Title: Interactive search algorithm of artificial intelligence for household classification on smart electricity meter data

Authors: M. Suresh; M.S. Anbarasi

Addresses: Department of IT, Manakula Vinayagar Institute of Technology, Pondicherry, India ' Department of IT, Pondicherry Engineering College, Pondicherry, India

Abstract: Smart grid (SG) is a future-generation power system commonly used to maintain electricity demand in a reliable and economic way using the latest information and communication technologies. It enables consumers and micro-energy producers to take a more active role in the electricity market and dynamic energy management (DEM). To maximise the accuracy of dynamic energy detection, research work designs an enhanced swarm-based big data analytics model for DEM in SG. In this paper, an artificial neural network (ANN)-based classification model for predicting future power consumption is proposed. A novel bio-inspired optimisation namely interactive search algorithm (ISA) is used for optimising the weights of the ANN. The results of the proposed model are compared with different performance measures to prove its efficiency. A detailed comparative results analysis takes place and the experimental results ensured the betterment of the proposed models over the state of art techniques. The compared results show the significance of the proposed model over existing algorithms.

Keywords: interactive search algorithm; ISA; classification; smart meter; artificial intelligence; internet of things; IoT.

DOI: 10.1504/IJESMS.2022.123952

International Journal of Engineering Systems Modelling and Simulation, 2022 Vol.13 No.3, pp.183 - 193

Received: 17 Jun 2021
Accepted: 16 Aug 2021
Published online: 05 Jul 2022 *

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