Dynamic State Estimation for Power Systems under Unconventional Measurements

This book presents advanced Dynamic State Estimation (DSE) methodologies across three power system classes: quasi-steady power systems, synchronous-generator-based multi-machine systems and renewable energy microgrids including unconventional measurements as time-delays, multi-rate measurements, and so forth.

This book presents advanced Dynamic State Estimation (DSE) methodologies across three power system classes: quasi-steady power systems, synchronous-generator-based multi-machine systems and renewable energy microgrids. The work tackles unconventional measurements including time-delays, multi-rate measurements, event-triggered transmissions, outliers, and sensor saturations including complex factors. The nine-chapter structure progresses from fundamentals through specific applications to future research directions. Explore state estimation in power systems and challenges in large, complex grids with high renewable energy integrationProvides step-by-step derivations of theoretical results and case studies based on widely used power system benchmarksAddresses two prominent research and technological aspects: soft computing for estimation and power electrical systemsConsiders practical issues such as online application and computational efficiency in the estimator designReviews analysis techniques such as optimal estimation technique, completing the square method, stochastic analysis technique, and entropy theoryThis book is aimed at graduate students and researchers in electrical engineering, power systems, control systems, and signal processing.