Comparison of offshore wind farm layout optimization using a genetic algorithm and a particle swarm optimizer

This article explores the application of a binary genetic algorithm and a binary particle swarm optimizer to the optimization of an offshore wind farm layout. The framework developed as part of this work makes use of a modular design to include a detailed assessment of a wind farm’s layout including validated analytic wake modeling, cost assessment, and the design of the necessary electrical infrastructure considering constraints. This study has found that both algorithms are capable of optimizing the layout with respect to levelized cost of energy when using a detailed, complex evaluation function. Both are also capable of identifying layouts with lower levelized costs of energy than similar studies that have been published in the past and are therefore both applicable to this problem. The performance of both algorithms has highlighted that both should be further tuned and benchmarked in order to better characterize their performance

A Review of Predictive and Prescriptive Offshore Wind Farm Operation and Maintenance

Offshore wind farms are a rapidly developing source of clean, low-carbon energy and as they continue to grow in scale and capacity, so does the requirement for their efficient and optimised operation and maintenance. Historically, approaches to maintenance have been purely reactive. However, there is a movement in offshore wind, and wider industry in general, towards more proactive, condition-based maintenance approaches which rely on operational data-driven decision making. This paper reviews the current efforts in proactive maintenance strategies, both predictive and prescriptive, of which the latter is an evolution of the former. Both use operational data to determine whether a turbine component will fail in order to provide sufficient warning to carry out necessary maintenance. Prescriptive strategies also provide optimised maintenance actions, incorporating predictions into a wider maintenance plan to address predicted failure modes. Beginning with a summary of common techniques used across both strategies, this review moves on to discuss their respective applications in offshore wind operation and maintenance. This review concludes with suggested areas for future work, underlining the need for models which can be simply incorporated by site operators and integrate live data whilst handling uncertainties. A need for further focus on medium-term planning strategies is also highlighted along with consideration of the question of how to quantify the impact of a proactive maintenance strategy

Experimental Data of Bottom Pressure and Free Surface Elevation including Wave and Current Interactions

From MDPI via Jisc Publications RouterHistory: accepted 2021-09-23, pub-electronic 2021-09-30Publication status: PublishedFunder: Engineering and Physical Sciences Research Council; Grant(s): EP/S000747/1Force plates are commonly used in tank testing to measure loads acting on the foundation of a structure. These targeted measurements are overlaid by the hydrostatic and dynamic pressure acting on the force plate induced by the waves and currents. This paper presents a dataset of bottom force measurement with a six degree-of-freedom force plate (AMTI OR6-7 1000, surface area 0.464 m × 0.508 m) combined with synchronised measurements of surface elevation and current velocity. The data cover wave frequencies between 0.2 to 0.7 Hz and wave directions between 0∘ and 180∘. These variations are provided for current speeds of 0 and 0.2 m/s and a variation of the current in the absence of waves covering 0 to 0.45 m/s. The dataset can be utilised as a validation dataset for models predicting bottom pressure based on free surface elevation. Additionally, the dataset provides the wave- and current-induced load acting on the specific load cell at a fixed water depth of 2 m, which can subsequently be removed to obtain the often-desired measurement of structural loads

Cross-sectorial learning of model testing methodologies aligned to technology TRL

This paper presents a state of the art review of Floating Offshore Wind Turbines (FOWT) tank testing in wave basins from the perspective of understanding how different test methodologies currently deployed can be correlated to the development stage of the design being tested. This approach was already adopted by the wave energy sector, however, for the FOWT sector this is not fully developed, and only briefly mentioned in guidance documents. An open question in the application of aerodynamic loads within wave basin testing is, how complex does it need to be? For wave basin testing facilities, it is important to understand how a test program must be set up to meet the clients’ requirements. The designs being tested may be at different development stages, i.e., different Technology Readiness Levels (TRL) and it is important to understand how the test configuration will impact the clients’ objectives. Three main tank test campaigns will be performed at FloWave Ocean Energy Research Facility using the UMaine VolturnUS-S reference platform developed for the IEA wind 15-MW offshore reference wind turbine. It will be used as a basis for the development of a staged development approach for the FOWT sector. In preparation for these tests, the present paper explores and evaluates the appropriateness, with relation to TRL, of different methodologies for including aerodynamic loads in wave basin testing of FOWT

Hydrodynamic performance of an innovative semisubmersible platform with twin wind turbines

The deployment of offshore wind turbines has focused primarily on shallow seas (such as the North Sea, Chinese coastal waters, and the New England coast) using bottom fixed foundations. However, much of the world’s offshore wind resource lies in deeper waters where bottom-fixed foundations are not suitable, and floating platforms must be utilised. To date, the majority of floating concepts have been developed to support a single wind turbine. This leads to a high capital cost for each individual platform and consequently a high levelised cost of energy. The W2Power platform (developed by EnerOcean S.L, Spain) currently supports a pair of 6 MW wind turbines on outward-leaning towers. The design significantly reduces the cost per installed MW, increases the structure’s natural period, added mass, and radiation damping. The platform, patented in 2009, was the world’s first twin-turbine platform and the first to be demonstrated at sea (2019). This paper presents the hydrodynamics of a 1:40 scale model of the W2Power platform using the well-known OrcaFlex software. The analysis has been carried out under extreme and operational conditions, and the resulting hydrodynamic loads and motion response are presented. The mooring system was found to be sensitive to wave direction, particularly when propagating along the current direction. Furthermore, the results showed advantages in the hydrodynamic responses for the W2Power platform as an innovative floating system

