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A parametric whole life cost model for offshore wind farms

  • LCA FOR ENERGY SYSTEMS AND FOOD PRODUCTS
  • Published:
The International Journal of Life Cycle Assessment Aims and scope Submit manuscript

Abstract

Purpose

Life cycle cost (LCC) considerations are of increasing importance to offshore wind farm operators and their insurers to undertake long-term profitable investments and to make electricity generation more price-competitive. This paper presents a cost breakdown structure (CBS) and develops a whole life cost (WLC) analysis framework for offshore wind farms throughout their life span (∼25 years).

Methods

A combined multivariate regression/neural network approach is developed to identify key cost drivers and evaluate all the costs associated with five phases of offshore wind projects, namely pre-development and consenting (P&C), production and acquisition (P&A), installation and commissioning (I&C), operation and maintenance (O&M) and decommissioning and disposal (D&D). Several critical factors such as geographical location and meteorological conditions, rated power and capacity factor of wind turbines, reliability of sub-systems and availability and accessibility of transportation means are taken into account in cost calculations. The O&M costs (including the cost of renewal and replacement, cost of lost production, cost of skilled maintenance labour and logistics cost) are assessed using the data available in failure databases (e.g. fault logs and O&M reports) and the data supplied by inspection agencies. A net present value (NPV) approach is used to quantify the current value of future cash flows, and then, a bottom-up estimate of the overall cost is obtained.

Results and discussion

The proposed model is tested on an offshore 500-MW baseline wind farm project, and the results are compared to experimental ones reported in the literature. Our results indicate that the capital cost of wind turbines and their installation costs account for the largest proportion of WLC, followed by the O&M costs. A sensitivity analysis is also conducted to identify those factors having the greatest impact on levelized cost of energy (LCOE).

Conclusions

The installed capacity of a wind farm, distance from shore and fault detection capability of the condition monitoring system are identified as parameters with significant influence on LCOE. Since the service lifetime of a wind farm is relatively long, a small change in interest rate leads to a large variation in the project’s total cost. The presented models not only assist stakeholders in evaluating the performance of ongoing projects but also help the wind farm developers reduce their costs in the medium–long term.

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Acknowledgments

The authors gratefully acknowledge the support provided by the owners of several European offshore wind farms during field visits and data collection.

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Authors and Affiliations

  1. Centre for Offshore Renewable Energy Engineering, Cranfield University, College Road, Bedford, MK43 0AL, Befordshire, UK

    Mahmood Shafiee, Feargal Brennan & Inés Armada Espinosa

Authors
  1. Mahmood Shafiee
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  2. Feargal Brennan
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  3. Inés Armada Espinosa
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Corresponding author

Correspondence to Mahmood Shafiee.

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Responsible editor: Thomas Swarr

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Shafiee, M., Brennan, F. & Espinosa, I.A. A parametric whole life cost model for offshore wind farms. Int J Life Cycle Assess 21, 961–975 (2016). https://doi.org/10.1007/s11367-016-1075-z

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  • DOI: https://doi.org/10.1007/s11367-016-1075-z

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