Wind turbine power optimisation is usually done with a blade element momentum (BEM) model using tabulated 2D airfoil polars of lift and drag. Current BEM models correct the airfoil polars for 3D crossflow by utilising a method that accounts for the pressure forces but neglects the viscous friction forces. Since swept blade turbines exp...

The aerodynamic losses caused by leading-edge erosion (LEE) on wind turbine blades are caused by damages at scales as small as 50 microns. To study how these minute damages affect the turbulent boundary layer over airfoils, we must have realistic, high-resolution models for testing in wind tunnels and with computational fluid dynamics ...

For wind turbine design optimisation, it is necessary to have a fast model to evaluate the loads at each design iteration. However, current IEC fatigue and ultimate load cases require time-dependent aeroelastic simulations that are too computationally expensive. Therefore, Barlas, Göçmen, and Riva (2024) investigate how inexpensive mac...

Leading-edge erosion (LEE) of wind turbine blades gradually degrades their aerodynamic performance. However, wind farm developers neglect the effect of LEE on wakes when estimating wind farm production. Therefore, Visbech et al. (2024) set out to quantify the impact of LEE on energy production with and without including it in the wake ...

The O&M cost of offshore wind turbines accounts for about 25% of the total lifecycle cost– Leading Edge Erosion (LEE) being one of the most critical damage types. O&M repair strategies are often reactive, meaning that repairs are only initiated after the blade damage reaches a particular threshold. However, is this O&M strategy the mos...

A wind turbine is a 20-year investment that slowly pays back. Over time, each turbine component gradually degrades until the day when its “damage budget” is entirely spent and it has reached its end-of-life. Modern wind turbines can be de-rated to comply with grid requirements, and while energy production reduces, so do the loads. We m...

Wind energy production depends on the changing weather conditions. As all wind turbines produce during windy periods, wind energy tends to earn lower market prices than the average producer— commonly measured as the Value Factor (VF). During the last ten years, the share of electricity covered by wind has increased from about 40% to 60...

Production loss due to Leading Edge Erosion (LEE) of wind turbine blades is hard to quantify as erosion develops continuously, and the damage geometry differs for each blade. Having reliable prediction tools, e.g., based on Computational Fluid Dynamics (CFD), would allow wind turbine operators to optimise the blade maintenance schedule...

As wind energy penetration in the US increases, the electricity price is expected to drop due to the so-called merit-order effect (MOE)—wind energy has low operating costs and tends to replace conventional generation. A recent paper compares the MOE in two US markets with different wind energy penetration, using advanced regression mod...

Despite the significance of rough-wall turbulent flows in many engineering applications (e.g. leading-edge erosion of wind turbine blades), we need up-to-date review papers on the topic. However, Kadivar, Tormey, and McGranaghan (2021) give us just that—with more than 500 references spanning 175 years of research, they analyse past and...

Energy systems dominated by wind can have significant day-to-day power variations. One solution may be low-wind turbines with oversized rotors, as they also produce power at low wind speed when conventional turbines stand still. But is it cost-efficient to reduce power variations by increasing the rotors of wind turbines compared to ot...

Quick et al. (2023) present Stochastic Gradient Descent (SGD) in wind farm optimisation and compare it to conventional deterministic gradient-based optimisation. The SGD method estimates the annual energy production using a Monte Carlo simulation that randomly samples the input distributions of atmospheric conditions (wind speed and di...

Graf et al. (2016) present a method for optimally selecting and placing wind turbines to maximise energy production. They use a heuristic optimisation algorithm that combines a hybrid genetic and a gradient-based algorithm, considering various constraints such as distance between turbines and extreme wind conditions. The study conclude...

Is it time to rethink wind farm siting? Could geographical diversity, not just wind speed, be the key to optimising renewable energy? While the current approach to wind farm siting, focused on high wind speed areas, may minimise the cost of energy production, it overlooks the potentially higher costs associated with integrating this va...

The wind industry relies on flow models to estimate wind turbine energy production. Flow models have many non-physical parameters that are not measurable, and model developers determine default values indirectly by calibrating them with large data sets. While the default parameters ensure accurate results on average, experienced users ...

