MATLAB Source Program for Distribution System Reliability Assessment Using Antithetic Sampling Monte Carlo Method

This MATLAB source program implements the antithetic sampling Monte Carlo method for assessing distribution system reliability. A distribution system refers to the transmission and distribution network spanning from substations to end-user electrical loads. The system must maintain continuous power supply to customers to ensure normal electricity consumption. The program employs the antithetic sampling Monte Carlo technique, a widely-used approach for evaluating distribution system reliability. This method is grounded in probability theory and stochastic process principles, simulating various system failures and random events to compute reliability indices. The implementation includes variance reduction through antithetic variates, where paired simulations with negative correlation are generated to improve computational efficiency. MATLAB provides robust mathematical computation and visualization capabilities, facilitating efficient implementation of the antithetic sampling Monte Carlo method. The code structure typically includes: - System component failure rate modeling using probability distributions - Random number generation with antithetic pairing for variance reduction - System state sampling and contingency analysis - Reliability index calculation (SAIDI, SAIFI, etc.) - Statistical analysis and convergence monitoring Key functions utilized include random number generators, statistical analysis tools, and custom algorithms for system state evaluation. The program outputs comprehensive reliability metrics with reduced computational variance compared to standard Monte Carlo approaches.