Presentation Transcript

1. Novel Decision Support System for Underground Power Network Asset Management

   AsawinRajakrom CAMT, CMU August 29, 2009
2. 230/500 kV 220/380 V Grid Station Power Plant 69/115 kV Customer 69/115 kV Substation 12/24 kV 12/24 kV Customer 220/380 V Customer Problem and Justification
3. Problem and Justification Failure of distribution feeder directly impacts end users’ wellbeing Concerns on safety, health, environment and aesthetics are increasingly high Network equipment is reaching its designed service age Overhead feeder facilities are vulnerable to external environment Investment on feeder rehabilitation is extremely high Better decision making of utility asset management can be obtained through a sort of DSS that can incorporate all impacted factors: technical, economical, societal, and environmental aspects.
4. Research Questions How shall the power distribution domain knowledge be modeled? How can the risks of distribution network failure be efficiently assessed? How can the costs involving network failure and preventive action be quantified? How can the social and environmental consideration be included in investment decision?
5. Key Assumptions Conversion of overhead distribution line into underground feeder is of the prime concern. Risk assessment is solely based on the performance of network components, not considering any other aspects such as network configuration, or operating process (e.g. switching philosophy). Snap shot comparison, investment cost of network reinforcement at the time of network failure is of interest and compared with the cost of failure. Available data are of sufficient quality to enable assessment modules to predict corresponding outputs/outcomes. DSS tries to replicate the decision making of human experts so that the utility expert’s judgment are assumed sufficient to validate the models.
6. Publications “Improvement of Underground Cable Installation Performance by Knowledge Management”, the 16th Conference of the Electric Power Supply Industry, Mumbai, India, 2006. “Asset Categorization for Enhanced Asset Management Using Object Oriented Approach”, the 16th Conference of the Electric Power Supply Industry, Mumbai, India, 2006. “Enhance Decision Making on Underground Power System Implementation Using MCDA”, the 16th Conference of the Electric Power Supply Industry, Mumbai, India, 2006. “Underground Power Line Risk Assessment Using Heuristic Approach”, the 1st Software, Knowledge, Information Management and Applications, Chiang Mai, Thailand, 2006.
7. Publications “Fuzzy Risk Assessment for Distribution System Asset Management”, Presented at the Conference of Asian Energy Week 2007, Bangkok, Thailand, 2007. “Fuzzy Multicriteria Approach for Power Distribution System Risk Analysis” , Presented at Energy21C: The 10th International Transmission and Distribution Conference & Exhibition, Sydney, Australia, 2007. “Determination of Power Distribution Network Risk Using Fuzzy Markov”, the 2nd Software, Knowledge, Information Management and Applications, Kathmandu, Nepal, 2008. “Asset Modeling To Support Cost-Risk Evaluation In Distribution System Asset Management”, the 17th Conference of the Electric Power Supply Industry, Macau SAR, China, 2008.
8. Methodologies and Tools Asset categorization CommonKADS Categorization and Assessment template Ontology 101 UML CIM/RDF/XML Risk assessment: Fuzzy logic Markov chain MS Excel
9. Methodologies and Tools Cost evaluation: Interrupted energy rate (IER) Work breakdown structure (WBS) MulticriteriaDecision Analysis: Analytic Hierarchy Process (AHP) Tools: Protégé 2000 MATLAB MS Excel
10. x x + + v x - DSS Framework Asset Categorization MCDA (AHP) Distress indicators Present Asset Condition FIS Technical Matter Investment Option Initial Asset Condition Operational Environment Public Interest Age FIS Markov Chain Deterioration Rate Future Asset Condition Present/Future Failure Likelihood Financial Index FIS Risk Module Decision Module Expected Repair Time Connected Load Customer Upgrade IER Replacement Outage Cost Resolution Cost Price Cap Conversion Utility Repair Cost Cost Module
