An optimal design of droop controller of a De-loaded PV system using nature-inspired algorithms

In photovoltaic (PV) penetrated systems, the active power support from PVs is expected during the load change situation to maintain the stability of the power system. The de-loading approach is common in PVs for generating an active power reserve, in this mode of operation (de-loading), the PVs are operated away from maximum power point resulting in an active power reserve. Most of the existing literature works have focused on developing an active power reserve in PVs but not on utilizing this reserve during a contingency condition. In this paper, a PV frequency regulation controller is developed which can optimally utilize the generated active power reserve for controlling the system frequency for load increase and decrease situations. In contrast to the other PV frequency regulation controllers, in this work, the gain value of the controller is not tuned using arbitrary or any other hit and trail methods, here, the value of the controller is tuned using the nature-inspired algorithms. Seven algorithms are used for obtaining the gain values; these values are tested on a single area and multi-area load frequency model in the SIMULINK software, the outputs obtained using these different values of gain are compared for different case scenarios. The obtained results indicate that for a sudden 15% load increase event in a single and multi-area models, a minimum frequency deviation of 0.3908 hz and 0.3076 hz is observed respectively when Firefly Algorithm is employed for gain optimization.