Power Quality Enhancement using Artificial Intelligence Techniques 1st Edition

Power Quality Enhancement using Artificial Intelligence Techniques — 1st Edition by Ahmed S. Abbas; Adel Ali Mohamed Abou El‑Ela; Ragab A. El‑Sehiemy; Adel A. Elbaset is a definitive guide for engineers, researchers, and utility professionals seeking practical, AI-driven solutions to modern power system challenges.

Opening with a clear overview of power quality problems—voltage sags, harmonics, flicker and transient disturbances—the book quickly engages readers by showing how artificial intelligence transforms detection, diagnosis, and mitigation strategies. It presents contemporary AI methods—neural networks, fuzzy logic, evolutionary algorithms and machine‑learning classifiers—applied directly to power systems and smart grid environments.

Readers will appreciate the balance of theory and practice: concise algorithm explanations, system-level control strategies, and realistic case studies that demonstrate improved reliability and reduced downtime. The authors emphasize actionable outcomes: faster fault identification, adaptive compensation, and optimized control of distributed generation and renewable integration.

Whether you work in transmission and distribution, renewable energy integration, industrial power systems or academic research, this book equips you with tools to design robust, intelligent mitigation schemes. Its global perspective makes it relevant to engineers in North America, Europe, the Middle East, Asia and Africa confronting evolving grid demands.

For professionals aiming to future‑proof networks and for graduate students wanting a hands‑on introduction to AI applications in power quality, this edition is an essential resource. Enhance your skillset and improve system performance—order your copy of Power Quality Enhancement using Artificial Intelligence Techniques (1st Edition) today.

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