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- Herausgeber: John Wiley & Sons
- Kategorie: Wissenschaft und neue Technologien
- Sprache: Englisch
A practical and systematic elaboration on the analysis, design and control of grid integrated and standalone distributed photovoltaic (PV) generation systems, with Matlab and Simulink models * Analyses control of distribution networks with high penetration of PV systems and standalone microgrids with PV systems * Covers in detail PV accommodation techniques including energy storage, demand side management and PV output power regulation * Features examples of real projects/systems given in OPENDSS codes and/or Matlab and Simulink models * Provides a concise summary of up-to-date research around the word in distributed PV systems
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Seitenzahl: 580
Veröffentlichungsjahr: 2017
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Table of Contents
Cover
Title Page
Copyright
Preface
Chapter 1: Overview
1.1 Current Status and Future Development Trends of Photovoltaic Generation around the World
1.2 Current Research Status of Grid-Connected Photovoltaic Generation
1.3 Summary
References
Chapter 2: Techniques of Distributed Photovoltaic Generation
2.1 Introduction to Distributed Photovoltaic Generation
2.2 Photovoltaic Cells
2.3 Inverter
2.4 Maximum Power Point Tracking Control
2.5 Summary
References
Chapter 3: Load Characteristics in Distribution Networks with Distributed Photovoltaic Generation
3.1 Introduction
3.2 Load Characteristics of a Distribution Network
3.3 The Output Characteristics of Photovoltaic Generation
3.4 Characteristics of the Net Load in a Distribution Network with Distributed Photovoltaic Generation
3.5 Power and Energy Analysis of Distributed Photovoltaic Generation
3.6 Summary
References
Chapter 4: Penetration Analysis of Large-Scale Distributed Grid-Connected Photovoltaics
4.1 Introduction
4.2 Economic Analysis of Distributed Photovoltaic Systems
4.3 Large-Scale Photovoltaic Penetration Analysis
4.4 Maximum Allowable Capacity of Distributed Photovoltaics in Distribution Network
4.5 Maximum Allowable Capacity of Distributed Photovoltaics Based on Random Scenario Method
4.6 Photovoltaic Penetration Improvement
4.7 Summary
References
Chapter 5: Power Flow Analysis for Distribution Networks with High Photovoltaic Penetration
5.1 Introduction
5.2 Power Flow Calculation for Distribution Networks with Distributed Photovoltaics
5.3 Voltage Impact Analysis of Distributed Photovoltaics on Distribution Networks
5.4 Loss Analysis in Distribution Network with Distributed Photovoltaics
5.5 Case Study
5.6 Summary
References
Chapter 6: Voltage Control for Distribution Network with High Penetration of Photovoltaics
6.1 Introduction
6.2 Voltage Impact Analysis in the Distribution Network with Distributed Photovoltaics
6.3 Voltage Control Measures
6.4 Photovoltaic Inverter Control Strategies
6.5 Modeling and Simulation
6.6 Case Study
6.7 Summary
References
Chapter 7: Short-Circuit Current Analysis of Grid-Connected Distributed Photovoltaic Generation
7.1 Introduction
7.2 Short-Circuit Characteristic Analysis of Distributed Photovoltaic Generation
7.3 Low-Voltage Ride-Through Techniques of Photovoltaic Generation
7.4 Simulation Studies
7.5 Calculation Method for Short-Circuit Currents in Distribution Network with Distributed Photovoltaic Generation
7.6 Summary
References
Chapter 8: Power Quality in Distribution Networks with Distributed Photovoltaic Generation
8.1 Introduction
8.2 Power Quality Standards and Applications
8.3 Evaluation and Analysis of Voltage Fluctuation and Flicker for Grid-Connected Photovoltaic Generation
8.4 Harmonic Analysis for Grid-Connected Photovoltaic Generation
8.5 Summary
References
Chapter 9: Techniques for Mitigating Impacts of High-Penetration Photovoltaics
9.1 Introduction
9.2 Energy Storage Technology
9.3 Application of Energy Storage Technology in Distribution Networks with High Photovoltaic Penetration
9.4 Demand Response
9.5 Application of Demand Response in Distribution Networks with High Penetration of Distributed Photovoltaics
9.6 Cluster Partition Control
9.7 Application of Cluster Partition Control in Distributed Grid with High-Penetration Distributed Photovoltaics
9.8 Summary
References
Chapter 10: Design and Implementation of Standalone Multisource Microgrids with High-Penetration Photovoltaic Generation
10.1 Introduction
10.2 System Configurations of Microgrids with Multiple Renewable Sources
10.3 Controls and Energy Management
10.4 Implementation of Standalone Microgrids
10.5 Summary
References
Index
End User License Agreement
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Guide
Cover
Table of Contents
Preface
Begin Reading
List of Illustrations
Chapter 1: Overview
Figure 1.1 Installation percentage of the world's top 10 PV markets in 2014.
Figure 1.2 Qaidam Basin's million kilowatts solar energy demonstration project.
Chapter 2: Techniques of Distributed Photovoltaic Generation
Figure 2.1 A grid-connected PV system.
Figure 2.2 Monocrystalline silicon solar cell.
Figure 2.3 Polycrystalline silicon solar cell.
Figure 2.4 The equivalent circuits of solar cells: (a) the solar cell ideal circuit model; (b) single-diode equivalent circuit; (c) double-diode equivalent circuit.
Figure 2.5 Single-diode model-based PV array's equivalent circuit.
Figure 2.6 Double-diode model-based PV array's equivalent circuit.
Figure 2.7 Typical
I–V
and
P–V
curves of a PV cell/module.
Figure 2.8 The impact of light irradiance on
I–V
curve and
P–V
curve.
Figure 2.9 The impact of surrounding temperature on
I–V
curve and
P–V
curve.
Figure 2.10 Four connection topologies of the inverter.
Figure 2.11 The topology of the series inverter.
Figure 2.12 The module integrated inverter topology.
Figure 2.13 The multiple series inverter topology.
Figure 2.14 A low-power single-phase PV grid-connected inverter with a flyback converter.
Figure 2.15 A high-power three-phase grid-connected inverter without isolation transformer.
Figure 2.16 A high large-power three-phase grid-connected inverter with a power transformer.
Figure 2.17 The schematic diagram of a three-phase grid-connected system.
Figure 2.18 Output power characteristic curve of a PV array.
Figure 2.19 The P&O method becomes invalid when the solar irradiance changes dramatically.
Figure 2.20 The flowchart of an IncCond algorithm.
Figure 2.21 The load type: (1) voltage source load; (2) impendence load; (3) impedance and voltage mixed load; (4) current source load.
