Modelling a storage system of a wind farm with a ramp-rate limitation: a semi-Markov modulated Brownian bridge approach

Abel Azze (), Guglielmo D’Amico (), Bernardo D’Auria () and Salvatore Vergine ()
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Abel Azze: CUNEF Universidad
Guglielmo D’Amico: University G. d’Annunzio of Chieti–Pescara
Bernardo D’Auria: University of Padova
Salvatore Vergine: Marche Polytechnic University

Annals of Operations Research, 2025, vol. 345, issue 1, No 2, 39-57

Abstract: Abstract We propose a new methodology to simulate the discounted penalty applied to a wind-farm operator by violating ramp-rate limitation policies. It is assumed that the operator manages a wind turbine plugged into a battery, which either provides or stores energy on demand to avoid ramp-up and ramp-down events. The battery stages, namely charging, discharging, or neutral, are modeled as a semi-Markov process. During each charging/discharging period, the energy stored/supplied is assumed to follow a modified Brownian bridge that depends on three parameters. We prove the validity of our methodology by testing the model on 10 years of real wind-power data and comparing real versus simulated results.

Keywords: Brownian bridge; Monte Carlo simulation; Power ramping; Semi-Markov process (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s10479-024-06236-6

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