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Load sharing, as an important challenge in microgrids (MGs), is realized commonly via a droop control method. Conventional droop control methods are not applicable in unpredictable renewable energy sources (RESs) like photovoltaic (PV) and wind turbines (WT) because their output power depends on the weather conditions and can be extracted only if these free sources are available. This paper considers two operating modes for these types of sources as Maximum Power Point Tracking (MPPT) and DC-link Voltage Control (DCLVC). These power sources usually operate in the MPPT mode unless the load of the MG drops to a lower level compared to the maximum power generation by RESs, in which case the sources switch to the DCLVC operating mode. This study proposed a method based on enhanced droop control, which helps RESs to choose their control mode locally without communication and share the demand of the AC MG with other dispatchable sources besides supplying its maximum power. The proposed method focused on supplying MG load from RESs as much as possible and simplicity in implementation. MG frequency helps the proposed controller to select its operation mode. Enhanced control for DC link voltage control is offered for inverter-based RESs. The validity of the proposed method is approved by simulations in the MATLAB/SIMULINK environment. [ABSTRACT FROM AUTHOR]

Summary: Transformers as 1 of the most important and expensive equipment of power network are under continuous exposure of faults. Periodic examinations for detecting and locating trivial deformation occurrences are indispensable for preventing their unexpected outage and costly, time‐consuming repair procedure. The most crucial step for fault detection is obtaining parameters of the detailed model. Acquiring parameters of the detailed model (APDM) is a nonlinear, nonconvex, and large‐scale problem that requires a powerful method to be solved. This paper proposed a novel method that gains benefit from new efficient functions of Fourier series coefficient and phase functions, an adaptive version of the PSO and fast calculation of coupled network matrices, to solve the problem. Experimental results on 2.64 and 120 kV set of transformer windings, constructed for this study, verified the precision of the proposed method for discovering the position and severity of the disk space variation fault. [ABSTRACT FROM AUTHOR]