Chapter 3: Load Characteristics in Distribution Networks with Distributed Photovoltaic Generation
Figure 3.1 The classification of load characteristic indices.
Figure 3.2 Four typical daily load profiles in four seasons: (a) industrial load; (b) agricultural load; (c) commercial load; (d) residential load.
Figure 3.3 Time-sequence load curves in the SA substation area.
Figure 3.4 Monthly load duration curve in July.
Figure 3.5 PDF of 5 min load fluctuation in July.
Figure 3.6 Time-sequence characteristic curves of PV generation in four seasons.
Figure 3.7 Time-sequence characteristic curves of PV generation under different weather conditions.
Figure 3.8 A field photograph of the distributed PV generation in the SA substation area.
Figure 3.9 The maximum daily output power curves of the distributed PV generation in four seasons.
Figure 3.10 The duration output power characteristic curves of the distributed PV generation in the four seasons.
Figure 3.11 The PDF of 5 min output power variation of the PV generation for the four seasons in 2014.
Figure 3.12 The monthly load duration curves of the SA substation area with/without the PV generation in July 2014.
Figure 3.13 The monthly load duration curves of the net load in July in the SA substation area.
Figure 3.14 The daily time-sequence characteristic curves of the system net load under different sizes PVs.
Figure 3.15 The PDF of the variations of system net load under different PV penetration levels.
Figure 3.16 The selection of the maximum load day.
Chapter 4: Penetration Analysis of Large-Scale Distributed Grid-Connected Photovoltaics
Figure 4.1 PV inverter price 2013–2030.
Figure 4.2 Simplified diagram of grid parity of PV electricity.
Figure 4.3 Schematic diagram of a typical electrical power distribution system.
Figure 4.4 Schematic diagram of unavailable PV output.
Figure 4.5 Annual load curve of the SA substation.
Figure 4.6 Net load duration curve.
Figure 4.7 Relationship between PV PP, CP, and grid-connected PV capacity.
Figure 4.8 Frequency distribution of PV output to load when .
Figure 4.9 Load curve of the SA substation when .
Figure 4.10 PUR and net load curve of the SA substation when .
Figure 4.11 Net load duration curve at different EP values.
Figure 4.12 Relationship between PV EP and PV capacity.
Figure 4.13 Diagram of relationship between PP, CP, and EP.
Figure 4.14 Relationship of PUR, PC, and PV EP.
Figure 4.15 PV-load distribution characteristics: (a) industrial load; (b) agricultural load; (c) commercial load; (d) residential load.
Figure 4.16 Installed PV capacity–EP curves of different types of load.
Figure 4.17 Impact of distributed PV system connection on local voltage.
Figure 4.18 Equivalent circuit of distribution network with distributed PV system.
Figure 4.19 Schematic diagram of the “random scenario.”
Figure 4.20 Evaluation process of maximum allowable PV capacity.
Figure 4.21 Topology of the 10 kV feeder of the SA substation.
Figure 4.22 Load profile of the 10 kV feeder in the SA substation in 2014.
Figure 4.23 Possible PV connection locations.
Figure 4.24 Distribution of PV capacity of distribution network.
Chapter 5: Power Flow Analysis for Distribution Networks with High Photovoltaic Penetration
Figure 5.1 Nondispatchable grid-connected PV system.
Figure 5.2 Dispatchable grid-connected PV system with energy storage.
Figure 5.3 Typical structure of a medium-voltage feeder in radial distribution network.
Figure 5.4 Load distributions on feeder.
Figure 5.5 Feeder voltage profiles under different PV locations.
Figure 5.6 (a) Voltage profiles and (b) active power flow under different PV capacities at node 1.
Figure 5.7 (a) Voltage profiles and (b) active power flow under different PV capacities at node 5.
Figure 5.8 (a) Voltage profiles and (b) active power flow under different PV capacities at node 9.
Figure 5.9 Voltage profiles for distributed installation of multiple PV systems.
Figure 5.10 Voltage profiles for centralized installation of multiple PV systems.
Figure 5.11 Diagram of typical distribution line.
Figure 5.12 Distribution loss under different PV capacities.
Figure 5.13 Distribution losses under different PV locations.
Figure 5.14 A 0.4 kV-level typical integration scheme for distributed PVs in China.
Figure 5.15 A10 kV-level typical integration scheme for distributed PVs in China.
Figure 5.16 The 10 kV feeder SA_F1 supplied by a 110 kV substation.
Figure 5.17 Voltage of key nodes on the feeder with/without PVs connection.
Figure 5.18 Node voltages at different locations with/without added PVs.
Figure 5.19 Power flow at the root of SA_F1 throughout the year of 2014.
Figure 5.20 Reverse power flow throughout the year of 2014.
Figure 5.21 Power flow in the SA area of the maximum PV output scenario.
Figure 5.22 Power loss comparison of substation SA with and without PVs.
Figure 5.23 Monthly peak output power of substation SA with and without PVs.
Figure 5.24 Monthly peak voltage of 10 kV/0.4 kV nodes of the SA substation with PVs.
Chapter 6: Voltage Control for Distribution Network with High Penetration of Photovoltaics
Figure 6.1 Simplified circuit diagram of distributed PVs connected to distribution network.
Figure 6.2 Curves of voltage variation at the PCC.
Figure 6.3 Available reactive power of PV inverter.
Figure 6.4 Control principle of a PV inverter.
Figure 6.5 Voltage adaptive control principle.
Figure 6.6 PV inverter variable power factor control curve.
Figure 6.7 PV inverter reactive voltage control curve.
Figure 6.8 Inverter
P–Q
capacity curve.
Figure 6.9 (a) Simplified and (b) equivalent circuit diagram of OLTC.
Figure 6.10 OLTC discrete control block diagram.
Figure 6.11 Control diagram of OLTC control structure in OpenDSS.
Figure 6.12 Simplified circuit of shunt capacitor compensation.
Figure 6.13 SC discrete control block diagram.
Figure 6.14 SC control model in OpenDSS.
Figure 6.15 PV system model.
Figure 6.16 PV control block diagram.
Figure 6.17
V–Q
control curve of PV inverter.
Figure 6.18 Solar irradiance change pattern on extreme day (May 1, 2014).
Figure 6.19 Solar irradiance change pattern on extreme day (July 16, 2014).
Figure 6.20 Comparison of the full-day load profile between a working day and a holiday on feeder SA-F1.
Figure 6.21 Load profile and PV output on feeder SA-F1 on a working day.
Figure 6.22 Voltage of C2 at the PCC on a working day.
