This paper presents a new method using GADS Toolbox in MATLAB (A Genetic Algorithm Approach) to find the optimal solution of optimal power flow based transmission losses. Optimal power flow (OPF) is a key area of concern in electric industries. The basic OPF solution is obtained with objective function as production cost minimization while satisfying a set of system operating constraints. For reactive power optimization the OPF problem is formulated as minimization of system active power losses and improvement in voltage stability of the system. In this paper GA based optimal power flow solution is presented for IEEE 30-bus test power system with objective as transmission losses minimization and optimal results by GA are also compared with solution obtained by using Particle Swarm Optimization Technique.

This paper presents the application of GeneticAlgorithm (GA) for solving optimal power flow problems. It is animportant tool for performance analysis of many power systemsproblems. Optimal power flow (OPF) is of very muchsignificance in power system operation analysis underderegulated environment of electricity industry. The OPFoptimizes a power system operating objective function, whilesatisfying a set of system operating constraints. The basic OPFsolution is obtained with production cost minimization as theobjective function and the optimal settings of the power systemare determined. OPF can also be formulated for reactive poweroptimization, as minimization of system active power losses andimproving the voltage stability in the system. In the presentpaper objective function is to reduce transmission losses usingGA, a IEEE 30-bus test power system is studied for optimalpower flow. It is described in the paper that GA based optimalpower flow can provide optimal solution

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In 2008, the launch of the Tesla proved to the public electric vehicles' ability to fuel and greenhouse gases reduction in the transport sector. It brought the worldwide spotlight on electric vehicles when, because of increased demand and fossil fuel prices, they reached unexpectedly high and developing countries needed strong economic growth. The capacity for energy storage by electric cars as well as the likely random discharge and loading of the grid are important challenges in operation and maintenance. The Optimal preparation techniques are important for large number of vehicles to be incorporated with the smart grid and electric vehicles. Greenhouse gas emissions are one of the major environmental problems and their emission rates are rising more quickly with rapid industrialization. This can be overcome by solar energy for transport. The purpose of the work proposed is to include a technology that supports green energy. The presented research underlines the functional properties of electric vehicle and illustrated literature review on recent developments of electric vehicles. The research paper also explains the fundamental components of electric vehicle incorporated with solar photovoltaic system. Research is useful in understanding properties and challenges in the field of electric vehicles. This research also involves the characteristic analysis of electric vehicles using mathematical modeling and design simulation. The secondary goal of this research is to implement the photovoltaic solar energy plant's equivalent design model. The solar photovoltaic system mathematical model has implemented using the MATLAB for maximum power point monitoring using the Cuckoo search algorithm.

This paper proposes a discrete Meyer wavelet transform (DMWT)-based evolving faults recognition system for the two-terminal series capacitor compensated transmission line (TTSCCTL). The particular region captured currents of the TTSCCTL are used to estimate the DMWT outputs. To authorize the performance of the DMWT, simulation studies have been done thus varying fault type, resistance, and switching time. The main advantage of DMWT is that it correctly recognizes all types of evolving faults in TTSCCTL by employing one-side fault current data only. It is also investigated that the proposed technique is robust to the deviation in the input fault parameters of TTSCCTL.