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Frontiers in Energy

ISSN 2095-1701

ISSN 2095-1698(Online)

CN 11-6017/TK

Postal Subscription Code 80-972

2018 Impact Factor: 1.701

Front. Energy    2016, Vol. 10 Issue (3) : 308-318    https://doi.org/10.1007/s11708-016-0415-9
RESEARCH ARTICLE
Generating capacity adequacy evaluation of large-scale, grid-connected photovoltaic systems
Amir AHADI(),Seyed Mohsen MIRYOUSEFI AVAL,Hosein HAYATI
Young Researchers and Elite Club, Ardabil Branch, Islamic Azad University, Ardabil 5615731567, Iran
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Abstract

Large-scale, grid-connected photovoltaic systems have become an essential part of modern electric power distribution systems. In this paper, a novel approach based on the Markov method has been proposed to investigate the effects of large-scale, grid-connected photovoltaic systems on the reliability of bulk power systems. The proposed method serves as an applicable tool to estimate performance (e.g., energy yield and capacity) as well as reliability indices. The Markov method framework has been incorporated with the multi-state models to develop energy states of the photovoltaic systems in order to quantify the effects of the photovoltaic systems on the power system adequacy. Such analysis assists planners to make adequate decisions based on the economical expectations as well as to ensure the recovery of the investment costs over time. The failure states of the components of photovoltaic systems have been considered to evaluate the sensitivity analysis and the adequacy indices including loss of load expectation, and expected energy not supplied. Moreover, the impacts of transitions between failures on the reliability calculations as well as on the long- term operation of the photovoltaic systems have been illustrated. Simulation results on the Roy Billinton test system has been shown to illustrate the procedure of the proposed frame work and evaluate the reliability benefits of using large-scale, grid-connected photovoltaic system on the bulk electric power systems. The proposed method can be easily extended to estimate the operating and maintenance costs for the financial planning of the photovoltaic system projects.

Keywords adequacy assessment      Markov method      large-scale grid-connected photovoltaic(PV) systems      long-term operation     
Corresponding Author(s): Amir AHADI   
Just Accepted Date: 12 May 2016   Online First Date: 15 July 2016    Issue Date: 07 September 2016
 Cite this article:   
Amir AHADI,Seyed Mohsen MIRYOUSEFI AVAL,Hosein HAYATI. Generating capacity adequacy evaluation of large-scale, grid-connected photovoltaic systems[J]. Front. Energy, 2016, 10(3): 308-318.
 URL:  
https://academic.hep.com.cn/fie/EN/10.1007/s11708-016-0415-9
https://academic.hep.com.cn/fie/EN/Y2016/V10/I3/308
Component Failure rate/(10-6failures·h–1)
PV modules 0.0152
String protection 0.313
DC switch 0.2
Inverter 40.29
AC circuit breaker 5.712
Grid protection 5.712
AC switch 0.034
Differential circuit breaker 5.712
Connector(couple) 0.00024
Battery system 12.89
Charge controller 6.44
Tab.1  Component failure rates
Fig.1  Electrical structure of large-scale, grid-connected PV systems
Fig.2  Overall system configuration incorporating PV system
Fig.3  Transition diagram of three states model
Fig.4  Markov model for a plant including

(a) One PV system; (b) two different PV systems

Fig.5  Example of stochastic process in Markov chain
Fig.6  Single line diagram of RBTS
Fig.7  The system load model
Size/MW Type Number FOR MTTF/h MTTR/h Maintenance/(week•a–1)
5 Hydro 2 0.010 4380 45 2
10 Thermal 1 0.020 2190 45 2
20 Hydro 4 0.015 3650 55 2
20 Thermal 1 0.025 1752 45 2
40 Hydro 1 0.020 2920 60 2
40 Thermal 2 0.030 1460 45 2
Tab.2  Generating unit reliability data for RBTS
Fig.8  Adequacy indices versus PV system total capacity
Fig.9  Reliability indices for RBTS by adding the PV system and the conventional generator
Peak load 190MW 205MW 220MW 235MW
Base case 10.437 45.796 124.226 264.930
Base case+ 20 MW PV system (FOR 8%) 2.795 9.821 24.636 104.366
Base case+ 20 MW PV system (FOR 9%) 2.878 10.212 25.718 106.111
Base case+ 20 MW PV system (FOR 10%) 2.961 10.603 26.801 107.857
Base case+ 20 MW PV system (FOR 11%) 3.044 10.994 27.883 109.602
Tab.3  Variation in the system LOLE (h/a) considering different values of FOR of PV systems
Peak load 190MW 205MW 220MW 235MW
Base case 119.885 401.315 1620.957 4350.287
Base case+ 20 MW PV system (FOR 8%) 25.248 96.685 338.818 1268.701
Base case+ 20 MW PV system (FOR 9%) 26.277 99.996 352.754 1302.197
Base case+ 20 MW PV system (FOR 10%) 27.305 103.308 366.690 1335.692
Base case+ 20 MW PV system (FOR11%) 28.334 106.619 380.626 1369.188
Tab.4  Variation in the system EENS (MWh/a) considering different values of FOR of PV systems
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[1] Seyed Mohsen MIRYOUSEFI AVAL,Amir AHADI,Hosein HAYATI. A novel method for reliability and risk evaluation of wind energy conversion systems considering wind speed correlation[J]. Front. Energy, 2016, 10(1): 46-56.
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