Power Maximization and Turbulence Intensity Management through Axial Induction-Based Optimization and Efficient Static Turbine Deployment

Mfon Charles,Mqhele Dlodlo,David T O Oyedokun

doi:10.3390/en14164943

Abstract

Layout optimization is capable of increasing turbine density and reducing wake effects in wind plants. However, such optimized layouts do not guarantee fixed T-2-T distances in any direction and would be disadvantageous if reduction in computational costs due to turbine set-point updates is also a priority. Regular turbine layouts are considered basic because turbine coordinates can be determined intuitively without the application of any optimization algorithms. However, such layouts can be used to intentionally create directions of large T-2-T distances, hence, achieve the gains of standard/non-optimized operations in these directions, while also having close T-2-T distances in other directions from which the gains of optimized operations can be enjoyed. In this study, a regular hexagonal turbine layout is used to deploy turbines within a fixed area dimension, and a turbulence intensity-constrained axial induction-based plant-wide optimization is carried out using particle swarm, artificial bee colony, and differential evolution optimization techniques. Optimized plant power for three close turbine deployments (4D, 5D, and 6D) are compared to a non-optimized 7D deployment using three mean wind inflows. Results suggest that a plant power increase of up to 37% is possible with a 4D deployment, with this increment decreasing as deployment distance increases and as mean wind inflow increases.

Highlights

Published: 12 August 2021Given the evident global effects of fossil fuels on the atmosphere, renewable energy sources have become even more vital for energy generation due to its wide availability.The Global Wind Energy Council (GWEC) in their 2020 global wind report suggests that the global wind power must triple over the decade to avert the most devastating effects on climate change and, keep global warming well below 2 ◦ C [1]
These economies of scale, in most cases, enforce close turbine installations in a wind plant and, this leads to increased power density, cause aerodynamic interactions, known as wakes, between operating turbines and could negatively impact on plant power production [2]
To observe and analyze the non-optimized and optimized system behavior, results are presented for a single major wake zone (MWZ) and for all deployment distances studied

Summary

Introduction

Published: 12 August 2021Given the evident global effects of fossil fuels on the atmosphere, renewable energy sources have become even more vital for energy generation due to its wide availability.The Global Wind Energy Council (GWEC) in their 2020 global wind report suggests that the global wind power must triple over the decade to avert the most devastating effects on climate change and, keep global warming well below 2 ◦ C [1]. Wind plants provide advantages in terms of economies of scale, increasing the amount of power that can be generated from a given area, reducing access constraints to individual turbines, and reducing length of interconnecting cables, reducing operation and maintenance costs [2]. These economies of scale, in most cases, enforce close turbine installations in a wind plant and, this leads to increased power density, cause aerodynamic interactions, known as wakes, between operating turbines and could negatively impact on plant power production [2]. This negative effect results from deficits in wind velocity available at the hub of each turbine due to its interaction with wakes from turbines around

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Discussion

Conclusion