The purpose of this paper is to relate the issues which have an impact on the interconnection of distributed resources to the utility grid. Impact that can be clearly seen is with respect to the types of distributed resources and the power electronic (PE) devices used to interface them. A balance has to be maintained between the type of DER's and the interfaces in order to get the maximum benefit of incorporating Distributed Generation to the grid. Islanding methods which are the means for creating the microgrids and islanding detection methods are a critical feature. These, together with protection and reliability features have been discussed in the paper.
This paper present the speed control of DC Motor based on boost converter under the controlling of fuzzy logic. The DC motor has armature and field winding in which armature winding is controlled by using boost converter which is triggered by fuzzy logic controller which consist of 7x7 rule and the input are change in error and rate of change of error and output is firing angle. The fuzzy logic controller gives smooth, reliable, efficient speed controlling of DC motor. Further the compative analysis between fuzzy logy and PID controller is assessed. The complete system is designed with SIMULINK/MATLAB for perfect analysis between two methods mentioned.
Electrical load forecasting is an essential feature in power systems planning, operation and control. The non-linearity and non-stationary nature of the data, however, poses a challenge in terms of accuracy. This article explores a deep learning technique, a long short-term memory recurrent neural network-based framework to tackle this tricky issue. The proposed machine learning model framework is tested on real time residential smart meter data showing promising results. A web application has also been developed to allow consumers to have access to greater levels of information and facilitate decision-making at their end. The performance of the proposed model is also comprehensively compared to other methods in the field of load forecasting showing more accurate results for the function of forecasting of load on short term basis.
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