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- Genre: Academic theses
Description
Solar power generation is the most promising technology to transfer energy consumption reliance from fossil fuel to renewable sources. Concentrated solar power generation is a method to concentrate the sunlight from a bigger area to a smaller area. The collected sunlight is converted more efficiently through two types of technologies: concentrated solar photovoltaics (CSPV) and concentrated solar thermal power (CSTP) generation. In this thesis, these two technologies were evaluated in terms of system construction, performance characteristics, design considerations, cost benefit analysis and their field experience. The two concentrated solar power generation systems were implemented with similar solar concentrators and solar tracking systems but with different energy collecting and conversion components: the CSPV system uses high efficiency multi-junction solar cell modules, while the CSTP system uses a boiler -turbine-generator setup. The performances are calibrated via the experiments and evaluation analysis.
ContributorsJin, Zhilei (Author) / Hui, Yu (Thesis advisor) / Ayyanar, Raja (Committee member) / Rodriguez, Armando (Committee member) / Arizona State University (Publisher)
Created2013
Description
This dissertation builds a clear understanding of the role of information in wireless networks, and devises adaptive strategies to optimize the overall performance. The meaning of information ranges from channel
etwork states to the structure of the signal itself. Under the common thread of characterizing the role of information, this dissertation investigates opportunistic scheduling, relaying and multicast in wireless networks. To assess the role of channel state information, the problem of opportunistic distributed opportunistic scheduling (DOS) with incomplete information is considered for ad-hoc networks in which many links contend for the same channel using random access. The objective is to maximize the system throughput. In practice, link state information is noisy, and may result in throughput degradation. Therefore, refining the state information by additional probing can improve the throughput, but at the cost of further probing. Capitalizing on optimal stopping theory, the optimal scheduling policy is shown to be threshold-based and is characterized by either one or two thresholds, depending on network settings. To understand the benefits of side information in cooperative relaying scenarios, a basic model is explored for two-hop transmissions of two information flows which interfere with each other. While the first hop is a classical interference channel, the second hop can be treated as an interference channel with transmitter side information. Various cooperative relaying strategies are developed to enhance the achievable rate. In another context, a simple sensor network is considered, where a sensor node acts as a relay, and aids fusion center in detecting an event. Two relaying schemes are considered: analog relaying and digital relaying. Sufficient conditions are provided for the optimality of analog relaying over digital relaying in this network. To illustrate the role of information about the signal structure in joint source-channel coding, multicast of compressible signals over lossy channels is studied. The focus is on the network outage from the perspective of signal distortion across all receivers. Based on extreme value theory, the network outage is characterized in terms of key parameters. A new method using subblock network coding is devised, which prioritizes resource allocation based on the signal information structure.
etwork states to the structure of the signal itself. Under the common thread of characterizing the role of information, this dissertation investigates opportunistic scheduling, relaying and multicast in wireless networks. To assess the role of channel state information, the problem of opportunistic distributed opportunistic scheduling (DOS) with incomplete information is considered for ad-hoc networks in which many links contend for the same channel using random access. The objective is to maximize the system throughput. In practice, link state information is noisy, and may result in throughput degradation. Therefore, refining the state information by additional probing can improve the throughput, but at the cost of further probing. Capitalizing on optimal stopping theory, the optimal scheduling policy is shown to be threshold-based and is characterized by either one or two thresholds, depending on network settings. To understand the benefits of side information in cooperative relaying scenarios, a basic model is explored for two-hop transmissions of two information flows which interfere with each other. While the first hop is a classical interference channel, the second hop can be treated as an interference channel with transmitter side information. Various cooperative relaying strategies are developed to enhance the achievable rate. In another context, a simple sensor network is considered, where a sensor node acts as a relay, and aids fusion center in detecting an event. Two relaying schemes are considered: analog relaying and digital relaying. Sufficient conditions are provided for the optimality of analog relaying over digital relaying in this network. To illustrate the role of information about the signal structure in joint source-channel coding, multicast of compressible signals over lossy channels is studied. The focus is on the network outage from the perspective of signal distortion across all receivers. Based on extreme value theory, the network outage is characterized in terms of key parameters. A new method using subblock network coding is devised, which prioritizes resource allocation based on the signal information structure.
ContributorsPaataguppe Suryanarayan Bhat, Chandrashekhar Thejaswi (Author) / Zhang, Junshan (Thesis advisor) / Cochran, Douglas (Committee member) / Duman, Tolga (Committee member) / Hui, Yu (Committee member) / Taylor, Thomas (Committee member) / Arizona State University (Publisher)
Created2011