Abstract

This research aims to predict the optimum surface orientation angles in solar panel installation to achieve maximum solar radiation. Incident solar radiation is calculated using koronakis mathematical model. Particle Swarm Optimization (PSO) is used as computational method to find optimum angle orientation for solar panel installation in order to get maximum solar radiation. A series of simulation has been carried out to calculate solar radiation based on monthly, seasonally, semi-yearly and yearly period. South-facing was calculated also as comparison of proposed method. South-facing considers azimuth of 0°. Proposed method attains higher incident predictions than South-facing that recorded 2511.03 kWh/m2for monthly. It were about 2486.49 kWh/m2, 2482.13 kWh/m2and 2367.68 kWh/m2 for seasonally, semi-yearly and yearly. South-facing predicted approximately 2496.89 kWh/m2, 2472.40 kWh/m2, 2468.96 kWh/m2, 2356.09 kWh/m2for monthly, seasonally, semi-yearly and yearly periods respectively. Semi-yearly is the best choice because it needs twice adjustments of solar panel in a year. Yet it considers inefficient to adjust solar panel position in every season or monthly with no significant solar radiation increase than semi-yearly and solar tracking device still considers costly in solar energy system. PSO was able to predict accurately with simple concept, easy and computationally efficient. It has been proven by finding the best fitness faster.

Details

Title
Prediction of the optimum surface orientation angles to achieve maximum solar radiation using Particle Swarm Optimization in Sabha City Libya
Author
Mansour, F A 1 ; Nizam, M 2 ; Anwar, M 3 

 Student, Mechanical Engineering Department, Sebelas Maret University, Surakarta 
 Professor, Electrical Engineering Department, Sebelas Maret University, Surakarta 
 Lecturer, Electrical Engineering Department, Sebelas Maret University, Surakarta 
Publication year
2017
Publication date
Mar 2017
Publisher
IOP Publishing
ISSN
17578981
e-ISSN
1757899X
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2563820577
Copyright
© 2017. This work is published under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.