{'fraction_non_alphanumeric': 0.017527675276752766, 'fraction_numerical': 0.0, 'mean_word_length': 5.458333333333333, '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}}
Optimal model predictive control of photovoltaic plants for frequency regulation in an interconnected power system

Due to growing development of photovoltaic (PV) plants in power systems, they are capable to provide ancillary service for frequency regulation. PV plants provide the required reserve of generation through operating below the maximum power point tracking. This paper proposes a model predictive control (MPC)-based approach for power control of PV plants contributing towards load frequency control (LFC). In MPC, the control signals are provided through optimizing a cost function which includes the plant model as well as current and past signals of the system. Since the successful performance of the controller depends on the well-adjusting of its weights, the weights of the controller are regulated by sine cosine algorithm to earn an optimal performance. Comprehensive discussions are presented on a three-area interconnected power system. The effectiveness of the proposed scheme is demonstrated through case studies and thereby relevant conclusions are drawn.