Application of an offshore wind farm layout optimization methodology at Middelgrunden wind farm

This is the author accepted manuscript. The final version is freely available from Elsevier via the DOI in this record.This article explores the application of a wind farm layout evaluation function and layout optimization framework to Middelgrunden wind farm in Denmark. This framework has been built considering the interests of wind farm developers in order to aid in the planning of future offshore wind farms using the UK Round 3 wind farms as a point of reference to calibrate the model. The present work applies the developed evaluation tool to estimate the cost, energy production, and the levelized cost of energy for the existing as-built layout at Middelgrunden wind farm; comparing these against the cost and energy production reported by the wind farm operator. From here, new layouts have then been designed using either a genetic algorithm or a particle swarm optimizer. This study has found that both optimization algorithms are capable of identifying layouts with reduced levelized cost of energy compared to the existing layout while still considering the specific conditions and constraints at this site and those typical of future projects. Reductions in levelized cost of energy such as this can result in significant savings over the lifetime of the project thereby highlighting the need for including new advanced methods to wind farm layout design.This work is funded in part by the Energy Technologies Institute (ETI) 699 and RCUK energy program for IDCORE (EP/J500847/1)

Simulating offshore wind contract for difference auctions to prepare bid strategies

This paper presents a novel agent-based, stochastic model, which uses game-theoretic principles to simulate Contract for Difference (CfD) auctions. The framework has use cases and implications for policymakers and renewable generators alike, and can be used by developers to prepare bidding strategy and for policymakers to empirically test auction design. The model is demonstrated through replication of the offshore wind CfD Allocation Round 3 (AR3) pot, and utilises high-level cost modelling distribution data to estimate bid prices for the competing projects. The model produces a distribution of most likely results which better categorises uncertainty, and through comparison of AR3 and simulation results, demonstrates how outcomes can be predicted with reasonable confidence by developers. Analysis show that the transmission network and grid connection charges are a significant barrier for projects in some geographical regions to be awarded a CfD contract, potentially hindering renewable deployment in those areas. Moreover, this paper demonstrates how players can use probability theory to select an optimum bidding strategy which maximises expected profit while factoring the uncertainty inherent in CfD auctions. Results show that a 1200 MW wind farm development can increase potential profits by £135 million over the CfD contract length in exchange for a 25 p.p. chance reduction in being awarded a subsidy

Group B <em>Streptococcus </em>engages an inhibitory siglec through sialic acid mimicry to blunt innate immune and inflammatory responses <em>in vivo</em>

Group B Streptococcus (GBS) is a common agent of bacterial sepsis and meningitis in newborns. The GBS surface capsule contains sialic acids (Sia) that engage Sia-binding immunoglobulin-like lectins (Siglecs) on leukocytes. Here we use mice lacking Siglec-E, an inhibitory Siglec of myelomonocytic cells, to study the significance of GBS Siglec engagement during in vivo infection. We found GBS bound to Siglec-E in a Sia-specific fashion to blunt NF-κB and MAPK activation. As a consequence, Siglec-E-deficient macrophages had enhanced pro-inflammatory cytokine secretion, phagocytosis and bactericidal activity against the pathogen. Following pulmonary or low-dose intravenous GBS challenge, Siglec-E KO mice produced more pro-inflammatory cytokines and exhibited reduced GBS invasion of the central nervous system. In contrast, upon high dose lethal challenges, cytokine storm in Siglec-E KO mice was associated with accelerated mortality. We conclude that GBS Sia mimicry influences host innate immune and inflammatory responses in vivo through engagement of an inhibitory Siglec, with the ultimate outcome of the host response varying depending upon the site, stage and magnitude of infection

Advancing Biological Understanding and Therapeutics Discovery with Small-Molecule Probes

Small-molecule probes can illuminate biological processes and aid in the assessment of emerging therapeutic targets by perturbing biological systems in a manner distinct from other experimental approaches. Despite the tremendous promise of chemical tools for investigating biology and disease, small-molecule probes were unavailable for most targets and pathways as recently as a decade ago. In 2005, the U.S. National Institutes of Health launched the decade-long Molecular Libraries Program with the intent of innovating in and broadening access to small-molecule science. This Perspective describes how novel small-molecule probes identified through the program are enabling the exploration of biological pathways and therapeutic hypotheses not otherwise testable. These experiences illustrate how small-molecule probes can help bridge the chasm between biological research and the development of medicines, but also highlight the need to innovate the science of therapeutic discovery.Chemistry and Chemical Biolog