Advances in Electric Power and Energy. Группа авторов
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11 PART III: STATE ESTIMATION FOR DISTRIBUTION SYSTEMS CHAPTER 10: PROBABILISTIC STATE ESTIMATION IN DISTRIBUTION NETWORKS 10.1 INTRODUCTION 10.2 STATE ESTIMATION IN DISTRIBUTION NETWORKS 10.3 IMPROVING OBSERVABILITY IN DISTRIBUTION NETWORKS 10.4 CONCLUSION REFERENCES CHAPTER 11: ADVANCED DISTRIBUTION SYSTEM STATE ESTIMATION IN MULTI‐AREA ARCHITECTURES 11.1 ISSUES AND CHALLENGES OF DISTRIBUTION SYSTEM STATE ESTIMATION 11.2 DISTRIBUTION SYSTEM MULTI‐AREA STATE ESTIMATION (DS‐MASE) APPROACH 11.3 APPLICATION OF THE DS‐MASE APPROACH 11.4 VALIDITY AND APPLICABILITY OF DS‐MASE APPROACH REFERENCES
12 PART IV: PARALLEL/DISTRIBUTED PROCESSING CHAPTER 12: HIERARCHICAL MULTI‐AREA STATE ESTIMATION 12.1 INTRODUCTION 12.2 PRELIMINARIES 12.3 MODELING AND PROBLEM FORMULATION 12.4 A BRIEF SURVEY OF SOLUTION TECHNIQUES 12.5 HIERARCHICAL STATE ESTIMATOR VIA SENSITIVITY FUNCTION EXCHANGES 12.6 ADD‐ON FUNCTIONS IN MULTI‐AREA STATE ESTIMATION 12.7 PROPERTIES 12.8 SIMULATIONS 12.9 CONCLUSIONS ACKNOWLEDGMENTS REFERENCES CHAPTER 13: PARALLEL DOMAIN‐DECOMPOSITION‐BASED DISTRIBUTED STATE ESTIMATION FOR LARGE‐SCALE POWER SYSTEMS 13.1 INTRODUCTION 13.2 FUNDAMENTAL THEORY AND FORMULATION 13.3 EXPERIMENTAL RESULTS 13.4 CONCLUSION REFERENCES CHAPTER 14: DISHONEST GAUSS–NEWTON METHOD‐BASED POWER SYSTEM STATE ESTIMATION ON A GPU 14.1 INTRODUCTION 14.2 BACKGROUND 14.3 PERFORMANCE OF DISHONEST GAUSS–NEWTON METHOD 14.4 GPU IMPLEMENTATION 14.5 SIMULATION RESULTS 14.6 DISCUSSIONS ON SCALABILITY 14.7 DISTRIBUTED METHOD OF PARALLELIZATION 14.8 CONCLUSIONS REFERENCES
13 INDEX
14 IEEE PRESS SERIES ON POWER ENGINEERING
List of Tables
1 Chapter 2TABLE 2.1 Line parameters.TABLE 2.2 Voltages: measured, true and estimated values.TABLE 2.3 Power injections: measured, true and estimated values.TABLE 2.4 Power flows: measured, true and estimated values.TABLE 2.5 State‐variable updates and convergency summary.TABLE 2.6 Residuals and normalized residuals.TABLE 2.7 Characterization of different state‐estimation formulations.TABLE 2.8 Example of alternative estimators: line characteristics.TABLE