Techno-economic optimisation of offshore wind farms based on life cycle cost analysis on the UK

Varvara Mytilinou,Athanasios J Kolios

doi:10.1016/j.renene.2018.07.146

Varvara Mytilinou, Athanasios J Kolios

Open Access

https://doi.org/10.1016/j.renene.2018.07.146

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Abstract

Abstract In order to reduce the cost of energy per MWh in wind energy sector and support investment decisions, an optimisation methodology is developed and applied on Round 3 offshore zones, which are specific sites released by the Crown Estate for offshore wind farm deployments, and for each zone individually in the UK. The 8-objective optimisation problem includes five techno-economic Life Cycle Cost factors that are directly linked to the physical aspects of each location, where three different wind farm layouts and four types of turbines are considered. Optimal trade-offs are revealed by using NSGA II and sensitivity analysis is conducted for deeper insight for both industrial and policy-making purposes. Four optimum solutions were discovered in the range between £1.6 and £1.8 billion; the areas of Seagreen Alpha, East Anglia One and Hornsea Project One. The highly complex nature of the decision variables and their interdependencies were revealed, where the combinations of site-layout and site-turbine size captured above 20% of total Sobol indices in total cost. The proposed framework could also be applied to other sectors in order to increase investment confidence.

Highlights

According to the 20-20-20 target on reducing carbon emissions and the Climate Conference in Paris (COP 21) on keeping the global warming temperature below 2 C, it is important to contribute to the Renewable Energy (RE) investment growth in the UK by making the investments more attractive, information-rich and less risky [1]
The Life Cycle Cost (LCC) model described in the methodology was used in the optimisation problem and 8 objectives were included in the process by utilising the NSGA II algorithm according to Fig. 1
This study demonstrated the effectiveness of a methodology by linking MOO with LCC as objective functions and comparing three different wind farm layouts in order to select the optimum solutions

Summary

Introduction

According to the 20-20-20 target on reducing carbon emissions and the Climate Conference in Paris (COP 21) on keeping the global warming temperature below 2 C, it is important to contribute to the Renewable Energy (RE) investment growth in the UK by making the investments more attractive, information-rich and less risky [1]. The UK technology roadmap highlights that the offshore wind costs need to be reduced to £100 per MWh by 2020 and greater confidence over financial motivations is required [2]. Offshore wind managed to reach 24% of the total installed power in Europe in 2015 compared to the 13% share the previous year [3]. 1716 offshore turbines are deployed in 32 offshore operational projects of an overall capacity of 6713.520 MW in the UK [4]. Significant price increases in the overall cost of turbines, their operational and maintenance costs etc. Have a direct impact on large-scale wind projects. The location of a wind farm and the type of support structure have great impacts on the overall strath.ac.uk (A.J. Kolios)

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Results

Conclusion