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Open Access funded by Engineering and Physical Sciences Research Council

open access

Highlights

Four optimal solutions were found between £1.6 and £1.8 billion of the total cost.

Norfolk Boreas includes the highest total costs per MW.

High-order interdependencies of more than two variables govern problem’s complexity.

Site-layout & site-turbine size account for 20% of the variability in expenditures.

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.

Keywords

Life Cycle Cost

NSGA II

Multi-objective optimisation

Round 3

UK

Sensitivity analysis

© 2018 The Author(s). Published by Elsevier Ltd.