Open Access

REVIEW

Autonomous Cyber-Physical Energy Systems: Self-Optimizing Integration of Solar–Wind Hybrids, Storage, and Electric Vehicles in AI-Driven Smart Grids

Sidhharth Shankar Mishra¹, Deva Brinda Deepak², S. Vidyasagar³, Jalpa Thakkar⁴, Mohan Kolhe^5,*
1 Energy Cluster, University of Petroleum and Energy Studies, Dehradun, India
2 Department of Science and Engineering, DIICSU (Dundee International Institute of Central South University), Changsha, China
3 Department of Electrical and Electronics Engineering, SRM Institute of Science and Technology, Kattankulathur, India
4 Department of Electrical Engineering, UPL University of Sustainable Technology, Ankleshwar, India
5 Faculty of Engineering & Science, University of Agder, Kristiansand, Norway
* Corresponding Author: Mohan Kolhe. Email:
(This article belongs to the Special Issue: Advances in Grid Integration and Electrical Engineering of Wind Energy Systems: Innovations, Challenges, and Applications)

Energy Engineering https://doi.org/10.32604/ee.2026.083539

Received 06 April 2026; Accepted 11 June 2026; Published online 09 September 2026

Abstract

The study examines the developmental stages of autonomous cyber-physical energy systems (CPES), concentrating on intelligent autonomous grids that incorporate self-stabilizing solar-wind hybrid generation, battery storage, electric vehicles, and AI-driven control mechanisms. A systematic critical review with some features of systematic reviews was carried out at this time. This research offers a thorough examination of the current literature concerning CPES architecture, integrated hybrid renewable and storage systems with electric vehicles, artificial neural networks employed for forecasting and control, digital twin technology, cybersecurity, and procurement trading in prominent indices. This organization employs a relative analysis coding framework that subdivides the study into system layers, optimization scenarios, uncertainty management strategies, implementation techniques, and validation contexts. The study demonstrates that genuine system autonomy is unattainable if isolated component optimization is regarded as the ultimate objective. It has a lot of parts, such as physical infrastructure, sensing and communication networks, predictive analytics and controls, resilience frameworks, and governance structures. HRES-EVS systems are very flexible and can pay off in the long run, but they are hard to use because of unclear policies, inconsistent compatibility with other systems, vulnerability to cyber and physical threats, and a lack of real-world experience that may come from not enough testing. Digital twins, edge computing, the Internet of Things (IoT), and artificial intelligence (AI) are all important parts of a flexible closed-loop intelligence system. The paper presents a cohesive conceptual framework that redefines CPES autonomy as an emergent, multi-faceted characteristic of smart energy ecosystems and suggests a future research agenda for the advancement of a resilient, carbon-conscious, decentralized, and governance-integrated Smart Grid.

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Keywords

Smart grids; hybrid renewable energy systems; artificial intelligence in energy; digital twin technology; energy storage and electric vehicles; grid resilience; decentralized energy systems; cybersecurity in smart grids; sustainable energy optimization

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