{'fraction_non_alphanumeric': 0.018736988202637056, 'fraction_numerical': 0.0013879250520471894, 'mean_word_length': 5.80188679245283, '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}}
Enhancing the Energy Utilization of Hybrid Renewable Energy Systems

Without question combining two or more renewable energy sources (RES) in hybrid topology can increase the overall system reliability and efficiency especially if they have a complementary nature. However, most RES has an intermittent nature of energy production due to dependency on weather conditions. Therefore, there are big challenges for coordinating between multiple sources of energy to optimize energy utilization. Therefore, this paper introduces a genetic algorithm (GA) based energy management and optimization method for Hybrid Renewable energy Systems (HRES). The proposed technique aims to determine the optimum share of power generation of each source so that minimizing the energy cost and emission and prolonging the battery lifetime. The proposed technique has been tested with an HRES system consists of Solar PV, Wind Generator, and Battery storage. different operating conditions of temperature, Irradiance, Wind speed, Battery status have been considered and tested. Also, the proposed method regards environmental and economical optimization and system reliability and security. The paper introduces the mathematical model of system components and compared the obtained results of simulation work and experimental work for validation under different operating conditions including real temperature, irradiance, wind speed, load profile for 24 hours.