Figure 6.23 Change trends in load, PV output, and reverse power flow on feeder SA-F1 under the holiday scenario.
Figure 6.24 Voltage of C2 at the PCC under the holiday scenario.
Figure 6.25 Reactive powers on the high-voltage side of main transformer no. 1 on a working day under the three control strategies.
Figure 6.26 Reactive powers on the high-voltage side of main transformer no. 2 on a working day under the three control strategies.
Figure 6.27 Composition of reactive power on the high-voltage side of no. 2 main transformer on a working day under the reactive voltage control strategy.
Figure 6.28 Composition of reactive power on the high-voltage side of no. 2 main transformer on a working day under the variable power factor control strategy.
Figure 6.29 Composition of reactive power on the high-voltage side of no. 2 main transformer on a working day under the constant power factor control strategy.
Figure 6.30 Comparison of reactive power absorbed by the PVs of C2 on a working day under the three control strategies.
Figure 6.31 Voltage comparison of C2 at the PCC on a working day under the three control strategies.
Figure 6.32 Comparison of reactive power absorbed by all PVs of substation SA on a working day under the three control strategies.
Figure 6.33 Comparison of power losses of substation SA on a working day under the three control strategies.
Figure 6.34 The three modes of PV output fluctuation.
Figure 6.35 PV output fluctuation of C2.
Figure 6.36 Reactive power on high-voltage side of no. 1 main transformer on holiday under the three control strategies.
Figure 6.37 Reactive power on high-voltage side of no. 2 main transformer on a holiday under the three control strategies.
Figure 6.38 Reactive power absorbed by the PVs of C2 on a holiday under the three control strategies.
Figure 6.39 Voltage profiles at the PCC of C2 during a holiday under the three control strategies.
Figure 6.40 Reactive power absorbed by all the PVs in substation SA for the holiday scenario under the three control strategies.
Figure 6.41 Comparison of power losses in substation SA for the holiday scenario under the three control strategies.
Figure 6.42 Voltage at the PCC of C2 on May 1, 2014, with different efficiencies of PVs under the reactive voltage control strategy.
Chapter 7: Short-Circuit Current Analysis of Grid-Connected Distributed Photovoltaic Generation
Figure 7.1 Control strategy of a PV inverter.
Figure 7.2 Equivalent circuit diagram of an inverter for short-circuit calculation.
Figure 7.3 (a) Positive-sequence and (b) negative-sequence equivalent circuits of PV inverter at AC side.
Figure 7.4 LVRT standards for PV generation made in different countries.
Figure 7.5 Chinese standards for reactive power support.
Figure 7.6 Structure of energy dump circuit on the DC side.
Figure 7.7 Diagram of positive and negative-sequence superposition control.
Figure 7.8 LVRT control strategy flow chart.
Figure 7.9 The topological structure diagram of simulation cases.
Figure 7.10 PV output waveforms in the case of three-phase grid voltage symmetrically dropping to 20%. (a) Positive-sequence
d
-axis and
q
-axis currents of inverter; (b) negative-sequence
d
-axis and
q
-axis currents of inverter; (c) three-phase output current of inverter; (d) Output active and reactive power of inverter; (e) voltage on the DC side of inverter.
Figure 7.11 PV output waveforms in the case of symmetrical 80% drop in three-phase grid voltage: (a) positive-sequence
d
-axis and
q
-axis currents of inverter; (b) negative-sequence
d
-axis and
q
-axis currents of inverter; (c) three-phase output current of inverter; (d) output active and reactive power of inverter; (e) voltage on the DC side of inverter.
Figure 7.12 PV output waveforms in the case of 80% two-phase voltage drop: (a) positive-sequence
d
-axis and
q
-axis currents of inverter; (b) negative-sequence
d
-axis and
q
-axis currents of inverter; (c) three-phase output current of inverter; (d) active and reactive power of inverter; (e) voltage on the DC side of inverter.
Figure 7.13 PV output waveforms in the case of 80% single-phase voltage drop: (a) positive-sequence
d
-axis and
q
-axis currents of inverter; (b) negative-sequence
d
-axis and
q
-axis currents of inverter; (c) three-phase output current of inverter; (d) active and reactive power of inverter; (e) voltage on the DC side of inverter.
Figure 7.14 A typical distribution network containing multiple distributed PV generation.
Figure 7.15 PV fault current vector.
Figure 7.16 Three-phase short-circuit equivalent network in a distribution network with PVs.
Figure 7.17 Positive-sequence network.
Figure 7.18 Negative-sequence network.
Figure 7.19 Combined-sequence network of a two-phase short-circuit fault.
Figure 7.20 Typical distribution network with distributed PV generation.
Figure 7.21 Three-phase short-circuit fault waveforms of bus D through a 0.1 Ω fault resistance without integration of distributed PV generation: (a) system voltage waveforms; (b) system current waveforms; (c) voltage waveforms at fault point; (d) current waveforms at fault point.
Figure 7.22 Three-phase fault waveforms of bus D through a 0.1 Ω fault resistance with integration of distributed PV generation: (a) system voltage waveforms; (b) system current waveforms; (c) voltage waveforms of PV generation 1, (d) current waveforms of PV generation 1; (e) voltage waveforms of PV generation 2; (e) current waveforms of PV generation 2; (g) voltage waveforms of PV generation 3; (h) current waveforms of PV generation 3; (i) voltage waveforms at fault point; (j) current waveforms at fault point.
Figure 7.23 Three-phase fault waveforms of bus B through 0.1 Ω fault resistance with integration of distributed PV generation: (a) system voltage waveforms; (b) system current waveforms; (c) voltage waveforms of PV generation 1, (d) current waveforms of PV generation 1; (e) voltage waveforms of PV generation 2; (e) current waveforms of PV generation 2; (g) voltage waveforms of PV generation 3; (h) current waveforms of PV generation 3; (i) voltage waveforms at fault point; (j) current waveforms at fault point.
Chapter 8: Power Quality in Distribution Networks with Distributed Photovoltaic Generation
Figure 8.1 Comparison of limit values of harmonic current of 6 MW PV generation integrated into a 10kV power grid.
Figure 8.2 Comparison of limit values of current harmonics of 300 kW PV generation integrated into a 380 V power grid.
Figure 8.3 Total demand distortion of PV inverter output current harmonics.
Figure 8.4 THD of PV inverter output current.
Figure 8.5 Equivalent circuit for PV voltage fluctuation and flicker evaluation.
Figure 8.6 Phasor diagram.
Figure 8.7 A PWM strategy.
