Presenter: Louis Pieterse (City Power) Author: Johanette van der Merwe (Eon Consulting) Co-Authors: Louis Pieterse (City Power); Kurt Dedekind (Eskom)

Transcription

1 Presenter: Louis Pieterse (City Power) Author: Johanette van der Merwe (Eon Consulting) Co-Authors: Louis Pieterse (City Power); Kurt Dedekind (Eskom)

2 Background Approach Modelling methodology Outcomes Conclusions

3 Previously network performance targets informed by benchmarking (overseas utilities): Benchmarking ignores current network topology Alternative approach required Initiated study into designed performance level of the network: Expected performance of a network is modelled (network topology, customer numbers, operating environment etc.) Purpose: inform operationally achievable performance levels of the network

4 Software packages (e.g. PowerFactory), require detailed network models Significant effort to create large utility-scale networks City Power s network consist of More than 100 substations (373 busbars) 276 station transformers MVA installed capacity More than km of MV cable More than load centres and More than customers. Alternative reliability modelling approach required

5 Alternative reliability modelling approach: Simplified approach, developed for Eskom Distribution ( ) Key network components (e.g. length of line) significantly impact network reliability Reasonable assumptions (failure rates, maintenance frequencies, travel/repair times) Outcomes: realistically expected (designed) performance base

6 Two separate modelling steps: 1. 1 Sub-transmission network modelling (substations and feeders 20 kv) 2. 2 Distribution network modelling (all feeders 20 kv) Sub-transmission Distribution 2 1

7 A B Sub-transmission modelling considered a decoupled approach: Substation reliability assessment Sub-transmission line reliability assessment Generation source A_Primary A A_Secondary Line A-C C_Primary Line B-C Generation source Line B-D B_Primary B_Secondary B Line C-E E_Primary C_Secondary D_Primary D_Secondary E_Secondary

8 Detailed model of the substation Substation reliability analysis annual outage frequency & duration for each busbar Substation replaced by equivalent busbars B1 (λ, MTTR) B LU1 LU2 LU1 LU2 B2 (λ, MTTR) B LD1 LD2 LD3 LD4 LD1 LD2 LD3 LD

9 Sub-transmission line reliability - failures of the line and the line isolators Total sub-transmission outage duration: U Tx U substation U line U Tx = U substation + U line : Outage duration (sub-transmission network) : Outage duration (substation faults) : Outage duration (line faults) (λ BB_A, MTTR BB_A, U BB_A ) (λ Total_A, MTTR Total_A, U Total_A ) (λ BB_B, MTTR BB_B, U BB_B ) (λ Total_B, MTTR Total_B, U Total_B ) (λ BB_C, MTTR BB_C, U BB_C ) (λ Total_C, MTTR Total_C, U Total_C ) Busbar A Line A-B (λ L_A-B, MTTR L_A-B, U L_A-B ) Busbar B Line B-C (λ L_B-C, MTTR L_B-C, U L_B-C ) Busbar C

10 Urban networks mainly two different equipment types Cables & load centres Equipment counts: # Isolators # Transformers # Fuses # Load centres #Load centres with customers allocated # Transformers # Breakers 0

11 Algorithm derived to determine the SAIDI and SAIFI for a specific feeder Algorithm considers: Number of components Protection devices Backfeedability Failure rates & repair durations SAIDI unpl_fdr = #Cable FR C + #Fuses FR F + #Discs FR D + #Trfrs #Fuses FR T T response + #Cable FR C Rtime C + #Fuses FR F Rtime F + #Discs FR D Rtime D

12 Reasonable assumptions (City Power specific): Key assumption: Networks are reasonably maintained and operated. Failure rates Per component Lines & Cables: failure rate/km Outage durations Dispatch, Travel (per area), Sectionalise, Fault find, Repair (per component), Switch Customer restoration factor (% customers restored via backfeed during fault repair) Ignores actual customer & equipment distribution evenly distributed model

