Soumya R. Mohanty

TL;DR: In this paper, the power quality disturbances in terms of statistical features are classified distinctly by use of modular probabilistic neural network (MPNN), support vector machines (SVMs), and least square support vector machine (LS-SVM) techniques.

TL;DR: In this article, a load frequency control (LFC) problem is presented using different optimization algorithms for two types of power system configurations: (i) hybrid configuration of thermal power system (TPS) integrated with DG, comprising wind turbine generators (WTGs), diesel engine generators (DEGs), fuel cells (FCs), aqua-electrolyzer (AE) and battery energy storage system (BESS), and two area interconnected power system with DG connected in area-1.

TL;DR: In this paper, a generalized neuron model is used for forecasting the short term electricity price of Australian electricity market, the preprocessing of the input parameters is accomplished using wavelet transform for better representation of the low and high frequency components, the free parameters of the generalized neurons model are tuned using environment adaptation method algorithm for increasing the generalization ability and efficacy of the model.

TL;DR: In this paper, small-signal analysis of isolated as well as interconnected autonomous hybrid distributed generation system for sudden variation in load demand, wind speed and solar radiation is presented, where ultracapacitors (UC) as an alternative energy storage element and interconnection of hybrid systems through tie-line is incorporated into the system for improved performance.

TL;DR: In this paper, the classification of islanding and power quality (PQ) disturbances in grid-connected distributed generation (DG) based hybrid power system is presented, where five different types of disturbances are considered for the classification problem.