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- Genre: Academic theses
- Creators: Phelan, Patrick
- Status: Published
Description
Wind measurements are fundamental inputs for the evaluation of potential energy yield and performance of wind farms. Three-dimensional scanning coherent Doppler lidar (CDL) may provide a new basis for wind farm site selection, design, and control. In this research, CDL measurements obtained from multiple wind energy developments are analyzed and a novel wind farm control approach has been modeled. The possibility of using lidar measurements to more fully characterize the wind field is discussed, specifically, terrain effects, spatial variation of winds, power density, and the effect of shear at different layers within the rotor swept area. Various vector retrieval methods have been applied to the lidar data, and results are presented on an elevated terrain-following surface at hub height. The vector retrieval estimates are compared with tower measurements, after interpolation to the appropriate level. CDL data is used to estimate the spatial power density at hub height. Since CDL can measure winds at different vertical levels, an approach for estimating wind power density over the wind turbine rotor-swept area is explored. Sample optimized layouts of wind farm using lidar data and global optimization algorithms, accounting for wake interaction effects, have been explored. An approach to evaluate spatial wind speed and direction estimates from a standard nested Coupled Ocean and Atmosphere Mesoscale Prediction System (COAMPS) model and CDL is presented. The magnitude of spatial difference between observations and simulation for wind energy assessment is researched. Diurnal effects and ramp events as estimated by CDL and COAMPS were inter-compared. Novel wind farm control based on incoming winds and direction input from CDL's is developed. Both yaw and pitch control using scanning CDL for efficient wind farm control is analyzed. The wind farm control optimizes power production and reduces loads on wind turbines for various lidar wind speed and direction inputs, accounting for wind farm wake losses and wind speed evolution. Several wind farm control configurations were developed, for enhanced integrability into the electrical grid. Finally, the value proposition of CDL for a wind farm development, based on uncertainty reduction and return of investment is analyzed.
ContributorsKrishnamurthy, Raghavendra (Author) / Calhoun, Ronald J (Thesis advisor) / Chen, Kangping (Committee member) / Huang, Huei-Ping (Committee member) / Fraser, Matthew (Committee member) / Phelan, Patrick (Committee member) / Arizona State University (Publisher)
Created2013
Description
The ability to design high performance buildings has acquired great importance in recent years due to numerous federal, societal and environmental initiatives. However, this endeavor is much more demanding in terms of designer expertise and time. It requires a whole new level of synergy between automated performance prediction with the human capabilities to perceive, evaluate and ultimately select a suitable solution. While performance prediction can be highly automated through the use of computers, performance evaluation cannot, unless it is with respect to a single criterion. The need to address multi-criteria requirements makes it more valuable for a designer to know the "latitude" or "degrees of freedom" he has in changing certain design variables while achieving preset criteria such as energy performance, life cycle cost, environmental impacts etc. This requirement can be met by a decision support framework based on near-optimal "satisficing" as opposed to purely optimal decision making techniques. Currently, such a comprehensive design framework is lacking, which is the basis for undertaking this research. The primary objective of this research is to facilitate a complementary relationship between designers and computers for Multi-Criterion Decision Making (MCDM) during high performance building design. It is based on the application of Monte Carlo approaches to create a database of solutions using deterministic whole building energy simulations, along with data mining methods to rank variable importance and reduce the multi-dimensionality of the problem. A novel interactive visualization approach is then proposed which uses regression based models to create dynamic interplays of how varying these important variables affect the multiple criteria, while providing a visual range or band of variation of the different design parameters. The MCDM process has been incorporated into an alternative methodology for high performance building design referred to as Visual Analytics based Decision Support Methodology [VADSM]. VADSM is envisioned to be most useful during the conceptual and early design performance modeling stages by providing a set of potential solutions that can be analyzed further for final design selection. The proposed methodology can be used for new building design synthesis as well as evaluation of retrofits and operational deficiencies in existing buildings.
ContributorsDutta, Ranojoy (Author) / Reddy, T Agami (Thesis advisor) / Runger, George C. (Committee member) / Addison, Marlin S. (Committee member) / Arizona State University (Publisher)
Created2013
Description
With the desire of high standards of comfort, huge amount of energy is being consumed to maintain the indoor environment. In US building consumes 40% of the total primary energy while residential buildings consume about 21%. A large proportion of this consumption is due to cooling of buildings. Deteriorating environmental conditions due to excessive energy use suggest that we should look at passive designs and renewable energy opportunities to supply the required comfort. Phoenix gets about 300 days of clear sky every year. It also witnesses large temperature variations from night and day. The humidity ratio almost always stays below the 50% mark. With more than six months having outside temperatures more than 75 oF, night sky radiative cooling promise to be an attractive means to cool the buildings during summer. This technique can be useful for small commercial facilities or residential buildings. The roof ponds can be made more effective by covering them with Band Filters. These band filters block the solar heat gain and allow the water to cool down to lower temperatures. It also reduces the convection heat gain. This helps rood ponds maintain lower temperatures and provide more cooling then an exposed pond. 50 μm Polyethylene band filter is used in this study. Using this band filter, roof ponds can be made up to 10% more effective. About 45% of the energy required to cool a typical residential building in summer can be saved.
