bluuebunny/crossref_metadata_2025 huggingface dataset:
Airborne wind energy systems flying optimal trajectories in turbulent wind using flight path tracking
Authors: Crismer J-B , Haas T , Duponcheel M , Winckelmans G
Published: June 2024

Airborne Wind Energy Systems (AWES) consist of tethered wings harvesting power from the wind. Rigid-wing (aircraft) pumping-mode AWES are considered here: they generate power during the reel-out phase and consume a fraction of this power during the reel-in phase. Those devices fly complex trajectories that require advanced control strategies. In the present work, we aim to develop a Large Eddy Simulation (LES) framework and improve the fidelity of existing models. The toolbox AWEbox is used for reference trajectories generation and control. Here the device is operated with a closed-loop control using a 6-DOF aircraft model. The aircraft is modeled using an actuator line (AL) for the wing, and the effects of the control surface are incorporated using their geometry and lift slope. The AL-based model is used to assess the robustness of the nonlinear model predictive controller against turbulence and to compare the performance between idealized conditions in AWEbox and turbulent wind conditions in the LES. The controller demonstrates high efficiency in tracking the reference trajectory and extracting the maximum power, even at high turbulence levels.
Numerical Prediction of Tonal Aeroacoustic Noise Produced by Small Wind Turbines
Authors: Zilstra Alison , Johnson David A.
Published: June 2024

The aeroacoustic design of small wind turbines (SWTs) can be challenging due to the possibility of the low Reynolds number (Re) flow over the blades generating tonal noise. The numerical prediction of this tonal noise using computational aeroacoustics can improve the understanding of the flow mechanisms behind the tonal noise to improve SWT blade design. In this study, wall-resolved incompressible large eddy simulation (LES) and the Ffowcs-Williams and Hawkings (FW-H) acoustic analogy are applied to a low Re airfoil, SD 7037, at Re = 4.1 × 104 to assess the ability of this method to predict tonal noise. The tonal prediction at 1° angle of attack aligned with experimental measurements and further analysis confirmed that the Kelvin-Helmholtz (K-H) rolls in the suction side laminar separation bubble (LSB) are the source of the aeroacoustic tone. The tone is due to the K-H rolls passing the trailing edge of the airfoil, and a secondary tone intermittently appears due to a 3D instability in the K-H roll. The accurate prediction of tonal noise using LES and FW-H opens the possibility of incorporating this method into the aeroacoustic design of low Re airfoils used for SWTs.
Dynamic stall of vertical-axis-wind-turbine rotor blades equipped with Gurney flaps and vortex generators
Authors: Ivanković Marin , Manolesos Marinos , Jentzsch Marvin , Kozmar Hrvoje , Nayeri Christian Navid
Published: June 2024

There are many important aerodynamic phenomena on vertical axis wind turbines. Particularly relevant is flow separation that causes structural fatigue and adversely affects self-starting characteristics of VAWTs at lower wind velocities. Passive flow-control devices on VAWTs rotor blades have been commonly studied to mitigate these adverse characteristics. While there are many studies on this topic, the dynamic stall characteristics of VAWTs rotor blades equipped with Gurney flaps (GFs) and vortex generators (VGs) are not completely clear. It is accordingly the goal of the present study to investigate the aerodynamic performance of the NACA 0021 airfoils in the angle of attack range from 0º to 360º. The experiments were performed in a wind tunnel using rotor blade equipped with VG and GF devices. Experimental results encompass aerodynamic force and moment coefficients of the NACA 0021 airfoil equipped with VGs and GFs. These devices proved to improve the aerodynamic characteristics of the NACA 0021 airfoil and to reduce the adverse effects of flow separation.
Critical design load case fatigue and ultimate failure simulation for a 10-m H-type vertical-axis wind turbine
Authors: Moore K R , Brownstein I D , Ross H K
Published: June 2024

While previous studies investigating critical vertical-axis wind turbine (VAWT) design load cases have focused on large and relatively flexible Darrieus designs, the bulk of current commercial products seeking certification fall in the relatively small, stiff, H-type configuration. Understanding the critical design load case impacts for both fatigue and ultimate failure for this size and type of VAWT is imperative for certification and to help break the cycle of historical VAWT failures. A reevaluation of each of the design load cases specified in IEC 61400-1 using the Offshore Wind ENergy Simulator (OWENS) validated aero-servo-elastic software is conducted for both fatigue and ultimate failure contributions. Several design load cases previously thought negligible may have high enough fatigue damage rates for H-VAWTs to warrant more careful consideration; these cases include parked, extreme wind shear, and direction change with gust. Additionally, full operation stop-start-stop cycles, which historically have not been a part of the standards, may contribute fatigue damage similar to other normal design load cases. In light of these potentially critical conditions, and the sizes of many of the current H-VAWT designs falling in the IEC 61400-2 small wind turbine standard, the standard may need to be expanded to enable design success of certified H-VAWT systems.
Investigating data-driven surrogates for the Ainslie wake model
Authors: Morabito Niccolò , Quaeghebeur Erik , Bliek Laurens
Published: June 2024

