Protecting cybersecurity is a non‐negotiable task for smart grids (SG) and has garnered
significant attention in recent years. The application of artificial intelligence (AI), particularly …

Smart grids represent a paradigm shift in the electricity industry, moving from traditional one‐
way systems to more dynamic, interconnected networks. These grids are characterised by …

The employment of deep learning (DL) in renewable energy forecasting (REF) may bring
novel cyberthreats. However, this fact has not drawn sufficient attention in the existing …

In integrated energy systems (IESs), reliable planning and operation are challenging owing
to significant uncertainties in energy production, utilization, and trading. To this end, this …

Accurate load forecasting is crucial to improve the stability and cost-efficiency of smart grid
operations. However, how to integrate multiple significant factors for enhancing load …

Abstract'Demand-side response'(DSR), a mechanism through which residential electricity
usage adapts based on external cues, has been conceptualized diversely, with numerous …

The ever-intensifying threat of climate change renders the electric power system undergoing
a profound transition toward net-zero emissions. Energy efficiency measures, such as …

The stability and reliability of a smart grid are challenged by the inherent intermittency and
unpredictability of renewable energy as its integration into the smart grid increases. This …

Blockchain is a peer-to-peer network that maintains a shared and trusted ledger by
packaging transactions into blocks. Blockchain technology powers Bitcoin, a decentralized …

Demand response (DR) plays a critical role in the advancement of smart grids, providing
dynamic solutions to conventional energy management methods. This research review …