Optimal wind farm placement considering system constraints and investment and uncertainty costs

Traditional methods of planning investment in Wind Energy Conversion Systems (WECS) focus on selecting sites that individually display the maximum total extractable wind energy. However, cost penalties associated with the uncertainty in Wind Power Production (WPP) may be non-negligible. This paper proposes a more holistic methodology to find the near optimal investment in WECS considering capital costs, uncertainty costs of WPP, and traditional thermal generator costs. The optimal number of turbines to be placed at each potential wind site is found system parameters using Particle Swarm Optimization (PSO), and DC Optimal Power Flow (DCOPF) is used to compute the merit of each candidate solution. The IEEE 14 Bus System is used. Potential wind sites are preselected, and WPP of each site is characterized by a probability distribution function. The impact of the investment costs and transmission capacity on the merit of spatial diversity of wind farms is discussed.