Offshore wind farm layout optimization using particle swarm optimization

Ajit C Pillai,Lars Johanning,John Chick,Mahdi Khorasanchi

doi:10.1007/s40722-018-0108-z

Abstract

This article explores the application of a wind farm layout optimization framework using a particle swarm optimizer to three benchmark test cases. The developed framework introduces an increased level of detail characterizing the impact that the wind farm layout can have on the levelized cost of energy by modelling the wind farm’s electrical infrastructure, annual energy production, and cost as functions of the wind farm layout. Using this framework, this paper explores the application of a particle swarm optimizer to the wind farm layout optimization problem considering three different levels of wind farm constraint faced by modern wind farm developers. The particle swarm optimizer is found to yield improvements in the layout with respect to the levelized cost of energy for the three benchmark cases when compared to two past studies. This highlights both applicability of the particle swarm optimizer to the problem and the ways in which a wind farm developer could make use of the present framework in the development and design of future wind farms.

Highlights

As the world transitions to a more sustainable energy sector, wind energy and in particular offshore wind farms represent a significant means for reducing the greenhouse gas emissions of electricity generation
In order to demonstrate the capabilities of the present framework using a particle swarm optimizer (PSO), the final layouts from the original study by Mosetti et al (1994) and the final layouts from a subsequent study by Grady et al (2005) are evaluated using the present evaluation function in order to offer a fair comparison to the new layouts proposed
This paper has presented the first results of an extended wind farm layout optimization framework making use of a more detailed levelized cost of energy (LCOE) evaluation function than existing layout optimization tools

Summary

Introduction

As the world transitions to a more sustainable energy sector, wind energy and in particular offshore wind farms represent a significant means for reducing the greenhouse gas emissions of electricity generation. Present Address: Renewable Energy Group, University of Exeter, Penryn, UK To meet this need, tools have been developed exploring the optimal placement of wind turbines, offshore substations, and intra-array cables within an offshore wind farm. The original work in wind farm layout optimization done by Mosetti et al (1994) laid the ground work for this field introducing a general approach that following work has continued to utilize. This approach includes the assessment of both the energy produced by a wind farm and the cost of the wind farm over the lifetime of the project. The most frequent optimization algorithm applied to the wind farm layout optimization problem has been the genetic algorithm with several studies exploring its applicability to the problem as posed by Mosetti et al (1994) and to more complex extensions

Results

Discussion

Conclusion