Dynamic estimation and control of power systems. ([2019])

• Record Type: Book
• Further Information: Note: Abhinav Kumar Singh, Bikash C. Pal.
• Authors: Singh, Abhinav Kumar; Pal, Bikash C
• Contents: Front Cover; Dynamic Estimation and Control of Power Systems; Copyright; Contents; About the Authors; Preface; List of Figures; List of Tables; List of Abbreviations; List of Symbols; 1 Introduction; 1.1 State of the art; 1.1.1 Energy management system; 1.1.2 Phasor measurement units (PMUs); 1.1.3 Flexible AC transmission system (FACTS); 1.1.4 Wide-area measurements and wide-area control; 1.1.5 Dynamic state estimation (DSE) and dynamic control; 1.2 Static state estimation (SSE) versus dynamic state estimation (DSE); 1.3 Challenges to power system dynamic estimation and control 1.4 Book organization2 Power System Modeling, Simulation, and Control Design; 2.1 Power system model; 2.1.1 Generating unit: a generator and its excitation system; 2.1.2 Power system stabilizers (PSSs); 2.1.3 FACTS control devices; 2.1.3.1 Thyristor-controlled series capacitor (TCSC); 2.1.3.2 Static VAR compensator (SVC); 2.1.3.3 Thyristor-controlled phase angle regulator (TCPAR); 2.1.4 Loads, network interface, and network equations; 2.2 Power system simulation and analysis; 2.2.1 Load ow analysis; 2.2.2 Initialization and time-domain simulation 2.2.3 Linear analysis and basics of control design2.2.3.1 System linearization; 2.2.3.2 Eigenvalues; 2.2.3.3 Participation factor and residue; 2.2.3.4 Controllable devices, controllers, inputs, and outputs: examples; 2.2.3.5 Electromechanical modes; 2.2.3.6 Interarea modes and mode shapes; 2.2.3.7 Residue-based linear control design; 3 Centralized Dynamic Estimation and Control; 3.1 NCPS modeling with output feedback; 3.1.1 State space representation of power system; 3.1.2 Sensors and actuators; 3.1.3 Communication protocol, packet delay, and packet dropout; 3.1.4 Controller; 3.1.5 Estimator 3.1.5.1 State prediction step3.1.5.2 Measurement prediction and Kalman update step; 3.2 Closed-loop stability and damping response; 3.2.1 Stability analysis framework of a jump linear system; 3.2.1.1 LMIs for mean-square stability; 3.2.1.2 LMIs for adequate damping response; 3.2.2 Physical signi cance of the developed LMIs; 3.3 Case study: 68-bus 16-machine 5-area NCPS; 3.3.1 System description; 3.3.2 Simulation results and discussion; 3.3.2.1 Operating condition 1 (base case); 3.3.2.2 Operating condition 2; 3.3.2.3 Effect of sampling period; 3.3.2.4 Robustness; 3.4 Limitations; 3.5 Summary 4 Decentralized Dynamic Estimation Using PMUs4.1 Problem statement and methodology in brief; 4.1.1 Problem statement; 4.1.2 Methodology; 4.2 Power system modeling and discrete DAEs; 4.2.1 Generators; 4.2.2 Excitation systems; 4.2.3 Power system stabilizer (PSS); 4.2.4 Network model; 4.3 Pseudoinputs and decentralization of DAEs; 4.4 Unscented Kalman lter (UKF); 4.4.1 Generation of sigma points; 4.4.2 State prediction; 4.4.3 Measurement prediction; 4.4.4 Kalman update; 4.5 Case study: 68-bus test system; 4.5.1 Noise variances; 4.5.1.1 Measurement noise; 4.5.1.2 Process noise
• Publisher Details: London, United Kingdom : Academic Press, an imprint of Elsevier
• Publication Date: 2019
• Extent: 1 online resource
• Subjects: 621.31; Electric power systems -- State estimation; Electric power systems -- Control; TECHNOLOGY & ENGINEERING / Mechanical; Electronic books
• Languages: English
• ISBNs: 9780128140062; 0128140062
• Related ISBNs: 9780128140055
• Notes: Note: Includes bibliographical references.; Note: Online resource; title from PDF title page (Ebsco, viewed October 15, 2018).
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.