11. Asset ImplementationCost ConditionGrade InvestmentCriteria Customer OutageCost Failure PointComponent Feeder Stressor AssetContainer name description commissioningDate name description commissioningDate name grade inspectionDate relativeImportanceDegree degree description degree description ampacity ratedVoltage predictedFailurePotential expectedFailureDuration failureDescription failureDate failureTime failureDuration customerID customerType IER kW priceCap costOfOutage has has is is compose compose is locateAt is has supply operateIn has has Location Component name coordinateX coordinateY materialCode materialDetail Asset Categorization
12. Feeder DuctBank AssetContainer ComponentGroup OverheadLine UndergroundLine PoleAssembly ATS ConductorAssembly Pole CableContainer UndergroundSwitches CircuitSwitches LinearComponent Conductor OHConductor UGCable LightningProtection UnitSubstation CableComponent Manhole PointComponent Conductor Asset UGCable Splice Splice Duct Manhole Rack RMU Guy Pole Fittings Arrester Groundwire Switches Recloser FuseCutout Splice Insulator Crossarm ampacity ratedVoltage predictedFailurePotential expectedFailureDuration length name description commissioningDate Component materialCode materialDetail
13. Simulation Simulated Feeder T1 T2 T3 Substation 24kV bus T4 3 4 1 2 5 6 7 8 9 10 11 12 13 3 MW Industry 14 15 Substation T1: 4,000 kVA T5 16 17 T2: 3,000 kVA 18 19 20 T3: 2,000 kVA T6 21 2 MW Commercial T4: 2,500 kVA 22 T5: 2,500 kVA 23 24 T6: 4,000 kVA 25 LS3 26
14. Simulation Feeder Condition Grade:
15. Simulation Failure Rate Contributed by Feeder Condition:
16. Simulation Financial Analysis of Alternative Options:
17. Simulation Investment Decision Hierarchy: Select the Most Suitable Feeder Rehabilitation Technical Financial Social Reliability Construction Maintenance Aesthetics Safety Bare OH Bare OH Bare OH Bare OH Bare OH Bare OH ASC OH ASC OH ASC OH ASC OH ASC OH ASC OH UG UG UG UG UG UG
18. Simulation Ranking of Investment Options:
19. Case Studies: Feeder Rehabilitation in Industrial Estate Feeder Condition Grade:
20. Case Studies: Feeder Rehabilitation in Industrial Estate Feeder Failure Rate:
21. Case Studies: Feeder Rehabilitation in Industrial Estate Financial Analysis of Alternative Options:
22. Case Studies: Feeder Rehabilitation in Industrial Estate Investment Decision Hierarchy: Select the Most Suitable Feeder Rehabilitation Technical Financial Social Reliability Construction Maintenance Aesthetics Safety ASC OH ASC OH ASC OH ASC OH ASC OH ASC OH UG UG UG UG UG UG
23. Case Studies: Feeder Rehabilitation in Industrial Estate Ranking of Investment Options:
24. Case Studies: Undergrounding Feeders in World Heritage Site Particular Requirement:
25. Case Studies: Undergrounding Feeders in World Heritage Site Investment Decision Hierarchy: Select the Most Suitable Underground System Technical Aesthetics Cost Conversion Extension Reliability Installation Maintenance DR-CS DR-CS DR-CS DR-CS DR-CS DR-CS DR-CS DR-US DR-US DR-US DR-US DR-US DR-US DR-US DB-CS DB-CS DB-CS DB-CS DB-CS DB-CS DB-CS DB-US DB-US DB-US DB-US DB-US DB-US DB-US
26. Case Studies: Undergrounding Feeders in World Heritage Site Ranking of Investment Options:
27. Conclusion and Future Work Asset model of expressivity, interchangeability, extensibility, reusability and integratability Human expert emulation of risk assessment Balancing of risk, cost and performance of asset through MCDM mechanism Proposed approaches can be extended to cover other area such as: Rehabilitation of transmission lines or substations Risk assessment of underground cable system
28. Thank you
29. Asset Categorization Purpose: To determine risks, costs and socials factors associated with the implementation of power distribution network. Domain: Encompass medium voltage distribution feeder including network components, network operation, and operational environment Scope: Limited to information that aids determining risks, costs and socials factors involved with distribution feeder.
30. Asset Categorization Informal description: Distribution feeder is used to carry electric current through electrical wire. Distribution feeder runs along public road. Overhead feeder is an electrical wire laying or hanging on insulator which in turn supported supporting structure. Failure occurs when feeder fails to perform an intended function such as carrying electric current, withstanding presence voltage, threatening the living standard. Power utility does not gain revenue due to unavailability of energy sale when feeder fails. Burying distribution network improve city aesthetics. etc.
