponsored by the Department of Energy’s Defense Threat Reduction Agency.
Most models simulating occupant exposure to contaminants in buildings use well-mixed zone models, which assume that contaminant levels are the same throughout a room (or zone). However, these models can under-predict high concentrations of contaminants because of this assumption. In contrast, CFD models are able to predict spatiotemporal variation but are computationally expensive. Jake’s paper describes a new method to parametrically characterize the spatiotemporal variability observed in CFD simulations as a first step in developing stochastic room surrogate models to replace well-mixed room representations.
Congratulations to Jake! His paper can be found for free here: https://rdcu.be/c7j8C
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The second TAG meeting for the Grid-Interactive Efficient District (GED) Project took place Monday, Oct. 31st. The multi-year, DOE-funded project’s TAG meetings occur at the beginning of each budget period. Principal investigators gathered to discuss progress and next steps for the project.
The GED project aims to create an open-source platform that makes optimizing energy use in microgrid and district energy systems more accessible. To do this, the project is creating, calibrating, and combining thermal, electrical, and control system models to more accurately predict energy use and potential savings. In addition to creating the novel platform, the researchers are conducting case studies on UT Austin and CU Boulder campuses to validate the platform and demonstrate potential energy savings.