13 Total outage duration: combine subtransmission network and distribution network contribution U Total = U Tx + U Dx U Tx U Dx U Total : Outage duration (sub-transmission network) : Outage duration (distribution network) :Total outage duration experienced by a customer

14 Valuable executive decision support derived from the outcomes: Performance targets Network criticality maps Impact of interventions

15 Modelled results used to determine performance targets Modelled performance less than actual performance Therefore phased approach: Improvement towards the designed performance level achieved over five-year period (linear improvement)

16 Actual performance compared to modelled performance Relative comparison used to flag problematic feeders Some error allowed (due to assumptions) Flagged if reported SAIDI > 3 x expected SAIDI All feeders identified highlighted spatially Geographically groupings, certain areas require specific focus

17 Identified and modelled specific performance improvement interventions: 1. Improve dispatch time: Dispatch time = 12.5% of the current estimated dispatch time 49% improvement in SAIDI 2. Build test branch capacity: Cable repair durations reduce by 50% 9% improvement in SAIDI 3. Improve the customer restoration factor: High level of interconnectivity. CR factor increased from 80% to 95% 9% improvement in SAIDI

18 Value of simplified modelling approach: Determine expected as-designed performance (< 4 months) Resources can be applied where biggest return on investment. Informed decisions regarding potential design changes and capital and refurbishment investment requirements. Developed understanding of performance levers and geographical areas that require additional focus. Highlighted deficiencies in network information and data. Develop cost- and time-effective what if scenarios. The approach is generic (can be applied in any electrical distribution utility)

19 The End

20 The authors would like to acknowledge the following people who contributed to this study: Martin Cameron and Dieter Gütschow for strategic inputs on the City Power project. Johan Coetzer for the modelling of the City Power MV network. Eskom s Reliability Planning Workgroup members who assisted with the development of this simplified approach: Clinton Carter-Brown and Theo Kleynhans.

21 Cameron, M.J., Carter-Brown, C. (2012): Electrical Utility distribution network capital planning a network reliability informed approach to prioritising investment for economic sustainability. Paper for the 2012 (63rd) Association of Municipal Electricity Undertakings (AMEU) Convention, October 2012, Emperors Palace, Kempton Park, Gauteng. Carter-Brown C., Cameron M.J., and Du Preez M.: Determining a relationship between Eskom Distribution network performance and capital investment. Paper for the 2008 Electricity Distribution Maintenance Summit, 9 June 2008, Gallagher Estate, Midrand, South Africa. Cameron, M.J., Carter-Brown C., and Vrey D.: Cost and performance implications of infrastructure investment options in the Eskom Distribution network. Paper for the 2008 Association of Municipal Electricity Undertakings (AMEU) Convention, October 2008, Buffalo City, South Africa. Cameron, M.J. and Carter-Brown, C. and Nunes, N.: Determining a relationship between Eskom Distribution network performance improvement and infrastructure investment cost. Paper developed for 2009 Congrès International des Réseaux Electriques de Distribution (C I R E D), 20th International Conference on Electricity Distribution Prague, 8-11 June 2009, Prague, Czech Republic. Cameron, M.J. and Carter-Brown, C.: Applying simplified network feeder reliability modelling as basis for pragmatic strategic management decision making regarding capital and operational investments a large scale application case study for Eskom Distribution Association of Municipal Electricity Undertakings (AMEU) Technical Convention, September 2011, Cape Town, South Africa. Van der Merwe, J. and Carter-Brown, C.: Simplified sub-transmission reliability modelling as a basis to prioritise system level investment, 7th Southern Africa Regional Conference, October 2013, Somerset West, South Africa. Brown R. E. (2002): Electric Power Distribution Reliability, 2 nd Ed., CRC Press, New York. Brown R. E., Taylor T.M. (1999): Modeling the impact of substations on distribution reliability, IEEE Power Engineering Society 1999 winter meeting, vol. 2.