A fuzzy Analysis to connect the large-scale distant wind farm to grid in probabilistic multi objective transmission expansion planning

As the share of wind energy in power system increases, consideration of these resources in power system planning, particularly in Transmission Expansion Planning (TEP) is becoming more and more important. In this paper, a Probabilistic Multi Objective Transmission Expansion Planning (PMO-TEP) is presented to find the optimal node for connecting the large-scale distant wind farm to the network from viewpoint of market competition. Furthermore, to investigate the uncertainty associated with wind speed variation and load prediction, a probabilistic analysis tool namely Two-Point Estimate Method (2PEM) is applied. The investment cost of new lines and congestion cost for enhancement of market competition are considered as multifarious objectives in PMO-TEP. Moreover, an overload index is evaluated to ensure that all optimal plans are satisfying the security constraint (n-1 criterion). Here, a Non-Dominated Sorting Genetic Algorithm II (NSGA-II) is utilized to handle the multi-objective optimization. Finally, a fuzzy decision-making analysis is used to obtain the optimal node for connecting the wind farm to the network among all optimal Pareto solutions. Different scenarios are demonstrated on the modified IEEE-RTS to trace the capability of proposed model.