Work

Using Approximation-Based Global Optimization Algorithm superEGO for Analyzing Wind Energy Potential

Year: 2025

Type: article

Abstract: Recent years have seen a considerable increase in clean, green electricity output from wind energy (WE). It is crucial to obtain the optimum parameters of the two-parameter Weibull distribution (TPWD) for wind speed (WS) to calculate the potential WE. This paper proposes to use the superEGO (SEGO) along with maximum likelihood estimation (MLE) to obtain optimum parameters of the TWPD for WS data. The results showed that SEGO provided better results compared other optimization algorithms used in this context. Moreover, the potential WE for Gdańsk, a city located by the Baltic Sea in northern Poland, was calculated using parameters obtained by using SEGO. It was observed that SEGO performs the best among other optimization algorithms to find optimum parameters for the two-parameter Weibull distribution along with MLE for wind speed.

Source: Energies

DOI: 10.3390/en18215631

Authors: Bartłomiej Igliński, Olgun Aydin, Jarosław Krajewski

Institutions: Nicolaus Copernicus University, Gdańsk University of Technology

Language: English

Topic: Wind Energy Research and Development

Subfield: Aerospace Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Affordable and clean energy, Climate action

Open Access status: gold

Estimated APC paid: $3,137