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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 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 __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.