Multi-Objective Particle Swarm Optimization-Based Decision Support Model for Integrating Renewable Energy Systems in a Korean Campus Building

Minjeong Sim, Dongjun Suh and Marc-Oliver Otto
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Minjeong Sim: Department of Convergence & Fusion System Engineering, Kyungpook National University, Sangju 37224, Korea
Dongjun Suh: Department of Convergence & Fusion System Engineering, Kyungpook National University, Sangju 37224, Korea
Marc-Oliver Otto: Department of Mathematics, Natural and Economic Sciences, Ulm University of Applied Sciences, Prittwitzstr, 10, 89075 Ulm, Germany

Sustainability, 2021, vol. 13, issue 15, 1-18

Abstract: Renewable energy systems are an alternative to existing systems to achieve energy savings and carbon dioxide emission reduction. Subsequently, preventing the reckless installation of renewable energy systems and formulating appropriate energy policies, including sales strategies, is critical. Thus, this study aimed to achieve energy reduction through optimal selection of the capacity and lifetime of solar thermal (ST) and ground source heat pump (GSHP) systems that can reduce the thermal energy of buildings including the most widely used photovoltaic (PV) systems. Additionally, this study explored decision-making for optimal PV, ST, and GSHP installation considering economic and environmental factors such as energy sales strategy and electricity price according to energy policies. Therefore, an optimization model based on multi-objective particle swarm optimization was proposed to maximize lifecycle cost and energy savings based on the target energy savings according to PV capacity. Furthermore, the proposed model was verified through a case study on campus buildings in Korea: PV 60 kW and ST 32 m 2 GSHP10 kW with a lifetime of 50 years were found to be the optimal combination and capacity. The proposed model guarantees economic optimization, is scalable, and can be used as a decision-making model to install renewable energy systems in buildings worldwide.

Keywords: renewable energy systems; multi-objective particle swarm optimization; retrofit; lifecycle cost (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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