Random Numbers Generation for Lifecycle-Cost Analysis of Energy Consuming Equipment

Lifecycle Cost Analysis has a key role in the development of energy efficiency standards for appliances, lighting, and other equipment. The analysis includes Monte Carlo simulations to estimate – from a sample of thousands of consumers with diverse profiles – the net-present value of all, lifetime costs associated with a piece of equipment to provide a certain amount of energy service. This report introduces a set of pseudo-random number generation functions developed in MS Excel VBA to support those simulations. It further compares the effectiveness of these functions to the effectiveness of similar ones available in a broadly used commercial software program. The effectiveness of the functions is evaluated from 17 sets of 1000 samples, each sample comprised of 10,000 pseudo-random numbers drawn from custom uniform, normal, triangular, Weibull and categorical distributions. All samples pass three relevant tests of pseudo-randomness, namely long period, uniformity and independence. The samples also prove to be statistically equivalent to their corresponding peers generated by the commercial software program.