Design of a solar PV tree system using multi-objective fuzzy logic MILP

• Main Author: Batiles, Jose Alfron Benedicto R.
• Format: text
• Language: English
• Published: Animo Repository 2019
• Subjects: Solar power plants; Photovoltaic power systems; Fuzzy logic; Mechanical Engineering
• Online Access: https://animorepository.dlsu.edu.ph/etd_masteral/7020
• Institution: De La Salle University

Solar PV systems are an improvement from conventional solar power as they address the variability of PV panels using energy storage technology. A solar PV system consists of three subsystems: the power generation subsystem, the battery storage subsystem, and the balance of system. A solar tree is a unique configuration to conventional solar power that could be applied to the power generation subsystem of a solar PV system. As the name implies, solar panels are scattered like leaves on a tree with the benefit of having improved solar irradiance and land availability. A solar PV tree system combines the benefits of these solar power technologies to improve the solar power output, solve the intermittency issue and fix the land allocation problem of conventional solar PV technology. A Fuzzy Logic Mixed Integer Linear Program (MILP) model was programmed through LINGO to consider the multi-objective issue of minimizing the system installation cost and maximize the reductions in carbon dioxide emissions of the solar PV tree system. The model input parameters included the nonutility facility data, the component specifications considered for installation, the price of buying electricity, the benefits of the net metering system, and the carbon emissions ratings of various power technologies. A global optimal solution was achieved with a degree of satisfaction of 0.5 and component installation at 5 PV panels and 1 battery unit. The output results were compared to a validation model and case studies to determine the effectivity of the solar PV tree system and the influence that varying certain factors have on the output results.