Determining available transfer capability (ATC) plays a significant role in a deregulated electricity market. ATC provides valuable information regarding the remaining transfer capability, after meeting existing commitments, for system operators and market participants. In recent times, the penetration of wind power generation is increasing significantly in modern power systems. Wind power generation is highly intermittent and uncertain. In literature, ATC is calculated with uncertainty in wind power generation using probabilistic density functions (PDFs). However, the PDFs of wind power generation are not always easily available. Interval arithmetic is an efficient way of representing an uncertain variable without the need of PDF of that particular uncertain variable. Relative distance measure (RDM) arithmetic is one of such interval arithmetic methods. In the proposed work, uncertainty in wind power generation is modeled using relative distance measure arithmetic. The optimization problem for finding ATC range with uncertainty is posed as two continuous linear programming problems (LPPs) in RDM-arithmetic. As LPP is convex inherently, the proposed RDM-arithmetic based ATC calculation method guarantees a globally optimal solution. The proposed RDM-arithmetic method is tested on IEEE 30-Bus and IEEE 118-Bus systems. The simulation results are compared with Monte Carlo simulation (MCS) based ATC and interval arithmetic ATC. It is observed from the simulation results that MCS underestimates ATC bounds and interval arithmetic overestimates. It is also observed and found that the proposed RDM-arithmetic based ATC calculation method takes significantly less computational time as compared to MCS and interval arithmetic-based ATC calculation method.