Artificial Intelligence for Sustainable Energy Systems 2: The Wiley-ISTE Follow-Up
Description
With Brent crude swinging on Strait of Hormuz risk and the EIA revising its output forecasts month to month, energy operators are leaning harder on intelligent systems to manage volatility — not just to cut emissions. Artificial Intelligence for Sustainable Energy Systems 2, edited by Inam Ul Haq, Sanna Mehraj Kak, and colleagues (Wiley-ISTE), extends the first volume's foundational AI-in-energy concepts with three new areas of coverage: AI-driven grid optimization, predictive maintenance for energy infrastructure, and renewable integration at scale — the operational layer the first volume didn't yet address.
Where this shows up in practice
The chapters translate directly into operational decisions, not abstract methods. Three examples the volume covers in depth:
Renewable generation forecasting — AI models that forecast wind and solar output hours ahead, so grid operators can balance supply without over-provisioning storage capacity.
Predictive maintenance — systems that flag turbine bearing wear and failure signatures weeks before a breakdown, turning an emergency outage during peak demand into a scheduled maintenance window.
Net-zero dispatch optimization — algorithms that route power across a grid to minimize cost and emissions simultaneously, which the volume frames as a practical planning tool for utilities working toward net-zero targets, not just a policy aspiration.
Why it matters for libraries and faculties right now
For energy and engineering libraries, this is a current, practice-oriented reference that connects AI methods directly to renewable deployment and net-zero policy — not a theoretical survey. It sits well alongside existing energy law and policy holdings, giving researchers and graduate students a technical counterpart to the regulatory literature, and gives engineering faculties a text that reads as applied rather than purely computational.
Why buy this book?
For energy engineers, policy practitioners, and academic libraries building an AI-and-energy collection, this volume translates AI methods into operational terms — grid stability, forecasting, and asset management — rather than treating sustainability and AI as separate topics.
CLNZ Books supports institutional invoicing and purchase orders for library and faculty acquisitions, with worldwide shipping included in every price. Explore the full Energy collection at CLNZ Books.
Q&A
What topics does this second volume add to the series?
AI-driven grid optimization, predictive maintenance for energy infrastructure, and large-scale renewable integration, building on the foundational AI-in-energy concepts from the first volume.
Who is this book written for?
Energy engineers, grid operators, policy practitioners, and academic researchers working at the intersection of artificial intelligence and energy systems.
Who are the editors?
Inam Ul Haq, Sanna Mehraj Kak, and co-editors, published by Wiley-ISTE.
How does this book relate to current energy market volatility?
It addresses the operational AI tools — forecasting, grid stability, predictive maintenance — that energy operators increasingly rely on to manage the kind of price and supply volatility seen in 2026's oil markets.
Does CLNZ Books support institutional and library orders?
Yes — institutional invoicing, purchase orders, and worldwide shipping are available for library and faculty acquisitions; see our How to Order page for details.
Where can I buy Artificial Intelligence for Sustainable Energy Systems 2?
Directly from CLNZ Books, with worldwide shipping and secure card or PayPal checkout — view the book here.