Abstract

The load requirement of a microgrid system fluctuates on an hourly manner. As the load demand rises and falls, utilities set various rates at different hours of the day, which is known as the time-of-usage (TOU) based electricity pricing. The two types of load that make up the microgrid system's hourly demand are elastic and inelastic. Demand-side management (DSM) restructures the entire demand model based on demand-price elasticity by moving elastic loads from peak load hours to those hours when the utility charges less. This research employs a hybrid intelligence method to reduce the total cost of three microgrid systems taking into account the implementation of DSM. Practical complexities like unit-commitment of the dispatchable fossil fuelled generators were considered. Numerical results project noticeable savings ranging from 8% to 18% for all the test systems when the DSM strategy was incorporated. A detailed comparative analysis with the results available in the literature corroborates the effectiveness of the proposed hybrid approach. Measures of central tendencies, non-parametric statistical analysis and algorithm execution time show better results of the hybrid optimization tool presented in this paper.

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