Reliability of Power Electronics Converters for Solar Photovoltaic Applications

Cover
Contents
List of figures
List of tables
About the Editors
1 Power electronics converters for solar PV applications
	1.1 Introduction
	1.2 Role of power electronics in solar PV systems
	1.3 DC–DC power electronics converters
		1.3.1  Buck converter
		1.3.2  Boost converter
		1.3.3  Buck-boost converter
		1.3.4  Single-ended primary inductance converter
		1.3.5  Ćuk converter
		1.3.6  Positive-output super-lift Luo converter
		1.3.7  Ultra-lift Luo converter
		1.3.8  Zeta converter
		1.3.9  Flyback converter
		1.3.10  Three-port half-bridge DC–DC converter
		1.3.11  Full-bridge converter
		1.3.12  Dual active bridge converter
		1.3.13  Multielement resonant converter
		1.3.14  Push-pull converter
	1.4 DC–AC converters
		1.4.1  Transformer-based inverter
		1.4.2  Transformerless inverter
			1.4.2.1  Half-bridge transformerless inverter
			1.4.2.2  Neutral point-clamped transformerless inverter
			1.4.2.3  Active neutral point-clamped transformerless inverter
			1.4.2.4  T-type transformerless inverter
			1.4.2.5  Three-switch transformerless inverter
			1.4.2.6  Full-bridge transformerless inverter
			1.4.2.7  H5 transformerless inverter
			1.4.2.8  Full-bridge transformerless inverter with midpoint switches and diodes
			1.4.2.9  H6-1 transformerless inverter
			1.4.2.10  Modified Highly Efficient and Reliable Inverter Concept
			1.4.2.11  oH5-1 transformerless inverter
			1.4.2.12  Modified transformerless inverter
	1.5 Summary
	References
2 Wear-out failure prediction of a PV microinverter
	2.1 System description and reliability evaluation process
		2.1.1 System description
		2.1.2 Reliability evaluation process
	2.2 Electrothermal and lifetime modeling
		2.2.1 Power loss modeling
		2.2.2 Thermal modeling
		2.2.3 Lifetime modeling
	2.3 Wear-out failure analysis of the PV microinverter
		2.3.1 Static annual damage of components
		2.3.2 Monte Carlo simulation
		2.3.3 System failure probability due to wear-out
	2.4 Reliability improvement of the PV microinverter
		2.4.1 Advanced multimode control of the qZSSRC
		2.4.2 New DC-link electrolytic capacitor with longer nominal lifetime
		2.4.3 Wear-out failure probability
	2.5 Summary
	References
3 Reliability analysis methods and tools
	3.1 Background and motivation
	3.2 Failure mode and effect analysis
	3.3 Design for reliability
	3.4 Software tools in design for reliability
	3.5 Reliability testing and robustness validation
		3.5.1 Qualitative test methods
		3.5.2 Quantitative test methods
		3.5.3 Qualification testing
	3.6 Summary
	References
4  Grid-connected solar inverter system: a case study
	4.1 Identifying the site for case study
		4.1.1 Site details
		4.1.2 Components used in the system
	4.2 Data collected for reliability study
		4.2.1 Failure rate of power electronic switches
			4.2.1.1 Thermal model of IGBT and diode
			4.2.1.2 IGBT failure rate
			4.2.1.3 Diode failure rate
			4.2.1.4 Capacitor failure rate
		4.2.2 Reliability of inverter
	4.3 Reliability study for the identified site
		4.3.1 Risk modeling for components of PV system
			4.3.1.1 The periodic discrete probability distribution of input power
		4.3.2 Reliability analysis of PV array
			4.3.2.1 Equivalent parameters for reliability of PV string
			4.3.2.2 State enumeration for PV array reliability analysis
			4.3.2.3 Effect of aging and degradation
		4.3.3 PV system risk indices
			4.3.3.1 Equivalent parameters for reliability of PV string
			4.3.3.2 Equivalent parameters for reliability of PV string
	4.4 Results of site study for reliability analysis
		4.4.1 Results of reliability indices
		4.4.2 Aging and degradation effects
		4.4.3 PV risk assessment
			4.4.3.1 Impact of temperature
			4.4.3.2 Impact of solar insolation
			4.4.3.3 Impact of capacitor equivalent series resistance
		4.4.4 Impact of the increased number of strings on PV system reliability
		4.4.5 Impact of panel failure rate on PV system reliability
	4.5 Summary
	References
5 Control strategy for grid-connected solar inverters
	Abstract
	5.1 Introduction
		5.1.1 Demands for grid-connected solar inverters
		5.1.2 General controls
	5.2 MPPT control
		5.2.1 Modeling of PV panels
		5.2.2 MPPT algorithm
	5.3 Solar inverter control
		5.3.1 Reference frame transformation
			A. Clarke transformation (abc→ αβ)
			B. Park transformation (αβ→ dq)
		5.3.2 Grid-connected current control
			A. Modeling of the grid current controller
			B. Design of the grid current controller
		5.3.3 PQ Control
			A. Modeling of the PQ control
			B. Design of the DC-link controller
		5.4 Case study
			5.4.1 PI controller for three-phase inverters
