This paper compiles, summarizes, and deliberates over one hundred important works on the different approaches and advances in the surveillance and diagnosis of the internal status of SF ₆ gas-insulated equipment (GIE), particularly partial discharge (PD) diagnosis in gas-insulated switchgear (GIS), and the proposed diagnosis techniques used. This review focused on four research aspects on PD diagnosis related to the SF ₆ decomposition mechanism under PD activity, the developments in PD detection techniques, PD sources identification, and PD severity evaluation. Besides, the effect of various factors such as gas pressure, applied voltage, and impurities on the deterioration of the insulation gas and its influence on the diagnosis process has been reviewed. Currently, some reviews on PD diagnosis in SF ₆ -insulated switchgear have been presented and analysed; however, to date, most of them tend to focus on various PD detection techniques in GIS, while others are not extensive and comprehensive reviews. Unlike the available review publications, this paper highlighted various aspects of PD diagnosis in GIS and created a base for further development. The research trend in this field is expected to be directed toward a comprehensive assessment. This review provided a position of the current PD diagnosis in GIS studies and developments that can be a guideline for researchers for further research on the topic’s actual impact in the field.

In this paper, the optimal allocation of constant and switchable capacitors is presented simultaneously in two operation modes, grid-connected and islanded, for a microgrid. Different load levels are considered by employing non-dispatchable distributed generations. The objective function includes minimising the energy losses cost, the cost of peak power losses, and the cost of the capacitor. The optimization problem is solved using the spotted hyena optimizer (SHO) algorithm to determine the optimal size and location of capacitors, considering different loading levels and the two operation modes. In this study, a three-level load and various types of loads, including constant power, constant current, and constant impedance are considered. The proposed method is implemented on a 24-bus radial distribution network. To evaluate the performance of the SHO, the results are compared with GWO and the genetic algorithm (GA). The simulation results demonstrate the superior performance of the SHO in reducing the cost of losses and improving the voltage profile during injection and non-injection of reactive power by distributed generations in two operation modes. The total cost and net saving values for DGs only with the capability of active power injection is achieved 105,780 $ and 100,560.54 $, respectively and for DGs with the capability of active and reactive power injection is obtained 89,568 $ and 76,850.46 $, respectively using the SHO. The proposed method has achieved more annual net savings due to the lower cost of losses than other optimization methods.