Microgrid Cyberphysical Systems: Renewable Energy and Plug-in Vehicle Integration

Description

Microgrid Cyberphysical Systems: Renewable Energy and Plug-in Vehicle Integration outlines the fundamental concepts on microgrid system design and control in a cyberphysical framework, focusing on the integration of renewables and EVs into microgrids. Including operational, control and management perspectives, the volume aims to optimize the reliability and economic performance of microgrids, focusing on power quality, storage and voltage and frequency control. The work encompasses generation, transmission, protection and load management under uncertainty and discusses critical drivers in robustness, uncertainty and sustainability management. Focusing on applied implementations, chapters are supported by detailed methods, heavy figurative explication, and comparative and integrative analysis. Case studies range across chapters. In addition, chapters are supported by representative experimental or test bed validations of proposed algorithms or methods which can be directly applied to reader problems. Front Cover Microgrid Cyberphysical Systems: Renewable Energy and Plug-in Vehicle Integration Copyright Contents Contributors Preface Chapter 1: Denial-of-service attack resilient control for cyber physical microgrid system 1. Introduction 2. Microgrid control design for DOS attack 2.1. Control objective under DOS attack 2.2. Secondary control 2.3. Preliminaries of graph theory 2.4. Consensus-based voltage error 2.5. Consensus-based frequency error 2.6. Sliding mode-based control strategy 2.7. Event-based SMC scheme in the absence of DOS attack 3. Event-based control in presence of DOS attack 3.1. DOS attack preliminaries time limitations 3.2. Parameter design for the convergence rate in absence of DOS 3.3. Parameter design for the divergence rate in presence of DOS 4. Verification and result analysis of the proposed scheme 4.1. Simulation results obtained from the proposed scheme and discussion 5. Conclusion References Chapter 2: Distributed generating system integration: Operation and control 1. Introduction 1.1. Research on distributed generating system integration: Focus area 1.2. IEEE standards for distributed generating system integration 2. Grid supporting mode of VSI in distributed generating system 2.1. Standards for distributed generating system integrations 2.2. Frequency Support 2.2.1. Fast grid frequency support from distributed energy resources: NREL REPORT, March, 2021 2.3. Voltage support 2.3.1. An overview of issues related to IEEE Std 1547-2018 requirements regarding voltage and reactive power control 2.3.2. Voltage ranges defined by ANSI C84.1 Traditional voltage regulation methods Voltage regulation using inverters 2.4. Inertial support 2.4.1. Three-phase grid-connected power converters with virtual inertia control 2.4.2. Virtual inertia control mechanism 3. Grid following mode of VSI in distributed generating system 3.1. Structure of grid-imposed frequency VSC system 3.2. Real and reactive power controller 3.3. VSC current control-SRF (DQ-control) 3.4. Phase locked loop (PLL) 3.5. Experimental results 4. Grid forming mode of VSI in distributed generating system 4.1. Conventional droop control approach 4.1.1. Power controller 4.1.2. Voltage controller 4.1.3. Current controller 4.2. Virtual synchronous machine (VSM) based control approach 4.2.1. Voltage controller 4.2.2. Frequency controller 5. Converter control in EV-based distributed generating system 5.1. Modified droop control for frequency regulation of EV-based system 5.2. Distributed control for voltage regulation of EV-based system 5.2.1. Model of EV chargers 5.2.2. Distributed control framework 5.2.3. Case study 6. Conclusions References Chapter 3: Short-term solar irradiance forecasting using ground-based sky images 1. Introduction 2. Methodology adopted for forecasting of solar irradiance using sky images 2.1. Preprocess sky images 2.2. Cloud pixel determination 2.2.1. Clear sky library 2.2.2. Computation of threshold value 2.2.3. Cloud pixels classification 2.3. Cloud movement determination 2.3.1. Application of optical flow algorithm 2.3.2. Compute representative velocity vector 2.4. Forecast solar irradiance 2.4.1. Clear sky model 2.4.2. Computation of clear sky index, Kt 2.4.3. Estimate solar irradiance for forecast horizon of 2min 2.5. Solar irradiance forecast 3. Updating clearness index Kt using RLS algorithm 4. Updating clearness index Kt using variable leaky LMS (VLLMS) algorithm 5. Conclusions References Chapter 4: Design and experimental validation of robust PID control for a power converter in a DC microgrid application 1. Introduction 2. QFT design of external disturbance minimization problem 2.1. QFT design for NMP system 3. Application of the proposed QFT design to NMP boost-type DC-DC power electronic converter 3.1. Desired specifications 3.1.1. Robust external disturbance rejection problem 3.1.2. Robust stability margin 3.2. Design frequency selection 3.2.1. Step 1: Template generation 3.2.2. Step 2: Generation of the QFT performance and stability margin bounds 3.2.3. Step 3: Loop-shaping technique: Controller design 3.2.4. Step 4: Design validation 4. Simulation studies 4.1. Linear simulation studies 4.2. Nonlinear simulation studies 4.2.1. Step variations (up/down) in the source voltage 4.2.2. Step variations in the load current 5. Experimental validation 5.1. Scenarios (a-b) 5.2. Scenario (c) 5.3. Scenarios (d-e) 6. Conclusions References Further reading Chapter 5: Control