A mixed-integer quasi-convex optimization model for joint transmission network and wind power investment problem

As one of the important renewable energy sources (RESs), the integration of wind energy into the electric grid is growing fast. This higher penetration level of wind power calls for requirements for reinforcing the existing transmission network to reduce wind power curtailment. In this context, this research focuses on developing a mathematical methodology for joint transmission network and wind power investment problem under a centralized approach. Unlike the existing models, where the objective function to be minimized is the overall cost, the objective function of this work is different. It is defined as the ratio of the total cost to the total wind power generation. The definition of this objective function allows the operator to minimize the total cost while maximizing the wind power output from wind farms. The convex AC power flow is utilized to model the power flow equations. The proposed investment model is mixed-integer quasi-convex programming (MIQCP) that is converted into a mixed-integer convex programming (MICP) problem. The numerical study indicates that the resulting MICP problem is computationally efficient, making it suitable for a realistic electric grid. In addition, it will promote the wind power output of wind farms.