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. (October 2021)

• Record Type: Journal Article
• Authors: Sim, Minjeong; Suh, Dongjun
• Is Part Of: Sustainable energy technologies and assessments. Volume 47(2021)
• Publication Date: 2021-10
• Subjects: Optimization -- PV -- GSHP -- LCC -- Multi-objective genetic algorithm; Renewable energy sources -- Periodicals; Energy development -- Technological innovations -- Periodicals; Electric power production -- Periodicals; Energy storage -- Periodicals; 333.79
• DOI: 10.1016/j.seta.2021.101490
• Languages: English
• ISSNs: 2213-1388

Abstract

Abstract: 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.