OPTIMIZATION OF WIND TURBINE PLACEMENT LAYOUT ON NON-FLAT TERRAINS
DOI:
https://doi.org/10.23055/ijietap.2014.21.6.1265Keywords:
Wind turbine, Cluster Identification Algorithm (CIA), Multi-Objective Genetic Algorithm (MOGA), Optimization of wind farm layout, Wind energyAbstract
To date, wind power has become very popular due to climate change, greenhouse gases and diminishing fossil fuels. Although wind turbine technology for electricity is already very mature, industry is looking to achieve the best utilization of the wind energy in order to fulfill the electrical needs for cities at a very affordable cost. In this paper, a method entitled Cluster Identification Algorithm (CIA) and an optimization approach called a Multi-Objective Genetic Algorithm (MOGA) has been developed. The main objective is to maximize the power and the efficiency, while minimize the cost caused by the size and quantity of wind turbines installed on non-flat terrains (i.e., a terrain with different heights). The fitness functions evaluated different population sizes and generation numbers to find the best options. Necessary assumptions are made in terms of wind directions, different turbine capacities and different turbine quantities available. Furthermore, this study considers how the downstream decay model from the wind energy theory describes a relationship between the wind turbines positioned ahead and the subsequent ones. Finally, a model relates the layout of wind farm with an optimal combination of efficiency, power and cost is suggested. A case study that addresses the three dimensional terrain optimization problems using the combination of CIA and MOGA algorithms is presented, which validates the proposed approach. This proposed methodology is expected to help solving other similar problems that occur in the renewable energy sectors.
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