Efficient and accurate calculation of wind turbine wakes are central to the design and analysis of wind farms. We present the promising results of an investigation into machine learning techniques for creating computationally efficient surrogates of the Ainslie wake model, as a computationally accessible stepping stone to more complex models. We have compiled an extensive dataset comprising 8600 wake fields, and explored a diverse range of techniques. Among these, the most promising techniques are regression decision trees (RDTs) and Fourier-expanded multi-layer perceptrons (FEMLPs) which have proven to be very effective for image applications. Even with smaller training sets, acceptable results are achieved, offering a feasible balance between size and performance. Both RDTs and FEMLPs excel in interpolation, while FEMLPs particularly showcase robust extrapolation capabilities. Visual comparisons show that RDTs outperform FEMLPs in terms of the smoothness of the generated wake fields. All techniques create surrogates that are at least six orders of magnitude faster than the Ainslie model implementation. The investigation results in a flexible pair of turbine wake surrogate models which are extremely fast and achieve high performance with a reasonable training time. Their generic nature makes them promising candidates for creating effective surrogates for more complex wake models.
Design for Repowering of Wind Farms: An Initial Framework
Authors: Bouzolin Daniel , Settelmaier Kyle , Todd Griffith D.
Published: June 2024

The need for clean and cost-effective energy sources is more pertinent than ever. Wind energy positions itself as a global contender in this role, offering a cost-effective and environmentally-friendly energy option. Furthermore, the wind energy industry is already starting to see numerous wind farms reaching 20+ years of life that require either repowering or decommissioning decisions to be made. Repowering offers many potential economic and sustainable benefits; however, many operators are faced with challenging decisions regarding whether to repower and how to optimally repower. This paper aims to address these challenges by introducing a novel comprehensive framework, known as “Design for Repowering”. In Design for Repowering, wind farms of the future would be designed with planned repowering in mind. Through integration of multiple criteria, including health monitoring/sensors, digital twins, and social/environmental factors, we aim to address open questions about repowering, such as the optimal timing, strategy, and economics of repowering decisions. Furthermore, the framework is applied to several case studies, illustrating its potential for solving some of the long-term challenges expected in the future of wind energy.
Multidisciplinary Wind Farm Electrical Infrastructure Optimization
Authors: Rodrigues Rafael Valotta , Rua Juan-Andres Perez
Published: June 2024

During the construction stage of a wind farm, it is paramount to consider which layouts are the most efficient. Recent literature has found that optimization of the annual energy production is not necessarily driven by the same factors as other economic metrics, such as the internal rate of return. One parameter that makes this particularly true is the electrical cable length and layout, which affect both the cash flow of the project and the investments. While placing turbines far from each other is beneficial to mitigate the wake effect, the capital expenditures associated with the longer cables affects economic metrics. On the other hand, even though placing turbines close to each other reduces cable expenses, wind turbine mechanical loads are challenging to determine from wake effects. This work investigates trends between annual energy production, internal rate of return, electrical cable layout, and turbine components degradation due to mechanical loads. Results point towards corroborating recent literature, finding financial opportunities to explore tighter layouts with shorter electrical cables.
Vertical axis wind turbine wake steering by pitched struts and blades
Authors: Ribeiro André F. P. , Ferreira Carlos S. , Casalino Damiano
Published: June 2024

Vertical axis wind turbines (VAWTs) have been identified as a technology that, in association with wake steering, can increase power density of wind farms. In this study, we validate a free wake method for VAWT wake prediction, which leads to satisfactory results. We then use this method to simulate wake steering by means of fixed pitched blades and struts. We demonstrate that combining pitched wakes and struts can lead to very advantageous wake behavior, but only when the interactions between the tip vortices are taken into account. The possibility to inject more high momentum flow into the wake while moving the vortex system away from the next turbine could make pitched blades and struts a powerful tool for future wind farms.
Modeling of Blockage and Wake Effect: Comparison with Field data
Authors: Maheshwari Priyank , Haize Julien , Pallud Maxime
Published: June 2024

We apply engineering approaches for estimating the induction zone in front of a wind turbine and escalating to the global blockage at wind farm and cluster of farms scale as well accounting for wind farm wake. The methods include the vortex cylinder model and the self-similar model for blockage, and Jensen and Eddy-viscosity models for the wake estimation. To calibrate each model, Reynold Average Navier-Stokes with Actuator disc simulations are employed. Every model’s efficacy is assessed in comparison to the validation data of an operated wind farm in Scotland with more than 100 turbines of 10 MW each. We also examine the widely used process within the wind industry for transferring the application of calibrated wake and blockage models from one wind farm. According to our simulation analysis, blockage causes sideways acceleration and upstream slowdown. This also result in a gradient in the power produced by each turbine on the farm, which, if not properly accounted for, appears to be a wake model constraint. Furthermore, the response of different turbine type in another environment is not effectively predicted by the blockage and wake model, which is based on a particular turbine type and environment.
How do wind farm blockage and axial induction control interact?
Authors: Bossanyi Ervin , Bleeg James
Published: June 2024

