Investigating the Power-COE trade-off for wind farm layout optimization considering commercial turbine selection and hub height variation

Highlights

A wide P-COE trade-off is achieved by optimizing turbine selection and hub height.

WFLO is more effective in offshore farms because of slower wake recovery.

WFLO is more effective at lower wind speeds and/or compact designed farms.

The turbine selection was biased towards larger diameter and then lower rated speed.

The optimal wind farm layout depends mainly on the optimization objective.

Abstract

New aspects were added to the wind farm layout optimization problem by including commercial turbine selection and a realistic representation for the thrust coefficient. The available manufacturers’ data were used to develop generic representation for the thrust coefficient, on which the wake and power calculations mainly depend. A simple field-based cost model was implemented. The optimization was performed for onshore and offshore conditions using MATLAB genetic algorithm, ga, solver for two simple test cases. Three objective functions were considered, individually: (1) the output power, (2) the capacity factor, and (3) the cost per output power.

The results showed that the flexibility of using different turbines and hub heights can provide a useful trade-off between power and cost. The trade-off was found to be wider in offshore cases, which means that the optimization is more useful in such conditions. The optimization for maximum capacity factor acts as a mid-point between the two design extremes of maximizing power and minimizing the cost of energy. Almost all turbines were selected at least once in an optimum layout. However, the priority in selection was for the turbines that have bigger diameter and/or lower rated speed amongst the other turbines of the same rated power.

Keywords

  • Wind farm layout optimization;
  • Genetic algorithm;
  • Commercial turbine selection;
  • Wind turbine thrust;
  • Hub height variation

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