Browsing by Author "Quinn, Jason C., committee member"
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Item Open Access A techno-economic study on the waste heat recovery options for wet cooled natural gas combined cycle power plants(Colorado State University. Libraries, 2018) Paudel, Achyut, author; Bandhauer, Todd M., advisor; Quinn, Jason C., committee member; Reardon, Kenneth F., committee memberIncreasing ambient temperature is known to have negative impacts on the performance of gas turbine and combined cycle power plants. There have been multiple approaches to mitigate this performance reduction. One such method involves cooling of the gas turbine inlet air. There are several different commercial techniques available, but they are energy intensive and require large capital investments. One potential option for cost reduction is to recover the waste heat emanating from the power plants to operate thermally activated cooling systems to cool the turbine inlet air. In this study, a 565 MW natural gas combined cycle power plant subjected to different waste heat recovery scenarios and gas turbine inlet chilling is assessed. A simplified thermodynamic and heat transfer model is developed to predict the performance of an evaporatively cooled NGCC power plant at varying ambient conditions. By taking typical meteorological year (TMY3) hourly weather data for two different locations – Los Angeles, California and Houston, Texas – the yearly output for this plant is predicted at a 100% capacity factor. The feasibilities of different waste heat recovery (WHR) systems including a gas turbine exhaust driven absorption chiller, a flue gas driven absorption chiller, a steam driven absorption chiller, and an electrically driven vapor compression chiller are assessed by calculating the Levelized Cost of Electricity (LCOE) for each scenario. In each of these cases, a parametric analysis was performed on the COP and the costs ($ per kWth) of the system. In these cases, the COP was varied from 0.2 to 2.0 (increments of 0.2), whereas the costs were varied logarithmically from $10 to $10,000 per kWth. The results of the analysis showed that for a fixed WHR system cost (i.e., $ per kWth), the system powered by flue gas generated the lowest LCOE, followed by the electrically-driven vapor compression chiller, steam-heated chiller, and finally, the gas turbine exhaust driven chiller for both geographic locations at all COP combinations. The analysis also investigated the impact of fixed investment cost, and the flue gas system again yielded the smallest LCOE and yielded a lower LCOE than the baseline case (no WHR) over a wide range of COPs. The maximum costs each of these systems could tolerate before the LCOE is higher than the baseline case was also determined. The flue gas driven absorption system had the highest tolerable costs at all COP combinations, followed by the vapor compression, steam, and gas turbine exhaust driven systems. As such, the flue gas powered system was identified as the most economic system to reduce the LCOE from the baseline case for a wide range of COP combinations at high tolerable costs for these two locations.Item Open Access Analysis and control co-design optimization of natural gas power plants with carbon capture and thermal energy storage(Colorado State University. Libraries, 2022) Vercellino, Roberto, author; Herber, Daniel R., advisor; Bandhauer, Todd M., advisor; Quinn, Jason C., committee member; Coburn, Timothy C., committee memberIn this work, an optimization model was constructed to help address important design and operation questions for a novel system combining natural gas power plants (NGCC) with carbon capture (CC) and hot and cold thermal energy storage (TES) units. The conceptualization of this system is motivated by the expected evolution of the electricity markets towards a carbon-neutral electricity grid heavily penetrated by renewable energy sources, resulting in highly variable electricity prices and demand. In this context, there will be an opportunity for clean, flexible, and cheap fossil fuel-based generators, such as NGCC plants with CC, to complement renewable generation. However, while recent work has demonstrated that high CO2 rates are achievable, challenges due to high capital costs, flexibility limitations, and the parasitic load imposed by CC systems onto NGCC power plants have so far prevented its commercialization. Coupling TES units with CC and NGCC would allow to store thermal energy into the TES units when the electricity prices are low, either by subtracting it from the NGCC or by extracting it from the grid, and to discharge thermal power at peak prices, from the hot storage (HS) to offset the parasitic load of the CC system and from the cold storage (CS) for chilling the inlet of the NGCC combustion turbine and increase the output of the cycle beyond nominal value. For the early-stage engineering studies investigating the feasibility of this novel system, a control co-design (CCD) approach is taken where key plant sizing decisions (including storage capacities and energy transfer rates) and operational control (e.g., when to store and use thermal energy and operate the power plant) are considered in an integrated manner using a simultaneous CCD strategy. The optimal design, as well as the operation of the system, are determined for an entire year (either all-at-once or through a moving prediction horizons strategy) in a large, sparse linear optimization problem. The results demonstrate both the need for optimal operation to enable a fair economic assessment of the proposed system as well as optimal sizing