1.- SOPCAWIND FP7 Project, http://www.sopcawind.eu. Retrieved on January 2014.

2.- Z. W Geem, J. H Kim, G. V Loganathan, “A New Heuristic Optimization Algorithm: Harmony Search”, Simulation, vol. 76, N. 2, pp. 60–68, 2001.

3.- I. Landa-Torres, S. Gil-Lopez, S. Salcedo-Sanz, J. Del Ser, J. A. Portilla-Figueras, “A Novel Grouping Harmony Search Algorithm for the Multiple-Type Access Node Location Problem”, Expert Systems with Applications, vol. 39, N. 5, pp. 5262–5270, 2012.

The installation of wind farms and the micrositing of wind turbines involve a high number of constraints and restrictions (e.g. protected environmental areas, radio communication infrastructure, or geographical unfeasibility) that must be carefully considered when designing a wind farm project. In this context, the SOPCAWIND (Software for the Optimal Place CAlculation for WIND farms) FP7 European project [1] aims at providing a specific tool for the optimum location of wind turbines within an area previously selected by the user. Since an optimal micro-siting of wind turbines involves different conflicting objective functions, i.e. maximization of the yield production and reduction of the capital cost, the research work proposes a multi-objective meta-heuristic algorithm capable of encounter Pareto optimal wind turbine placements along each objective. Specifically, a novel multi-objective adaptation of the Harmony Search (HS) algorithm [2] is developed which has obtained excellent results in the field of combinatorial optimization [3]. Experimental simulation results in synthetic and realistic scenarios over a certain region of the Basque Country (northern Spain) will be presented and discussed in order to highlight the practical applicability of the proposed algorithm.

AbstractAbstract

A Novel Multi-objective Algorithm for the OptimalPlacement of Wind Turbines with Cost

and Yield Production Criteria

Diana Manjarres (1), Valentin Sanchez (1), Javier Del Ser (1), Itziar Landa-Torres (1), Sergio Gil-Lopez (1), Naïma Vande Walle (2), Nikolaz Guidon (2)

(1) OPTIMA Business Area (ICT-ESI), Tecnalia Research & Innovation, Zamudio, Spain(2) 3E, Brussels, Belgium.

PO. IDPO. ID282282

Multi-objective Harmony Search Algorithm (NSHS-II)Multi-objective Harmony Search Algorithm (NSHS-II)

Concluding RemarksConcluding Remarks

EWEA 2014, Barcelona, Spain: Europe’s Premier Wind Energy Event

EWEA 2014, Barcelona, Spain: Europe’s Premier Wind Energy Event

This paper presents a novel meta-heuristic approach based on the Harmony Search algorithm for efficiently solving the problem of optimally deploying turbines in wind farms under the aforementioned criteria and constraint set. The performance of the obtained multi-objective HS algorithm (NSHS-II) is assessed by several Monte Carlo realizations in a real-based scenario in the Basque Country (northern Spain). The achieved results provide a diverse set of Pareto optimal solutions representing the encountered wind farm layouts within a predefined project area. Therefore, the proposed tool will help any given wind farm designer to optimally select the layout of the wind farm according to the specific requirements of the project and existing location constraints of the region.

ReferencesReferences

AcknowledgmentsAcknowledgments

Simulation ResultsSimulation Results

Flow diagram of the proposed NSHS-II algorithm

Actual wind farm deployments (left). A wind farm solution obtained for the NSHS-II algorithm (right).

The Basque Country scenario:- Turbine model: Vestas V90 2MW- Number of turbines: Nmin=2, Nmax=10- Rotor diameter: 90m; Hub height=80m

SOPCAWIND is funded by the European Commission within the FP7-ICT-2011-SME-DCL, that is, FP7 ICT SME Initiative for Digital Content and Languages programme, under Grant Agreement nº 296164)