ContributorsSiddiqui, Mohd. Aqdus (Author) / Bryan, Harvey (Thesis advisor) / Reddy, T Agami (Committee member) / Kroelinger, Michael D. (Committee member) / Arizona State University (Publisher)
Created2013
Description
Tesla turbo-machinery offers a robust, easily manufactured, extremely versatile prime mover with inherent capabilities making it perhaps the best, if not the only, solution for certain niche applications. The goal of this thesis is not to optimize the performance of the Tesla turbine, but to compare its performance with various working fluids. Theoretical and experimental analyses of a turbine-generator assembly utilizing compressed air, saturated steam and water as the working fluids were performed and are presented in this work. A brief background and explanation of the technology is provided along with potential applications. A theoretical thermodynamic analysis is outlined, resulting in turbine and rotor efficiencies, power outputs and Reynolds numbers calculated for the turbine for various combinations of working fluids and inlet nozzles. The results indicate the turbine is capable of achieving a turbine efficiency of 31.17 ± 3.61% and an estimated rotor efficiency 95 ± 9.32%. These efficiencies are promising considering the numerous losses still present in the current design. Calculation of the Reynolds number provided some capability to determine the flow behavior and how that behavior impacts the performance and efficiency of the Tesla turbine. It was determined that turbulence in the flow is essential to achieving high power outputs and high efficiency. Although the efficiency, after peaking, begins to slightly taper off as the flow becomes increasingly turbulent, the power output maintains a steady linear increase.
ContributorsPeshlakai, Aaron (Author) / Phelan, Patrick (Thesis advisor) / Trimble, Steve (Committee member) / Wang, Liping (Committee member) / Arizona State University (Publisher)
Created2012
Description
This thesis outlines the development of a vector retrieval technique, based on data assimilation, for a coherent Doppler LIDAR (Light Detection and Ranging). A detailed analysis of the Optimal Interpolation (OI) technique for vector retrieval is presented. Through several modifications to the OI technique, it is shown that the modified technique results in significant improvement in velocity retrieval accuracy. These modifications include changes to innovation covariance portioning, covariance binning, and analysis increment calculation. It is observed that the modified technique is able to make retrievals with better accuracy, preserves local information better, and compares well with tower measurements. In order to study the error of representativeness and vector retrieval error, a lidar simulator was constructed. Using the lidar simulator a thorough sensitivity analysis of the lidar measurement process and vector retrieval is carried out. The error of representativeness as a function of scales of motion and sensitivity of vector retrieval to look angle is quantified. Using the modified OI technique, study of nocturnal flow in Owens' Valley, CA was carried out to identify and understand uncharacteristic events on the night of March 27th 2006. Observations from 1030 UTC to 1230 UTC (0230 hr local time to 0430 hr local time) on March 27 2006 are presented. Lidar observations show complex and uncharacteristic flows such as sudden bursts of westerly cross-valley wind mixing with the dominant up-valley wind. Model results from Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS®) and other in-situ instrumentations are used to corroborate and complement these observations. The modified OI technique is used to identify uncharacteristic and extreme flow events at a wind development site. Estimates of turbulence and shear from this technique are compared to tower measurements. A formulation for equivalent wind speed in the presence of variations in wind speed and direction, combined with shear is developed and used to determine wind energy content in presence of turbulence.
ContributorsChoukulkar, Aditya (Author) / Calhoun, Ronald (Thesis advisor) / Mahalov, Alex (Committee member) / Kostelich, Eric (Committee member) / Huang, Huei-Ping (Committee member) / Phelan, Patrick (Committee member) / Arizona State University (Publisher)
Created2013
Description
Commitment to an activity is widely studied in leisure research. Serious Leisure Perspective (SLP) describes characteristics a committed activity participant possesses. The Psychological Continuum Model (PCM) describes the psychological process a person goes through to become committed to a leisure activity. Awareness, attraction, attachment and loyalty make of the four stages of PCM. Both perspectives have been used to describe committed leisure activity participants and commitment to organized recreational events. Research on leisure activity has yet to determine how the individual becomes loyal. Therefore, the purpose of this study is to determine the process in which recreation activity participates becomes loyal and to identify who can be labels as serious within the PCM Framework. Data was obtained from an online electronic survey distributed to participants of four U.S. marathon and half marathon events. A total of 579 responses were used in the final analysis. Path analysis determined the process in which a runner becomes committed. MANOVA is used to determine difference between leisure groups in the four stages of PCM. Results indicate that activity participants need to go through all four stages of PCM before becoming loyal. As knowledge increases, individuals are more motivated to participate. When the activity satisfies motives and becomes a reflection of their identity, feelings become stronger which results in loyalty. Socialization is instrumental to the progression through the PCM Framework. Additionally, attachment is the "bottleneck" in which all loyal activity participants my pass through. Differences exist between serious leisure groups in the attachment and loyalty stages. Those that are `less serious' are not as committed to the activity as their counterparts.
