Optimization of Electricity Consumption Using Evolutionary Algorithms

This paper offers optimized values of electricity consumption for a smart home which has different appliances working round the year. Two evolutionary algorithms, Particle Swarm Optimization (PSO) and Cuckoo algorithm have been used to predict the optimal value of the energy consumption in a given weather. The results of both algorithms have been studied in different temperature slabs and further compared to formulate a hypothesis to explain the reason of a certain optimal value for a given weather. The dataset of smart homes was taken from Kaggle and it had the information of appliances as well as the weather. The redundant and unimportant factors have been eliminated using statistical techniques and the consumption data was applied on both the algorithms and the trends were studied. It was concluded that the optimal consumption values vary according to external factors, temperature playing a major role.

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Gupta, Deepak and Tilwalia, Ritika and Jain, Anisha, Optimization of Electricity Consumption Using Evolutionary Algorithms (April 1, 2020). Proceedings of the International Conference on Innovative Computing & Communications (ICICC) 2020, Available at SSRN: https://ssrn.com/abstract=3565796 or http://dx.doi.org/10.2139/ssrn.3565796