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At present, wind energy industry is facing major design constraints in boosting the power output. These can be overcome by setting up the right turbine at the right place. This paper proposes an optimized layout design of a wind farm by using Definite Point selection(DPS) and genetic algorithm, which can minimize the cost per unit power and minimum wake effects, while sustaining the obligatory space between adjacent turbines for operation safety. The existing cost per unit power can be reduced by changing the dimensions of wind farm with constant area. In this study, the velocity deficits caused by the wakes of each turbine were calculated by using Jensens wake model. The total area of wind farm 2 Km x 2 Km was divided into 10x10 cells with each cell having dimensions 200 m x 200 m. The results showed that power output of the wind farm by using the same area in different dimension was increased even when the total numbers of wind turbines were the same. It was observed that 32 wind turbines in 2 Km x 2 Km area could produce a total power of 16,251.56 kW with fitness value of 0.001537. The present research results had been validated using the results from previous studies.

The optimized network reconfiguration and Distributed Generations (DG) sizing with allocation instantaneously via Particle Swarm Optimization (PSO) proposed a new way of allocation DG based on low voltage profile. This method consists of three steps. It started with categorized the switching sequences for radial network configuration while observe the P losses and the profile of voltage without DG. The second step is reconfiguration feeder for reduce losses via DGs allocation based on substations geographical location. The final step is sizing and allocation DGs at each bus with low voltage profile produced from the first step, used to mend the voltage profile and minimize the Plosses also compared the result with the geographical based allocation results. The objective of this study is to mend the voltage profile while decreasing the Plosses by using optimization technique considering network reconfiguration, DGs Sizing and allocation concurrently. Four cases are compared which is case 1 is the initial case and taken as a reference. All three stages are tested on standards IEEE 33 bus system by using Particle Swarm Optimization (PSO) technique in MATLAB software. This method proved that improvement of Plosses and voltage profile has been made by change of the switching topology with DGs sizing and allocation technique respectively.