{'fraction_non_alphanumeric': 0.009251471825063078, 'fraction_numerical': 0.0, 'mean_word_length': 5.574585635359116, '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}}
Novel application of differential evolution algorithm for estimating fuel cost function of thermal generating units

Fuel cost curve of thermal power plants are generally based on steady state measurements and are constantly influenced by several aspects such as the operating temperature and oldness of generators. Therefore, it is very important to periodically update the coefficients of fuel cost characteristics in order to reflect changes in operating conditions and ensure economic operation of power systems. This paper proposes a novel application of differential evolution (DE) algorithm for estimating the optimal parameters of fuel cost curves of thermal units. The estimation problem is converted into a minimization problem, where the objective function is the total absolute error to be minimized. The performance of the proposed method is demonstrated through several test cases using different models of the generator fuel cost curve. The results of the proposed approach are compared with other methods published in the literature. The comparison results confirm the effectiveness and superiority of the proposed DE algorithm for solving the described estimation problem.