{'fraction_non_alphanumeric': 0.020066889632107024, 'fraction_numerical': 0.002229654403567447, 'mean_word_length': 5.554744525547445, '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}}
DG Capacity Assessment in Distribution Network Considering Uncertainties Using Multi-Parametric Programming

With the penetration of distributed generation (DG) growing in actives distribution network (ADN), the operational uncertainties are raised as well as reversal power flow in ADN. In order to adequately dissipate the DGs in the distribution networks, the study of distributed power capacity assessment is indispensable for DGs' planning and construction. This paper proposes a new multi-scenario optimization method by introducing the multi-parametric programming. The random parameters are analyzed in the parameter space, and the parameter space is divided into several critical regions. In this way, the optimal result can be represented as functions of random parameters in each critical region. The tests on the IEEE 33 buses system shown the proposed algorithm correct and efficient.