ContributorsMurphey, Elizabeth M (Author) / Lee, Woojin (Thesis advisor) / Hultsman, Wendy (Thesis advisor) / Larsen, Dale (Committee member) / Chisum, Jack (Committee member) / Arizona State University (Publisher)
Created2014
Description
The need for alternative energy efficient building heating and cooling technologies has given rise to the development and widespread use of Ground Coupled Heat Pump (GCHP) systems. This dissertation looks at the feasibility of using GCHP systems as a viable economic alternative to traditional air source cooling systems (ASHP) for conditioning buildings in the hot, semi-arid climate of Phoenix, Arizona. Despite high initial costs, GCHPs are gaining a foothold in northern climates where heating dominates, in large part due to government incentives. However, due to issues associated with low ground heat exchanger (GHE) efficiency and thermally-induced soil deformations, GCHPs are typically not considered a viable option in hot climates with deep groundwater and low permeability soil. To evaluate the energy performance and technical feasibility of GCHPs in Phoenix, the DOE 5,500 sq.ft small office, commercial building prototype was simulated in EnergyPlus to determine the cooling and heating loads. Next, a commercial software program, Ground Loop Design (GLD), was used to design and simulate the annual energy performance of both vertical (V-GCHPs) and horizontal GCHPs (H-GCHPs). Life cycle costs (LCC) were evaluated using realistic market costs both under dry, as well as fully saturated soil conditions (meant as an upper performance limit achievable by ground modification techniques). This analysis included performing several sensitivity analyses and also investigating the effect of financial rebates. The range of annual energy savings from the GCHP system for space cooling and heating was around 38-40% compared to ASHPs for dry soil. Saturated soil condition significantly affects the length of the GHE. For V-GCHPs, there was about 26% decrease in the length of GHE, thereby reducing the initial cost by 18-19% and decreasing the payback period by 24-25%. Likewise, for H-GCHPs, the length of GHE was reduced by 25% resulting in 22% and 39-42 % reduction in the initial cost and payback period respectively. With federal incentives, H-GCHPs under saturated soil conditions have the least LCC and a good payback periods of 2.3-4.7 years. V-GCHPs systems were been found to have payback periods of over 25 years, making them unfeasible for Phoenix, AZ, for the type of building investigated.
ContributorsTambe, Vaibhavi Parmanand (Author) / Reddy, T Agami (Thesis advisor) / Kavanzanjian, Edward (Thesis advisor) / Bryan, Harvey (Committee member) / Arizona State University (Publisher)
Created2014
Description
The objective of this thesis is to investigate the various types of energy end-uses to be expected in future high efficiency single family residences. For this purpose, this study has analyzed monitored data from 14 houses in the 2013 Solar Decathlon competition, and segregates the energy consumption patterns in various residential end-uses (such as lights, refrigerators, washing machines, ...). The analysis was not straight-forward since these homes were operated according to schedules previously determined by the contest rules. The analysis approach allowed the isolation of the comfort energy use by the Heating, Venting and Cooling (HVAC) systems. HVAC are the biggest contributors to energy consumption during operation of a building, and therefore are a prime concern for energy performance during the building design and the operation. Both steady state and dynamic models of comfort energy use which take into account variations in indoor and outdoor temperatures, solar radiation and thermal mass of the building were explicitly considered. Steady State Inverse Models are frequently used for thermal analysis to evaluate HVAC energy performance. These are fast, accurate, offer great flexibility for mathematical modifications and can be applied to a variety of buildings. The results are presented as a horizontal study that compares energy consumption across homes to arrive at a generic rather than unique model - to be used in future discussions in the context of ultra efficient homes. It is suggested that similar analyses of the energy-use data that compare the performance of variety of ultra efficient technologies be conducted to provide more accurate indications of the consumption by end use for future single family residences. These can be used alongside the Residential Energy Consumption Survey (RECS) and the Leading Indicator for Remodeling Activity (LIRA) indices to assist in planning and policy making related to residential energy sector.
