Reliable Non-Parametric Techniques for Energy System Operation and Control

Capture the future of power system management with Reliable Non-Parametric Techniques for Energy System Operation and Control by Hongcai Zhang, Yonghua Song, Ge Chen, and Peipei Yu. This authoritative volume introduces robust, data-driven non-parametric methods designed to improve grid reliability, stability, and efficiency in rapidly changing energy markets.

Grounded in practical applications and rigorous analysis, the book explains how non-parametric techniques can overcome modeling uncertainty in modern energy systems. Readers will find clear explanations of key approaches, guidance for integrating renewable generation and distributed resources, and strategies for forecasting, optimization, and real-time control. Ideal for engineers, researchers, utility operators, and graduate students, the text bridges theory and practice with actionable insights relevant to power systems in North America, Europe, Asia-Pacific, and emerging markets worldwide.

Featuring case studies and comparative evaluations, this work helps practitioners evaluate method performance under real operational constraints and regulatory environments. Whether you’re managing grid stability, designing control schemes, or pursuing research in data-driven energy solutions, the book supplies the tools to make informed decisions and deploy reliable control strategies.

Clear, concise, and forward-looking, Reliable Non-Parametric Techniques for Energy System Operation and Control is a must-have resource for anyone tackling the challenges of modern energy system operation and control. Enhance your toolkit for resilient, efficient power systems—order your copy today and stay at the forefront of non-parametric, data-driven energy solutions.

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