PO005

Impacts of Financial Optimisation Objectives on Wind Farm Design

Richard Gale 1, Kester Gunn2
1Uniper, Nottingham, UK, 2E.ON, Coventry, UK

Abstract

Offshore Wind Energy continues to form the basis of decarbonising the energy system in many countries in Europe and across the world.  However there is a clear need to deliver this infrastructure in a cost effective manner; both for companies who construct & operate and for governments who must maintain energy security in an affordable manner.  Advancements in optimisation algorithms combined with refocussing the optimisation for financial project drivers rather than simply wind farm yield are applied to design wind farm layout.  Work has been undertaken to investigate the impact of the choice of financial optimisation objectives on the layout design and CAPEX of the wind farm.

Method

An advanced evolutionary algorithm combined with complex geometric representations of layouts has been applied to the design of wind farm layouts.

Rather than relying on yield alone (calculated using industry standard software) as the objective, a standard financial model was used to combine many additional design drivers, for example GIS based cost information (e.g. variation in foundation cost across a site) and an advanced cable routing algorithm to estimate cable costs. The tool has been applied to both regular lattice grid arrays and irregular arrays.

Thus, layouts can be optimised for yield, or for a range of financial objectives (Cost of Energy, NPV, etc.). Studies were undertaken, on offshore wind farm sites to understand the sensitivity of wind farm layout design to different optimisation objectives.

Results

Examination of optimisation results show that wind farm designs based on yield optimisation will not deliver best value against any of the financial metrics considered (except in non-real-world design cases).  Rather financial optimisation objectives should be used and this will result in different wind farm designs to the simple yield optimisation cases.  It has been shown however that the choice of objective will also alter the design of the wind farm layout.  Thus choosing the correct financial metric is important for the industry in designing for return on investment and for governments in maximising value for investment in renewables support mechanisms.

Conclusions

In order to deliver Offshore Wind Energy in a cost effective manner companies should seek to leverage their existing investment and resources fully.  Improvements in the design of offshore wind farms through focussing on optimising for financial objectives is delivered by the various cost drivers to be more effectively balanced by the income they deliver.  Simple yield optimisation has been shown to lead to non-financially optimum layout with a resulting impact on return on investment.  Further, the choice of financial objective is important as different financial measures have been shown to produce different wind farm layouts.

Objectives

By demonstrating the results of improved optimisation through a number of case studies delegates with receive:

1) An improved understanding of the interactions of different cost drivers on offshore wind farms.

2) A greater understanding of the impact that certain financial metrics have on the design of wind farms

3) Suggestions for financial metrics that deliver better results when used as the optimisation objective