iosr-JEEE   Volume-5 ~ Issue-4

Abstract: Numerous optimization paradigms have been developed for power system optimization tasks till date but none has found the level of acceptance which is being received by evolutionary soft computing methods. Traditional methods are found to be inefficient for complex practical problems with equality and inequality constraints therefore the complexity of the task reveals the necessity for development of efficient algorithms to accurately locate the optimum solution. The present paper proposes to solve complex constrained optimization problems using differential evolution (DE) with multiple mutation strategies. The role of control parameters and mutation strategies of DE algorithm in achieving the global best result is critically explored.The depleting reserves of fossil fuel and growing concern about environmental protection dictates the integration of renewable power resources into the power grid. Including wind power with the conventional power has become very popular in recent years due to the rapid development of technology in this field. Modeling of wind-thermal system is required to find the optimal wind generator capacity that can be integrated into the existing system such that all operating constraints are satisfied. The developed algorithm is tested on a standard test system taking into consideration the wind uncertainty and ramp-rate limits of thermal power units. The results clearly demonstrate the effectiveness of the proposed method in finding feasible and efficient globally optimal solutions

Keywords - Differential evolution, equality and inequality constraints, mutation strategies, wind-thermal economic dispatch

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Abstract: Mammography is an efficient and contemporary option in diagnosing breast cancer among all ages of women. Nevertheless, the radiologist's has remarkable influence on revelation of the mammogram. It is a difficult and challenging task in identifying the masses in the breast region of a digital mammography. The proposed research intends to develop an image processing algorithm in identifying malignancy by using an automated segmentation technique for mammogram. The proposed work deals with an approach for extracting the malignant masses in mammograms for detection of breast cancer. The work proposed is based on the following procedure: (a)Removing the noise and the background information. (b)Applying thresholding and retrieving the largest region of interest (ROI). (c)Performing the morphological operations and extracting the ROI and identifying the malignant mass from the screened images of the breast. This method was tested over several images of various patients taken from a cancer hospital and implemented using Matlab code. Thus, capable in executing the pre-processed image effectively and detected the segmentation region and identified the malignant data for assessment.

Keywords - Malignancy , Mammogram, Morphological, ROI, Segmentation, Thresholding.

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Abstract: In this age of depleting fossil fuels, more emphasis has to be placed on the renewable sources of energy. People are conscious about a clean and pollution free environment and thus a primary candidate in this respect would be solar energy. In this paper the maximum power point of a PV system is tracked using a fuzzy logic controller. The advantages of a fuzzy logic controller are that it is robust, doesn't require the exact knowledge of the model and is relatively simple to design. Using an FLC (fuzzy logic controller) is considered as an intelligent method of maximum power point tracking.

Keywords – Fuzzy logic controller, Maximum power point tracking, MPPT algorithm, Photovoltaic system

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