Proceeding of the Electrical Engineering Computer Science and Informatics
Vol 5: EECSI 2018

Sizing Optimization and Operational Strategy of Hres (PV-WT) using Differential Evolution Algorithm

Ilham Pakaya (Universitas Muhammadiyah Malang, Indonesia)
Zulfatman Has (University of Muhammadiyah Malang, Indonesia)
Annas Alif Putra (Universitas Muhammadiyah Malang, Indonesia)



Article Info

Publish Date
18 Sep 2019

Abstract

The instability of energy resources and corresponding cost of the system are the main two problems for designing the hybrid solar-wind power generation systems. The configuration of the system must have a high reliability on the power supply availability but with a minimum cost. The purpose of this paper is to find the most optimum or balanced configuration between technical reliability and total annual cost for the PV module number, the wind turbine number, and the battery number. The appropriate strategy of load management is needed by adjusting the potential energy resource to the load power demand. Loss of Power Supply Probability (LPSP) is a method to determine the ratio of power generation unavailability by the system configuration which used as technical analysis. Annualized Cost of System (ACS) is a method to determine the total annualized cost of the project lifetime which used as economic analysis. The result from the simulation showed that the Differential Evolution (DE) algorithm can be an alternative method to find the best configuration with a low number of LPSP and ACS. Since DE has a better efficacy and faster time to find global optimum than other algorithms.

Copyrights © 2018






Journal Info

Abbrev

EECSI

Publisher

Subject

Computer Science & IT Electrical & Electronics Engineering

Description

Proceeding of the Electrical Engineering Computer Science and Informatics publishes papers of the "International Conference on Electrical Engineering Computer Science and Informatics (EECSI)" Series in high technical standard. The Proceeding is aimed to bring researchers, academicians, scientists, ...