Wake losses significantly reduce wind farm output, but wind farm flow control (WFFC) can substantially reduce these losses, using wake steering (yawing upstream turbines) and/or axial induction control (reducing turbine power and thrust to weaken their wakes). Previous work shows that ignoring wind farm blockage in traditional wake models represents a prediction bias of similar order to the gains achievable with WFFC. Axial induction control works by changing turbine thrust, which is also the cause of blockage; this raises the question of how the two effects interact. Induction control can more than compensate for any loss due to blockage, but here we investigate the relationship further. Induction control reduces turbine thrust coefficients to reduce wake losses, but this should also reduce blockage, suggesting that induction control might achieve higher gains in practice than predicted with blockage effects ignored. An engineering model for blockage effects was added to the wind farm code LongSim, and steady-state gains calculated for a well-known offshore wind farm, with and without blockage. The results confirm that the power gains are indeed higher if blockage is modelled. These results are corroborated by comparisons against RANS (Reynolds-Averaged Navier Stokes) simulations, in which blockage effects are implicitly modelled.
Graph-based Deep Reinforcement Learning for Wind Farm Set-Point Optimisation
Authors: Sheehan H , Poole D , Silva Filho T , Bossanyi E , Landberg L
Published: June 2024

Wake steering is a form of wind farm control in which upstream turbines are deliberately yawed to misalign with the free-stream wind in order to prevent their wakes from impacting turbines further downstream. This technique can give a net increase in power generated by an array of turbines compared to greedy control, but the optimisation of multiple turbine set-points under varying wind conditions can be infeasibly complex for traditional, white-box models. In this work, a novel deep reinforcement learning method combining the standard Deep Deterministic Policy Gradient algorithm with a graph representation of potential inter-turbine wake connections was trained to apply wake steering to an array of nine turbines under varying wind directions. The method demonstrated strong performance for wind directions with large potential farm power gains. A steady-state wind farm solver was used, employing a “quasi-dynamic” approach to sampling wind directions, to achieve an additional 47 MW (6.5%) power over four wind directions compared to greedy control.
An international benchmark for wind plant wakes from the American WAKE ExperimeNt (AWAKEN)
Authors: Bodini N , Abraham A , Doubrawa P , Letizia S , Thedin R , Agarwal N , Carmo B , Cheung L , Corrêa Radünz W , Gupta A , Goldberger L , Hamilton N , Herges T , Hirth B , Iungo G V , Jordan A , Kaul C , Klein P , Krishnamurthy R , Lundquist J K , Maric E , Moriarty P , Moss C , Newsom R , Pichugina Y , Puccioni M , Quon E , Roy S , Rosencrans D , Sanchez Gomez M , Scott R , Shams Solari M , Taylor T J , Wharton S
Published: June 2024

This article introduces the first benchmark study within the International Energy Agency Wind Task 57 framework, focusing on wind plant wakes. Leveraging data from the American WAKE ExperimeNt (AWAKEN), the benchmark aims to assess the accuracy of simulation tools in modeling wind plant wakes and their impact on the downstream flow under diverse inflow conditions. The AWAKEN field campaign, conducted in Oklahoma from 2022 to 2024, provides unprecedented observations of wind plant-atmosphere interactions, thus offering a large dataset to validate numerical models of different complexity. The benchmark will include three phases—code calibration, blind comparison, and iteration—allowing participants to refine their numerical models based on the feedback from the benchmark team. This article describes the benchmark case study selected from observations providing details on atmospheric conditions, wake evidence, and wind turbine operation. The benchmark’s structure and timeline, along with the expected publication of results, are discussed as well. This collaborative effort aims to enhance the accuracy of wind plant wake simulations, thus contributing to the improvement of wind energy production estimates.
Land-based wind plant wake characterization using dual-Doppler radar measurements at AWAKEN
Authors: Abraham Aliza , Hamilton Nicholas , Bodini Nicola , Hirth Brian , Schroeder John , Letizia Stefano , Krishnamurthy Raghavendra , Newsom Rob , Moriarty Patrick
Published: June 2024

Wind plant wakes have been shown to persist for tens of kilometers downstream in offshore environments, reducing the power output of neighboring plants, but their behavior on land remains relatively unexplored through observation. This study capitalizes on the unique and extensive field data collected for the American WAKE ExperimeNt (AWAKEN) project underway in northern Oklahoma. X-band dual-Doppler radars deployed at this site measure wind speed and direction at 25-m and 2-min resolution within a 30-km range, capturing the interactions between three neighboring wind plants. These measurements show that the wake of one wind plant extends at least 15 km downstream under easterly wind and stable atmospheric conditions. Though the wake wind speed increases within the first 10 km, it plateaus at 90% of the freestream wind speed. The spanwise velocity distribution within the wake initially shows the clear signature of the wind plant layout, which is smoothed as it propagates downstream, indicating spanwise momentum transfer is a key mechanism in wind plant wake development and recovery. These findings have important implications for wind plant siting decisions and resource assessments, and provide insights into atmospheric interactions at the wind plant scale.
LES on wind turbines by comparison of Vortex Particle Method and Finite Volume Method codes
Authors: Roperch M , Mulakaloori V H C , Bénard P , Pinon G
Published: June 2024

