Hybrid Energy System with Optimized Storage for Improvement of Sustainability in a Small Town

Fengchang Jiang, Haiyan Xie and Oliver Ellen
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Fengchang Jiang: Taizhou Polytechnic College, Taizhou 225300, Jiangsu, China
Haiyan Xie: Department of Technology, College of Applied Science and Technology, Illinois State University, Normal, IL 61790-5100, USA
Oliver Ellen: Department of Technology, College of Applied Science and Technology, Illinois State University, Normal, IL 61790-5100, USA

Sustainability, 2018, vol. 10, issue 6, 1-16

Abstract: With the rise of renewable energy comes significant challenges and benefits. The current studies on the incorporation of renewable-energy policies and energy-storage technologies attempt to address the optimization of hybrid energy systems (HESs). However, there is a gap between the currents needs of HES in small towns for energy independence and the understanding of integrated optimization approaches for employing the technology. The purpose of this research is to determine the technical, systematic and financial requirements needed to allow a city or community to become independent of the utilization of traditional energy and develop a reliable program for a clean and environment-friendly energy supply. This paper presents the sensitivity analysis and Bayesian prediction (SABP) method for the optimized design of a hybrid photo-voltaic wind energy system. This method uses the actual data to analyze and compare the main, optimized and desired scenarios of HES designs. The results show that optimized design can minimize the cost of the energy generated while reliably matching local electricity demand. The SABP system helps to eliminate the dependence on traditional energy resources, reduce transition costs by purchasing electricity, and decrease the financial burden of a small city.

Keywords: renewable energy; independent energy resources; solar; wind; energy storage; Bayesian analysis; prediction (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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