Distributed Control Methods and Cyber Security Issues in Microgrids

✍ Scribed by Wenchao Meng (editor), Xiaoyu Wang (editor), Shichao Liu (editor)

• Publisher: Academic Press
• Year: 2020
• Tongue: English
• Leaves: 289
• Category: Library

✦ Synopsis

Distributed Control and Cyber Security Issues in Microgrids presents a thorough treatment of distributed control methods and cyber security issues for power system researchers and engineers. With the help of mathematical tools, this reference gives a deep understanding of microgrids and new research directions, addressing emerging concepts, methodologies and applications of monitoring, control and protection in smart microgrids with large-scale renewables. With the integration of more distributed or aggregated renewables and the wide utilization of power electronic devices, the smart microgrid is facing new stability and security challenges.

• Includes global case studies to demonstrate distributed control success stories
• Offers detailed illustrations and flowcharts to address challenges and technical solutions for those working in power systems in utilities and industry
• Showcases new challenges faced in the stability and security of smart microgrids

✦ Table of Contents

Cover
Distributed Control Methods and Cyber Security Issues in Microgrids
Copyright
Contributors
Preface
1
Sliding mode control of grid-connected power converters for microgrid applications
Introduction of sliding mode control
First-order sliding mode control
Second-order sliding mode control
Mathematical models of power converters
Mathematical model of three-phase two-level AC/DC power converters
Mathematical model of DC/DC buck converters
SMC for power converters
SMC of three-phase AC/DC power converters
Mode uncertainties
Control objectives
Controller design
Extended state observer
Capacitor voltage regulation
Grid current tracking
Simulation results
SMC for DC/DC buck converters
Control objectives
Design of controller
Voltage regulation loop
Current tracking loop
Simulation results
Against load resistance variation
Against input voltage variation
Against reference voltage variation
Conclusion
References
2
Distributed voltage restoration and power allocation control in islanded DC microgrids
Introduction
Problem formulation and objectives
Droop control
Objectives
Distributed secondary control for voltage restoration
Controller design
Stability analysis
Distributed secondary control with pinning gain
Control parameters selection
Simulation results
Proposed distributed secondary control
Case A: Backup DG plug-and-play
Case B: Different pinning gains
Robustness test with respect to temporary fault
Comparison with existing methods
Experimental validation
Experimental results with resistant load
Experimental results with constant power load
Experimental results with communication time delay
Conclusion
References
3
Optimal distributed secondary control for a microgrid
Introduction
Preliminaries
Graph theory
Closed-loop optimal control algorithm
Proposed optimal distributed control strategy
Optimal distributed finite-time secondary frequency control and active power sharing
Optimal distributed secondary voltage control and reactive power sharing
Communication delay analysis
Algorithm implementation
Simulation analysis
Performance evaluation the proposed optimal distributed control strategy
Convergence analysis
Influence analysis of the communication delay
Robustness analysis against the uncertainties of parameters
Influence analysis of the bounded control input
Plug-and-play capability analysis
Scalability test
Conclusion
References
4
Distributed power control of flexible loads in microgrids
Coordinated active power dispatch control for a microgrid
Distributed pinning consensus on networks and corporation optimization
Distributed pinning consensus algorithm
Dispatch optimization of units in microgrid by λ-iteration algorithm
Corporation dispatch control of units in a microgrid
Distributed λ-iteration optimization of active power
Solution without power constraints
Solution with power constraints
Case studies
Case 1: The full participation of DGs and ESUs
Case 2: Exit of ESUs and time-varying demand
Case 3: The plugging-in DGs to share the active power
Conclusion
Demand response load following control of smart grids
Problem formulation and aggregate evaluation of TCLs
Basic model of a single TCL and an aggregator
Aggregate evaluation of TCL aggregator
Look-ahead economic dispatch to provide load following trajectories
Distributed pinning control of multiple aggregated TCLs
Simulation and results
Aggregate evaluation of the aggregator
Reference power trajectories solving
Demand response load following control of TCLs
Conclusion
References
5
False data injection attacks on inverter-based microgrid in autonomous mode
Introduction
Inverter-based microgrid structure
Physical layer
Cyber-communication layer
System dynamic model
Small signal model
Active power reference
System performance under FDI attacks
Distributed load sharing control under FDI attacks
Impacts of FDI attacks
Simulation examples
Stable region
System performance under attack strategy 1
System performance under attack strategy 2
Discussion
Conclusion
References
6
Distributed finite-time control of aggregated energy storage systems for frequency regulation in multiarea microg
Introduction
Background
Literature survey
Contributions
Proposed frequency control scheme
System overview
Multiarea microgrids
Proposed disturbance observer
System disturbance observer
Band-pass filter
Distributed finite-time control of ESA
Communication graph
Finite-time consensus control of ESA
Stability analysis
Numerical illustrations
Results and discussions
Case 1: System contingency
Case 2: Normal operation
Case 3: Multiarea microgrids
Case 4: Comparison with linear control algorithm
Conclusion
References
7
Distributed optimization algorithm for economic dispatch: A bisectional approach
Introduction
System modeling
Problem formulation
Centralized solution to the EDP
Introduction to consensus-like algorithm
Graph theory and nonnegative matrices
Consensus-like algorithm
Distributed bisection algorithm: Design and analysis
Distributed algorithm for aggregate demand
Distributed algorithm for feasibility test
Distributed bisection algorithm
Convergence analysis and stopping criteria
Numerical examples
Case 1: The EDP with quadratic cost functions only
Case 2: EDP with nonquadratic cost functions
Case 3: Convergence speed analysis
Case 4: The comparison with the algorithm in 6345156
Case 5: Implementation on IEEE 118-bus system
Conclusion and discussion
References
8
Scheduling of EV battery swapping in microgrids
Introduction
Background, motivation, and contributions
Literature
Problem formulation
Network model
DC power flow equations
Fix-point linearization of power flow equations
DistFlow equations and SOCP relaxation
Operational constraints
Battery swapping scheduling
Centralized solution
Distributed solutions
Relaxations
Distributed solution via ADMM
Distributed solution via dual decomposition
Numerical results
Setup
Centralized solution
Nearest-station policy
Optimal assignments
Optimality of generalized Benders decomposition
Exactness of SOCP relaxation
Computational effort
Benefit
Distributed solutions
Convergence
Suboptimality (comparison with centralized solution)
Exactness of SOCP relaxation
Scalability
Concluding remarks
Summary
Model limitations
Appendix: Proof of [TEO:NUMBER]Theorem 1
References
9
Dispatch strategy of energy bank system with hybrid energy storage
Introduction
EBS model structure
Definition in energy bank system
Energy bank system model and structure
Trading model
Call auction
Rule of maximum transaction volume
Rule of treaty violation
Listed-energy and listed-price (LELP) model
Selling listed-price
Buying listed-price
Assessment indices
Deposit system of energy
Figure of deposit energy currency
Operation model of DSE
Economic model of DSE
Case study
System description
Simulation
Conclusion
References
10
False data injection attacks and countermeasures in smart microgrid systems
Introduction
Preliminaries and problem formulation
Network model
Physical network
Communication network
Dynamic model
UIO-based detector
Problem formulation
Main results
Potential stealthy attacks
Attack impacts analysis
Countermeasures
Simulation
Conclusions
References
Index
Back Cover