THE USE OF LIFE-CYCLE ANALYSIS TO REDUCE THE ENVIRONMENTAL IMPACT OF MATERIALS IN MANUFACTURING

This thesis is composed of three life-cycle analysis (LCA) studies of manufacturing to determine cumulative energy demand (CED) and greenhouse gas emissions (GHG). The methods proposed could reduce the environmental impact by reducing the CED in three manufacturing processes. First, industrial symbiosis is proposed and a LCA is performed on both conventional 1 GW-scaled hydrogenated amorphous silicon (a-Si:H)-based single junction and a-Si:H/microcrystalline-Si:H tandem cell solar PV manufacturing plants and such plants coupled to silane recycling plants. Using a recycling process that results in a silane loss of only 17 versus 85 percent, this results in a CED savings of 81,700 GJ and 290,000 GJ per year for single and tandem junction plants, respectively. This recycling process reduces the cost of raw silane by 68 percent, or approximately $22.6 and $79 million per year for a single and tandem 1 GW PV production facility, respectively. The results show environmental benefits of silane recycling centered around a-Si:H-based PV manufacturing plants. Second, an open-source self-replicating rapid prototype or 3-D printer, the RepRap, has the potential to reduce the environmental impact of manufacturing of polymer-based products, using distributed manufacturing paradigm, which is further minimized by the use of PV and improvements in PV manufacturing. Using 3-D printers for manufacturing provides the ability to ultra-customize products and to change fill composition, which increases material efficiency. An LCA was performed on three polymer-based products to determine the CED and GHG from conventional large-scale production and are compared to experimental measurements on a RepRap producing identical products with ABS and PLA. The results of this LCA study indicate that the CED of manufacturing polymer products can possibly be reduced using distributed manufacturing with existing 3-D printers under 89% fill and reduced even further with a solar photovoltaic system. The results indicate that the ability of RepRaps to vary fill has the potential to diminish environmental impact on many products. Third, one additional way to improve the environmental performance of this distributed manufacturing system is to create the polymer filament feedstock for 3-D printers using post-consumer plastic bottles. An LCA was performed on the recycling of high density polyethylene (HDPE) using the RecycleBot. The results of the LCA showed that distributed recycling has a lower CED than the best-case scenario used for centralized recycling. If this process is applied to the HDPE currently recycled in the U.S., more than 100 million MJ of energy could be conserved per annum along with significant reductions in GHG. This presents a novel path to a future of distributed manufacturing suited for both the developed and developing world with reduced environmental impact. From improving manufacturing in the photovoltaic industry with the use of recycling to recycling and manufacturing plastic products within our own homes, each step reduces the impact on the environment. The three coupled projects presented here show a clear potential to reduce the environmental impact of manufacturing and other processes by implementing complimenting systems, which have environmental benefits of their own in order to achieve a compounding effect of reduced CED and GHG.

Twelve factors influencing sustainable recycling of municipal solid waste in developing countries

