{'fraction_non_alphanumeric': 0.01288659793814433, 'fraction_numerical': 0.0, 'mean_word_length': 5.472222222222222, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Monte Carlo simulation of residential electricity demand for forecasting maximum demand on distribution networks

The prevalent engineering practice (PEP) for maximum demand estimation in low-voltage (LV) electricity networks is based on an After Diversity Maximum Demand (ADMD) modified by a diversity factor. This method predicts the maximum likely voltage drop accounting for consumer diversity. However, this approach does not take into account the stochastic nature of the demand and is inconsistent with international power quality standards. We present a Monte Carlo simulation model of consumer demand taking into account the statistical spread of demand in each half hour using data sampled from a gamma distribution. The parameters of the gamma distribution are based on data metered at a number of residential properties fed by one transformer. The simulated demand is corrected for temperature and total consumption. The simulated profiles at the residential properties are aggregated and the simulated maximum demand is compared with actual maximum demand at a given transformer and an entire distribution network showing good agreement in both cases.