decisions due to sensitivity to a variety of scenarios, including different market conditions, site locations, and technology options. After detailed analysis, the technology shows remarkable promise in that it outperforms NGCC power plants with state-of-the-art CC systems in many of the scenarios evaluated. The best overall TES technology solution relies on cheap excess grid electricity from renewable sources to charge the TES units -- the HS via resistive heating and the CS through an ammonia-based vapor compression cycle. Future enhancements to the optimization model are also discussed, which include additional degrees of freedom to the CC system, adapting the model to evaluate other energy sources and storage technologies, and considering uncertainty in the market signals directly in the optimization model.Item Open Access Economic impact of thermal energy storage on natural gas power with carbon capture in future electricity markets(Colorado State University. Libraries, 2022) Markey, Ethan James, author; Bandhauer, Todd M., advisor; Quinn, Jason C., committee member; Herber, Daniel R., committee memberAs policies evolve to reflect climate change goals, the use of fossil fuel power plants in expected to change. Specifically, these power plants will need to incorporate carbon capture and storage (CCS) technologies to significantly reduce their carbon emissions, and they will be operated flexibly to accommodate the growing concentration of renewable energy generators. Unfortunately, most CCS technologies are very expensive, and they impose a parasitic heat load on the power plant, thereby decreasing net power output and the ability to operate flexibly. This research evaluated the economic potential of using hot and cold thermal energy storages (TES) to boost the net power output and flexibility of a natural gas combined cycle (NGCC) power plant with CCS capabilities. Resistively heated hot TES was used to offset the parasitic heat load imposed on the NGCC by the CCS unit while vapor compression cooled cold TES was used to chill the inlet air to the power plant. Thermodynamic models were created for the base NGCC + CCS power plant, the hot TES equipment, and the cold TES equipment, to determine key performance and cost parameters such as net power output, fuel consumption, emissions captured, capital costs, and operational costs. These parameters were then used to simulate the operation of the power plant with and without the TES technologies in accordance with fourteen electricity pricing structures predicted for different future electricity market scenarios. The difference in net present value (NPV) between the base NGCC + CCS power plant and power plant with the TES technologies was used as the primary economic metric in this analysis. The NPV benefit from increased revenue due to TES utilization was found to outweigh the NPV penalty from the additional capital costs. This positive economic result was attributed to the low cost of the TES equipment and the ability to charge the storages using cheap electricity from high levels of renewable output. The results have shown that hot TES increased NPV in 12 of 14 market scenarios while the cold TES increased NPV in 14 of 14 market scenarios. A combination of both hot and cold TES yielded the largest increases in NPV.Item Open Access Modeling and design of a power boosted turbo-compression cooling system(Colorado State University. Libraries, 2021) Roberts, Nickolas Richard, author; Bandhauer, Todd M., advisor; Quinn, Jason C., committee member; Cale, James, committee memberWaste heat recovery technologies have the potential to reduce fuel consumption and address increased electricity and cooling demands in shipboard applications. Existing thermally driven power and cooling technologies are simply too large to be installed on ships where space for new equipment is extremely limited. This study addresses major shipboard challenges through the modeling and design of a volume optimized turbo-compression cooling system (TCCS). The TCCS is driven by low-grade waste heat in the shipboard diesel generator set jacket water and lubrication oil and was designed to be a drop-in replacement of electric chiller systems. A case study of a marine diesel generator set and electric chiller is presented, including annual engine loading and seawater temperature profiles. Three TCCS integration options and five working fluids (R134a, R1234ze(E), R1234yf, R245fa, R515a) were evaluated over the range of case study conditions using a fixed heat exchanger effectiveness thermodynamic model. The hybrid thermally and electricity driven "power boosted" TCCS reduced electricity consumption for cooling by over 100 kWe. Plate and frame heat exchanger models were used to size and optimize the system to fit within the volume of a commercial centrifugal chiller of equal cooling capacity. The system used R134a, provided 200-tons of cooling, and had an electric coefficient of performance (COP) of 9.84 at the design conditions. Optimized heat exchanger and pipe geometries were fixed, and the model was run over the range of case study conditions to determine annual fuel savings of 92.1 mt yr-1 and a weighted average generator set power density improvement of 11.0%. Heat exchangers, turbomachinery, and piping were solid modeled to demonstrate that the system fits within the required footprint (40.6 ft2) and volume (267 ft3). The designed system was estimated to cost $295,036 in equipment and $442,554 in total installed costs. The resulting payback period was 5.77 years while operating for only 3,954 hours per year. Over a 15-year period, the net present