Online load frequency control in wind integrated power systems using modified Jaya optimization - Pradhan, Chittaranjan; Bhende, Chandrashekhar N. (Engineering applications of artificial intelligence, 2019)
The Jaya optimization algorithm is recognized as a simple and faster population-based heuristic search algorithm. However, due to the absence of algorithm-specified parameter, its performance may degrade in terms of convergence speed and obtain the optimal value for the real-world complex optimization problems which are usually nonlinear and non-differentiable in nature. To deal with the aforesaid scenarios, a modified Jaya optimization algorithm (MJOA) is proposed by considering a weight parameter in the search process. Two methods are proposed on the basis of the selection of weight parameter, one is a linear weight (LW) and the other is a fuzzy logic based mechanism. It is found that MJOA is quite accurate and faster in convergence for complex problems. The proposed MJOA has used for online tuning the controller parameters of automatic generation control (AGC) of wind integrated power system. Further, a frequency deviation tolerance concept is proposed to reduce the number of executions of MJOA. The proposed methodology helps in recovering the frequency excursions of the power system with a faster convergence performance and requirements of less computational burden. Such features are very important in smart-grid operational necessities for improving its stability performance. The real-time simulation studies are carried out on an embedded platform using xPC target board of the wind farm integrated IEEE-39 bus test system. •Modified the JAYA optimization algorithm (MJOA) by embedding weight parameter.•Linear weight and fuzzy-based methods are implemented to vary the weight parameter.•The MJOA is successfully tested for online load frequency control in power system.•Frequency deviation tolerance concept to reduce the number of executions of MJOA.