{'fraction_non_alphanumeric': 0.029118136439267885, 'fraction_numerical': 0.0, 'mean_word_length': 5.6098901098901095, '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}}
Performance analysis of Solar PV-diesel based autonomous hybrid power system using FFA and CSA optimized controller

This paper presents a comparative performance study of Cuckoo Search Algorithm (CSA) and Firefly Algorithm (FA) optimized proportional plus integral (PI) controller for the frequency control of solar-diesel-fuel cell-battery-aqua electrolyser based autonomous hybrid power system. In such an autonomous hybrid power system, infinite bus concept is not applicable. Therefore, with changing load, generation or both, power system frequency deviates from the nominal value. Thus, controllers are used to mitigate this frequency deviation. There are several tuning rules for obtaining the controller parameters, such as manual tuning, Ziegler Nichols tuning, Cohen-coon tuning etc., however, complexities arise during their implementation. Moreover, recent trend is to use automatic tuning. In this paper, parameters of controllers are tuned by CSA and FA under certain disturbance conditions of the hybrid power system. The simulation results reveal that performance of CSA optimized controllers are better than FA optimized controllers in terms of settling time, overshoot, oscillations.