{'fraction_non_alphanumeric': 0.013071895424836602, 'fraction_numerical': 0.0009337068160597573, 'mean_word_length': 5.871794871794871, '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}}
Solving an Electricity Generating Capacity Expansion Planning Problem by Generalized Benders' Decomposition

This paper discusses application of generalized Benders' decomposition in a model for planning least-cost investments in electricity generating capacity subject to probabilistic reliability constraints. The planning problem is decomposed into a set of subproblems, each representing the operation of a set of generating plants of fixed capacity in 1 year, and a master problem, representing optimal capacity investments over the entire planning horizon. The subproblems are solved using a procedure called probabilistic simulation, which calculates the expected cost of operating the generating system, the reliability level, and dual multipliers reflecting the value of small changes in the plant capacities. The master problem is a linear program which uses these dual multipliers to approximate the nonlinear cost and reliability functions. The solution to the capacity expansion problem is found by iteratively solving the master problem and the subproblems.