The aim of this paper is to compare two different computational methods that analyse the flow around wind turbine using Large-Eddy-Simulations (LES). The first method uses a three-dimensional unsteady Lagrangian Vortex Particle method (VP) associated to a lifting-line (LL) approach providing radial loads, integrated thrust and power coefficients, circulations and angle of attack across the turbine blades. The second method solves the incompressible Navier-Stokes equations with the classical Finite Volume (FV) method coupled to the Actuator Line (AL) method to model the rotor blades. Both methods are compared by means of a benchmark consisting in a single full-scale NREL5MW wind turbine and the results are thus compared to Martínez-Tossas et al (2018). The comparisons involve loads, angle of attack and velocity along the blade. Wakes downstream of the turbine are analysed via the evolution of flow fields as mean velocity and vorticity. Results are found to be in good agreement with the verification case. A comparison is also performed on the evaluation of the numerical cost, precision and efficiency of both computational methods.
Wake Effects in Lower Carbon Future Scenarios
Authors: Lundquist Julie K. , Rosencrans David J. , Roberts Owen , Lopez Anthony , Mai Trieu
Published: June 2024

In August 2022, the U.S. Congress passed the Inflation Reduction Act (IRA), which intended to accelerate U.S. decarbonization, clean energy manufacturing, and deployment of new power and end-use technologies. The National Renewable Energy Laboratory has examined possible scenarios for growth by 2050 resulting from the IRA and other emissions reduction drivers and defined several possible scenarios for large-scale wind deployment. These scenarios incorporate large clusters of turbines operating as wind farms grouped around existing or likely transmission lines which will result in wind farm wakes. Using a numerical weather prediction (NWP) model, we assess these wake effects in a domain in the U. S. Southern Great Plains for a representative year with four scenarios in order to validate the simulations, estimate the internal wake impact, and quantify the cluster wake effect. Herein, we present a validation of the ”no wind farm” scenario and quantify the internal waking effect for the ”ONE” wind farm scenario. Future work will use the “MID” scenario (more than 8000 turbines) and the “HI” scenario (more than 16,000 turbines) to quantify the effect of cluster wakes or inter-farm wakes on power production.
Measurements and modelling of the wind speed profile in the induction zone of an offshore wind turbine
Authors: Cleve Jochen
Published: June 2024

Large wind turbine rotors require the measurement of the wind speed profile across the whole rotor for accurate performance and load assessments. Acquiring these measurements close to the rotor - in the induction zone - has the advantage of high correlation between the wind at the measurement location and the wind that acts on the rotor. In this paper measurements of the wind speed field upstream of a multi-megawatt wind turbine are presented and compared with a simple model of the deceleration of wind speeds in the induction zone. The measurements are taken at several distances in front of the rotor and include the full shear profile across the rotor, which is incorporated into the model by scaling the radial induction field with a free stream shear profile. The model captures the observations very accurately if a mirror turbine is included to model the effect of the ground plane. This model validation provides further evidence of the feasibility to conduct power curve verifications with measurements in the induction zone.
Further improvements to the double-Gaussian wake model
Authors: Zengler C P , Braunbehrens R , Tamaro S
Published: June 2024

In onshore wind farms, the turbine-to-turbine distance can be in the order of three diameters or less. In these circumstances, traditional wake models, developed for the far wake region, lose accuracy. The double-Gaussian wake model is an approach to extend algebraic wake modelling to the near wake region, where the wake is not yet self-similar. In this work, the double-Gaussian wake model is advanced by performing large eddy simulations of a reference wind turbine and a scaled wind turbine model to investigate how the thrust coefficient and the turbulence intensity influence the near wake and wake recovery. Results show that in the near wake the maximum velocity deficits move towards the outer part of the rotor with an increasing thrust coefficient. Thus, a thrust coefficient dependent position of the double-Gaussian peaks is proposed. In addition, a wake expansion function including turbulence intensity and thrust coefficient is tuned. The new model proves to be capable of predicting the wake of different turbine models under various ambient conditions and operational states.
Profit-optimal data-driven operation of a hybrid power plant participating in energy markets
Authors: Anand A , Petzschmann J , Strecker K , Braunbehrens R , Kaifel A , Bottasso C L
Published: June 2024