Sustainable management of solid waste is a global concern, as exemplified by the United Nations Millennium Development Goals (MDG) that 191 member states support. The seventh MDG indirectly advocates for municipal solid waste management (MSWM) by aiming to ensure environmental sustainability into countries’ policies and programs and reverse negative environmental impact. Proper MSWM will likely result in relieving poverty, reducing child mortality, improving maternal health, and preventing disease, which are MDG goals one, four, five, and six, respectively (UNMDG, 2005). Solid waste production is increasing worldwide as the global society strives to obtain a decent quality of life. Several means exist in which the amount of solid waste going to a landfill can be reduced, such as incineration with energy production, composting of organic wastes, and material recovery through recycling, which are all considered sustainable methods by which to manage MSW. In the developing world, composting is already a widely-accepted method to reduce waste fated for the landfill, and incineration for energy recovery can be a costly capital investment for most communities. Therefore, this research focuses on recycling as a solution to the municipal solid waste production problem while considering the three dimensions of sustainability environment, society, and economy. First, twenty-three developing country case studies were quantitatively and qualitatively examined for aspects of municipal solid waste management. The municipal solid waste (MSW) generation and recovery rates, as well as the composition were compiled and assessed. The average MSW generation rate was 0.77 kg/person/day, with recovery rates varying from 5 – 40%. The waste streams of nineteen of these case studies consisted of 0 – 70% recyclable material and 17 – 80% organic material. All twenty-three case studies were analyzed qualitatively by identifying any barriers or incentives to recycling, which justified the creation of twelve factors influencing sustainable municipal solid waste management (MSWM) in developing countries. The presence of regulations, enforcement of laws, and use of incentive schemes constitutes the first factor, Government Policy. Cost of MSWM operations, the budget allocated to MSWM by local to national governments, as well as the stability and reliability of funds comprise the Government Finances factor influencing recycling in the third world. Many case studies indicated that understanding features of a waste stream such as the generation and recovery rates and composition is the first measure in determining proper management solutions, which forms the third factor Waste Characterization. The presence and efficiency of waste collection and segregation by scavengers, municipalities, or private contractors was commonly addressed by the case studies, which justified Waste Collection and Segregation as the fourth factor. Having knowledge of MSWM and an understanding of the linkages between human behavior, waste handling, and health/sanitation/environment comprise the Household Education factor. Individuals’ income influencing waste handling behavior (e.g., reuse, recycling, and illegal dumping), presence of waste collection/disposal fees, and willingness to pay by residents were seen as one of the biggest incentives to recycling, which justified them being combined into the Household Economics factor. The MSWM Administration factor was formed following several references to the presence and effectiveness of private and/or public management of waste through collection, recovery, and disposal influencing recycling activity. Although the MSWM Personnel Education factor was only recognized by six of the twenty-two case studies, the lack of trained laborers and skilled professionals in MSWM positions was a barrier to sustainable MSWM in every case but one. The presence and effectiveness of a comprehensive, integrative, long-term MSWM strategy was highly encouraged by every case study that addressed the tenth factor, MSWM Plan. Although seemingly a subset of private MSWM administration, the existence and profitability of market systems relying on recycled-material throughput, involvement of small businesses, middlemen, and large industries/exporters is deserving of the factor Local Recycled-Material Market. Availability and effective use of technology and/or human workforce and the safety considerations of each were recurrent barriers and incentives to recycling to warrant the Technological and Human Resources factor. The Land Availability factor takes into consideration land attributes such as terrain, ownership, and development which can often times dictate MSWM. Understanding the relationships among the twelve factors influencing recycling in developing countries, made apparent the collaborative nature required of sustainable MSWM. Factors requiring the greatest collaborative inputs include waste collection and segregation, MSWM plan, and local recycled-material market. Aligning each factor to the societal, environmental, and economic dimensions of sustainability revealed the motives behind the institutions contributing to each factor. A correlation between stakeholder involvement and sustainability existed, as supported by the fact that the only three factors driven by all three dimensions of sustainability were the same three that required the greatest collaboration with other factors. With increasing urbanization, advocating for improved health for all through the MDG, and changing consumption patterns resulting in increasing and more complex waste streams, the utilization of the collaboration web offered by this research is ever needed in the developing world. Through its use, the institutions associated with each of the twelve factors can achieve a better understanding of the collaboration necessary and beneficial for more sustainable MSWM.

Detection of complex point targets with distributed assets in a MIMO radar system

The report explores the problem of detecting complex point target models in a MIMO radar system. A complex point target is a mathematical and statistical model for a radar target that is not resolved in space, but exhibits varying complex reflectivity across the different bistatic view angles. The complex reflectivity can be modeled as a complex stochastic process whose index set is the set of all the bistatic view angles, and the parameters of the stochastic process follow from an analysis of a target model comprising a number of ideal point scatterers randomly located within some radius of the targets center of mass. The proposed complex point targets may be applicable to statistical inference in multistatic or MIMO radar system. Six different target models are summarized here – three 2-dimensional (Gaussian, Uniform Square, and Uniform Circle) and three 3-dimensional (Gaussian, Uniform Cube, and Uniform Sphere). They are assumed to have different distributions on the location of the point scatterers within the target. We develop data models for the received signals from such targets in the MIMO radar system with distributed assets and partially correlated signals, and consider the resulting detection problem which reduces to the familiar Gauss-Gauss detection problem. We illustrate that the target parameter and transmit signal have an influence on the detector performance through target extent and the SNR respectively. A series of the receiver operator characteristic (ROC) curves are generated to notice the impact on the detector for varying SNR. Kullback–Leibler (KL) divergence is applied to obtain the approximate mean difference between density functions the scatterers assume inside the target models to show the change in the performance of the detector with target extent of the point scatterers.

