A comprehensive analysis of grid-based wind turbine layout using an efficient binary invasive weed optimization algorithm with levy flight. (15th July 2022)

• Record Type: Journal Article
• Authors: Koc, Ismail
• Is Part Of: Expert systems with applications. Volume 198(2022)
• Publication Date: 2022-07-15
• Subjects: Invasive weed optimization -- Levy flight -- Wind turbine placement -- Turbine layout -- Binary algorithm; Expert systems (Computer science) -- Periodicals; Systèmes experts (Informatique) -- Périodiques; Electronic journals; 006.33
• DOI: 10.1016/j.eswa.2022.116835
• Languages: English
• ISSNs: 0957-4174

Abstract

Highlights: A novel invasive weed optimization algorithm based on levy flight (LFIWO) is proposed. Nine different layout systems are proposed for optimizing wind turbine placement. A new repair operator is developed in order to make the candidate solutions feasible. Experimental studies are performed with ten binary variants for both of IWO and LFIWO. LFIWO obtains the better results than those of the other algorithms in the literature. Abstract: Wind energy has attracted great attention in recent years due to the increasing demand for alternative energy sources. Gathering the maximum amount of energy from wind energy is directly related to the layout of wind turbines in wind farm. This study focuses on grid-based wind turbine layout problem in an area of 2 km × 2 km. In order to solve this problem, 9 novel grids of 11 × 11, 12 × 12, … and 19 × 19 are proposed in this paper in addition to 10 × 10 and 20 × 20 turbine grids which have already used in the literature. A new repair operator is recommended, taking into account the distance constraint between two adjacent cells in turbine layout problem, and thus the obtained solutions are made feasible. Furthermore, a levy flight-based IWO (LFIWO) algorithm is developed to optimize the layout of the turbines in wind farm. The basic IWO algorithm and the proposed LFIWO algorithm are compared on 11 different turbine layouts. Experimental studies are carried out for both algorithms under equal conditions with the help of 10 different binary versions. According to the comparisons performed using 11 different grids, LFIWO demonstrates a much superior success than the IWO algorithm. In addition, the proposed 19 × 19 grid reveals the best success among the other grids. When compared to the other studies in the literature, it is seen that LFIWO surpasses the other algorithms in terms of solution quality. As a result, it can be clearly stated that the proposed binary version of LFIWO is a competitive and effective binary algorithm.