Ieee Std C62 36 2016 Revision Of Ieee Std C62 36 2014
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Artificial Intelligence Supported Power Quality Prediction and Mitigation
This thesis introduces a fully data driven approach for the prediction and optimization of critical electrical grid states due to poor power quality. Therefore, a nonvolatile memory model for time series forecasting, designed to profit especially from big data bases and complex pattern use cases as well as an Artificial Intelligence based Smart Demand Side Management framework to enable system inherent resources / components for minimization of harmonic disturbances is applied to measured power grid scenarios.
High-Power Electromagnetic Effects on Electronic Systems
This is the first book that comprehensively addresses the issues relating to the effects of radio frequency (RF) signals and the environment of electrical and electronic systems. It covers testing methods as well as methods to analyze radio frequency. The generation of high-powered electromagnetic (HPEM) environments, including moderate band damped sinusoidal radiators and hyperband radiating systems is explored. HPEM effects on component, circuit, sub-system electronics, as well as system level drawing are discussed. The effects of HPEM on experimental techniques and the standards which can be used to control tests are described. The validity of analytical techniques and computational modeling in a HPEM effects context is also discussed. Insight on HPEM effects experimental techniques and the standards which can be used to control tests is provided, and the validity of analytical techniques and computational modeling in a HPEM effects context is discussed. This book dispels myths, clarifies good experimental practice and ultimately draws conclusions on the HPEM interaction with electronics. Readers will learn to consider the importance of HPEM phenomena as a threat to modern electronic based technologies which underpin society and to therefore be pre-emptive in the consideration of HPEM resilience.