Current Volume 8
Abstract
The transition to renewable energy and decentralized grid operations demands intelligent, real-time decision-making capabilities. This paper investigates the role of AI agents powered by LLMs and domain specific retrieval systems in optimizing smart grid operations, including load balancing, demand forecasting, outage diagnostics, and renewable integration. We propose a hybrid agent framework that combines historical grid telemetry with real-time energy data to generate explainable recommendations for grid operators. Particular attention is given to safety, reliability, and adversarial robustness, as energy infrastructure represents a critical national asset. Through simulations and prototype deployments in utility environments, we show that AI agents can reduce operational latency, enhance grid resilience, and support compliance with evolving regulatory standards. This work contributes to the responsible digitization of the energy sector and demonstrates AI’s potential in advancing sustainability goals.
Keywords
Artificial Intelligence Agents, Smart Grid Operations, Renewable Energy Management, Multi-Agent Systems, Energy Forecasting and Optimization
Citations
IRE Journals:
Sai Santhosh Polagani
"AI Agents for Smart Grid Operations and Renewable Energy Management" Iconic Research And Engineering Journals Volume 8 Issue 11 2025 Page 1278-1292
IEEE:
Sai Santhosh Polagani
"AI Agents for Smart Grid Operations and Renewable Energy Management" Iconic Research And Engineering Journals, 8(11)
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