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Department of Convergence & Fusion System Engineering Kyungpook National University
Because of the unavailability of standard renewable power generation capacity and the ambiguous sales methods for each building type, there has been indiscriminate installation of renewable energy sources to increase the mandatory installation rate of renewable energy. Importantly, campus buildings are high energy-consuming buildings that have considerable energy-saving potential. Herein, we present a model that maximizes the total life cycle cost (LCC) of a building using energy simulation programs (EnergyPlus & DesignBuilder) by considering various costs and efficiencies depending on the capacity and efficiency of the photovoltaic (PV) and ground-source heat pumps (GSHP) systems and optimization analysis using heuristic solution and multi-objective genetic algorithm. Based on economic factors, a Korean campus residential building was used as a case study, and the expense of the optimization models of seven applicable scenarios were analyzed. Each scenario is a method for selling renewable energy power, and it is possible to determine the building type and the effect of the sales method by analyzing the results of these scenarios. This method could be used to develop installation guidelines for integration of renewable energy systems into newly built buildings and provide the basis for decision-making by studying retrofitting of existing buildings to enhance energy efficiency.
Minjeong Sim; Dongjun Suh. A heuristic solution and multi-objective optimization model for life-cycle cost analysis of solar PV/GSHP system: A case study of campus residential building in Korea. Sustainable Energy Technologies and Assessments 2021, 47, 101490 .
AMA StyleMinjeong Sim, Dongjun Suh. A heuristic solution and multi-objective optimization model for life-cycle cost analysis of solar PV/GSHP system: A case study of campus residential building in Korea. Sustainable Energy Technologies and Assessments. 2021; 47 ():101490.
Chicago/Turabian StyleMinjeong Sim; Dongjun Suh. 2021. "A heuristic solution and multi-objective optimization model for life-cycle cost analysis of solar PV/GSHP system: A case study of campus residential building in Korea." Sustainable Energy Technologies and Assessments 47, no. : 101490.
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 m2 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.
Minjeong Sim; Dongjun Suh; Marc-Oliver Otto. Multi-Objective Particle Swarm Optimization-Based Decision Support Model for Integrating Renewable Energy Systems in a Korean Campus Building. Sustainability 2021, 13, 8660 .
AMA StyleMinjeong Sim, Dongjun Suh, Marc-Oliver Otto. Multi-Objective Particle Swarm Optimization-Based Decision Support Model for Integrating Renewable Energy Systems in a Korean Campus Building. Sustainability. 2021; 13 (15):8660.
Chicago/Turabian StyleMinjeong Sim; Dongjun Suh; Marc-Oliver Otto. 2021. "Multi-Objective Particle Swarm Optimization-Based Decision Support Model for Integrating Renewable Energy Systems in a Korean Campus Building." Sustainability 13, no. 15: 8660.