Work

Towards an Explainable Artificial Intelligence approach for smart grid systems

Year: 2025

Type: article

Abstract: As global energy demands escalate, effective management of electrical grids and reducing carbon emissions have become critical objectives. This paper proposes a novel system which employs Explainable Artificial Intelligence (XAI) to enhance the operational efficiency of smart grids by predicting energy consumption and optimizing resource allocation accordingly. The integration of XAI addresses the complexity of grid management by offering transparency into AI-driven predictions, thus fostering user trust and facilitating informed decision-making. The system comprises data collection and preparation, energy consumption prediction using XAI models, and an optimisation module that ensures efficient grid operations. Eventually, this research can be seen as a step forward to further contribute towards sustainable, cost-effective, and reliable smart grid management.

Source: Discover Artificial Intelligence

DOI: 10.1007/s44163-025-00261-5

Authors: Mahmoud Alfayan, Hani Hagras

Institution: University of Essex

Language: English

Topic: Energy Load and Power Forecasting

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

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

Open Access status: gold

Estimated APC paid: $1,590