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  <title><![CDATA[Phd Defense by Junchen Yan]]></title>
  <body><![CDATA[<p><strong>School of Civil and Environmental Engineering</strong></p>

<p>&nbsp;</p>

<p><strong>Ph.D. Thesis Defense Announcement</strong></p>

<p>&nbsp;</p>

<p>Parametric Life Cycle Assessment of Combined Cooling, Heating,</p>

<p>and Power Integrated with Renewable Energy and Energy Storage</p>

<p>&nbsp;</p>

<p>&nbsp;</p>

<p>By</p>

<p><strong>Junchen Yan</strong></p>

<p>&nbsp;</p>

<p>Advisor:</p>

<p><strong>Dr. John C. Crittenden (CEE)</strong></p>

<p>&nbsp;</p>

<p><strong>Committee Members:</strong></p>

<p>Dr. John E. Taylor (CEE), Dr. Marilyn A. Brown (PUBP),</p>

<p>Dr. Santiago Carlos Grijalva (ECE), Dr. Valerie Thomas</p>

<p>(ISyE), Dr. Yongsheng Chen (CEE)</p>

<p>&nbsp;</p>

<p><strong>Date and Time:</strong> Friday, December 13th, 2019 at 12:00 noon</p>

<p>&nbsp;</p>

<p><strong>Location</strong> Capstone Building, Room 338C, 828 West Peachtree St</p>

<p>&nbsp;</p>

<p>Complete Announcement, with abstract, is attached.</p>

<p>&nbsp;</p>

<p>Buildings use about 40% of global energy supply, mainly from natural gas and electric grids powered by fossil<br />
fuel-based centralized power plants. This study examines a more sustainable energy generation system --- the<br />
distributed combined cooling, heating, and power integrated with renewable energy and energy storage system<br />
(CCHP-RE-ESS). A parametric hybrid life cycle assessment framework approach is used to evaluate the<br />
environmental, economic, and social impacts of the proposed distributed energy generation system. The rationale for<br />
a parametric LCA approach is that it extends conventional LCA, which is cases-specific and shows how impacts<br />
change with different input factors such as ambient temperature, climate, and operation strategies. The impact results<br />
integrate with a multi-objective optimization method, Pareto front, to find the optimal environmental and economic<br />
impact trade-offs for different building energy demand scenarios. The parametric framework includes six<br />
commercially available trigeneration technologies: two for prime movers (microturbine and fuel cells), two for<br />
renewables (solar power and small wind turbine), and two for energy storage (lithium-ion battery and compressed air<br />
energy storage). The model is able to find the best combination of technologies and their corresponding sizes for<br />
different building demand profiles. After billions of simulations, the Microturbine-Solar PVs-Lithium ion Battery and<br />
Fuel Cells-Solar PVs-Lithium-ion Battery are two optimal distributed energy solutions. The simulation impact result<br />
shows that the system can primarily reduce the environmental impact as compared to the conventional energy system.<br />
However, the life cycle cost of CCHP-RE-ESS is higher than the traditional energy generation, especially for fuel<br />
cell-based system.<br />
Finally, the model evaluates the social cost and the current U.S. clean energy policy incentives impacts on the<br />
distributed CCHP-RE-ESS system. The model uses the Air Pollution Emission Experiments and Policy model to<br />
evaluate the marginal damages emissions on a dollar per ton basis. Results show that the social cost of conventional<br />
energy is significantly higher than the distributed energy generation. Based on the simulation result, it is estimated<br />
that the installation of the distributed CCHP-RE-ESS can help avoid more than 50 billion dollars of social cost per<br />
year for commercial buildings in U.S. Besides, the model study the cost-saving potential of current U.S. clean energy<br />
policy incentives, including federal tax credit, low-interest loan, and Modified Accelerated Cost Recovery System<br />
(MACRS). The tax credit and MACRS can primarily reduce the cost of distributed energy by average 50%, while<br />
low-interest loan increases the cost by average 30%. In some scenarios, the after-policy life cycle cost of distributed<br />
energy generation is competitive compared to conventional power, but for most situations, the life cycle cost is still<br />
higher as compared to conventional power. Future work includes: (1) integrate more trigeneration technologies (e.g.,<br />
thermal storage), (2) adopting hybrid operation strategy that switching between following electrical load and<br />
following the thermal load, and (3) customized building design for more realistic building energy demand profile.</p>
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