Green Machine Learning and Big Data for Smart Grids

Grab the future of energy management with Green Machine Learning and Big Data for Smart Grids by V. Indragandhi — a practical, research-driven guide that connects sustainable power systems with cutting-edge data science. Ideal for engineers, utility managers, researchers, and policy makers, this book turns complex concepts into actionable strategies for modern grids.

Inside, you’ll find clear explanations of how machine learning and big data analytics drive greener, more resilient smart grids. Topics cover predictive load forecasting, real-time demand response, renewable integration, anomaly detection, and optimization techniques that reduce waste and cut costs. Case studies and algorithmic insights demonstrate real-world applications across varied environments — from urban distribution networks to rural microgrids.

Why this book matters: it bridges the gap between environmental goals and technological tools, showing how data-driven approaches can unlock energy efficiency and greater reliability. Whether you’re deploying advanced metering infrastructure, optimizing distributed generation, or designing policy frameworks, the methods here scale for utilities and stakeholders worldwide — relevant to North America, Europe, India, and the Asia-Pacific.

Discover practical workflows, performance metrics, and implementation considerations that help teams move from pilot to production. The writing is technical yet accessible, balancing theory with hands-on examples so readers can apply solutions immediately.

Ready to elevate your grid strategy? Add Green Machine Learning and Big Data for Smart Grids by V. Indragandhi to your shelf and start transforming data into sustainable energy outcomes. Order your copy today and join the movement toward smarter, greener power systems.

Note: eBooks do not include supplementary materials such as CDs, access codes, etc.