An energy management system (EMS) is formulated for a hybrid power plant (HPP), consisting of a wind power plant and battery storage plant, participating in bidding stages in the German energy market. The EMS utilizes supervisory control and data acquisition (SCADA) measurements from the site to improve power forecast from the wind power plant. First, the measurement data are used together with numerical weather prediction data to accurately forecast local wind conditions. Second, the measurement data are used to adapt a baseline engineering wake model that gives the total wind power generation for a given input wind condition. The EMS also uses an online cyclic damage minimization approach to accurately balance the battery damage cost against the revenue obtained by market bidding. An HPP controller is formulated to ensure proper tracking of optimal set-points. When compared with standard formulations, the proposed approach shows an accurate estimation and balancing of revenue and costs and a significant reduction in the power deviation penalty, which leads to significantly higher overall profit.
Effects of wind turbine rotor tilt on large-scale wind farms
Authors: Kasper Jens H. , Stevens Richard J.A.M.
Published: June 2024

Recent studies have explored the use of rotor tilt adjustments to reduce wake losses in wind farms. While downward wake deflection in aligned wind farms has shown promise for significant power gains, the impact of wind farm layout on the effectiveness of tilt strategies is not yet fully understood. Additionally, the effect on downstream farms remains unclear. Our large eddy simulations reveal that a rotor tilt of 20 degrees significantly reduces wake losses in aligned wind farms. For wind farms with 8 turbine rows, we observe an overall increase in wind farm productivity of up to 11%. However, tilting the rotors may decrease power production in staggered wind farms, where wake losses are inherently lower due to the increased spacing between turbines. Our findings also suggest that a downstream wind farm might benefit from an upstream farm implementing rotor tilt, although this advantage is primarily observed in the first row of the downstream farm.
Gust-detection from velocity azimuth display Doppler wind lidar profiling at the WiValdi research park.
Authors: Wildmann N , Thayer J D , Detring C , Päschke E
Published: June 2024

This study presents a new retrieval for gusts from Doppler wind lidar (DWL) velocity azimuth display (VAD) scans. The scanning mode which is presented allows for retrieval of mean wind speed, vertical wind speed, turbulence kinetic energy and peak gust speed with a single strategy. It is validated against sonic anemometer measurements at 90 m above ground and a reference DWL gust mode with faster scanning speed at the boundary-layer field site Falkenberg of the DWD. The new algorithm is then run on a multi-year dataset to obtain statistics of gusts at the WiValdi research park. It enables analyses not only at hub height, but also up to 500 m aloft with a reasonable availability above 60%. A case study of a convective cold pool shows the potential of the method to detect and analyze the vertical and horizontal structure of gusts with the proposed method. It highlights the importance of measurements throughout the boundary layer to understand the related physical processes to wind ramps and gusts.
FLOW-Alaiz benchmark for coupled terrain and array interaction flow models. Baseline Results
Authors: Sanz Rodrigo J , Oxley G , Tobias Olsen B
Published: June 2024

The FLOW-Alaiz benchmark is established to enhance flow models in complex terrain, building on insights and datasets from previous IEA Task 31 benchmarks around the same test site. The new benchmark aims to create a composite validation dataset by gathering measurements from different periods, notably, the New European Wind Atlas (NEWA) ALEX17 experiment and the Alaiz Site Calibration (SC) campaign. The overall study focuses on wind conditions relevant to siting, power performance, and energy yield prediction. Initial results use industry-standard flow models as baselines such as SiteFlow and PyWAsP/PyWAsP-CFD, all in neutral steady-state conditions. Public datasets, documentation, and evaluation scripts are available in the FLOW-Hub repository to provide transparency on the evaluation methodology while private data is kept on SGRE premises for blind testing. Baseline results focus on cross-predictions and wind profiles for the North and South sectors. Cross-predictions reveal challenges in the NEWA case due to large elevation differences and complex flow interactions in the valley, while SC campaigns show better performance in more realistic siting conditions. Wind profiles for neutral conditions generally align with expectations with main limitations in the wake of flow-separation and forest canopy zones. A comparison with vertical profiles from the ALEX17 Diurnal Cycles benchmark highlights potential improvements from high-fidelity mesoscale-to-microscale modeling, revealing distinct variations in wind shear and profile characteristics when stability is used to categorize the atmospheric conditions.
Comparing methods for coupling wake models to an atmospheric perturbation model in WAYVE
Authors: Devesse Koen , Stipa Sebastiano , Brinkerhoff Joshua , Allaerts Dries , Meyers Johan
Published: June 2024

As offshore wind farms grow in size, the blockage effect associated with the atmospheric gravity waves they trigger is expected to become more important. To model this, recent research has produced an Atmospheric Perturbation Model (APM), which simulates the mesoscale flow in the atmospheric boundary layer at a low computational cost compared to traditional methods. However, as a simplified reduced-order model, it can not resolve individual turbine wakes, and has to be coupled to an engineering wake model to predict farm power output. Over the years, three coupling methods have been developed, and been combined into the open-source framework WAYVE. This paper compares them, discussing both their theoretical validity and their performance. For the latter, we validate the velocities and power outputs predicted by WAYVE against 27 LES simulations. We find that the velocity matching (VM) and the pressure-based (PB) methods perform the best. Of these two, the VM method is more consistent with the APM output, while the PB method has a significantly lower computational cost.
Enhanced Wind Farm Maintenance Scheduling Including Wake Effects
Authors: Santos Pereira R B , Bussolati C , Fonseca F C , Lourenço A , Medda R
Published: June 2024

