Averaged model of modular multilevel converter in rotating DQ frame.

This paper proposes an average model of Modular Multilevel Converter (MMC) in rotating DQ frame. The proposed MMC model has a modular structure and can be linked with other power elements such as AC and DC subsystems. Modelling in DQ frame has numerous advantages over traditional ABC frame in terms of simulation speed and convenience for linearization. The main challenge of developing DQ model of MMC is to deal with the multiplication terms of dynamic equations of MMC. To overcome this complexity, a generic form is first introduced for each product variable mathematical equations of the average MMC model in ABC frame and then the multiplication results are transferred to DQ frame after ignoring the higher harmonics. The detailed model and the proposed DQ average model are implemented in PSCAD/EMTDC. The simulation results of the two models show very good matching which in turn confirms the accuracy of the proposed model. Also, the DQ average model is considerably faster than the detailed and even ABC average models

Optimisation of offshore wind farm maintenance.

The installed capacity of European Offshore Wind Turbines (OWT) is likely to rise from the 2014 value of 7GW to 150GW in 2030. However maintenance of OWT is facing unprecedented challenges and cost 35% of lifetime costs. This will be equivalent to £14billion/year by 2030 if current OWT maintenance schemes are not changed. However the complexities around OWT operation require tools and systems to optimise OWT maintenance. The design of optimal OWT maintenance requires failure analysis of over 10,000 components in OWT for which there is little published work relating to performance and failure. In this work, inspection reports of over 400 wind turbine gearboxes (source: Stork Technical Services) and SCADA data (source: Shetland Aerogenerators Ltd) were studied to identify issues with performance and failures in wind turbines. A modified framework of Failure Mode Effects and Criticality Analysis (i.e. FMECA+) was designed to analyse failures according to the unique requirements of OWT maintenance planners. The FMECA+ framework enables analysis and prediction of failures for varied root causes, and determines their consequences over short and long periods of time. A software tool has been developed around FMECA+ framework that enables prediction of component level failures for varied root causes. The tool currently stores over 800 such instances. The need to develop a FMECA+ based Enterprise Resource Planning tool has been identified and preliminary results obtained from its development have been shown. Such a software package will routinely manage OWT data, predict failures in components, manage resources and plan an optimal maintenance. This will solve some big problems that OWT maintenance planners currently face. This will also support the use of SCADA and condition monitoring data in planning OWT maintenance, something which has been difficult to manage for a long time

Modular multilevel converter modulation using fundamental switching selective harmonic elimination method.

This paper address the issue of low order harmonics in a modular multilevel converter (MMC). Using fundamental switching selective harmonic elimination (SHE), the control angles are calculated from nonlinear equations by Newton-Raphson method. The selective harmonic elimination equations are solved in such a way that the first switching angle is used to control the magnitude of the fundamental voltage and the remaining angles are used to eliminate the lowest odd, non-triplen harmonics components as they dominate the total harmonic distortion of the converter. The concept is validated using a 9-level detailed model of MMC in PSCAD/EMTDC®. The simulation result shows a good agreement with theoretical analysis and in comparison with conventional sinusoidal pulse width modulation (SPWM), the proposed method, eliminates low order harmonics, leading to a low total harmonic distortion

Failure prognostic schemes and database design of a software tool for efficient management of wind turbine maintenance.

Wind Turbines require numerous and varied types of maintenance activities throughout their lifespan, the frequency of which increases with years in operation. At present the proportion of maintenance cost to the total cost for wind turbines is significant particularly for offshore wind turbines (OWT) where this ratio is ∼35%. If this ratio is to be reduced in-spite of adverse operating conditions, pre-mature component failures and absence of reliability database for wind turbine components, there is a need to design unconventional maintenance scheme preferably by including novel failure prediction methodologies. Several researchers have advocated the use of Artificial Neural Networks (ANN), Bayesian Network Theory (BNT) and other statistical methods to predict failure so as to plan efficient maintenance of wind turbines, however novelty and randomness of failures, nature and number of parameters involved in statistical calculations and absence of required amount of fundamental work required for such advanced analysis have continued to maintain the high cost of maintenance. This work builds upon the benefits of condition monitoring to design methods to predict generic failures in wind turbine components and exhibits how such prediction methods can assist in cutting the maintenance cost of wind turbines. This study proposes using a dedicated tool to assist with failure prediction and planning and execution of wind turbine maintenance. The design and development of such an all-inclusive tool will assist in performing administrative works, inventory control, financial calculations and service management apart from failure prediction in wind turbine components. Its database will contain reference to standard management practices, regulatory provisions, staff details and their skillsets, service call register, troubleshooting manuals, installation guide, service history, details of customers and clients etc. that would cater to multiple avenues of wind turbine maintenance. In order to build such a software package, a robust design of its database is crucial. This work lists prerequisites for choosing a physical database and identifies the benefits of relational database software in controlling large amounts of data of various formats that are stored in such physical databases. Such a database would be an invaluable resource for reliability studies, an area of interest for both academic researchers and the industry that are identifying avenues to economise wind turbine operations

A prognostic decision model for offshore wind turbines maintenance.

