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

Renewable energy systems are an alternative to existing achieve savings and carbon dioxide emission reduction. Subsequently, preventing the reckless installation of renewable formulating appropriate policies, including sales strategies, is critical. Thus, this study aimed reduction through optimal selection capacity lifetime solar thermal (ST) ground source heat pump (GSHP) that can reduce buildings most widely used photovoltaic (PV) systems. Additionally, explored decision-making for PV, ST, GSHP considering economic environmental factors such as strategy electricity price according policies. Therefore, optimization model based on multi-objective particle swarm was proposed maximize lifecycle cost target PV capacity. Furthermore, verified a case campus in Korea: 60 kW ST 32 m2 GSHP10 with 50 years were found be combination The guarantees optimization, scalable, install worldwide.