Effect of Advanced Metaheuritic Techniques for Wind Farm Layout Optimization

Abstract

There are several environmental issues such as emission of greenhouse gases and global warming that result from the use of fossil fuels. So, there is a need to move towards the renewable energy sources which have less environmental effects and can be considered as a source of cleaner energy production. Out of all the available renewable energy sources, wind energy ranks at the top in terms of carbon footprint, water utilization and social impacts. In the last few decades, wind energy has a remarkable growth for the electric power generation that uses the wind turbine to convert the wind energy in the form of electric energy. The main strive in today‟s development of wind turbines is to build bigger rotors and increase the efficiency of the turbine that are able to extract more energy out of the wind. When it comes to the planning and designing of a wind farm, the placement of turbines is crucial because the power generation of a wind turbine decreases if it is in the wake zone produced by the upstream turbines. Hence, an effective placement of wind turbines that reduces the wake effect and maximizes the power generation of a wind farm is imperative. The main focus of proposed research study is to analyze and optimize the wind farm layout optimization problem (WFLO). The aim of WFLO problem is to find the optimum placement of wind turbines in such a way that downstream turbines are under the minimal wake or no wake conditions. To this end, following work is carried out in this thesis: (i) Evaluate the effectiveness of recently developed advanced metahuristic methods such as TLBO, HTS and PVS for optimizing the WFLO problem (ii) Modify recently develop advanced metahuristic methods to make it more effective to solve the WFLO problem (iii) Development of the geometrical pattern-based approach for turbine positioning in a wind farm and (iv) Implement the proposed methodology and compare the power output for the actual site of Gujarat region. The investigation revealed that the optimal layout of wind farm produced by the geometrical pattern based approach produces the higher power generation compared to other approaches (i.e., grid-based approach, unrestricted placement approach) available in the literature. The velocity deficits produced by each turbines placed in geometrical patter based approach is reduced which leads to the higher power generation. It can be summarized that the pattern based approach has the improvement in mean power output by 8.89, 7.76 and 0.84 percentages for the variable wind speed with variable wind direction compared to grid-based placement of turbine for the genetic algorithm (GA) and the quadratic optimization (OQ) with xvi mixed integer linear (MIL) method and the unrestricted placement approach used in the available literatures respectively. It can also be outlined that some of the enhancement in the basic TLBO, HTS and PVS is indeed effective and can produce better results on a challenging WFLO problem. The pattern based approach is successfully applied to the real wind site of Kutch district, Gujarat and obtains the improvement in power output by 4.29 percentages compared to the existing layout of wind farm. In general, outcomes of the present study seem to be useful for wind farm developers, planners, and decision makers for developing a wind farm layout. Keywords: Wind farm layout optimization, Wind energy, Wake effect, Geometrical patternbased approach, Land availability constraints, Teaching-learning based optimization, Heat transfer search algorithm, Passing vehicle search algorithm.