New paradigm for lifecycle data collection for eco-management of distributed units of a multi-sources renewable energy system

A major goal of this paper is to consider a new paradigm of monitoring and predictive maintenance decision support of distributed hybrid renewable energy power units, driven by data, economic and ecologic requirements. A renewable energy power unit is a multi-component multistate complex system. In this paper, colored stochastic Petri nets are suggested to model, evaluate and forecast the health conditions of components, and to drive and update the data collection process through the unit lifetime. The approach allows monitoring the health conditions of the unit and predicting the reliability of its components, on the base of a non-parametric model.

[1]  M. C. Jones,et al.  A reliable data-based bandwidth selection method for kernel density estimation , 1991 .

[2]  Peter Tavner,et al.  Reliability analysis for wind turbines with incomplete failure data collected from after the date of initial installation , 2009, Reliab. Eng. Syst. Saf..

[3]  Faouzi Ghorbel,et al.  Some statistical properties of the kernel-diffeomorphism estimator , 1997 .

[4]  D. Titterington,et al.  Estimation Problems with Data from a Mixture , 1978 .

[5]  E. Parzen On Estimation of a Probability Density Function and Mode , 1962 .

[6]  G.J. Vachtsevanos,et al.  A particle filtering-based framework for real-time fault diagnosis and failure prognosis in a turbine engine , 2007, 2007 Mediterranean Conference on Control & Automation.

[7]  Daming Lin,et al.  A review on machinery diagnostics and prognostics implementing condition-based maintenance , 2006 .

[8]  Hai Qiu,et al.  Physics-based Remaining Useful Life Prediction for Aircraft Engine Bearing Prognosis , 2009 .

[9]  Jeffrey K. Uhlmann,et al.  New extension of the Kalman filter to nonlinear systems , 1997, Defense, Security, and Sensing.

[10]  N. Zerhouni,et al.  Hidden Markov Models for failure diagnostic and prognostic , 2011, 2011 Prognostics and System Health Managment Confernece.

[11]  Essam Shehab,et al.  Obsolescence management for long-life contracts: state of the art and future trends , 2010 .

[12]  Pameet Singh,et al.  Obsolescence Driven Design Refresh Planning for Sustainment-Dominated Systems , 2006 .

[13]  Sunil Menon,et al.  Neural Network Models for Usage Based Remaining Life Computation , 2006 .

[14]  James Stephen Marron,et al.  Comparison of data-driven bandwith selectors , 1988 .

[15]  J. Twidell Renewable energy: implementation and benefits , 1993 .

[16]  Domenico Grimaldi,et al.  Java-based distributed measurement systems , 1998, IEEE Trans. Instrum. Meas..