PARAMETRIC LIFE CYCLE ASSESSMENT OF COMBINED COOLING, HEATING, AND POWER INTEGRATED WITH RENEWABLE ENERGY AND ENERGY STORAGE
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Buildings use about 40% of global energy supply, mainly from natural gas and electric grids powered by fossil fuel-based centralized power plants. This study examines a more sustainable energy generation system --- the distributed combined cooling, heating, and power integrated with renewable energy and energy storage system (CCHP-RE-ESS). A parametric hybrid life cycle assessment framework approach is used to evaluate the environmental, economic, and social impacts of the proposed distributed energy generation system. The rationale for a parametric LCA approach is that it extends conventional LCA, which is cases-specific and shows how impacts change with different input factors such as ambient temperature, climate, and operation strategies. The impact results integrate with a multi-objective optimization method, Pareto front, to find the optimal environmental and economic impact trade-offs for different building energy demand scenarios. The parametric framework includes six commercially available trigeneration technologies: two for prime movers (microturbine and fuel cells), two for renewables (solar power and small wind turbine), and two for energy storage (lithium-ion battery and compressed air energy storage). The model is able to find the best combination of technologies and their corresponding sizes for different building demand profiles. After billions of simulations, the Microturbine-Solar PVs-Lithium ion Battery and Fuel Cells-Solar PVs-Lithium-ion Battery are two optimal distributed energy solutions. The simulation impact result shows that the system can primarily reduce the environmental impact as compared to the conventional energy system. However, the life cycle cost of CCHP-RE-ESS is higher than the traditional energy generation, especially for fuel cell-based system.Finally, the model evaluates the social cost and the current U.S. clean energy policy incentives impacts on the distributed CCHP-RE-ESS system. The model uses the Air Pollution Emission Experiments and Policy model to evaluate the marginal damages emissions on a dollar per ton basis. Results show that the social cost of conventional energy is significantly higher than the distributed energy generation. Based on the simulation result, it is estimated that the installation of the distributed CCHP-RE-ESS can help avoid more than 50 billion dollars of social cost per year for commercial buildings in U.S. Besides, the model study the cost-saving potential of current U.S. clean energy policy incentives, including federal tax credit, low-interest loan, and Modified Accelerated Cost Recovery System (MACRS). The tax credit and MACRS can primarily reduce the cost of distributed energy by average 50%, while low-interest loan increases the cost by average 30%. In some scenarios, the after-policy life cycle cost of distributed energy generation is competitive compared to conventional power, but for most situations, the life cycle cost is still higher as compared to conventional power.
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