Page 254 - Fundamentals of Ocean Renewable Energy Generating Electricity From The Sea

244 Fundamentals of Ocean Renewable Energy

FIG. 9.4 Visualization of the wake effect in a wind farm. (Reproduced with kind permission of
Vattenfall.)

between turbines, maintenance cost, and a larger leased area. Therefore, finding
the optimum layout is an optimization problem.
Estimating the reduction of wind speed in the wake of a turbine can be
achieved by simplified methods, based on the distance of the turbines, hub
height, and radius of turbines (e.g. [5,6]), or wakes can be more accurately
simulated using CFD codes and high performance computing (e.g. [7,8]).

Decision Variables
In micro-siting of offshore wind farms, the layout of the farm, which consists of
several variables, needs to be optimized. The simplest case is when the number
and the capacity of turbines are given, in which the locations of the turbines are
the decision variables. More complicated cases involve more decision variables,
such as the number, size, type, and hub-heights of turbines, in addition to the
locations of the wind turbines.

Objective Functions
As mentioned before, a renewable energy system can be optimized by a single
or multiple objective functions. The simplest objective function is AEP (max-
imize). This objective function does not take into account the cost associated
with AEP, which is a major factor in the decision-making process. Referring
to the concept of levelized cost of energy (LCOE) introduced in Chapter 1, the
ratio of the cost of energy to electricity production can be minimized, which is a
more practical objective function. This objective function takes into account the
increased cost of electrical cables and other elements of the farm when turbine
spacing is increased: