© The Institution of Engineering and Technology
This study presents an integrated approach for reliability planning and risk estimation in active distribution systems. By incorporating the use of accurate reliability equivalents for different medium voltage/low voltage networks and load subsectors, a probabilistic methodology is proposed to capture both power quality and reliability aspects in power system planning, which potentially avoids the underestimation of system's performance at bulk supply points. A ‘time to restore supply’ concept, based on security of supply legislation, is introduced to quantify the effect of different network functionalities such as the use of backup supply or automatic/manual reconfiguration schemes. The range of annual reliability indices reported by 14 network operators in the UK is also used for the validation of reliability results, which allows estimating the risk of interruption times above the regulator-imposed limits. Accordingly, conventional reliability assessment procedures are extended in this study by analysing a meshed urban distribution network through the application of a time-sequential Monte Carlo simulation. The proposed methodology also acknowledges the use of time-varying fault probabilities and empirical load profiles for a more realistic estimation of customer interruptions. A decision-making approach is shown by assessing the impact of several network actions on the accuracy of reliability performance results.
References
-
-
1)
-
9. Brown, R.E.: ‘Electric power distribution reliability’ (CRC Press, 2002).
-
2)
-
13. Hernando-Gil, I., Hayes, B., Collin, A., et al: ‘Distribution network equivalents for reliability analysis. Part 2: Storage and demand-side resources’. 4th IEEE PES Innovative Smart Grid Technologies (ISGT Europe), Copenhagen, Denmark, 2013, pp. 1–5.
-
3)
-
28. Collin, A., Hernando-Gil, I., Acosta, J., et al: ‘An 11 kV steady state residential aggregate load model. Part 1: Aggregation methodology’. IEEE PowerTech conf., Trondheim, Norway, 2011, pp. 1–8.
-
4)
-
11. Hernando-Gil, I., Hayes, B., Collin, A., et al: ‘Distribution network equivalents for reliability analysis. Part 1: Aggregation methodology’. 4th IEEE PES Innovative Smart Grid Technologies (ISGT Europe), Copenhagen, Denmark, 2013, pp. 1–5.
-
5)
-
6)
-
20. Rubinstein, R.Y., Kroese, D.P.: ‘Simulation and the Monte Carlo method’ (John Wiley & Sons, 2011).
-
7)
-
8)
-
9)
-
10. Energy Networks Association (ENA): ‘Engineering recommendations P2/6: Security of supply’, 2005.
-
10)
-
22. Sankarakrishnan, A., Billinton, R.: ‘Sequential Monte Carlo simulation for composite power system reliability analysis with time varying loads’, IEEE Trans. Power Syst., 1995, 10, (3), pp. 1540–1545 (doi: 10.1109/59.466491).
-
11)
-
15. Ilie, I.-S., Hernando-Gil, I., Djokic, S.Z.: ‘Theoretical interruption model for reliability assessment of power supply systems’, IET Gener. Transm. Distrib., 2013, 8, (4), pp. 670–681 (doi: 10.1049/iet-gtd.2013.0339).
-
12)
-
18. Billinton, R., Allan, R.N.: ‘Reliability evaluation of power systems’ (Plenum Press, 1996).
-
13)
-
29. Toledano, S.Y.: ‘Techniques and processes in medium and low voltage electrical installations’ (Editorial Paraninfo, 2007), .
-
14)
-
12. Billinton, R., Wang, P.: ‘Reliability-network-equivalent approach to distribution-system-reliability evaluation’, IEE Gener. Transm. Distrib., 1998, 145, (2), pp. 149–153 (doi: 10.1049/ip-gtd:19981828).
-
15)
-
16)
-
27. Siemens Energy: ‘Power System Simulator for Engineering’, .
-
17)
-
18)
-
24. Ilie, I.-S., Hernando-Gil, I., Djokic, S.Z.: ‘Risk assessment of interruption times affecting domestic and non-domestic electricity customers’, Int. J. Electr. Power Energy Syst., 2014, 55, pp. 59–65 (doi: 10.1016/j.ijepes.2013.08.030).
-
19)
-
14. Energy Networks Association (ENA): ‘National fault and interruption reporting scheme – national system and equipment performance’, 2010.
-
20)
-
21)
-
3. Council of European Energy Regulators: , 2008.
-
22)
-
26. Montgomery, D.C., Runger, G.C.: ‘Applied statistics and probability for engineers’ (John Wiley & Sons, 2010).
-
23)
-
23. Bhuiyan, M.R., Allan, R.: ‘Modelling multistate problems in sequential simulation of power system reliability studies’, IEE Gener. Transm. Distrib., 1995, 142, (4), pp. 343–349 (doi: 10.1049/ip-gtd:19951871).
-
24)
-
16. Hernando-Gil, I., Ilie, I.-S., Djokic, S.: ‘Reliability performance of smart grids with demand-side management and distributed generation/storage technologies’. 3rd IEEE PES Innovative Smart Grid Technologies (ISGT Europe), Berlin, Germany, 2012, pp. 1–8.
-
25)
-
26)
-
17. Ilie, I.-S., Hernando-Gil, I., Djokic, S.: ‘Reliability equivalents of LV and MV distribution networks’. IEEE Energy Conf. (Energycon), Florence, Italy, 2012, pp. 343–348.
-
27)
-
21. Billinton, R., Wang, P.: ‘Teaching distribution system reliability evaluation using Monte Carlo simulation’, IEEE Trans. Power Syst., 1999, 14, (2), pp. 397–403 (doi: 10.1109/59.761856).
-
28)
-
25. Hadjsaïd, N., Sabonnadière, J.C.: ‘Electrical distribution networks’ (Technology & Engineering ed., John Wiley & Sons, 2013).
-
29)
-
19. Billinton, R., Li, W.: ‘Reliability assessment of electrical power systems using Monte Carlo methods’ (Springer, 1994).
-
30)
-
31)
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