Discrete complex-valued code pathfinder algorithm for wind farm layout optimization problem

Abstract

• A discrete complex-valued code pathfinder algorithm (DCPFA) has been proposed. • The DCPFA algorithm’s exploration and exploitation abilities were improved. • The DCPFA is applied to solve wind farm layout optimization (WFLO) problem. • The experimental results show that DCPFA found solutions have lower cost values per unit of power. In wind farm planning, it is necessary to optimize the location of turbines to reduce the influence of eddy currents between each other and generate more energy. This problem is also transformed into a discrete optimization problem, it is named wind farm layout optimization (WFLO) problem, to solve this optimization problem we can obtain the optimal turbine placement scheme. With the complexity of wind condition in WFLO problem increases, it becomes very difficult to solve, so more and more researchers use metaheuristic algorithms to solve this problem. Improve the solution accuracy of the WFLO problem, it will increase renewable energy use and lowering carbon emissions. In order to improve the solution accuracy of WFLO problem, a discrete complex-valued code pathfinder algorithm (DCPFA) has been proposed in this paper, and used to solve the WFLO problem. In DCPFA, the algorithm’s exploration ability was improved, and the algorithm achieves a balance between exploration and exploitation. To test the performance of DCPFA in solving the WFLO problem, two complex wind conditions in wind farms are simulated. Comparing the results with other famous metaheuristic optimization algorithms and recently published literature, the DCPFA found a solution that will have lower cost values per unit of power, such as DCPFA’s solution in wind condition (1) can output 34120(KW), it is bigger than RSA’s 32498(KW) and GA’s 32038(KW), DCPFA’s solution in wind condition (2) can output 19375(KW), it is bigger than SSA’s 17781(KW) and BPSO-TVAV’s 15796 (KW). More importantly, in the objective function (Cost/KW), DCPFA is also ranked first in two wind condition. According to the experimental results, it can be explained that DCPFA’s effectiveness and robustness in solving WFLO problems.