31. Asset Categorization Classes and Attributes: Pole is a distribution network component Material cost of pole is 8,104.00 baht. Labor cost of pole installation is 8,376.80 baht. Condition grade of pole inspected on March 20, 2009 is 1.8. Feeder comprises of overhead cable and underground cable. Feeder PI417 supplies Imperial Hotel. etc.
32. Asset Categorization Classes and Attributes: AssetContainer name is Feeder contains Component code commissioningDate unitPrice Asset name is is is is Conductor Insulator Pole
33. Risk Assessment Condition Grade of Distribution Assets:
34. Risk Assessment Feeder Component Categories and Contributing Weight:
35. Risk Assessment Category and Overall Condition Grade: Hj = [W1j …Wij … WNij]*[C1j… Cij… CNii] Cijis condition grade fuzzy set of each distress indicator Wij is scalar normalized weight given to each distress indicatorHj is condition grade fuzzy set of category C = [W1 …Wi … WM]*[H1… Hj… HM] Hj is condition grade fuzzy set of cateogoryWj is scalar normalized weight given to each categoryCis overall condition grade fuzzy set
36. Risk Assessment Fuzzy Rules for Deterioration Model:
37. Risk Assessment Time Based Condition Grade Evaluation Using Markov Transition Model:
38. Risk Assessment Fuzzy Inference System: Expert Knowledge Field Data Subjective Objective Knowledge Base Inputs Inference Output Fuzzification Defuzzification Degree of feeder overload Degree of feeder overvoltage Degree of exposure to mechanical harmfulness Asset condition Failure likelihood
39. Risk Assessment Stage Wise Fuzzy Reasoning Process: RB1: Load current Ambient temp. Ventilation Thermal violation degree RB2: Lght. exposure Lghtprotectn. Pollution Voltage violation degree RB4: Thermal Voltage Mechanical Stressor degree RB5: Stressor Condition grd. Failure possibility RB3: Tree Accident Animal Mecha. contact degree
40. Risk Assessment Fuzzy inference rules to deduce feeder failure possibility:
41. Cost Evaluation Sectoral Customer Damage Cost (Sectoral IER)
42. Cost Evaluation Average and Composite Damage Cost (IER)
43. Cost Evaluation Price Cap
44. Cost Evaluation Work Breakdown Structure (WBS)
45. Cost Evaluation Typical Cost Figure for 1 Circuit-km UG Feeder:
46. Cost Evaluation Concept of Loss of Fixed Asset by Prevention Replacement
47. Analytical Hierarchy Process (AHP) Hierarchical Structure Decision Model: Goal Criterion1 Criterion2 Criterion3 Subcriterion12 Subcriterion11 Alternative1 Alternative1 Alternative1 Alternative1 Alternative2 Alternative2 Alternative2 Alternative2 Alternative3 Alternative3 Alternative3 Alternative3 Alternative4 Alternative4 Alternative4 Alternative4
48. Analytical Hierarchy Process (AHP) Numerical Rating and Verbal Preference:
49. Analytical Hierarchy Process (AHP) Comparison Matrix: i, j = 1,…., n aij = 1,….,9 aji = 1/aij
50. Analytical Hierarchy Process (AHP) Consistency Check: Determine the principal Eigen value: lmax Compute the consistency index (CI) Compute the consistency ration (CR)
51. Simulation Results Analysis and Discussion: Data modeling Data availability and sufficiency Accuracy: Inclusion of impacted factors Expert knowledge Applicability
52. Case Studies: Feeder Rehabilitation in Industrial Estate Results Analysis and Discussion: Failure rate of assessed feeder estimated from DSS of 1.5 times/year lower than actual events of 7. Result obtained looks alright when compared to other feeders operating in neighboring area. Difference possibly due to: Different deterioration behavior of components Some components may deteriorate faster than 2d0 under certain stressor Fuzzification and fuzzy rules design, workmanship, switching, overheat/overvoltage effect or particular features inherent to assessed feeder. Undergrounding system cannot compete with overhead counterpart if only financial aspects are considered. Cost figured already provided for each option.
53. Case Studies: Undergrounding Feeders in World Heritage Site Results Analysis and Discussion: Aesthetic and world heritage site harmony are prime important for decision making. Information on feeder configuration and design are offered by asset model. Cost figured already provided for each option. If there exist more criteria/requirements to examine, they can be added into the decision hierarchy without any difficulty