With the expansion and dissemination of offshore wind farms, the costs associated with asset maintenance and operation become ever more relevant. Among maintenance activities, preventive interventions represent a significant share of the costs and, as opposed to corrective interventions, may be calendarized according to the farm operator’s strategy. In an offshore wind farm there is often aerodynamic interaction between different machines, namely as a given upstream turbine extracts energy from the wind, it will necessarily reduce the energy available for a turbine that is downstream in the farm. This is broadly referred to as wake effects. The relative proximity of turbines within a farm means such an interaction results in lower energy yield for downstream turbines. Maintenance activities require the shutdown of the turbine, hence the turbine under maintenance effectively produces no wake effect. It follows that, depending on weather conditions, the sequence of wind turbines to be deactivated for large preventive maintenance campaigns may impact the total energy production of an offshore wind farm, especially when the wind direction is considered. The present study investigates the potential of incorporating wake effects in the scheduling of offshore wind farm maintenance activities, considering a reference farm layout and using historical climate data for a real offshore site. Different maintenance scenarios are considered, including distinct maintenance vessels and different intervention criteria. Results show there is a small but relevant potential gain in energy yield when the maintenance scheduling is determined including wake effects, with annual energy production increase of up to 0.18% for the parametric values considered.
Need For Speed: Fast Wind Farm Optimization
Authors: Sarcos Maria , Quick Julian , Hahmann Andrea N. , Alonso-De-Linaje Nicolas G. , Davis Neil , Friis-Møller Mikkel
Published: June 2024

The Wind in my Backyard (WIMBY) project is developing a web interface to aid communities in siting wind energy projects. As part of this siting tool, users will be able to find realistic wind farm layouts for any proposed site in Europe, given certain constraints. When designing this tool, there arises a need for speed: realistic layouts must be designed in computational times that are appropriate for a web interface. In this study, we compare two optimization algorithms: a gradient-based algorithm, referred to as stochastic gradient descent (SGD), and a gradient-free method, referred to as smart-start. The trade-offs between the optimal energy yield and optimization computational time are characterized via a parameter sweep, considering a site in Denmark. This analysis considered farms with 10, 25, and 50 turbines. We find that smart-start yielded the best results for very short computational times, and that SGD yielded layouts with higher energy yields when considering larger computational times.
Advancing weather predictions for offshore wind farm maintenance through deep learning
Authors: Dighe V. V. , Liu Y.
Published: June 2024

Historical met-ocean data are widely used in the decision support tools to evaluate different operations & maintenance (O&M) strategies for offshore wind energy. Although effective, they are often very limited, which may not be able to represent prolonged offshore weather conditions at the wind farm sites. This hinders their application to the O&M planning. In this paper, a deep learning approach is proposed to build up the stochastic weather generator, in which the long short-term memory neural network is leveraged to simulate wind and wave time series data. The neural network is trained using the (limited) historical met-ocean dataset to accurately capture the statistical characteristics of wind and wave conditions. The results demonstrate the effectiveness of the proposed stochastic weather generator in delivering both open-loop and closed-loop forecasting for wind speed and significant wave height data, thereby supporting both corrective and preventive maintenance activities. The case study reveals that the open-loop forecast excels in short-term hourly met-ocean parameter predictions, while the closed-loop forecast proficiently captures the met-ocean patterns within a predefined window. Although the closed-loop forecast for wave parameters generally follows the measurements trend, it diverges from the actual measurements; a discrepancy likely due to the complex spatial-temporal dynamics of waves not completely captured by the LSTM model. The proposed LSTM model, considered as a complementary but connected solution, is able to enhance the utility of the limited historical data in O&M planning.
The global blockage effect of a wind farm cluster - an LES study
Authors: Meijer J , Steinfeld G , Vollmer L , Dörenkämper M
Published: June 2024

The interaction of wind farm clusters with the atmospheric flow is complex. It comes along with phenomena that have still not been fully understood in detail. However, having an understanding of the flow is a prerequisite for the derivation of models that can accurately and with limited computational resources replicate the most prominent features of the flow. This study exploits large-eddy simulations (LES) to create a better understanding of the wind farm cluster blockage under a set of different atmospheric conditions. The specific wind farm cluster consists of three wind farms, with a relatively narrow gap between the two northernmost wind farms. Results reveal that under conventionally neutral boundary layers, the induction zone relatively large is when there is a low atmospheric boundary layer height with a strong temperature inversion. In our LES study, wind speed is reduced between 2% and 4% 2D upstream of the front row of the wind farm, while inside the gap of the wind farm cluster, there is an acceleration of the wind speed. Comparatively, blockage for a solitary row or single wind turbine is similar and smaller than for a whole cluster. On average, turbines in the front row of a cluster produce 5.1% less power than a single turbine.
Enhancing Wind Farm Efficiency Through Active Control of the Atmospheric Boundary Layer’s Vertical Entrainment of Momentum
Authors: Ferreira Carlos , Bensason David , Broertjes Thomas J. , Sciacchitano Andrea , Martins Flavio A. C. , Ajay Adhyanth Giri
Published: June 2024