ContributorsGarkhail, Rahul (Author) / Reddy, T Agami (Thesis advisor) / Bryan, Harvey (Committee member) / Addison, Marlin (Committee member) / Arizona State University (Publisher)
Created2014
Description
Multi-touch tablets and smart phones are now widely used in both workplace and consumer settings. Interacting with these devices requires hand and arm movements that are potentially complex and poorly understood. Experimental studies have revealed differences in performance that could potentially be associated with injury risk. However, underlying causes for performance differences are often difficult to identify. For example, many patterns of muscle activity can potentially result in similar behavioral output. Muscle activity is one factor contributing to forces in tissues that could contribute to injury. However, experimental measurements of muscle activity and force for humans are extremely challenging. Models of the musculoskeletal system can be used to make specific estimates of neuromuscular coordination and musculoskeletal forces. However, existing models cannot easily be used to describe complex, multi-finger gestures such as those used for multi-touch human computer interaction (HCI) tasks. We therefore seek to develop a dynamic musculoskeletal simulation capable of estimating internal musculoskeletal loading during multi-touch tasks involving multi digits of the hand, and use the simulation to better understand complex multi-touch and gestural movements, and potentially guide the design of technologies the reduce injury risk. To accomplish these, we focused on three specific tasks. First, we aimed at determining the optimal index finger muscle attachment points within the context of the established, validated OpenSim arm model using measured moment arm data taken from the literature. Second, we aimed at deriving moment arm values from experimentally-measured muscle attachments and using these values to determine muscle-tendon paths for both extrinsic and intrinsic muscles of middle, ring and little fingers. Finally, we aimed at exploring differences in hand muscle activation patterns during zooming and rotating tasks on the tablet computer in twelve subjects. Towards this end, our musculoskeletal hand model will help better address the neuromuscular coordination, safe gesture performance and internal loadings for multi-touch applications.
ContributorsYi, Chong-hwan (Author) / Jindrich, Devin L. (Thesis advisor) / Artemiadis, Panagiotis K. (Thesis advisor) / Phelan, Patrick (Committee member) / Santos, Veronica J. (Committee member) / Huang, Huei-Ping (Committee member) / Arizona State University (Publisher)
Created2014
Optimization of the implementation of renewable resources in a municipal electric utility in Arizona
Description
A municipal electric utility in Mesa, Arizona with a peak load of approximately 85 megawatts (MW) was analyzed to determine how the implementation of renewable resources (both wind and solar) would affect the overall cost of energy purchased by the utility. The utility currently purchases all of its energy through long term energy supply contracts and does not own any generation assets and so optimization was achieved by minimizing the overall cost of energy while adhering to specific constraints on how much energy the utility could purchase from the short term energy market. Scenarios were analyzed for a five percent and a ten percent penetration of renewable energy in the years 2015 and 2025. Demand Side Management measures (through thermal storage in the City's district cooling system, electric vehicles, and customers' air conditioning improvements) were evaluated to determine if they would mitigate some of the cost increases that resulted from the addition of renewable resources.
In the 2015 simulation, wind energy was less expensive than solar to integrate to the supply mix. When five percent of the utility's energy requirements in 2015 are met by wind, this caused a 3.59% increase in the overall cost of energy. When that five percent is met by solar in 2015, it is estimated to cause a 3.62% increase in the overall cost of energy. A mix of wind and solar in 2015 caused a lower increase in the overall cost of energy of 3.57%. At the ten percent implementation level in 2015, solar, wind, and a mix of solar and wind caused increases of 7.28%, 7.51% and 7.27% respectively in the overall cost of energy.
In 2025, at the five percent implementation level, wind and solar caused increases in the overall cost of energy of 3.07% and 2.22% respectively. In 2025, at the ten percent implementation level, wind and solar caused increases in the overall cost of energy of 6.23% and 4.67% respectively.
Demand Side Management reduced the overall cost of energy by approximately 0.6%, mitigating some of the cost increase from adding renewable resources.
In the 2015 simulation, wind energy was less expensive than solar to integrate to the supply mix. When five percent of the utility's energy requirements in 2015 are met by wind, this caused a 3.59% increase in the overall cost of energy. When that five percent is met by solar in 2015, it is estimated to cause a 3.62% increase in the overall cost of energy. A mix of wind and solar in 2015 caused a lower increase in the overall cost of energy of 3.57%. At the ten percent implementation level in 2015, solar, wind, and a mix of solar and wind caused increases of 7.28%, 7.51% and 7.27% respectively in the overall cost of energy.
In 2025, at the five percent implementation level, wind and solar caused increases in the overall cost of energy of 3.07% and 2.22% respectively. In 2025, at the ten percent implementation level, wind and solar caused increases in the overall cost of energy of 6.23% and 4.67% respectively.
Demand Side Management reduced the overall cost of energy by approximately 0.6%, mitigating some of the cost increase from adding renewable resources.
ContributorsCadorin, Anthony (Author) / Phelan, Patrick (Thesis advisor) / Calhoun, Ronald (Committee member) / Trimble, Steve (Committee member) / Arizona State University (Publisher)
Created2014