Stochastic Prediction of Offshore Wind Farm LCOE through an Integrated Cost Model. (February 2017)

• Record Type: Journal Article
• Authors: Ioannou, Anastasia; Angus, Andrew; Brennan, Feargal
• Is Part Of: Energy procedia. Volume 107(2017)
• Page Start: 383
• Page End: 389
• Publication Date: 2017-02
• Subjects: Offshore wind farm -- probabilistic cost model -- Monte Carlo simulation -- levelised cost of electricity -- stochastic inputs; Power resources -- Congresses; Power resources -- Periodicals; Power resources; Conference proceedings; Periodicals; 333.7905
• DOI: 10.1016/j.egypro.2016.12.180
• Languages: English
• ISSNs: 1876-6102

Abstract

Abstract: Common deterministic cost of energy models applied in offshore wind energy installations usually disregard the effect of uncertainty of key input variables – associated with OPEX, CAPEX, energy generation and other financial variables – on the calculation of levelized cost of electricity (LCOE). The present study aims at expanding a deterministic cost of energy model to systematically account for stochastic inputs. To this end, Monte Carlo simulations are performed to derive the joint probability distributions of LCOE, allowing for the estimation of probabilities of exceeding set thresholds of LCOE, determining certain confidence intervals. The results of this study stress the importance of appropriate statistical modelling of stochastic variables in order to reduce modelling uncertainties and contribute to a better informed decision making in renewable energy investments.