Data di Pubblicazione:
2019
Abstract:
A novel method was developed to detect the optimal onshore wind farm layout driven by the characteristics of
all commercially-available wind turbines. A huge number of turbine combinations (577) was processed, resulting
in 22,721 generated layouts. Various assumptions and constraints were considered, mostly derived from
the literature, including site features, wind conditions, and layout design. For the latter, an irregularly staggered
turbine array configuration was assumed. Wake effects were simulated through the Jensen's model, while a
typical turbine thrust coefficient curve as a function of wind speed was originally developed. A detailed cost
model was used, with levelized cost of energy selected as primary and capacity factor as secondary objective
function. The self-organizing maps were used to address a thorough analysis, proving to be a powerful means to
straightforwardly achieve a comprehensive pattern of wind farm layout optimization.
In general, the two optimization functions basically match, while for higher wind potential sites, increasing
capacity factor did not necessarily result in decreasing levelized cost of energy. The latter may be minimised by
reducing the total number of turbines or the overall wind farm capacity, as well as maximising rotor diameters or
minimising rated wind speeds; increasing rated power or hub height is only beneficial for mid-potential sites.
The mere maximisation of wind farm energy production is a misleading target, as corresponding to mid-to-high
values of levelized cost of energy. In contrast to previous studies, the use of turbines with different rated power,
rotor diameter or hub height should be avoided.
Tipologia CRIS:
01.01 Articolo in rivista
Keywords:
Wind farm layout optimization (WFLO); Wake model; Wind turbine database; Wind turbine spacing; Levelized cost of energy (LCoE); Self-organizing map (SOM)
Elenco autori:
Gualtieri, Giovanni
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