			5.4.2 PR controller for single-phase inverters
		5.5 Summary
		References
6 Control strategy for grid-connected solar inverter for IEC standards
	6.1 LVRT requirement for control
		6.1.1 Permissible limit for voltage fluctuation
		6.1.2 Permissible limit for frequency fluctuation
		6.1.3 Power factor, reactive current injection, and reactive power requirement
		6.1.4 Overview of LVRT requirement based on grid codes
	6.2 Control strategy used to meet LVRT standards
		6.2.1 Generator-side converter
			6.2.1.1 Cost function
			6.2.1.2 Control algorithm
		6.2.2 Grid-side converter
			6.2.2.1 Inverter modeltationary reference
			6.2.2.2 Cost functionSimilar to the cost function definition
			6.2.2.3 Current tracking control algorithm and simulation
		6.2.3 Control structure on symmetrical faults
		6.2.4 Control structure and minimization function under unbalanced faults
		6.2.5 Experimental analysis
	6.3 Anti-islanding requirements for control
		6.3.1 IEEE Standard for Interconnection and Interoperability of resources with interfaces (IEEE 1547)
		6.3.2 Utility-interconnected PV inverters—test procedure of islanding prevention measures (IEC 62116)
		6.3.3 IEEE recommended practice for utility interface of PV systems (IEEE 929)
		6.3.4 Requirement overview for anti-islanding operation
	6.4 Control strategy used to meet anti-islanding standards
		6.4.1 Communication-based islanding detection scheme
			6.4.1.1 Power line carrier (PLC) communication
			6.4.1.2 Transfer trip
		6.4.2 Local islanding detection scheme
			6.4.2.1 Passive islanding detection technique
				6.4.2.1.1 Frequency surge/over or under frequency
				6.4.2.1.2 Rate of change in frequency
				6.4.2.1.3 Over or under voltage
				6.4.2.1.4 Harmonics distortion
				6.4.2.1.5 Phase jump detection
			6.4.2.2 Active islanding detection technique
				6.4.2.2.1 Frequency shift (slip mode)
				6.4.2.2.2 Active frequency drift
				6.4.2.2.3 Frequency shift (Sandia)
				6.4.2.2.4 Frequency jump
				6.4.2.2.5 Voltage shift (Sandia)
				6.4.2.2.6 Impedance measurement method
		6.4.3 Intelligent islanding detection scheme
			6.4.3.1 ANN-based islanding detection
			6.4.3.2 FLC-based islanding detection technique
			6.4.3.3 ANFIS-based islanding detection techniques
			6.4.3.4 Decision tree-based islanding detection method
	6.5 Reactive power control and its effect on reliability
	6.6 Conclusion
	References
7 Thermal image based monitoring of PV modules and solar inverters
	7.1 Introduction
	7.2 Review of fault detection of PV modules
	7.3 Thermal image-processing-based fault analysis
		7.3.1 Preprocessing
		7.3.2 Image segmentation
		7.3.3 Feature extraction
		7.3.4 Image classification
	7.4 CNN-based fault diagnosis of solar PV modules
		7.4.1 Convolution layer
		7.4.2 Rectified linear unit
		7.4.3 Pooling
	7.5 CNN-based fault diagnosis of solar PV modules
		7.5.1 Feature extraction
	7.6 Summary
	References
8 Failure mode classification for grid-connected photovoltaic converters
	8.1 Introduction
	8.2 Components of power electronic converters
		8.2.1 IGBT failure
			8.2.1.1 Wear out failure
			8.2.1.2 Catastrophic failure
		8.2.2 Thermal modelling of IGBT
			8.2.2.1 Analytic models
			8.2.2.2 Numeric models
			8.2.2.3 Network models
		8.2.3 Cooling measures
		8.2.4 DC-link capacitor failure
		8.2.5 Power diode failure
	8.3 Failure mechanisms of power semiconductors
		8.3.1 Failure mode, mechanisms and effects analysis
		8.3.2 Power semiconductor failure mechanisms
			8.3.2.1 Aluminium reconstruction
			8.3.2.2 Bond fatigue
			8.3.2.3 Die-attach fatigue and delamination
			8.3.2.4 Substrate cracking
			8.3.2.5 Bond-wire melting
			8.3.2.6 Die-attach voiding
			8.3.2.7 Aluminium corrosion
			8.3.2.8 Latch-up
			8.3.2.9 Avalanche breakdown
			8.3.2.10 Partial discharge
			8.3.2.11 Electrochemical and silver migration
			8.3.2.12 Dielectric breakdown
			8.3.2.13 Time-dependent dielectric breakdown
			8.3.2.14 Hot carrier injection
			8.3.2.15 Competing failure mechanisms
		8.3.3 Power semiconductor failure modes and mechanisms
	8.4 Data preparation and feature extraction
		8.4.1 Wavelet transform
		8.4.2 Harmony search algorithm
		8.4.3 Statistical features
			8.4.3.1 Feature vector representation
				8.4.3.1.1 Signal preprocessing
				8.4.3.1.2 Normalization
				8.4.3.1.3 Reference vector
			8.4.3.2 Feature extraction
		8.4.4 Principle component analysis
	8.5 Machine learning approach
		8.5.1 K-nearest neighbour classifier
		8.5.2 Fault classification algorithm
	8.6 Failure mode effect classification analysis
		8.6.1 Approaches for criticality analysis
		8.6.2 Approaches for severity analysis
		8.6.3 Occurrence
		8.6.4 Detection
	8.7 Summary
	References
Index
Back cover