Since the two works conducted by Mosetti et al. Thus, using continuous approach sound more appropriate to explore all feasible positions of wind turbines within wind farm area. But using such a methodology limits the feasible solutions of WTs placement due to the predefined grids. In the literature, discrete approach is widely used to describe WF layout. Whilst the second approach called the continuous representation assumed that WTs can be placed at any position within the specified WF boundaries. The center of each square represents the possible placement of WTs indicated by binary variables (0 and 1). The first proposed approach consists of discretizing WF area into equal square grids. īefore reviewing some works that have done in this context, it is important to note that there are two basic approaches to represent the WF layout using heuristic methods. These methods includes genetic algorithm, evolutionary algorithm, particle swarm optimization algorithm and among others methods that can found in detail in these references. These algorithms are based on different optimization techniques in which heuristic methods widely used. The main objective conducted by these works is developing numerical algorithms that maximize power/energy production (in other words decreases the wake effect) and minimize the cost while satisfying certain constraints. Up to now, this problem has received a big attention by scientific research which is justified by the huge numbers of studies that have been addressed in the literature. In this regard and in order to mitigate the wake effect among each WTs placement, wind farm design layout optimization (WFDLO) remains the best strategy to maximize WF performances. Consequently, it gives rise to maintenance cost and diminishes the power production of downstream turbines. Many published works provide that wake interferences generated randomly by upstream turbines cause a significant reduction of wind speed and increase turbulence intensity. However, the quality and quantity of expected power produced by WF are generally reduced by various sources of losses in which wake effect is considered the most influencing one. At this stage, several conflicting objectives, mechanisms and constraints have been imposed while requiring a balance between them in order to ensure the viability of wind energy project.ĭesigning wind farm (WF) layout refers to find the optimal placement of each individual WT from others inside the specific WF boundaries. As a result of this evolution, the design process becomes highly complex from the point of the significant energy capacity to be produced, which generally requires hundreds of wind turbines (WTs) to be installed over a limited area. For instance, the wind energy investments in Europe has received the biggest part of new renewable energy finance about 63% in 2018, up from 52% in 2017. The important interest and efforts devoted by government, energy production, industries and academic research to electricity production from renewable and clean energy with the maturity of existed technologies justify the biggest exploitation of wind energy over the recent years. It should includes as well the number of WTs that influence significantly the power production and WF cost. In addition, it demonstrated that selecting WTs based uniquely on rotor diameter size is not always a good idea. The results showed that designing WF with big WTs gives best design layout. With the aim to analyze the impact of WTs types on WF objectives, four commercial WTs are considered in the second step. The effectiveness of such a methodology is validated and compared with the reference and irregular layout of hors-rev1 offshore WF. In the first step, an optimization model using genetic algorithm with continuous layout representation is developed to look for the optimal design as a function of WTs placement. The main objective of the current study is to design WF area that maximizes the extraction of wind power with low cost. The present paper investigates optimization study of realistic offshore WF design layout (horns-rev1). An optimization approach is seriously needed to deal with this complexity, especially with current trend of large WFs area with important number of wind turbines (WTs). Seeking for an appropriate design of wind farm (WF) layout constitutes a complex task in a wind energy project.
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