In this paper we have proposed a non- linear mathematical model for a wind turbine. The objective function maximizes the power of the wind turbine and the constraints are related to the rotor and tower costs. Rotor diameter and hub height are the variables which affect on power of the wind turbine, so we have considered them as decision variable in our mathematical model. By increasing rotor diameter and hub height the power of the turbine will increase but the costs don’t let the infinitive increase in rotor diameter and height. The model applied for a typical case study and the results of solving the model for it have shown in the paper.
Wind energy and its conversion is part of renewable energy resources as cheaper and cleaner energy today even though the initial cost varies from place to place. Most of the government sector always promotes renewable energy with a provision of subsidies as observed worldwide. Wind energy is an actual solution over costlier conventional energy sources. If it is not properly placed and the selection of turbine design is not up to the mark, then investments may require more time to acquire Net Profit Value called as NPV. This research work is focused on the development of mathematical models to optimize the turbine size and locations considering all constraints such as the distance between the turbines, hub height, and investment in internal road and substation cost. Particle-Swarm-Optimization is an intelligent tool to optimize turbine place and size. The database management system is selected as the appropriate data storage platform for before and after optimization simulation. Various plots and excel outputs of .net programming are addressed for the success of optimization algorithms for the purpose of wind turbine placement and WTG design is suggested to manage wind energy such that power system reliability has been improved and the same is monitored through the reliability indices.