Frequent unscheduled random maintenance activities have significantly increased the operating cost of Offshore Wind Turbines (OWT). These activities account for ∼65% of the overall OWT maintenance costs or 23% of the lifetime costs of OWT, equivalent to ∼ £26 M/yr for a 100MW offshore wind farm. This work performs a quantitative evaluation of the maintenance model suggested by Sinha Y et al. (2013) as a means to determine the threshold levels for planning an economical but effective maintenance for OWT. This study suggests that the model put forward provides a comprehensive framework to make maintenance decisions for OWT components by questioning their Availability, Reliability, Safety, Productivity and Availability of Upgrade Technology. Some case studies have been discussed towards the end of this work that validates this model and brings financial benefits. It is expected that practical use of the maintenance decision model, along with relationships developed in this work, would result in planning for economical, effective and efficient OWT maintenance

A SMART software package for maintenance optimisation of offshore wind turbines.

Offshore Wind Turbine (OWT) maintenance costs in between 20 - 35% of the lifetime power generation cost. Many techniques and tools that are being developed to curtail this cost are challenged by the stochastic climatic conditions of offshore location and the wind energy market. A generic and OWT centric software packages that can smartly adapt to the requirement of any offshore wind farm and optimise its maintenance, logistics and spares-holding while giving due consideration to offshore climate and market conditions will enable OWT operators to centralise their operation and maintenance planning and make significant cost reductions. This work aims to introduce the idea of a comprehensive tool that can meet the above objectives, and give examples of data and functions required. The package uses wind turbine condition monitoring data to anticipate component failure and proposes a time and maintenance implementation strategies that is developed as per the requirements of HSE and government regulations for working in the offshore locations and at heights. The software database contains key failure analysis data that will be an invaluable asset for future researchers, turbine manufacturers and operators, that will optimise OWT power generation cost and better understand OWT working. The work also lists some prevalent tools and techniques developed by industries and researchers for the wind industry

Significance of effective lubrication in mitigating system failures: a wind turbine gearbox case study.

The effectiveness of lubrication in machines mainly depends on the physical and chemical properties of lubricating oil, like quantity, level of suspended particles, effect of external load/shear forces, temperature amongst others. Periodic inspection of lubricating oil for its grade of viscosity, H2O content, fuel content, amount and nomenclature of suspended particles etc. assists maintenance personal in assessing the quality of oil and its residual life. Such assessments are also useful in determining health of the system in which the lubricating oil was used. This work discusses about industrial Wind Turbine Gearbox lubrication, its importance, applications, oil analysis method and lists constituents found in the oil. Results lead us to the conclusion that additives in the oil protect the gearbox from wear and tear during initial years of operation. Analysis also suggests that re-lubrication process should be performed every 18 months time interval to optimise the life of gearbox components. Other results and advice for lubrication are also listed

Efficiency improvement of vertical axis wind turbines with an upstream deflector.

The suitability of using an upstream deflector to improve the efficiency of a vertical axis wind turbine is presented in this study. A two-dimensional vertical axis wind turbine (VAWT) was modelled and simulated using ANSYS Fluent 14.0 computational fluid dynamics (CFD) software to solve the k-epsilon (RNG) turbulence model. Firstly, the open rotor design was optimised by varying orientation and pitch angle, prior to analysing the effect increasing wind speed had on the turbine performance. A maximum efficiency of 19.101% was achieved and was used as the open rotor design. A series of curved upstream deflectors were then evaluated in terms of efficiency improvements against the original open rotor design. Installation of the deflector resulted in a redirection of the fluid flow from the returning turbine blade, therefore reducing the negative torque induced on the system. Additionally, deflector width angles of 45o and 36o were found to improve the turbine performance by 1.266%. Finally, a scale model of the wind turbine was constructed and experimentally tested using a wind tunnel. No correlation between the CFD and experimental results was found due to variations in the wind speed tested by both methods. However, the VAWT design operated at a reasonably efficient level during the experimental testing, even under suboptimal conditions

Useful pharmacodynamic endpoints in children: selection, measurement, and next steps.

Pharmacodynamic (PD) endpoints are essential for establishing the benefit-to-risk ratio for therapeutic interventions in children and neonates. This article discusses the selection of an appropriate measure of response, the PD endpoint, which is a critical methodological step in designing pediatric efficacy and safety studies. We provide an overview of existing guidance on the choice of PD endpoints in pediatric clinical research. We identified several considerations relevant to the selection and measurement of PD endpoints in pediatric clinical trials, including the use of biomarkers, modeling, compliance, scoring systems, and validated measurement tools. To be useful, PD endpoints in children need to be clinically relevant, responsive to both treatment and/or disease progression, reproducible, and reliable. In most pediatric disease areas, this requires significant validation efforts. We propose a minimal set of criteria for useful PD endpoint selection and measurement. We conclude that, given the current heterogeneity of pediatric PD endpoint definitions and measurements, both across and within defined disease areas, there is an acute need for internationally agreed, validated, and condition-specific pediatric PD endpoints that consider the needs of all stakeholders, including healthcare providers, policy makers, patients, and families.Pediatric Research advance online publication, 11 April 2018; doi:10.1038/pr.2018.38