{'fraction_non_alphanumeric': 0.016910069177555727, 'fraction_numerical': 0.0, 'mean_word_length': 5.78125, '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}}
A comparative study on particle swarm optimisation algorithms for economic dispatch with multiple fuels

Economic dispatch (ED) is one of the essential functions in the operational planning of power systems that is to determine the optimum scheduling of generation at a particular time that minimises the total production cost while satisfying the operating constraints. A number of computation techniques have progressively been proposed to solve this important issue. One of them is a particle swarm optimisation (PSO), which belongs to the evolutionary computation techniques, and shows superiority to other evolutionary computation techniques in terms of less computation time, easy implementation with high quality solution, stable convergence characteristic and independent from initialisation. Accordingly, this paper presents the three traditional PSO algorithms to solve the ED problem with smooth cost function and multiple fuels. Furthermore, the comparative study on the three PSO algorithms have been implemented so as to investigate the ability among the PSO algorithms in terms of solution quality, frequency of convergence, convergence characteristic, as well as diversity characteristic. The simulation results are also compared with those obtained by the state-of-the-art algorithms.