Distributed Energy Systems: Multi-Objective Design Optimization Based on Life Cycle Environmental and Economic Impacts

Krisha Maharjan, Jian Zhang (), Heejin Cho and Yang Chen
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Krisha Maharjan: Department of Mechanical Engineering, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
Jian Zhang: Richard J. Resch School of Engineering, University of Wisconsin-Green Bay, Green Bay, WI 54311, USA
Heejin Cho: Department of Mechanical Engineering, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
Yang Chen: Department of Industrial and Systems Engineering, North Carolina A&T State University, Greensboro, NC 27411, USA

Energies, 2023, vol. 16, issue 21, 1-21

Abstract: The distributed energy system (DES) represents an innovative approach to energy generation and distribution that promotes decentralization and diversification of energy sources. DESs can offer numerous benefits, including increased resiliency, reduced transmission losses, improved efficiency, and lower carbon emissions. The optimal design of a DES requires careful consideration of various factors such as geographical location, climate conditions, and energy demand patterns. This paper utilizes a multi-objective genetic algorithm to optimize the combination of technologies and their corresponding sizes in a distributed energy system for three types of commercial buildings—hospitals, large offices, and large hotels across eight different climate zones in the U.S. A range of technologies are considered for integration into the DES. These technologies include photovoltaic systems, wind turbines, combined heat and power systems, solar thermal collectors, and electrical and thermal energy storage. The two objectives considered are maximizing the reduction in carbon dioxide emissions and minimizing the life cycle costs for the DES. The purpose of this study is to optimize and evaluate the multi-objective design of distributed energy systems aimed at decentralizing and diversifying energy sources. The analysis of optimized DES designs across all 24 case scenarios shows that a balance between cost saving and emission reduction has been achieved. Although this study primarily focuses on specific buildings and climate zones, the methods and findings can be adapted for a wider variety of building types across different geographical locations, thus paving the way for more widespread adoption of optimized distributed energy systems.

Keywords: distributed energy system; design optimization; multi-objective; life cycle cost; emissions (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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