value and internal rate of return were $176,734 and 16%, respectively.Item Open Access Modeling and simulation to investigate the electrification potential of medium- and heavy-duty vehicle fleets(Colorado State University. Libraries, 2023) Trinko, David A., author; Bradley, Thomas H., advisor; Quinn, Jason C., committee member; Simske, Steven, committee member; Hurrell, James, committee memberThis project involves developing and integrating new modeling tools to simulate the dynamics of electric medium- and heavy-duty fleet vehicle adoption. A technical and economic modeling tool, combining a data-driven hardware cost model with a cost-optimal charging strategy microsimulation, enables tailored analysis of the costs and benefits of electrifying individual fleets. Next, a novel text synthesis process, applied to a curated corpus of literature, quantifies trade-offs between technical, economic, and other factors in the fleet vehicle procurement decision. The outcomes of these tasks combine with knowledge from recent literature on fleet decision processes to specify the vehicle procurement model used by fleets in an agent-based model of the medium- and heavy-duty electric vehicle market. This model embodies an especially disaggregated approach to adoption modeling, internalizing factors and dynamics that conventional adoption models externalize. In particular, explicitly modeling the formation and diffusion of opinions among agents enables experiments that conventional models cannot support. Demonstrations show, for example, that increasing the extent of interactions between populations with different proclivities to electric vehicles has an asymmetrical outcome. High-proclivity electric vehicle adoption is generally unaffected as interactions increase, but low-proclivity adoption is accelerated. By representing individual fleets' requirements and costs at a high level of detail, incorporating an adoption decision model informed by a wide body of empirical research, and broadening the array of variables and dynamics available for experimentation, this integrated model offers a new way to understand the urgent challenge of eliminating emissions from the most emissions-intensive transportation sectors.Item Open Access Predictive energy management strategies for hybrid electric vehicles applied during acceleration events(Colorado State University. Libraries, 2019) Trinko, David A., author; Bradley, Thomas H., advisor; Quinn, Jason C., committee member; Anderson, Charles W., committee memberThe emergence and widespread adoption of vehicles with hybrid powertrains and onboard computing capabilities have improved the feasibility of utilizing predictions of vehicle state to enable optimal energy management strategies (EMS) to improve fuel economy. Real-world implementation of optimal EMS remains challenging in part because of limits on prediction accuracy and computation speed. However, if a finite set of EMS can be pre-derived offline, instead of onboard the vehicle in real time, fuel economy improvements may be possible using hardware that is common in current production vehicles. Acceleration events (AE) are attractive targets for this kind of EMS application due to their high energy cost, probability of recurrence, and limited variability. This research aims to understand how a finite set of EMS might be derived and applied to AEs based on predictions of basic AE attributes to achieve reliable fuel economy improvements. Models of the 2010 Toyota Prius are used to simulate fuel economy for a variety of control strategies, including baseline control, optimal EMS control derived via dynamic programming, and pre-derived control applied with approximate prediction to AEs. Statistical methods are used to identify correlations between AE attributes, optimal powertrain control, and fuel economy results. Then, key AE attributes are used to define AE categorization schemes of various resolutions, in which one pre-derived EMS is applied to every AE in a category. Last, the control strategies are simulated during a variety of drive cycles to predict real-world fuel economy results. By simulating fuel economy improvement for AEs both in isolation and in the context of drive cycles, it was concluded that applying pre-derived EMS to AEs based on predictions of initial and final velocity is likely to enable reliable fuel economy benefits in low-aggression driving.Item Open Access Simulation-based tsunami evacuation risk assessment and risk-informed mitigation(Colorado State University. Libraries, 2021) Wang, Zhenqiang, author; Jia, Gaofeng, advisor; Ellingwood, Bruce R., committee member; Mahmoud, Hussam N., committee member; Quinn, Jason C., committee memberEarthquake-induced tsunami can be very destructive involving significant loss of life. Evacuation to safety zones is regarded as one of the most effective ways to save lives from the tsunami strike due to the limited effectiveness of structural countermeasures. However, it is extremely challenging to successfully evacuate many people under the multi-hazard environment within a condensed time frame, especially under the near-field tsunami. Proper evacuation planning is crucial to support effective evacuation and reduce casualty. For effective evacuation planning, it is important to better understand the complex evacuation behavior for recommending proper response and behavior in an emergency. Also, it is important to have a clear picture of evacuation risk for informing policy and decision-making. Furthermore, it is important to identify effective pre-event mitigation strategies for effective risk reduction. Important limitations