Figure 8.8 Harmonic distribution in case of triangular waveform modulation in a single-phase inverter.
Figure 8.9 Harmonic distribution of a symmetrical modulation in a single-phase inverter.
Figure 8.10 Harmonic distribution in case of three-phase SVPWM.
Figure 8.11 Distribution of THD
u
% on feeder after the connection of PVs to different nodes.
Figure 8.12 Distribution of THD
i
on the feeder at different PV nodes.
Figure 8.13 Distribution of THD
u
% under different sizes of PV generation at node 1.
Figure 8.14 Distribution of THD
i
under different sizes of PV generation to node 1.
Figure 8.15 Distribution of THD
u
% under different sizes of PV generation at node 5.
Figure 8.16 Distribution of THD
u
% under different sizes of PV generation at node 9.
Figure 8.17 Distribution of THD
u
% introduced by a 5 MW PV system connected in a distributed way.
Figure 8.18 Distribution of THD
u
% along bus SA_F1 in the test substation.
Chapter 9: Techniques for Mitigating Impacts of High-Penetration Photovoltaics
Figure 9.1 Classification of energy storage technologies.
Figure 9.2 Technical maturity of energy storage technologies.
Figure 9.3 Relationship between the effective weighting factor and SOC of a lead–acid battery.
Figure 9.4 Plan for integrating PVs into the distribution network.
Figure 9.5 The PV active power profile in the distribution network.
Figure 9.6 Local
L
indices at PV nodes in the distribution network.
Figure 9.7 Comparison of PV hosting capacity.
Figure 9.8 Comparison of
L
indices in three cases.
Figure 9.9 Load curves of different users.
Figure 9.10 Incentive-based DR effect.
Figure 9.11 Load transfer algorithm implementation flow chart.
Figure 9.12 Schematic diagram of DR solving process.
Figure 9.13 (a) Solar radiation curve and (b) load curve.
Figure 9.14 The load curves before and after the DR for (a) for typical overcast and rainy weather, (b) typical cloudy weather, and (c) typical sunny weather.
Figure 9.15 PV penetration and customer satisfaction with different percentages of shiftable load capacity.
Figure 9.16 Basic framework of distributed PV cluster control in distribution network.
Figure 9.17 Network partition and process of voltage control.
Figure 9.18 Flowchart of the proposed sub-community zonal voltage control.
Figure 9.19 Topology of the real feeder with future PV installation.
Figure 9.20 Current and future PV installations in the feeder.
Figure 9.21 Annual solar irradiance and load profiles (i.e., in 8760 h).
Figure 9.22 PV inverter efficiency versus per unit input power curve.
Figure 9.23 Annual voltage profiles for all nodes.
Figure 9.24 Modularity ρ function versus the number of clusters.
Figure 9.25 The curtailed active power and the absorbed reactive power of the PV units using the proposed scheme.
Figure 9.26 Voltage profiles under different scenarios.
Figure 9.27 Curtailed active and absorbed reactive power as a percentage under the non-partition management scheme.
Figure 9.28 Voltage magnitude profiles under the two different control schemes.
Figure 9.29 Varying solar irradiance profile used in the dynamic simulations.
Figure 9.30 Voltage profile of node 24 under three conditions: no control, proposed method, and non-partition dispatch scheme.
Chapter 10: Design and Implementation of Standalone Multisource Microgrids with High-Penetration Photovoltaic Generation
Figure 10.1 Schematic diagram of a DC MG.
Figure 10.2 Schematic of an AC MG: (a) PFAC; (b) HFAC.
Figure 10.3 Schematic diagram of a hybrid MG.
Figure 10.4 Illustration of a centralized control paradigm.
Figure 10.5 Illustration of a distributed control paradigm.
Figure 10.6 Illustration of a hybrid hierarchical control paradigm.
Figure 10.7 Configuration diagram of Dongfushan MG.
Figure 10.8 Photographs of the devices in the Dongfushan MG.
Figure 10.9 System operation modes.
Figure 10.10 Power management flowchart of Mode 1.
Figure 10.11 Power management flowchart of Mode 2.
Figure 10.12 Power management flowchart of Mode 3.
Figure 10.13 Flowchart of the optimization process.
Figure 10.14 Historical data of a typical year: (a) power percentage of the WTs; (b) power percentage of the PVs; (c) load demand.
Figure 10.15 The operation time of DE versus the RES generation penetration.
Figure 10.16 Breakdown of the life-cycle cost.
Figure 10.17 RES utilization (and lifetime of BS) versus BS storage capacity.
Figure 10.18 Optimization results of different system sizing schemes.
Figure 10.19 Simulation study results of the system with the optimal configuration. (a) Operation state of the RES and the DE. (b) The SOC distribution of the BS. (c) Power output distribution of the DE.
Figure 10.20 Configuration diagram of the plateau MG.
Figure 10.21 Flowchart of virtual bidding.
Figure 10.22 Visualization of operation scheduling.
Figure 10.23 Dynamic response process of the proposed EMS in different time scales.
Figure 10.24 The RTDS–PXI real-time simulation platform (A: real-time monitoring of PXI; B: real-time simulation results of MG).
Figure 10.25 Classification and functions of the agents.
Figure 10.26 Schematic diagram of the real-time PXI–RTDS simulation/validation platform.
