{'fraction_non_alphanumeric': 0.02056555269922879, 'fraction_numerical': 0.0, 'mean_word_length': 5.282258064516129, '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 novel GA-ANFIS hybrid model for short-term solar PV power forecasting in Indian electricity market

Abstract Solar photovoltaic (PV) power is a most important green energy source of electricity. Accurate solar PV power forecasting is a vital requirement for integration of PV power with electricity grid, stability of grid and its management. This paper proposed, a novel hybrid model, combining genetic algorithm (GA) and adaptive network based fuzzy inference system (ANFIS) for short term solar PV power forecasting in Indian electricity market. The developed hybrid model is applied for study of PV power forecasting in Indian electricity market. Performance of developed model is compared with four different models and proposed model has given more accurate forecasting.