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Frontiers in Energy

Front. Energy    2016, Vol. 10 Issue (2) : 125-135     https://doi.org/10.1007/s11708-015-0392-4
RESEARCH ARTICLE |
Reliability evaluation of future photovoltaic systems with smart operation strategy
Amir AHADI(),Hosein HAYATI,Seyed Mohsen MIRYOUSEFI AVAL
Young Researchers and Elite Club, Ardabil Branch, Islamic Azad University, Ardabil 5615731567, Iran
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Abstract

This paper investigates a new operation strategy for photovoltaic (PV) systems, which improves the overall reliability of the system as a result of the improvement in the reliability of the critical components. First, a mathematical model is proposed using the fault tree analysis (FTA) to estimate the reliability of the PV systems in order to find the suitable maintenance strategies. The implementations demonstrate that it is essential to employ smart maintenance plans and monitor the identified most critical components of PV systems. Then, an innovative analytical method based on the Markov process is presented to model smart operation plans in PV systems. The impact of smart operation strategy on the PV systems is then evaluated. The objective of this paper is to develop plans for improving the reliability of PV systems. A series of case studies have been conducted to demonstrate the importance of smart operation strategies for PV systems as well as the applicability and feasibility of the proposed method.

Keywords smart operation strategy      renewable energy      fault tree analysis (FTA)      Markov model     
Corresponding Authors: Amir AHADI   
Just Accepted Date: 20 November 2015   Online First Date: 04 January 2016    Issue Date: 27 May 2016
 Cite this article:   
Amir AHADI,Hosein HAYATI,Seyed Mohsen MIRYOUSEFI AVAL. Reliability evaluation of future photovoltaic systems with smart operation strategy[J]. Front. Energy, 2016, 10(2): 125-135.
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http://journal.hep.com.cn/fie/EN/10.1007/s11708-015-0392-4
http://journal.hep.com.cn/fie/EN/Y2016/V10/I2/125
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Amir AHADI
Hosein HAYATI
Seyed Mohsen MIRYOUSEFI AVAL
Fig.1  Large-scale grid connected PV systems control scheme
Fig.2    Smart monitoring application for large-scale grid connected PV systems
Fig.3  Markov model for component of PV systems with smart operation strategy
Fig.4  Flowchart for PV system reliability assessment with smart operation strategy
Component Power/kW
100 200 500 1000 1500 2000 2500
PV modules 437 874 2166 4351 6517 8702 10868
String protection 23 46 114 229 343 458 572
DC switch 3 6 15 27 42 57 72
Inverter 1 2 5 9 14 19 24
AC circuit breaker 1 2 5 9 14 19 24
Grid protection 1 1 1 1 1 1 1
AC switch 1 1 1 1 1 1 1
Differential circuit breaker 1 1 1 1 1 1 1
Connector (couple) 874 1748 4332 8702 13034 17404 21736
Battery system 16 30 76 150 224 298 372
Charge controller 1 1 1 1 1 1 1
Tab.1  Number of components for each PV system
Component Failure rate/10-6h-1 Reference
PV modules 0.0152 [28]
String protection 0.313 [29]Sect.6-2
DC switch 0.2 [29]Sect.22-1
Inverter 40.29 [23]
AC circuit breaker 5.712 [29]Sect.14-5
Grid protection 5.712 [29]Sect.14-5
AC switch 0.034 [29]Sect.14-1
Differential circuit breaker 5.712 [29]Sect.14-5
Connector (couple) 0.00024 [29]Sect.17-1
Battery system 10.9589 [30]
Charge controller 5.4794 [30]
Tab.2  Component failure rates
Fig.5  Single line diagram of system under study
Reliability Power/kW
100 200 500 1000 1500 2000 2500
1 year/% 78.3716 64.9282 36.9896 16.6818 6.5229 2.5457 0.9954
20 years/% 0.7641 0.0177 0 0 0 0 0
Tab.3    Reliability of overall system for a period of one and 20 years of operations
Priority Component Reliability status Coordinated maintenance
1 Inverter Critical Continuously maintenance
2 String protection Intense Continuously & Periodical maintenance
3 PV modules Critical Continuously maintenance
4 AC circuit breaker Critical Continuously maintenance
5 DC switch Normal Periodical maintenance
6 Charge controller Normal Periodical maintenance
7 Grid protection Normal Periodical maintenance
8 Differential circuit breaker Normal Periodical maintenance
9 Connector (couple) Normal Periodical maintenance
10 AC switch Normal Periodical maintenance
11 Battery system Normal Periodical maintenance
Tab.4  Critical component priorities
Type of failure Failure rate/%
Capacitor failure 60
Inverter bridge failure 35
Mechanical failure 5
Tab.5  Ratio of failure for solar inverters
State Failure rate/10-6h-1 Repair rate/failure·h-1
State 0 l0 = 40.29 m0 = 0:04166
State 1 l1 = 24.174 m1 = 0:0833
State 2 l2 = 14.1015 m2 = 0:0833
State 3 l3 = 2.0145 m3 = 0:04166
Tab.6    Failure and repair rates for solar inverter
Fig.6  Markov chain for solar inverter
Inverter reliability Power/kW
100 200 500 1000 1500 2000 2500
Without monitoring (1 year)/% 88.2497 77.8801 53.5262 32.4653 17.3775 9.3015 4.9787
With monitoring (1 year)/% 99.3770 98.7578 96.9233 94.5303 91.6219 88.8030 86.0708
Without monitoring (20 year)/% 8.2085 0.6738 0.0004 0.0000 0.0000 0.0000 0.0000
With monitoring (20 year)/% 88.2497 77.8801 53.5262 32.4653 17.3775 9.3015 4.9787
Tab.7    Reliability of inverter with and without smart operation strategy
Inverter reliability Power/kW
100 200 500 1000 1500 2000 2500
Without monitoring (1 year)/% 78.3716 64.9282 36.9896 16.6818 6.5229 2.5457 0.9954
With monitoring (1 year)/% 88.2533 82.3337 66.9794 48.5728 34.3914 24.3043 17.2084
Without monitoring (20 years)/% 0.7641 0.0177 0 0 0 0 0
With monitoring (20 years)/% 8.2152 2.0491 0.0330 0.0001 0 0 0
Tab.8    Reliability of overall PV system with and without smart operation strategy
Inverter reliability Power/kW
100 200 500 1000 1500 2000 2500
Without monitoring (1 year)/% 78.3716 64.9282 36.9896 16.6818 6.5229 2.5457 0.9954
With monitoring (1 year)/% 88.2533 82.3337 66.9794 48.5728 34.3914 24.3043 17.2084
Without monitoring (20 years)/% 0.7641 0.0177 0 0 0 0 0
With monitoring (20 years)/% 8.2152 2.0491 0.0330 0.0001 0 0 0
Tab.9  Reliability of overall PV system with and without smart operation strategy
Fig.7  Impacts of operational failure for solar inverter considering Pu
Fig.8    Variation of reliability of overall PV system regarding inverter monitoring and considering Pu
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