List of Tables
Chapter 1: Overview
Table 1.1 World's top 10 PV manufacturers in 2014
Chapter 2: Techniques of Distributed Photovoltaic Generation
Table 2.1 Comparison of the solar cells
Table 2.2 The classification of PV inverters
Table 2.3 The restriction of the maximum islanding detection time
Chapter 3: Load Characteristics in Distribution Networks with Distributed Photovoltaic Generation
Table 3.1 The maximum load and the maximum load utilization hour in a 110 kV SA substation of City J in 2014
Table 3.2 China State Grid's technical standards on power fluctuation of grid-connected PV generation [18]
Table 3.3 Standards for connecting distributed generation to distribution network [19]
Table 3.4 The daily operation hours and the daily effective operation hours of PV generation
Table 3.5 The maximum load, the maximum load utilization hours, and the peak load duration hours of the system with/without the distributed PV generation
Table 3.6 Load factor and peak–valley difference of the system with/without the distributed PV generation
Table 3.7 The peak load duration of the net load in January, April, July, and October of 2014 in the SA substation area
Table 3.8 The maximum fluctuation of system net load under different PV capacities
Chapter 4: Penetration Analysis of Large-Scale Distributed Grid-Connected Photovoltaics
Table 4.1 Typical daily PV penetration of different types of load
Chapter 5: Power Flow Analysis for Distribution Networks with High Photovoltaic Penetration
Table 5.1 Comparison of typical power flow calculation methods for distribution network [1]
Table 5.2 Location of the distributed PV system in simulation scenarios
Table 5.3 Different capacities of the distributed PV system at node 1 for different simulation scenarios
Table 5.4 PV locations under distributed installation cases
Table 5.5 PV locations under centralized installation cases
Table 5.6 Range of the PV capacities
Table 5.7 PV installation of SA_F1
Table 5.8 Data of load and PV system
Table 5.9 Statistical operation data of SA_F1 with PVs in year 2014
Table 5.10 Electrical data for the SA substation
Table 5.11 Data for the distributed PV systems
Table 5.12 Statistical PV data for the SA substation
Table 5.13 Simulation results of substation SA with PVs connected
Table 5.14 Index comparison of the SA substation with and without PVs
Chapter 6: Voltage Control for Distribution Network with High Penetration of Photovoltaics
Table 6.1 AccepTable deviations of supply voltage in China (GB/T 12325-2008)
Table 6.2 AccepTable deviations of supply voltage (120 V) in the USA (ANSI C84.1)
Table 6.3 Tap stalls of main transformer (no. 1 or no. 2) and high-voltage side voltage in SA substation
Table 6.4 Information for distributed PVs on feeder SA-F1
Table 6.5 Actions of all capacitor banks in different control strategies
Table 6.6 Number of reactive power regulation periods and number of reactive power regulation users on a working day under the three control strategies
Table 6.7 Action times of capacitor banks during the whole day (holiday scenario) under the three control strategies
Table 6.8 Number of PV reactive regulation periods and number of reactive regulation users for the holiday scenario under the three control strategies
Chapter 7: Short-Circuit Current Analysis of Grid-Connected Distributed Photovoltaic Generation
Table 7.1 Voltage response requirements of distributed power supply
Table 7.2 Overcurrent protection standard for distributed PV supply
Table 7.3 Parameters of the distribution network with PV generation
Table 7.4 Comparison of simulation results in case 1
Table 7.5 Comparison of simulation results in case 2
Table 7.6 Comparison of simulation results in case 3
Chapter 8: Power Quality in Distribution Networks with Distributed Photovoltaic Generation
Table 8.1 Brief comparison of power quality provisions in China and international PV integration standards
Table 8.2 Limit values of PV current harmonics stipulated in GB/T200426-2006 and IEEE Std 1547
Table 8.3 Comparison of limit values of current harmonics of a 6 MW PV generation integrated into a 10 kV power grid
Table 8.4 Comparison of limit values of current harmonics of a 300 kW PV generation integrated into a 380 V power grid
Table 8.5 Limit values of voltage harmonics of a public supply network
Table 8.6 First-level limit values of low- and medium-voltage users
Table 8.7 Voltage changes at the PCC
Table 8.8 Voltage flicker at the PCC calculated using the curve analysis method
Table 8.9 Piecewise representation of SVPWM process
Table 8.10 Grid-connected PV capacities in practical cases
Chapter 9: Techniques for Mitigating Impacts of High-Penetration Photovoltaics
Table 9.1 Lead-carbon battery energy storage power station projects
Table 9.2 Li-ion battery energy storage power station projects
Table 9.3 Vanadium redox flow battery energy storage power station projects
Table 9.4 Voltage control of sub-community
C
4
Table 9.5 Comparison of the two schemes
Chapter 10: Design and Implementation of Standalone Multisource Microgrids with High-Penetration Photovoltaic Generation
Table 10.1 Operation parameters
Table 10.2 Characteristics of wind and solar resources
Table 10.3 System sizing with different objectives
Table 10.4 Available choices of units in the Dongfushan MG
Table 10.5 Operation practice of year 2011 (August to December)
Grid-Integrated and Standalone Photovoltaic Distributed Generation Systems
Analysis, Design, and Control
Bo Zhao
State Grid Zhejiang Electric Power Research Institute Hangzhou, China
Caisheng Wang
Electrical and Computer Engineering Department, Wayne State University Detroit, USA
Xuesong Zhang
State Grid Zhejiang Electric Power Research Institute Hangzhou, China
This edition first published 2018 by John Wiley & Sons Singapore Pte. Ltd under exclusive licence granted by China Electric Power Press for all media and languages (excluding simplified and traditional Chinese) throughout the world (excluding Mainland China), and with non-exclusive license for electronic versions in Mainland China.
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Library of Congress Cataloging-in-Publication Data
Names: Zhao, Bo, 1977- author.
Title: Grid-Integrated and standalone photovoltaic distributed generationsystems : analysis, design and control / Dr. Bo Zhao, State Grid ZhejiangElectric Power Research Institute, Hangzhou, China; Dr. Caisheng Wang, Electrical and Computer Engineering Department, Wayne State University, Detroit, USA; Dr. Xuesong Zhang, State Grid Zhejiang Electric Power Research Institute, Hangzhou, China.
Description: Hoboken, NJ, USA : Wiley, 2017. | Includes bibliographical references and index. |
Identifiers: LCCN 2017011367 (print) | LCCN 2017026557 (ebook) | ISBN 9781119187363 (pdf) | ISBN 9781119187356 (epub) | ISBN 9781119187332 (cloth)
Subjects: LCSH: Photovoltaic power generation. | Interconnected electric utility systems. | Distributed generation of electric power.
Classification: LCC TK1087 (ebook) | LCC TK1087 .Z45 2017 (print) | DDC 621.31/244-dc23
LC record available at https://lccn.loc.gov/2017011367
Cover Design: Wiley
Cover Image: © Petmal/Gettyimages
Preface
With the progress of technology, human beings have undergone the transition from industrial civilization to ecological civilization, from extensive and inefficient expending to economical and efficient consumption, and from high carbon production to low carbon production. The present fossil-energy-dominated world energy paradigm is gradually changing into a multiple energy structure and will eventually be dominated by nonfossil energy. Against this background, the development of distributed photovoltaic (PV) generation systems, characterized by adaptation to local conditions, clean and efficient, decentralized layout, and local consumption, have experienced phenomenal growth in the past two decades. The world total solar power capacity had reached over 227 GW by 2015 and over 50 GW of the solar capacity were added in that year. Over 28 GW of solar power had been installed in the USA by the end of 2016. The PV capacity in Germany is currently over 40 GW. China is expected to deploy 70 GW PVs by 2017. The International Energy Agency estimates that solar power will become one of the mainstream energy sources by 2050 and contribute about 11% of world electricity generation. The majority of these PV systems have been and will be installed in distribution networks. As a result, the PV penetration level will become unprecedentedly high (e.g., well over 50%) and continue to grow in many distribution networks around the world. The high penetration of PV systems has led to great technical challenges, including voltage problems, harmonics, grid protection, and so on, in the operation and development of modern distribution networks.