In contemporary wind farm design, the primary focus has traditionally been on reducing wake interference to optimize energy capture from horizontal wind flows. However, with the scaling up of wind farms, their interaction with the Atmospheric Boundary Layer (ABL) evolves, making vertical entrainment the main mechanism for the exchange of momentum and energy. This study introduces a methodical approach to augment the efficiency of large-scale offshore wind farms by actively controlling this vertical entrainment of momentum within the ABL. The strategy involves the precise engineering of advection fluxes to alter wind flow dynamics, utilizing turbines as effective vortex generators, toward a process of ”regenerative wind farming.” This setup aims to create a vorticity and vertical flux system akin to those observed in highly unstable ABLs. Expanding upon previous studies that focused on single Vertical Axis Wind Turbines (VAWTs), our research explores the implementation of multi-rotor systems equipped with lift-generating wings. These systems are designed to exert forces perpendicular to the prevailing wind direction, thus creating trailing vortices and directing the flow orthogonally for improved vertical advection. This research is part of a comprehensive investigative framework that combines experiments and multifidelity simulations. The current study extends those findings to wind farm simulations, aiming to assess the impact of ABL control on a full wind farm scale. The first part of the work validates an established analytical wind farm performance model against real wind farm data for thirty-one wind farms in the North Sea and Baltic Sea. The results confirm the predicted trend of decreased performance with increased wind farm size and density. The model is used to calculate the performance of a wind farm for varying regimes of vertical entrainment due to the creation of large-scale circulatory systems. The results are compared against 3D vortex simulations of the full wind farm in ”regenerative wind farming” mode. Our results demonstrate a notable improvement in wind speeds at the turbine hub height and the potential to double the feasible density of wind farms without compromising efficiency compared to traditional setups. These findings suggest a promising pathway towards a more sustainable and profitable future in wind energy, achieved through the strategic manipulation of ABL momentum, regenerating the energy in the wind farm.
Prediction of the Slagging and Fouling of Indonesian Coal with Hard Wood from Central and East Java
Authors: Suyatno  , Ghazidin H , Samudra H E , Ruhiyat A S , Prayoga M Z E , Darmawan A , Prabowo
Published: June 2024

Indonesia as an agricultural country has abundant biomass potential, especially wood waste in Java. The prospect of co-firing is considered ideal to overcome the problem of coal use in boilers. This is also in line with supporting the Indonesian government program in increasing the use of renewable energy. Samples of coal co-firing with wood waste from Central Java and East Java were selected for this study. Furthermore, blending between coal and wood biomass from Central and East Java with a composition ratio of (25%:75%) and (50%:50%). Furthermore, it is predicted based on the risk tendency of slagging and fouling. The risk of slagging, fouling, abrasion, and corrosion with theoretical index. In general, increasing the composition of coal blending with hardwood increases the tendency of slagging and fouling. However, blending coal with hardwood from Central Java at a mixture of (25%:75%) can be recommended because it has a low risk of slagging and fouling.
Garden Waste for Sustainable Development in Indonesia
Authors: Supriatna N. K. , Aminuddin  , Zuldian P. , Hesty N. W. , Aprianti N. , Handayani H. , Alamsyah R. , Surjosatyo A.
Published: June 2024

The world continues to grapple with the multifaceted challenges of waste management. Indonesia faces a growing challenge: garden waste makes up 13% of unmanaged waste (4.2 million tons in 2022). With a legal mandate for extensive green spaces, this waste stream is likely to increase. This study assesses the potential of garden waste across Indonesia and explores utilization technologies. We explore options for sustainable utilization by analyzing existing waste management data and leveraging relevant research. Preliminary findings suggest substantial garden waste volume with potential for biofuels and other valuable products, contributing to low-carbon development in Indonesia.
Influence of photoanode pre-heating treatment temperatures prior to dye immersion process on dye-sensitized solar cells photovoltaic performances
Authors: Hatta Mohammad , Azizah Evi Nur , Rabelsa Gita , Hidayat Jojo , Pranoto Lia M. , Shobih  , Budiawan Widhya , Ardy Nugroho Ferry Anggoro , Firdaus Yuliar
Published: June 2024

