Unrestricted wind farm layout optimization (UWFLO): Investigating key factors influencing the maximum power generation

A new methodology, the Unrestricted Wind Farm Layout Optimization (UWFLO), that addresses critical aspects of optimal wind farm planning is presented in this paper. This methodology simultaneously determines the optimum farm layout and the appropriate selection of turbines (in terms of their rotor diameters) that maximizes the net power generation. The farm layout model obviates traditional restrictions imposed on the location of turbines. A standard analytical wake model has been used to account for the velocity deficits in the wakes created by individual turbines. The wind farm power generation model is validated against data from a wind tunnel experiment on a scaled down wind farm. Reasonable agreement between the model and experimental results is obtained. The complex nonlinear optimization problem presented by the wind farm model is effectively solved using constrained Particle Swarm Optimization (PSO). It is found that an optimal combination of wind turbines with differing rotor diameters can appreciably improve the farm efficiency. A preliminary wind farm cost analysis is performed to express the cost in terms of the turbine rotor diameters and the number of turbines in the farm. Subsequent exploration of the influences of (i) the number of turbines, and (ii) the farm land size, on the cost per Kilowatt of power produced, yields important observations.

[1]  Souma Chowdhury,et al.  Improvements to single-objective constrained predator–prey evolutionary optimization algorithm , 2010 .

[2]  Andrew Kusiak,et al.  Power optimization of wind turbines with data mining and evolutionary computation , 2010 .

[3]  Aidan While,et al.  Engineering and energy yield: The missing dimension of wind turbine assessment , 2014 .

[4]  Julio Hernández,et al.  Survey of modelling methods for wind turbine wakes and wind farms , 1999 .

[5]  M. Y. Hussaini,et al.  Placement of wind turbines using genetic algorithms , 2005 .

[6]  Javier Serrano González,et al.  Optimization of wind farm turbines layout using an evolutive algorithm , 2010 .

[7]  Helcio R. B. Orlande,et al.  Inverse and Optimization Problems in Heat Transfer , 2006 .

[8]  S. A. Herman PROBABILISTIC COST MODEL FOR ANALYSIS OF OFFSHORE WIND ENERGY COSTS AND POTENTIAL , 2002 .

[9]  Kalyanmoy Deb,et al.  A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..

[10]  Murat Tunc,et al.  Optimal positioning of wind turbines on Gökçeada using multi‐objective genetic algorithm , 2010 .

[11]  F. W. Lanchester,et al.  A CONTRIBUTION TO THE THEORY OF PROPULSION AND THE SCREW PROPELLER , 2009 .

[12]  James Kennedy,et al.  Particle swarm optimization , 1995, Proceedings of ICNN'95 - International Conference on Neural Networks.

[13]  Hans Georg Beyer,et al.  Modelling Tools for Wind Farm Upgrading , 2003 .

[14]  Luciano Castillo,et al.  Response Surface Based Cost Model for Onshore Wind Farms Using Extended Radial Basis Functions , 2010, DAC 2010.

[15]  J. Kaldellis,et al.  The economic viability of commercial wind plants in Greece A complete sensitivity analysis , 2000 .

[16]  Martin Otto Laver Hansen,et al.  Aerodynamics of Wind Turbines , 2001 .

[17]  Andrew Kusiak,et al.  Optimization of wind turbine energy and power factor with an evolutionary computation algorithm , 2010 .

[18]  Chris T. Kiranoudis,et al.  Short-cut design of wind farms , 2001 .

[19]  Byungik Chang,et al.  Review of Computer-Aided Numerical Simulation in Wind Energy , 2013 .

[20]  C. Meneveau,et al.  Experimental study of the horizontally averaged flow structure in a model wind-turbine array boundary layer , 2009 .

[21]  Morten Lybech Thøgersen,et al.  Recalibrating Wind Turbine Wake Model Parameters – Validating the Wake Model Performance for Large Offshore Wind Farms , 2006 .

[22]  Jun Wang,et al.  Irregular-shape wind farm micro-siting optimization , 2013 .

[23]  A. Betz Introduction to the Theory of Flow Machines , 1966 .

[24]  M. Goldberg,et al.  Jobs and Economic Development Impact (JEDI) Model Geothermal User Reference Guide , 2012 .

[25]  Charles Meneveau,et al.  Interaction Between a Wind Turbine Array and a Turbulent Boundary Layer , 2010 .

[26]  Carlo Poloni,et al.  Optimization of wind turbine positioning in large windfarms by means of a genetic algorithm , 1994 .

[27]  J. Højstrup,et al.  A Simple Model for Cluster Efficiency , 1987 .

[28]  Rebecca J. Barthelmie,et al.  Analytical modelling of wind speed deficit in large offshore wind farms , 2006 .

[29]  Ervin Bossanyi,et al.  Wind Energy Handbook , 2001 .

[30]  Charles Meneveau,et al.  Direct mechanical torque sensor for model wind turbines , 2010 .

[31]  James F. Manwell,et al.  Offshore Wind Farm Layout Optimization (OWFLO) Project: Preliminary Results , 2006 .

[32]  A. Messac,et al.  Optimizing the unrestricted placement of turbines of differing rotor diameters in a wind farm for maximum power generation , 2010, DAC 2010.

[33]  Jens Nørkær Sørensen,et al.  Analysis of Power Enhancement for a Row of Wind Turbines Using the Actuator Line Technique , 2007 .