Reliability measures of second order semi-Markov chain applied to wind energy production

TL;DR

This paper introduces a second order semi-Markov chain model for wind speed to evaluate reliability, availability, and maintainability of wind energy production, validated through real data and simulations.

Contribution

It presents a novel application of second order semi-Markov processes to model wind speed and compute dependability measures for wind energy systems.

Findings

Model accurately reproduces wind speed statistical features.

Dependability measures can be computed analytically and via simulation.

Results align well with real energy production data.

Abstract

In this paper we consider the problem of wind energy production by using a second order semi-Markov chain in state and duration as a model of wind speed. The model used in this paper is based on our previous work where we have showed the ability of second order semi-Markov process in reproducing statistical features of wind speed. Here we briefly present the mathematical model and describe the data and technical characteristics of a commercial wind turbine (Aircon HAWT-10kW). We show how, by using our model, it is possible to compute some of the main dependability measures such as reliability, availability and maintainability functions. We compare, by means of Monte Carlo simulations, the results of the model with real energy production obtained from data available in the Lastem station (Italy) and sampled every 10 minutes. The computation of the dependability measures is a crucial point in the planning and development of a wind farm. Through our model, we show how the values of this quantity can be obtained both analytically and computationally.