In recent years, the authors and their teams have undertaken a series of PV-related projects, such as the implementation of PV systems for Jiaxing PV Science Park, Jianshan New Industrial Zone in Haining, and Hangzhou Bay New Zone PV Science Park. The main characteristic of these projects was to analyze the impact of integration of distributed PVs into the distribution networks at high penetration and develop measures to better accommodate those sources.
This book is the result of over 10 years of research on distributed PVs and integration of PVs in distribution networks and microgrids. It combines the theory, modeling, analysis and control, and the actual implementation of distributed PVs in one place. The book is focused on the operation and control of distribution networks and microgrids with high penetration of distributed PVs, covering the topics of PV hosting capacity analysis, power flow of distribution networks, reactive voltage regulation, short-circuit current calculation, power quality evaluation, methods of integrating distributed PVs into distribution networks at high penetration levels, and actual system implementation experiences. The book is intended to be a resource for all engineers, and for all those interested in designing policies for facilitating renewable energy development. An overview of the chapters covered in the book is now presented.
Chapter 1 introduces the current status and future development trends of PVs around the world. The PV industry development history of different countries, including the USA, Japan, Germany, and China, and the relevant policies, laws, and demonstration projects in these countries are also briefly introduced. Chapter 2 gives a brief coverage of the basic techniques of distributed grid-connected PV systems, with focus on their configurations, components and maximum power point tracking techniques. Chapter 3 presents the load characteristics of a distribution network with and without distributed PVs and provides theoretical foundations for further analysis on PV penetration and power flow in distribution networks.
Chapter 4 covers the concepts of PV power penetration, capacity penetration and energy penetration, analyzes the key challenges in different development stages of distributed grid-connected PV, studies the impact of grid-connected PVs on distribution networks, explores the maximum allowable capacity of grid-connected PVs under the requirement of safe and stable operation of the distribution networks, and presents the methods to increase PV penetration in distribution networks.
Chapter 5 introduces various power flow calculation methods for distribution networks. It then shows the impact of PVs on the power flow in distributed networks, including voltage variation and distribution loss caused by the PVs added. Models of voltage and distribution loss considering PVs are established, which are then used to analyze the impact of different PV capacities and locations.
Chapter 6 addresses one of the important issues caused by high PV penetration: the voltage control of distribution networks with distributed PVs. In this chapter, the impacts on voltage due to distributed PVs are analyzed first and three control strategies (the constant power factor control strategy, variable power factor control strategy, and the reactive voltage control strategy) and relevant modeling methods are then introduced.
Chapter 7 analyzes the short-circuit characteristics of distributed PVs under symmetrical and asymmetrical grid voltage sags, discusses different low voltage ride-through (LVRT) standards for PVs and the LVRT control strategies, and characterizes the fault currents of PVs. An iterative algorithm is given in the chapter for the calculation of fault currents for distribution networks with distributed PVs.
Chapter 8 discusses the impact of grid-connected PVs on power quality. Chinese and international standards on PV integration harmonic requirements are compared and discussed. The differences in power quality terms and the methods for analyzing the impacts due to distributed PVs on distribution network power quality are given.
Chapter 9 discusses various technologies, including energy storage, demand response, and a network partition-based zonal control technology to better accommodate PVs for distribution networks.
Chapter 10 is a good addition to the other chapters in the book by addressing microgrids with PVs. The chapter reviews the configurations of AC, DC, and AC/DC hybrid microgrids, system unit sizing of microgrid components, and the control framework and the implementation of microgrids. The optimal design, planning, and control of microgrids are given in the chapter through a discussion of the implementation examples of two real standalone microgrids. The implementation and operation experiences and lessons learned from the two microgrids are also summarized in the chapter.
The authors are honored to have the privilege to work with their collaborators for this book, which is a result of an exemplar group effort. Mr. Yibin Feng and Dr. Junhui Zhao are the main authors of Chapter 1. Dr. Xuesong Zhang and Dr. Junhui Zhao are the leading authors of Chapter 2, along with Dr. Jinhui Zhou for Chapter 3, Miss Chen Xu and Dr. Jian Chen for Chapter 5, Prof. Li Guo for Chapter 7, Mr. Peng Li and Prof. Zaijun Wu for Chapter 8. Professor Ming Ding and Professor Hongbin Wu of Hefei University of Technology offered a great deal of help to the authors. Professor Saleh A. Al-Jufout from Tafila Technical University kindly helped proofread Chapter 5. The authors also would like to thank team members and students for their help and contributions to this book, including Da Lin, Ke Xu, Xiaohui Ge, Ziling Wang, Ke Wang, Meidong Xue, Xiangjin Wang, Chuanliang Xiao, Zhichen Xu, Haifeng Qiu, Tingli Hu, Chang Fu, Zhongyang Zhao, Michael Fornoff, and Nicholas Lin.
An important feature of this book is that there are case studies accompanied with simulation studies for many chapters. We hope this book and the examples given in the book will be useful to industry professionals, educators, students, and researchers worldwide in developing distributed PVs at high penetration level.
Bo Zhao State Grid Zhejiang Electric Power Research Institute, ChinaCaisheng Wang Wayne State University, USAXuesong Zhang State Grid Zhejiang Electric Power Research Institute, China
August, 2017
Chapter 1Overview
1.1 Current Status and Future Development Trends of Photovoltaic Generation around the World
With the growing `challenges in global resource depletion, global warming, and ecological deterioration, increasing attention has been given to renewable energy generation, especially to photovoltaic (PV) generation. The global market of PVs has experienced a rapid increase since 1998, with a yearly increase of 35% of the installed capacity. The total PV installed capacity was 1200 MW in 2000, and PV installations rose rapidly up to 188 GW in 2014 and is projected to be 490 GW by 2020 [1]. With the rapid development of the PV industry, the market competition is getting increasingly fierce. The investment in the PV market is being boosted in some countries and regions, like the USA, China, Japan, and Europe. By the end of 2014, the global production of PV modules was around 50 GW, in which China increased 27.2% from the previous year to 35 GW, contributing 70% of the global production [2]. The global production of PV modules is expected to reach 85 GW and maintain the momentum of rapid growth [3].
