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Analytic Research Foundations for the Next-Generation Electric Grid [Pehme köide]

  • Formaat: Paperback / softback, 161 pages, kõrgus x laius: 279x216 mm
  • Ilmumisaeg: 15-May-2016
  • Kirjastus: National Academies Press
  • ISBN-10: 0309392314
  • ISBN-13: 9780309392310
  • Formaat: Paperback / softback, 161 pages, kõrgus x laius: 279x216 mm
  • Ilmumisaeg: 15-May-2016
  • Kirjastus: National Academies Press
  • ISBN-10: 0309392314
  • ISBN-13: 9780309392310
Electricity is the lifeblood of modern society, and for the vast majority of people that electricity is obtained from large, interconnected power grids. However, the grid that was developed in the 20th century, and the incremental improvements made since then, including its underlying analytic foundations, is no longer adequate to completely meet the needs of the 21st century. The next-generation electric grid must be more flexible and resilient. While fossil fuels will have their place for decades to come, the grid of the future will need to accommodate a wider mix of more intermittent generating sources such as wind and distributed solar photovoltaics.





Achieving this grid of the future will require effort on several fronts. There is a need for continued shorter-term engineering research and development, building on the existing analytic foundations for the grid. But there is also a need for more fundamental research to expand these analytic foundations. Analytic Research Foundations for the Next-Generation Electric Grid provide guidance on the longer-term critical areas for research in mathematical and computational sciences that is needed for the next-generation grid. It offers recommendations that are designed to help direct future research as the grid evolves and to give the nation's research and development infrastructure the tools it needs to effectively develop, test, and use this research.