Good wind farm production data is vital for performance evaluations or training machine learning algorithms. But before we use the data, we must identify and remove abnormal data that can introduce unwanted biases. Instead of using a single method to determine all anomalies, Wang et al. (2023) apply specialised methods in succession (b...

A Hybrid Wind-Hydrogen System (HWHS) can perform energy arbitrage to maximise revenue, i.e. produce electricity when the tariff rates are high and hydrogen when the tariff is low. Another operational strategy can be to maximise the production of green hydrogen. When making HWHS investment decisions, the operational objective impacts th...

The relentless reduction of the Cost Of Energy (COE) has made wind energy one of the cheapest sources of electricity. However, as the penetration of renewables in open-market grids increases, it starts to affect the electricity price so that it can be practically zero on windy days. Therefore, to become profitable, modern wind energy s...

Green hydrogen and electrolysis technology will be central to the future energy market, but with many competing technologies, it is hard to get an objective overview. However, Nami et al. (2022) provide just that, with a thorough techno-economic comparison of different alkaline (AEC) and solid oxide (SOEC) electrolysis technologies. Na...

Atmospheric boundary-layer flow over heterogeneous surfaces is a multi-scale problem that is impossible to “resolve” by any wind simulation; every level of computational grid refinement brings a new level of surface detail. Therefore, even the most advanced flow model depends upon subgrid-scale parameterisations often derived using ide...

The negative effect of leading-edge erosion on wind turbine production is well known. The repetitive impact of rain droplets on the fast-moving wind turbine blades gradually erodes the surface, causing a loss in aerodynamic efficiency. Without timely repairs, the blade’s structural integrity can eventually become threatened. However, p...

Many countries do not have the renewable energy sources needed to cover their energy demand. Therefore, they may consider importing green energy commodities like hydrogen, methane, methanol or ammonia in an effort to decarbonise. In a new paper, Moritz, Schönfisch, and Schulte (2022) analyse the global cost of producing the four green ...

Energy loss caused by leading edge erosion of wind turbine blades can be significant but is challenging to quantify as measurement uncertainty is high. An alternative to measurements is numerical modelling, which usually requires detailed information not readily available (like airfoil characteristics). In a recent paper, Bak (2022) su...

Wind farm flow models can be ranked according to their “fidelity” level, referring to the degree of sophistication of the underlying mathematical description. When applied within their validation region, these physics-driven models are accurate but will never reach full “real-life” complexity. So, instead of developing models of ever h...

Research indicates that the co-location of electrolysis and offshore wind is cheaper than green hydrogen production onshore. However, Gea Bermúdez et al. (2021) argue that such studies are imperfect as they only consider a limited part of the value chain. Green hydrogen has the potential to provide synergy and flexibility across the en...

To use SCADA data for wind turbine performance evaluation, we must clean the data by removing curtailment, downtime, and other anomalies. However, when eliminating data, there is a risk of introducing unwanted biases and losing the statistical characteristics of the evaluated power curve. A new paper by Morrison, Liu, and Lin (2022) in...

When accessing site conditions for wind turbines, it is typical to apply steady-state “RANS” models to predict average quantities like turbulence intensity and wind shear. However, it may also be helpful to investigate unsteady effects like wake meandering, unstable thermal stratification, and flow separation due to complex terrain. Hi...

“Green” hydrogen is a central part of the IEAs Net-Zero scenario, and the needed build-out of wind turbines and electrolysers is enormous. However, the transition is slow due to the high cost compared to the “grey” alternatives. Electricity accounts for most of the green hydrogen cost, and about 25% of the electricity cost of offshore ...

When the wind speed (WS) is low, the electricity price is high; this is normal in Denmark. Due to our high penetration of wind energy, we often import expensive electricity during low WS periods and export it cheaply when the WS is high, and there is excessive power. Wind turbines traditionally reach their rated power at 13 m/s and cut...

In a recent paper, He et al. (2022) make a cost-benefit analysis of co-locating green hydrogen production on the transformer station of offshore wind farms. They analyse the Levelized Cost of Hydrogen (LCOH) for scenarios where hydrogen production capacity increase from 0% to 100% of the wind farm power capacity and for different shore...