Recently, a number of countries announced their policies and plans to further promote the development of PVs [4, 5]. The US Environmental Protection Agency (EPA) published its Clean Power Plan on June 2, 2014, promising that the usage of renewable energy (including solar energy) will be doubled within 10 years. The US Department of Energy (DOE) will spend $15 million to help families, enterprises and communities develop the solar energy program [6]. The Japanese Government enacted laws, like the Renewable Energy Special Measure Law and the Renewable Portfolio Standard Law, to identify the development objectives of new energy in Japan and the responsibilities of the participating parties [7]. China has highlighted a few key and crucial demonstration projects of the PV technologies in the Outline of the National Program for Long- and Medium-Term Scientific and Technological Development (2006–2020), the National 11th Five-Year Scientific and Technological Development Plan and the Renewable Energy 12th Five-Year Plan [4–8].
It is noteworthy that the USA and Japan have both worked through the PVs “Industry Roadmap Through 2030 And Beyond.” Japan expects that the future research and development pattern of PVs could be changed from creating an initial PV market based on the government's guide to creating a mature PV market based on cooperation and work sharing among academia, industry, and government, and targets to have a total PV installation capacity of 100 GW in 2030. The USA anticipates that the development pattern of the PV industry could be changed from export led to national investment oriented, promoting the industry's significant growth by devoting on the advancement of technologies and market and expansion of the domestic demand. It is projected to install 19 GW of PVs yearly in the USA, with the expectation of a total installed capacity of 200 GW by 2030. By then the cost of the PVs will decline to $0.06/kW, and PVs will make up an important part of the electricity market and become one of the main sources of electricity.
As to the development of the PV industry in China, from the viewpoint of the current status and future trend, the estimated installed capacity was for 300 MW, 1.8 GW, 10 GW, and 100 GW in 2010, 2020, 2030, and 2050 respectively in the Medium and Long Term Development Plan of Renewable Energies (2007), which is apparently lower than actual development and lags behind the trend of the PV industry. Meanwhile, China has not proposed clear goals of the method, direction, and path for developing the critical technologies and devices that has already limited the advancement of the PV industry. In terms of the grid-connected PVs, there is a lack of complete and systematic regulations and policies for operation and management, electricity price, and system maintenance. Therefore, actively promoting the research and practical applications in the Chinese PV industry to follow the main stream of the global PV industry development will be of profound significance in the future.
At present, some developed countries (such as the USA, Germany, Australia, Japan, etc.) are leading the research and development of PV technologies. For example, Australia, represented by Professor Martin A. Green from the University of New South Wales, has made a great contribution to the development of PV cells by leading the research of single crystalline silicon solar cells in the world and proposing the concept of the third-generation PV cells [9]. The USA, the UK, Germany, Spain, Japan, and so on initiated the PV industry and applications early and have experienced rapid development. Although China's PV industry started late, it has experienced exponential growth. Especially after 2004, stimulated by the large demand from the European market, China's PV industry has boomed and saw over 100% yearly growth for five years in a row. In 2007, China became the largest producer of PV cells. China's PV production exceeded 50% of global production in 2010. China has gradually formed an orbicular chain in the PV industry, from silicon material, PV cells, to PV systems and applications [10, 11]. As shown in Table 1.1, China's PV manufacturers now take a dominant role in the world's PV production. Of the world's top 10 PV manufacturers, six are from China and all the top five are from China. Among them, the number one manufacturer Trina Solar produced 3.66 GW in 2014, closely followed by Yingli Green Energy, which yielded 3.36 GW [2].
Table 1.1 World's top 10 PV manufacturers in 2014
Manufacturer
Country
Rank
Production
(GW)
(%)
Trina Solar
China
1
3.66
14.6
Yingli Green Energy
China
2
3.36
13.4
Canadian Solar
China
3
3.11
12.4
Jinko Solar
China
4
2.94
11.7
JA Solar
China
5
2
8.0
Sharp
Japan
5
2
8.0
Renesolar
China
7
1.97
7.8
First Solar
USA
8
1.85
7.4
Hanwha SolarOne
South Korea
9
1.45
5.8
Sunpower
USA
10
1.4
5.6
In 2014, global PV installations increased by 17%, while the total installed capacity reached 47 GW. Figure 1.1 shows the market share of the world's top 10 PV countries in 2014. The top 10 countries were China, Japan, the USA, the UK, Germany, France, South Africa, Australia, India, and Canada with a total installed capacity of 38.3 GW, which accounted for 81.5% of the global increase [12]. As an emerging market, Asia has become the preeminent PV market in the world and took 59% of the global installation in 2014. Although China will maintain its position as the largest PVs market in the world, its development has apparently slowed down recently. Japan has continued its strong growth. The USA surpassed Europe to be the second largest PVs market and took 19.3% of installations in 2014. The European PVs market kept shrinking in 2014 and took only 16.8% of new installations. Spurred by the renewable energy laws, the UK's PVs market flourished in 2014 and exceeded Germany for the first time to be the country with the most new PVs in Europe [2].
Figure 1.1 Installation percentage of the world's top 10 PV markets in 2014.
1.1.1 USA
Way back to June 26, 1997, President Clinton announced the “Million Solar Roofs Initiative,” which planned to install 1 million roof-top solar systems by 2010, including PV panels and solar thermal collectors. This initiative was driven by the trend of social development and the professionals dedicated to the research and development of PV generation. Two immediate reasons for proposing this initiative were:
Large greenhouse gas emissions lead to global warming, which requires the reduction of the reliance on conventional energy sources. If the “Million Solar Roofs Initiative” was implemented successfully, the CO
2
emissions would be reduced by more than 3 million tons by the end of 2010.
In the USA, the technologies of PV panels and solar thermal collectors were mature and implemented in mass production.
At present, the “Million Solar Roofs Initiative” has been carried out in some regions, such as the Civano project in Tucson, AZ. Owing to the huge potential of renewable energy resources in Hawaii, solar power has become the mainstream of the local energy supply and an important part of economic development. In 2001, the California State Government proposed the world-famous “California Solar Initiative Program,” planning to install 1 million PV systems in 10 years by investing $3.2 billion. In September 2004, the US Department of Energy published “Our Solar Power Future: The US Photovoltaics Industry Roadmap Through 2030 And Beyond,” revealing an ambitious development plan for the PV industry. In 2006, the USA passed President Bush's Solar Energy Initiative, which increased research funding to $148 million to strengthen the competiveness of the nation's PV technologies. In April, 2008, the mayor of Philadelphia announced the intention to build the first megawatt-level PV plant in the marine park in Pennsylvania. In May 2008, Duke Energy announced the plan to purchase all of the generation from a 16 MW PV plant in Charlotte, North Carolina. In the middle of June 2008, PEPCO Energy Services signed the contract to build a 2.36 MW PV plant on the roof of the Atlantic City Convention Center in New Jersey. All of the aforementioned projects have been completed.
