Work

AI-based model for Prediction of Power consumption in smart grid-smart way towards smart city using blockchain technology

Year: 2024

Type: article

Abstract: A smart city is an urban area that is safe, economically successful, and gives its residents great living conditions by allocating resources in the best way possible. Smart grid (SG) is the financial benefits of a complicated and smart power system that can keep up with rising demand. It has to do with saving energy and being environmentally friendly. Growing populations and the use of new technologies have caused a big rise in energy use, which is causing big problems for the environment and energy security. It is very important and significant to use blockchain technology and artificial intelligence (AI) to solve problems with power control. A data can be collected on using a smart city in an power consumed smart grid data and pre-process using a Z-Score normalization technique and it can be extracting a features using a Spatial Temporal Correlation (STC) is to assess smart grid power usage within the context of a smart city using large-scale, high-dimensional data. Ensuring data integrity, privacy, and trust among grid applicants, transmit the data securely and reliably to a centralized or distributed cloud platform utilizing blockchain technology. A secure transmission and storage using Distributed Authentication and Authorization (DAA) protocol work on distributed manner. In order to achieve precise load forecasting, it incorporates a Long-Short-Term-Memory based Recurrent Neural Network with Improved Sparrow Search Algorithm (LSTM-RNN-ISSA). The smart grid may then record the projected results. A communication can be done on a smart grid to the users; Blockchain-Based Smart Energy Trading with Adaptive Volt-VAR Optimization (BSET-AVVO) algorithm can be used for effective communication. A quickly balancing electrical load and supply via Task-Oriented Communication mechanism in real-time demand response. Finally, our proposed method performs successfully better than the existing approaches.

Source: Intelligent Systems with Applications

DOI: 10.1016/j.iswa.2024.200440

Author: Emran Aljarrah

Institution: Jadara University

Language: English

Topic: Smart Grid and Power Systems

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Industry, innovation and infrastructure, Affordable and clean energy, Sustainable cities and communities, Climate action

Open Access status: gold

Estimated APC paid: $1,500