{'fraction_non_alphanumeric': 0.013568521031207599, 'fraction_numerical': 0.0027137042062415195, 'mean_word_length': 4.811023622047244, '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': 1, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Design and Development of BP Neural Network-based Wind Power Prediction System of Dechang Wind Farm

In this paper, Sichuan Dechang Wind Farm is taken as the research object. A wind power prediction model is established based on the BP neural network, the weight and the threshold of the BP neural network are optimized with FOA algorithm, and the wind power in the next 24h is predicted based on the numerical weather prediction and historical operation data. A wind power prediction system of Dechang Wind Farm is designed and developed based on the actual business requirements of the power plant. Based on the tests, this system operates stably and reliably, which can provide reference for wind power prediction of other wind farms.