On March 2015, the US Solar Energy Industries Association (SEIA) released the US Solar Energy Insight Report of 2014 Year in Review. The executive summary of the 2014 report stated that the PV installations in the USA reached 6201 MWdc, up 30% over 2013. The cumulative solar PV installed capacity has reached 18.3 GWdc, and solar accounted for 32% of new generating capacity in the USA, second only to natural gas. It also investigated all kinds of PVs and concluded that the residential solar has soared over the past 3 years, posting annual growth rates over 50% in 2012, 2013, and 2014. In the report of US Solar Industry Year in Review 2009, which was released in April 2010, by SEIA, Lawrence Berkeley National Laboratory, it was estimated that compliance with existing solar and distributed generation carve-outs would require roughly 9000 MW of solar capacity by 2025 [13, 14].
The National Renewable Energy Laboratory (NREL) of the US Department of Energy began its operation in 1977 as the Solar Energy Research Institute and changed its name to NREL in 1991. Nowadays, there are more and more institutions carrying out research on solar energy in the USA. Various incentives have been issued to encourage the development of renewable generation, like feed-in tariffs, investment subsidies, renewable energy certificates, and so on.
1.1.2 Japan
Japan's PV development initially started from a medium- and long-term research and development plan on replacing petroleum by solar-based renewable energy in 1974. The plan, also known as the Sunshine Program, was proposed by the Ministry of Economy, Trade and Industry (METI). After that, the Japanese Government established the New Energy and Industrial Technology Development Organization (NEDO) to take charge of the industrialization of photoelectricity. The industrialization procedure of PV cells was accelerated by large government funds, which dramatically reduced the production cost of PV cells and significantly improved the production technologies. For example, the conversion efficiency of polycrystalline silicon casting substrate increased from 12.7% in 1984 to 15.7% in 1988, while the conversion efficiency of amorphous silicon cells increased from 8.25% in 1985 to 10.1% in 1988.
After the 1992 World Economic and Environmental Conference, more attention was paid to environmental problems, such as climate change due to human activities. Since 1994, METI has implemented preferential policies to subsidy residential PV systems by up to 50% of the total cost, including the cost of inverters, PV panels, grid connection system, and construction. In addition, contractors can also get the same subsidization. The promotion greatly prompts the growth of residential PV installation. Although Japan was falling into the bursting of the bubble economy at that time, the citizens still actively applied for roof-top PV projects. For instance, the total number of applications was 33 000 (121 MW) between 1994 and 1999, while there were 26 000 applications in 2000 (96 MW), which was nearly the summation of the total installation of the previous 5 years.
In 2000, Japan set out the “PVs Industry Roadmap Through 2030 And Beyond,” which aimed to transfer the PV research and development from creating an initial PV market guided by government to creating a mature PV market based on the collaboration among academia, industry, and government, and expected the total installed capacity to be 100 GW in 2030. If it can be realized, PV generation can provide approximately 50% of residential electricity consumption, which is 10% of the total electricity demand in Japan. To accelerate the increase of PV generation, on June 28, 2009, NEDO amended the roadmap and predicted the cost of PV generation could decline to $0.14/kW in 2020 and to $0.07/kW in 2030 [15].
As one of the measures taken after the 2011 Fukushima nuclear power plant accident, Japan started to strive to develop PV-based renewable energy generation. On July 1, 2012, the PV Subsidies Act was enacted in Japan. According to this act, Japan's electric companies must purchase the electricity generated by home and industry solar energy, and the feed-in tariff was set as ¥42/kWh (approximately $0.54/kWh) [16]. Although the feed-in tariffs gradually declined in 2013 and 2014, Japan is still the country that has the highest subsidy on PV systems around the world.
1.1.3 Germany
Germany has the largest PV installed capacity in the world so far. Its experience in promoting PV development from the aspects of policymaking, management, and technologies has been the model for several other countries. In 2000, the German Government released the German Renewable Energy Act (EEG-2000) and successfully completed the “100,000 Roofs Programme” in 2003. In 2004, the accumulated PV capacity in Germany surpassed that in Japan and became a leading country in PV generation. The new PV installations in Germany was 1.5 GW in 2008, 3.2 GW in 2009, and peaked at around 7.5 GW between 2010 and 2012. At that time the plan to reach a PVs installed capacity of 10 GW in 2020 had been achieved in advance. However, since 2013, there have been some issues raised related to this renewable energy, such as overload operation and fast growth of electricity price caused by renewable energy subsidies. Therefore, on August 1, 2014, the German Government published the revised German Renewable Energy Sources Act to strictly control the increasing scale of renewable energy generation and reduce funding on newly built projects. Under this new policy, newly installed PVs capacity decreased by 41.3% to around 1.9 GW and kept decreasing for the next 2 years [2]. By the end of 2014, the total German accumulated PV capacity reached 38 GW, and PV generation has turned out to be the largest renewable energy source in Germany: 6.3% of the total energy generated in Germany was from PV generation.
Some effective measures were taken by the German Government to promote PV generation, such as bank loans, feed-in tariffs, and so on. In Germany, if people install PV panels on their own roofs, the generated power can be sold to power grids just like they are running a small power plant, and the country subsidizes up to €0.574/kWh. Currently, the PV industry in Germany has become very active. However, impacted by the widespread European debt crisis and the price decline of PV modules, Germany has begun to repeatedly slash PV subsidies since 2009. The subsidies were cut on July 1 and October 1 of 2010. Compared with 2009, the feed-in tariff of PV installations was decreased by 33–35% in 2011 [17]. According to the latest Renewable Energy Act, the subsidies for renewable energy will be settled through bidding no later than 2017.
While striving to develop its domestic PV industry, Germany also actively expands oversea markets based on its superior technologies. For example, in 2009, Solon SE won the bidding over an 11 MW PV plant project in Spain, which was invested in by Renewable Energies and PVs Spain S.L. (REPS), a majority owned subsidiary of the Norwegian energy company Statkraft AS. In addition, at present, the German company SMA has the largest market share of PV inverters.
1.1.4 China
China has excellent natural resources for exploiting solar energy. Two-thirds of China has considerably good solar irradiance. Provinces like Xizang (Tibet), Qinghai, Xinjiang, Gansu, Ningxia, and Inner Mongolia have the richest solar resources in the country. Eastern, southern and northeastern China are in the second class of the solar irradiance, while the areas of Sichuan Basin and Guizhou Province come last in terms of solar resources.
