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- Genre: Academic theses
Description
Fish farming is a fast growing industry, which, although necessary to feed an ever growing worldwide population, has its share of negative environmental consequences, including the release of drugs and other waste into the ocean, the use of fish caught from the ocean to feed farm raised fish, and the escape of farm raised fish into natural bodies of water. However, the raising of certain types of fish, such as tilapia, seems to be an environmentally better proposition than raising other types of fish, such as salmon. This paper will explore the problems associated with fish farming, as well as offer a model, based on the literature, and interviews with fish farmers, to make small-scale fish farming both more environmentally, and more economically, sustainable. This paper culminates with a model for small-scale, specifically semi-subsistence, fish farmers. This model emphasizes education of the fish farmers, as well as educators learning from the fish farmers they interact with. The goal of this model is to help these fish farmers become both more environmentally and economically sustainable.
ContributorsLongoni, Robert A (Author) / Parmentier, Mary Jane (Thesis advisor) / Grossman, Gary (Committee member) / Macia, Narciso (Committee member) / Arizona State University (Publisher)
Created2011
Description
The prevalence of renewable generation will increase in the next several decades and offset conventional generation more and more. Yet this increase is not coming without challenges. Solar, wind, and even some water resources are intermittent and unpredictable, and thereby create scheduling challenges due to their inherent “uncontrolled” nature. To effectively manage these distributed renewable assets, new control algorithms must be developed for applications including energy management, bridge power, and system stability. This can be completed through a centralized control center though efforts are being made to parallel the control architecture with the organization of the renewable assets themselves—namely, distributed controls. Building energy management systems are being employed to control localized energy generation, storage, and use to reduce disruption on the net utility load. One such example is VOLTTRONTM, an agent-based platform for building energy control in real time. In this thesis, algorithms developed in VOLTTRON simulate a home energy management system that consists of a solar PV array, a lithium-ion battery bank, and the grid. Dispatch strategies are implemented to reduce energy charges from overall consumption ($/kWh) and demand charges ($/kW). Dispatch strategies for implementing storage devices are tuned on a month-to-month basis to provide a meaningful economic advantage under simulated scenarios to explore algorithm sensitivity to changing external factors. VOLTTRON agents provide automated real-time optimization of dispatch strategies to efficiently manage energy supply and demand, lower consumer costs associated with energy usage, and reduce load on the utility grid.
ContributorsCardwell, Joseph (Author) / Johnson, Nathan (Thesis advisor) / Rogers, Bradley (Committee member) / Macia, Narciso (Committee member) / Arizona State University (Publisher)
Created2015