The depletion of natural resources and the intermittence renewable energy have pressed need for a hybrid microgrid, combining benefits both AC DC microgrids, minimizing overall deficiency shortcomings increasing reliability system. microgrid also supports decentralized grid control structure, aligning with current scattered concentrated load scenarios. Hence, there is an to explore reveal integ...

Neural networks (NNs) are discriminative classifiers which have been successfully integrated with hidden Markov models (HMMs), either in the hybrid NN/HMM or tandem connectionist systems. Typically, the NNs are trained with the framebased cross-entropy criterion to classify phonemes or phoneme states. However, for word recognition, the word error rate is more closely related to the sequence cla...

Optimization of energy management in hybrid SOFC-based DC microgrid considering high efficiency and operating safety as external load power rises, has superiority time response, output efficiency, thermal response avoiding fuel exhaustion.

In order to study the influence of system parameters on the stability and dynamic performance of combination-configuration microgrid based on droop control, small-signal model is established at the point of steady state. By calculating the eigenvalues of state matrix, the small-signal stability of combination-configuration microgrid can be directly analyzed. Based on sensitivity analysis, the k...

In this paper, a new formulation for discriminative training of HMMs is presented. This formulation uses a properly trained MLP in a simple interconnection with HMMs called “Cascade HMM/ANN Hybrid”. Our training algorithm has simple realization in comparison with other discriminative training for HMMs such as MDI and MMI. We also present a rigid mathematical proof of its convergence. We found t...

We introduce a novel way to employ codebooks trained by Learning Vector Quantization together with hidden Markov models. In previous work, LVQ-codebooks have been used as frame labelers. The resulting label stream has been modeled and decoded by discrete observation HMMs. We present a way to extract more information out of the LVQ stage. This is accomplished by modeling the class-wise quantizat...

Power availability from renewable energy sources (RES) is unpredictable, and must be managed effectively for better utilization. The role that a hybrid storage system (HESS) plays vital in this context. Renewable along with systems can provide power management DC microgrid environment. In paper, the optimal PI-controller-based proposed effective utilization of power. model, PI controller develo...