Table of Contents



Front Matter Summary 1 Physical Structure of the Existing Grid and Current Trends 2 Organizations and Markets in the Electric Power Industry 3 Existing Analytic Methods and Tools 4 Background: Mathematical Research Areas Important for the Grid 5 Preparing for the Future 6 Mathematical Research Priorities Arising From the Electric Grid 7 Case Studies 8 Building a Multidisciplinary Research Community Appendixes Appendix A: Workshop Agenda Appendix B: Committee Biographies Appendix C: Acronyms
Summary 1(6)
1 Physical Structure of the Existing Grid and Current Trends
7(25)
Introduction
7(1)
Basic Grid Concepts
8(8)
Interconnected Alternating Current Power Grids
8(2)
Power Grid Time Scales
10(1)
Basic Circuits---Quasi-Steady-State Time Frame
11(2)
Three-Phase Power Systems and Per-Phase Analysis
13(3)
Illustrative Types of Analysis Needed for the Grid
16(14)
Power Flow---Steady-State Analysis
16(4)
Interconnected Power System Steady-State Operations
20(4)
Longer-Term Power System Planning
24(1)
Power System Stability
25(4)
Distribution Systems
29(1)
Organization of the Report
30(1)
References
31(1)
2 Organizations and Markets in the Electric Power Industry
32(12)
Introduction
32(1)
History of Federal and State Regulation with Regional Standards Development
32(3)
Regulatory Development
33(1)
Reliability Organization Development
33(1)
North American Regional Entities
34(1)
Changes in Regulation
34(1)
U.S. Wholesale Power Markets
35(2)
Common Features of Electric Markets
37(1)
Electricity Market Co-optimization
37(1)
Pricing
37(3)
Energy Pricing Example
38(1)
Day-Ahead Market
38(1)
Unit Commitment
38(2)
Scarcity Pricing
40(1)
Capacity Markets
40(1)
U.S. Bilateral Markets
40(1)
Examples of International Markets
41(1)
Australian National Electricity Market
41(1)
German Electricity Market
41(1)
Conclusions
42(1)
References
42(2)
3 Existing Analytic Methods and Tools
44(17)
Introduction
44(1)
Power Flow (Load Flow)
44(4)
Steady-State Contingency Analysis
48(1)
Optimal Power Flow and Security-Constrained Optimal Power Flow
49(1)
State Estimation
50(2)
Transient Stability and Longer-Term Dynamics
52(3)
Short-Circuit Analysis
55(1)
Electromagnetic Transients
55(1)
Harmonic Analysis
56(1)
Generation Analytics
56(2)
Modeling High-Impact, Low-Frequency Events
58(1)
References
59(2)
4 Background: Mathematical Research Areas Important for the Grid
61(23)
Introduction
61(2)
Dynamical Systems
63(2)
Optimization
65(6)
General-Purpose Optimization Methods and Software
65(2)
Grid-Related Continuous Optimization
67(1)
Mixed-Integer Linear Programs
67(2)
Stochastic Optimization
69(2)
Control
71(2)
Protection
71(1)
Primary Control
71(1)
Secondary Control
72(1)
Tertiary Control
73(1)
Risk Analysis, Reliability, Machine Learning, and Statistics
73(6)
Regression
74(1)
Classification and Hazard Modeling
74(1)
Causal Inference
75(1)
Clustering
76(1)
Reliability Modeling with Physical Models
77(1)
Cascading Failures
78(1)
Data Assimilation
78(1)
Complexity and Model Reduction in the Time of Big Data
79(2)
Uncertainty Quantification
81(1)
References
82(2)
5 Preparing for the Future
84(9)
Introduction
84(1)
Uncertainty in What Lies Ahead
84(1)
Technologies That Will Enhance the Observability of the Grid
85(2)
Technologies That Will Enhance the Controllability of the Grid
87(1)
Effects of Climate Change
88(1)
Mathematical and Computational Challenges in Grid Architectures
88(1)
Mathematical and Computational Challenges in Local Distribution Grid Architectures
89(2)
Mathematical and Computational Challenges in Managing Interdependencies Between the Transmission and Local Distribution Grids/Microgrids
91(1)
References
92(1)
6 Mathematical Research Priorities Arising from the Electric Grid
93(18)
Introduction
93(1)
Synthetic Data for Facilitating the Creation, Development, and Validation of New Power System Tools for Planning and Operations
94(3)
Random Topology Networks
96(1)
Data-Driven Models of the Electric Grid
97(2)
The Role of Control Theory in the Changing Electric Energy Systems
99(1)
Physics-Based Simulations for the Grid
100(3)
Data-Driven Approaches for Improving Planning, Operations, and Maintenance and for Informing Other Types of Decision Making
103(2)
Creating Hybrid Data/Human Expert Systems for Operations
103(1)
Machine-Learning Models for Hazard Modeling and Reliability
103(1)
Visualization Tools for Understanding Data
104(1)
Detecting Who Has No Power
104(1)
Machine Learning for Long-Term Planning
104(1)
Optimization
105(3)
Convex Relaxation in Grid-Related Optimization
105(1)
Robust and Chance-Constrained Optimization
106(2)
Challenges in Modeling the Electric Grid's Coupling with Other Infrastructures
108(1)
References
109(2)
7 Case Studies
111(17)
Introduction
111(1)
Case Study in Optimization: PJM's Daily Operations
111(5)
Day-Ahead Market
112(2)
Real-Time Markets
114(1)
Capacity Market---Reliability Pricing Model Optimization
115(1)
Financial Transmission Rights
115(1)
Challenges for the Day-Ahead Unit Commitment Formulation
115(1)
Case Study in Mathematical Needs for the Modeling and Mitigation of Low-Frequency Events
116(3)
Interdisciplinary Modeling
118(1)
Rare Event Modeling
118(1)
Resilience Control Center Design
118(1)
Resilience Power System Design
119(1)
Case Study in Data-Centered Asset Maintenance: Predicting Failures in Underground Power Distribution Networks
119(3)
Data Integration
120(1)
Handling Unstructured Text
121(1)
Rare Event Prediction
121(1)
Causal Inference
121(1)
Visualization and Interpretation of Results
121(1)
Machine-Learning Methods Comprehensible to Human Experts
121(1)
Case Study in Synchrophasors
122(3)
Overview of Synchrophasors
122(2)
Application of Synchrophasors
124(1)
Mathematical Challenges to Improve Synchrophasor Measurements
124(1)
Case Study in Inverter-Based Control for Stabilizing the Power System
125(1)
References
126(2)
8 Building a Multidisciplinary Research Community
128(11)
Introduction
128(1)
Example of a Multidisciplinary Team: PSERC
129(1)
Example of a Multidisciplinary Effort: Markets
129(2)
Examples from Other Disciplines
131(1)
Recommendation for Synthetic Data Libraries
132(1)
Recommendation for Software Libraries
132(1)
Recommendation for Increased R&D Coordination
133(1)
Recommendation for a National Center
134(1)
References
135(4)
APPENDIXES
A Workshop Agenda
139(2)
B Committee Biographies
141(4)
C Acronyms
145