of PV and EV connected smart grid 1. Introduction 1.1. PV market penetration 1.2. EV market growth 2. Impact of PV and EV on the electricity grid 2.1. Impact on power system stability 2.2. Impact on power quality 2.3. Impact on electricity market 3. Smart microgrids, classifications, and interconnection of sources 3.1. Classification of microgrids 3.1.1. University campus or institutional microgrids (UCI-μ grids) 3.1.2. Islanded or remote microgrid (IR-μ girds) 3.1.3. Commercial or industrial microgrids (CI-μ grids) 3.2. Microgrid configurations and infrastructure 3.2.1. AC microgrid 3.2.2. DC microgrid 3.2.3. Hybrid microgrid 4. Control architecture for efficient operation of microgrids 4.1. Grid connected system and control of the DC side 4.2. Grid connected system and control of AC side 4.2.1. abc reference frame 4.2.2. αβ reference frame 4.2.3. dq reference frame 4.3. Controllers for the grid-side inverter 4.3.1. PQ controller Conventional open-loop Conventional closed-loop Advanced open-loop PQ controller 4.3.2. Current controllers Modified dq-current controller The multi-functional current controller (MFCC) 4.3.3. Synchronization techniques dq-PLL Decoupling network in αβ-domain PLL (DNabPLL) Harmonic-interharmonic DC offset PLL (HIHDOPLL) Enhanced prefiltering moving average filter type 2 PLL 5. EV modeling and charging algorithms 5.1. EV modeling techniques 5.2. Charging algorithms for EVs 6. Digital real-time simulators 6.1. dSPACE 6.2. OPAL-RT 6.3. Speedgoat 6.4. RTDS 7. Conclusions References Chapter 6: Adaptive control of islanded AC microgrid 1. Introduction 2. Detailed modeling of islanded AC MG 3. Proposed adaptive control scheme 3.1. Adaptive voltage and reactive power control 3.2. Adaptive frequency and active power control 4. Simulation results and analysis 5. Conclusion References Chapter 7: Proactive defense system for enhanced resiliency of power grids with microgrids 1. Introduction 2. Dependencies and energy management in deregulated grid 2.1. Market model for procurement of reactive power 2.2. Voltage control area formation 2.3. Automatic voltage control (AVC) in emerging grid 3. Renewable uncertainty instigated disturbance propagation 4. Enhancing the power grid resiliency against long-term voltage instability 5. Proactive defense methodology for enhancing power system resiliency 6. Implementation of presented methodology 7. Case studies and discussions 7.1. Case 1: Investigation of propagation characteristics of disturbance 7.2. Case 2: Investigation about the influence of concentrated reactive power support on disturbance propagation 7.3. Case 3: Investigation about the effectiveness of distributed reactive power support on disturbance propagation 7.4. Case 4: Influence of nonlinear long line reverberation characteristics on all the above three cases 8. Conclusions References Chapter 8: Adaptive controller-based shunt active power filter for power quality enhancement in grid-integrated PV systems 1. Introduction 2. Filter configuration 2.1. MPPT algorithm 2.2. Reference current estimation 3. Modeling of three-phase three-wire SAPF 4. PI controller for DC voltage stabilization 4.1. Transfer function for DC-link capacitor 4.2. Transfer function of VSI 4.3. Transfer function of PI controller 5. MRAC for DC voltage stabilization 6. Simulation results 6.1. Case I: Balanced supply with steady-state load condition 6.2. Case II: Balanced supply with varying load condition 6.3. Case III: Balanced supply with parameter variation of SAPF 7. Experimental results 7.1. Case I: Balanced supply with steady-state load condition 7.2. Case II: Balanced supply with varying load condition 7.3. Case III: Balanced supply with parameter variation of SAPF 8. Conclusions References Chapter 9: Issues and challenges in microgrid protection 1. Introduction 2. Microgrid protection challenges 3. Review of microgrid protection schemes 3.1. Overcurrent protection schemes 3.2. Differential protection schemes 3.3. Distance protection schemes 3.4. New microgrid protection techniques 3.5. Rate of angle difference-based protection scheme 3.6. Integrated impedance angle-based protection scheme 3.7. Impedance Difference-Based microgrid protection scheme 4. Conclusions References Chapter 10: Protection schemes in microgrid 1. Introduction 2. Classification of microgrids 2.1. Classification of microgrids based on location 2.1.1. Urban and rural microgrid 2.1.2. Utility microgrid 2.1.3. Community or campus microgrid 2.1.4. Industrial microgrid 2.1.5. Stand-alone or off-grid microgrid 2.2. Classification based on capacity 2.3. Classification of microgrids based on power supply 2.3.1. AC microgrids 2.3.2. DC microgrid 2.3.3. Hybrid AC/DC microgrid 3. Hierarchical control architecture of microgrids 4. Protection issues in microgrids 5. Protection schemes for AC microgrids 5.1. Nonadaptive protection for microgrids 5.2. Adaptive protection for microgrids 5.2.1. Adaptive overcurrent protection scheme 5.2.2. Adaptive differential scheme 5.2.3. Symmetrical component based adaptive protection scheme 6. Protection schemes for DC microgrids 6.1. Current-based protection scheme 6.2. Voltage-based protection scheme 6.3. Traveling wave-based protection scheme 6.4. Interruption in DC current-based protection scheme 7. Protection scheme for hybrid AC/DC microgrid 7.1. Fuse-based short-circuit protection of converter 7.2. Protection scheme based on islanding detection 7.3. Protection scheme for DC lines in hybrid AC/DC microgrid with multilevel converter 8. Conclusion References Index Back Cover