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Title	Cost Minimization In A Smart Grid Using A Genetic Algorithm
ID_Doc	16300
Authors	Wanjala J.; Langa H.M.; Walingo T.
Year	2024
Published	International Conference on Science, Engineering and Business for Driving Sustainable Development Goals, SEB4SDG 2024
DOI	http://dx.doi.org/10.1109/SEB4SDG60871.2024.10630258
Abstract	Demand side management (DSM), which intelligently manages loads, will be a key component of the smart grid of the future. DSM initiatives provide several advantages when implemented through smart city home energy management systems. Utilities operate at lower peak demand, and consumers benefit from lower electricity prices. This research presents a genetic algorithm based DSM model for residential customers' appliance scheduling. The following scenario - smart houses using renewable energy sources - is simulated in the time-of-use pricing environment of the model. According to simulation findings, the suggested approach schedules the appliances in an ideal way, which lowers power bills. © 2024 IEEE.
Author Keywords	Battery Storage System; Demand Side Management; Energy Storage; Genetic Algorithm; Renewable Energy; Schedulable Loads; Smart Grid

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