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Energy storage optimization using modified cuckoo search
Wiebe, Kyle Garrett
Wiebe, Kyle Garrett
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2023-12
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Renewable generation is a topical area of research due to its low environmental impact compared with conventional generation and the current push to reduce fossil fuel emissions. However, inconsistencies in renewable power generation can cause a variety of power system problems. Energy storage technologies, such as batteries, are able to be used to help smooth out the inconsistent generation patterns of renewable resources. This ability to, partially or completely, remedy the unpredictability inherent to renewable generation makes battery storage an important topic for academic progress and optimization to increase industry utilization. There are numerous parameters pertaining to batteries and the power grid that can be optimized, one of which being economic optimization, which is the subject of this thesis. This optimization goal enhances battery systems’ feasibility of installation in the industry. This thesis presents a modified version of Cuckoo Search Optimization [1] and validates it with a more conventional optimization technique, Dynamic Programming [2]. It is then shown how this optimization technique can be applied to optimize a battery’s charge and discharge schedule and to implement economic battery sizing for various battery capital cost estimates.
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Thesis (M.S.)-- Wichita State University, College of Engineering, Dept. of Electrical and Computer Engineering
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Wichita State University
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© Copyright 2023 by Kyle Wiebe
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