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AI Explainability and Governance in Smart Energy Systems
Hardcover
Series: Energy Engineering
Technology & EngineeringGeneral Science
ISBN13: 9781837244010
Publisher: Institution of Engineering & Technology
Published: Dec 1 2026
Pages: 396
Language: English
Artificial intelligence may have the potential to deliver more efficient, reliable and sustainable energy systems, particularly by helping to manage the complexity of distributed generation and demand-side management. However, stakeholders expect interpretability and explainability, and AI tools must also be transparent, secure and trustworthy. Explainable AI (XAI) models are intended to make AI algorithms more transparent and understandable without reducing their performance and efficiency.
When AI is used in the energy sector, evaluating huge and complex datasets and making decisions to predict generation or consumption patterns, to help controlling voltage and frequency, or to control wind turbines and solar systems, owners and operators need to know and trust the algorithms to be willing to relinquish control of their assets to them.
AI Explainability and Governance in Smart Energy Systems is a comprehensive reference, written by an international team of experts. Chapters cover AI explainability in energy systems, integrated forecasting of generation and load, energy storage, integration of IoT and edge computing, AI explainability with blockchain, AI-driven energy markets, policy, and governance, case studies, human-AI collaboration, climate resilience, ethical and social implications, ethical considerations and future perspectives.
The book is intended for an audience of academic researchers in smart energy technology and XAI, energy markets and energy management, as well as for advanced students in energy systems-related subjects.
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