Several efforts of photoanode treatment, such as surface modification, doping introduction, defect engineering, and heating treatment, have been developed to improve the photovoltaic performances of dye-sensitized solar cells (DSSC). Amid these options, alternative routes that require less demanding conditions are highly sought. Here we introduce an effective and convenient, non-vacuum low-temperature procedure to enhance the DSSC’s photovoltaic performances by photoanode pre-heating treatment prior to the dye immersion process. The experimental result showed that pre-heating treatment at 120 °C improves the efficiency and short-circuit current by about 28.4% and 19.1%, respectively. The conducted transient photovoltage measurements revealed that the increase of pre-heating temperatures leads to a longer electron lifetime and higher charge collection efficiency.
Mapping of Household Photovoltaic Research in Indonesia: A literature review using bibliometric analysis
Authors: Damayanti S , Dinaseviani A
Published: June 2024

This research aims to undertake a bibliometric study on household photovoltaics within the Indonesian context. The objectives include mapping the global trends in publications related to household photovoltaics, mapping the trends within the Indonesian context, analyzing the performance of authors, affiliations, sources, and papers, identifying research hot topics, and determining research themes. This study utilized 122 Scopus-indexed articles. The findings reveal an increasing trend in the number of publications on household photovoltaics both globally and within the Indonesian context. In the Indonesian context, Tarigan, E stands out as the most relevant author, the University of Indonesia emerges as the most relevant affiliation, IOP Conference Series: Earth and Environmental Science leads as the most relevant source, Renewable Energy takes the lead as the most influential source, and article title ’Energy and Economic Losses Caused by Dust on Residential Photovoltaic (PV) Systems Deployed in Different Climate Areas,’ stands out as the most influential. This study identified five themes as hot topics (Photovoltaic Quality and Performance, Economic Analysis of Photovoltaic Systems, Net Metering and Inverter of Rooftop Photovoltaic in Indonesia, Monitoring System of Residential Solar Panels, and Technical and Economics of Solar Power Plants) and four research themes (The Adoption of Household Rooftop Photovoltaics and Influencing Factors, Design and Planning for Rooftop Solar Panel Deployment, Rooftop Photovoltaics Adoption and Renewable Energy Targets, and Economic Analysis of Rooftop Photovoltaic).
2D Geological Structure Identification in Mount Ciremai Geothermal Area using the GGMplus Data.
Authors: Yasmin H S , Pirzada S J , Sahroni T R , Soekarno H , Pranoto B , Puspa A D , Alfisah
Published: June 2024

West Java’s Mount Ciremai holds substantial geothermal potential, marked by hot spring manifestations, which can be an alternative energy source. This research utilizes the GGMplus satellite gravity method, employing First Horizontal Derivative (FHD), Second Vertical Derivative (SVD), and 2D inversion to analyze the geothermal area’s geological structure and subsurface conditions. The results reveal fault structures, including reverse and normal fault types in Mount Ciremai. Specific details for both the Pejambon and Sangkanhurip lines and the Pejambon and Ciniru lines indicate distinct layers with varying densities (2.4 – 2.7 g/cm3) and depths. These layers comprise pyroclastic flow deposits, andesite-basaltic rock, caprock (clay rock), and a reservoir (sandstone), shedding light on the geothermal potential of this region.
The Role of Thermal and Electrical Energies to Increase the Pepper Quality: A Review
Authors: Rustandi Dadang , Irmansyah  , Wijonarko Sensus , Kurniati Mersi , Maftukhah Tatik
Published: June 2024

Indonesia is one of the most prominent pepper producers and consumers worldwide. Indonesian pepper quality, however, is still low. The pepper’s low-quality problem is caused by the processing that still uses the traditional (conventional) method. This study reviews many techniques that have the potential to improve pepper quality. The review result from the references shows that waiting time (delaying) in the ripening process can increase the pepperine level from 4.33 % to 6.60 %. The pepperine level is the most vital parameter to show pepper quality. However, a more comprehensive result that compares the conventional and non-conventional methods for all kinds of pepper quality parameters still could not be obtained.
Influences of pH control in the organic liquid fertilizer production using MASARO technology
Authors: Abidin A Z , Steven S , Siregar N S , Hutahaean A C , Yemensia E V , Otivriyanti G , Wardani M L D , Mulyono M , Soekotjo E S A , Sasongko N A , Djamal M
Published: June 2024

Indonesia’s food security compels the government to develop food and land intensification as a long-term national program. It cannot be denied that food productivity is closely related to fertilizer demand considering that Indonesia is an agricultural country. However, to date, 86.5% of Indonesian farmers rely on synthetic fertilizers which are adverse to the environment. On the other hand, Indonesia is the 2nd largest food waste producer and most of them are still unprocessed. Therefore, a practical solution to overcome this problem is to offer the application of MASARO technology. This technology can convert 1 kg of degradable waste into 10 L of organic liquid fertilizer so that it can increase agricultural productivity while replacing the role of synthetic fertilizers. In the organic liquid fertilizer production process, pH is an important parameter of the entire fermentation process where the value should be in the range of 3.9-4.2. However, the manual process still requires a long production duration, 28 days, because of pH value overshoot. By implementing a pH control system, the duration of organic liquid fertilizer production can be cut by 57% (from 672.8 hours to 288.6 hours) so the effect is proven can provide optimal and effective fermentation.