An explorative optimization algorithm for sparse scheduling in-home energy management with smart grid

Abstract

Purpose

Electricity utilization at electricity peak hour may differ from every single administration region, for example, mechanical region, business territory and residential zone. This paper introduces a demand-side load management (DSM) strategy, which is one of the utilization of smart grid (SG) that is fit for controlling loads inside the residential working so that the client fulfillment is augmented at least expense.

Design/methodology/approach

In this paper, a heuristic algorithms-based energy management controller is intended for a residential region in a SG. Here, Antlion Optimization technique is used for DSM techniques such as load shifting, peak clipping, and valley filling in the residential sectors for 24 h with the help of stochastic function to determine the detection of random distribution of the load.

Findings

This proposed algorithm offered the greatest fulfillment and least expense caused by the consumers when compared to the traditional cost by taking the individual consumer preferences for the loads and the ideal time scheduling for the load, which is obtained from the rebuilding trap.

Originality/value

Simulation results demonstrate that the comparison of the cost incurred by the users obtained by the DSM techniques is satisfiable.

Citation

Gajula, V. and R., R. (2020), "An explorative optimization algorithm for sparse scheduling in-home energy management with smart grid", Circuit World, Vol. 46 No. 4, pp. 335-346. https://doi.org/10.1108/CW-06-2019-0057