Modeling the effects of seasonal weather and site conditions on wind turbine failure modes

It is important that the impact of the offshore environment on wind turbine reliability is reduced significantly due to the importance of offshore wind deployment to global energy targets. Future development may otherwise be compromised by unsustainable operation and maintenance (O&M) costs. This paper aims to improve the accuracy of offshore O&M models by accounting for any relationship between certain weather characteristics and wind turbine failure modes. This is done using maintenance data from a UK onshore wind farm and weather data from a weather station located nearby. Non-parametric Mixture Models are estimated from the data and they are used to calculate a more accurate, weather dependent, failure rate which will be used in future research for Markov Chain Monte Carlo Simulation. This research will be of particular interest to wind turbine operators and manufacturer

Back on the Rails -- Competition and Productivity in State-owned Industry

The importance of Total Factor Productivity (TFP) in explaining output changes is widely accepted, yet its sources are not well understood. We use a proprietary data set on the oor-level operations at the Bhilai Rail and Structural Mill (RSM) in India to understand the determinants of changes in plant productivity between January 2000 and March 2003. During this period there was a 35% increase in output with minimal changes in the stock of physical capital or the number of employees, but sizable reductions in the number and duration of various types of production delays. We model interruptions to the production process as a function of worker characteristics and find that a large part of the avoidable delay reductions are attributable to training. Overall, changes in all delays account for over half the changes in productivity. Our results provide some explanation for the large within-industry di erences in productivity observed in developing countries and also suggest that specic knowledge-enhancing investments can have very high returns. Our approach also provides an example of how detailed data on production processes can be fruitfully used to better understand TFP changes, which have typically been treated as residuals in growth-accounting exercises.Total Factor Productivity (TFP), Plant level data, Competitiveness and trade.

Synthesis and Stochastic Assessment of Cost-Optimal Schedules

We present a novel approach to synthesize good schedules for a class of scheduling problems that is slightly more general than the scheduling problem FJm,a|gpr,r_j,d_j|early/tardy. The idea is to prime the schedule synthesizer with stochastic information more meaningful than performance factors with the objective to minimize the expected cost caused by storage or delay. The priming information is obtained by stochastic simulation of the system environment. The generated schedules are assessed again by simulation. The approach is demonstrated by means of a non-trivial scheduling problem from lacquer production. The experimental results show that our approach achieves in all considered scenarios better results than the extended processing times approach

Multi-objective optimisation of machine tool error mapping using automated planning

Error mapping of machine tools is a multi-measurement task that is planned based on expert knowledge. There are no intelligent tools aiding the production of optimal measurement plans. In previous work, a method of intelligently constructing measurement plans demonstrated that it is feasible to optimise the plans either to reduce machine tool downtime or the estimated uncertainty of measurement due to the plan schedule. However, production scheduling and a continuously changing environment can impose conflicting constraints on downtime and the uncertainty of measurement. In this paper, the use of the produced measurement model to minimise machine tool downtime, the uncertainty of measurement and the arithmetic mean of both is investigated and discussed through the use of twelve different error mapping instances. The multi-objective search plans on average have a 3% reduction in the time metric when compared to the downtime of the uncertainty optimised plan and a 23% improvement in estimated uncertainty of measurement metric when compared to the uncertainty of the temporally optimised plan. Further experiments on a High Performance Computing (HPC) architecture demonstrated that there is on average a 3% improvement in optimality when compared with the experiments performed on the PC architecture. This demonstrates that even though a 4% improvement is beneficial, in most applications a standard PC architecture will result in valid error mapping plan

Wind turbine condition assessment through power curve copula modeling

Power curves constructed from wind speed and active power output measurements provide an established method of analyzing wind turbine performance. In this paper it is proposed that operational data from wind turbines are used to estimate bivariate probability distribution functions representing the power curve of existing turbines so that deviations from expected behavior can be detected. Owing to the complex form of dependency between active power and wind speed, which no classical parameterized distribution can approximate, the application of empirical copulas is proposed; the statistical theory of copulas allows the distribution form of marginal distributions of wind speed and power to be expressed separately from information about the dependency between them. Copula analysis is discussed in terms of its likely usefulness in wind turbine condition monitoring, particularly in early recognition of incipient faults such as blade degradation, yaw and pitch errors

A Simulation Based Approach for Determining Maintenance Strategies

Manufacturing organizations are continuously in the mode of identifying and implementing mechanisms to achieve a competitive edge. To this point manufacturers have recognized the critical role of equipment in the productivity of manufacturing operations. With the current trend of manufacturers attempting to lean out their production processes, primary and auxiliary equipment have become even more important to manufacturers as measured by productivity, quality, delivery, and cost metrics. As a result of the focus on lean manufacturing, maintenance management has found a new vigor and purpose to increase equipment capacity and capability. However, the most proactive maintenance strategy is not always the most effective utilization of resources. It is typical for manufacturers to integrate both reactive and proactive maintenance to define a cost effective maintenance strategy. A simulation-based approach is presented that allows an end user to develop such a maintenance strategy

Maintenance Scheduling in Power Electronic Converters Considering Wear-out Failures

Power electronic converters are one of failure sources in energy systems, and hence drivers of downtime costs in power systems. Different approaches can be employed for converter reliability enhancement including design/control for reliability methods, condition monitoring and fault diagnosis, and maintenance strategies. This paper proposes optimal preventive maintenance strategies based on wear-out failure model of converter components. The proposed approaches employ two different performance measures at converter-level and system-level. The converter-level measures take into account planned and unplanned maintenance times or costs in a single unit or small-scale system. Moreover, the system-level measure considers not only maintenance times, but also energy losses and additional maintenance costs induced by aging of the converter components. The outcome is optimal replacement time of converter and its components, which depends on the employed performance measure. Optimal replacement scheduling is of importance for risk management and decision-making during planning of modern power electronic based power systems. The applicability of the proposed approaches is illustrated by numerical analysis in a photovoltaic system