A clustering‐based technoeconomic analysis for wind farm and shunt capacitor allocation in radial distribution systems

Summary This article investigates a clustering‐based approach to simultaneously seek the optimal allocation of wind farm (WF) and shunt capacitor (SC) in distribution systems. The stochastic nature of wind turbines leads the allocation problem to become more intricate nowadays. Hence, the application of probabilistic methods for this stochastic analysis is a vital requirement. This study implements a K ‐means clustering method to bunch the wind turbines output power into appropriate clusters. Then, the data, clustered by K ‐means, are directly used in the Monte Carlo calculations. This results in computational burden reduction. The optimization process is performed by particle swarm optimization (PSO) methodology. The decision variables of PSO are the location and capacity of WF and SCs. The energy loss cost and investment costs of WF and SCs are selected as the objective functions for the proposed optimization problem. The proposed optimal allocation methodology is implemented on several benchmark IEEE case studies to illustrate its effectiveness and thereby to draw the relevant conclusions.