exist in current research on the above aspects. Tsunami evacuation simulation using the agent-based model has been used to investigate the complex evacuation behavior; however, existing agent-based evacuation models usually neglect or simplify many important factors and/or mechanisms associated with the evacuation. The neglect or simplification would make the evacuation simulation less realistic and hence a good understanding of evacuation behavior challenging. For the quantification of tsunami evacuation risk, a systematic framework that can address complex evacuation models and uncertainty (including aleatory and epistemic uncertainties) models is needed; however, no such framework has been developed for the quantification of tsunami evacuation risk. Also, some important uncertainties such as that in the seismic damage to the bridge are usually neglected or the uncertainty quantification is simplified. In this case, it would be difficult to assess the evacuation risk accurately and provide a clear picture of the evacuation risk. For effective pre-event evacuation risk mitigation, the effectiveness of different mitigation strategies needs to be quantitatively evaluated to identify more effective strategies. However, the effectiveness of the mitigation strategy is usually evaluated more qualitatively than quantitatively. Furthermore, the evaluation is typically conducted without systematically considering various uncertainties, which makes the identified strategies not robust to uncertainties. In tsunami evacuation risk assessment and mitigation, risk evaluation using general stochastic simulation techniques (e.g., Monte Carlo simulation) typically entails significant computational challenges. Efficient algorithms are needed to alleviate such computational challenges and facilitate such tasks. To bridge the above knowledge gaps, this research proposes a generalized framework for simulation-based tsunami evacuation risk assessment and risk-informed mitigation. The framework is built layer by layer through integrating tsunami evacuation simulation using agent-based modeling (ABM) technique, simulation-based evacuation risk assessment, sensitivity analysis of evacuation risk, and risk-informed evaluation of mitigation strategies. An improved agent-based tsunami evacuation model is developed for more realistic tsunami evacuation simulation by incorporating many of the typically neglected or simplified but important factors and/or mechanisms in the evacuation. Using the proposed agent-based evacuation model, a simulation-based framework is proposed to quantify the evacuation risk, in which various uncertainties (including aleatory and epistemic uncertainties) associated with the evacuation are explicitly considered and modeled by proper selection of probability distribution models. Sensitivity analysis of evacuation risk with respect to the epistemic uncertainty is performed, and the sensitivity information can be used to guide effective epistemic uncertainty reduction and hence for more accurate risk assessment. Also, sensitivity analysis is performed to identify critical risk factors, and the sensitivity information can be used to guide effective evacuation modeling and selection of candidate risk mitigation strategies. Risk-informed evaluation of different types of candidate mitigation strategies (including infrastructural and non-infrastructural strategies) is conducted to identify more effective strategies that are robust to uncertainties. Efficient sample-based approaches are developed to alleviate the computational challenges in evacuation risk assessment, sensitivity analysis, and risk-informed evaluation of mitigation strategies. As an illustrative example, the proposed framework is applied to tsunami evacuation risk assessment and risk-informed mitigation for the coastal community of Seaside, Oregon.Item Open Access Technoecomonic optimization and working fluid selection for an engine coolant driven turbo-compression cooling system(Colorado State University. Libraries, 2018) Young, Derek Nicholas, author; Bandhauer, Todd M., advisor; Quinn, Jason C., committee member; Burkhardt, Jesse, committee memberThe abundance of low grade waste heat presents an opportunity to recover typically unused heat energy and improve system efficiencies in a number of different applications. This work examines the technoeconomic performance of a turbo-compression cooling system designed to recover ultra-low grade (≤ 100°C) waste heat from engine coolant in large marine diesel engine-generator sets. In addition, five different working fluids (R134a, R152a, R245fa, R1234ze(E), and R600a) were studied for this application to better understand the effects of fluid properties on technical and economic system performance. A coupled thermodynamic, heat exchanger, and economic model was developed to calculate the payback period of the turbo-compression cooling system. Then, the payback period was minimized by optimizing the surface area of the heat exchangers by varying the effectiveness of the heat exchangers. The sensitivity of the payback period to the heat exchanger effectiveness values was quantified to inform future design considerations. The turbo-compression cooling system with R152a had the lowest payback period of 1.67 years and an initial investment of $181,846. The R1234ze(E) system had the highest cooling capacity of 837 kW and the highest overall COP of 0.415. The R152a system provided cooling for $0.0060 per kWh which was nearly 10 times cheaper than the cost of cooling provided by a traditional electrically driven vapor compression system onboard a marine vessel.