Optimal game theoretic distributed control methodologies in small scale power systems

This dissertation presents the competitive control methodologies for small-scale power system (SSPS). A SSPS is a collection of sources and loads that shares a common network which can be isolated during terrestrial disturbances. Micro-grids, naval ship electric power systems (NSEPS), aircraft power systems and telecommunication system power systems are typical examples of SSPS. The analysis and development of control systems for small-scale power systems (SSPS) lacks a defined slack bus. In addition, a change of a load or source will influence the real time system parameters of the system. Therefore, the control system should provide the required flexibility, to ensure operation as a single aggregated system. In most of the cases of a SSPS the sources and loads must be equipped with power electronic interfaces which can be modeled as a dynamic controllable quantity. The mathematical formulation of the micro-grid is carried out with the help of game theory, optimal control and fundamental theory of electrical power systems. Then the micro-grid can be viewed as a dynamical multi-objective optimization problem with nonlinear objectives and variables. Basically detailed analysis was done with optimal solutions with regards to start up transient modeling, bus selection modeling and level of communication within the micro-grids. In each approach a detail mathematical model is formed to observe the system response. The differential game theoretic approach was also used for modeling and optimization of startup transients. The startup transient controller was implemented with open loop, PI and feedback control methodologies. Then the hardware implementation was carried out to validate the theoretical results. The proposed game theoretic controller shows higher performances over traditional the PI controller during startup. In addition, the optimal transient surface is necessary while implementing the feedback controller for startup transient. Further, the experimental results are in agreement with the theoretical simulation. The bus selection and team communication was modeled with discrete and continuous game theory models. Although players have multiple choices, this controller is capable of choosing the optimum bus. Next the team communication structures are able to optimize the players’ Nash equilibrium point. All mathematical models are based on the local information of the load or source. As a result, these models are the keys to developing accurate distributed controllers.

DISTRIBUTED APPROACH FOR SOLVING OPTIMAL POWER FLOW PROBLEMS IN THREE-PHASE UNBALANCED DISTRIBUTION NETWORK

The objective of this report is to study distributed (decentralized) three phase optimal power flow (OPF) problem in unbalanced power distribution networks. A full three phase representation of the distribution networks is considered to account for the highly unbalance state of the distribution networks. All distribution network’s series/shunt components, and load types/combinations had been modeled on commercial version of General Algebraic Modeling System (GAMS), the high-level modeling system for mathematical programming and optimization. The OPF problem has been successfully implemented and solved in a centralized approach and distributed approach, where the objective is to minimize the active power losses in the entire system. The study was implemented on the IEEE-37 Node Test Feeder. A detailed discussion of all problem sides and aspects starting from the basics has been provided in this study. Full simulation results have been provided at the end of the report.

AGENT BASED, DISTRIBUTED CONTROL STRATEGIES AND OPTIMIZATION OF PLUG-IN ELECTRIC VEHICLES ON SMART/MICROGRID ARCHITECTURES

This thesis will present strategies for the use of plug-in electric vehicles on smart and microgrids. MATLAB is used as the design tool for all models and simulations. First, a scenario will be explored using the dispatchable loads of electric vehicles to stabilize a microgrid with a high penetration of renewable power generation. Grid components for a microgrid with 50% photovoltaic solar production will be sized through an optimization routine to maintain storage system, load, and vehicle states over a 24-hour period. The findings of this portion are that the dispatchable loads can be used to guard against unpredictable losses in renewable generation output. Second, the use of distributed control strategies for the charging of electric vehicles utilizing an agent-based approach on a smart grid will be studied. The vehicles are regarded as additional loads to a primary forecasted load and use information transfer with the grid to make their charging decisions. Three lightweight control strategies and their effects on the power grid will be presented. The findings are that the charging behavior and peak loads on the grid can be reduced through the use of distributed control strategies.