John J. Simmins Senior Project Manager IntelliGrid Program October 5, 2012

Transcription

1 A Monetization of Missing and Inaccurate GIS Data for the Purpose of Justifying Investment in GIS Data Improvement Initiatives Smart Grid Information Sharing Webcast GIS Interest Group John J. Simmins Senior Project Manager IntelliGrid Program October 5, 2012

2 Contents Some context for the GIS research EPRI survey results Cost/benefit analysis model 2

3 Vision of the Future Affordability Dependability Efficiency 3

4 GIS Data Quality Project 4

5 GIS Data We react slowly to shifting work volumes due to manual resource allocation processes. We react inconsistently to information requests. We execute simple business tasks with high skill and high cost resources. We have costly and inconsistent asset management processes. Process automation is limited by our incomplete and inaccurate operational data. We have minimal ability to accurately and quickly measure our business performance. Process standardization is limited by vertically integrated systems. 5

6 Smart Grid Systems Distribution Automation Demand Response Asset Management SCADA DMS / OMS AMI Materials Mgt. Maint. Mgt. Engineering Analysis Mobile GIS GIS Mapping Graphic Design Work Mgt. Operations Management IVR Work Optimization SCADA GIS MDMS CMMS Central Databases Executive Information System BI / Analytics Mobile Workforce CIS CRM Mobile GIS Customer Management Customer Empowerment 6

7 How Data Enables Workflows Work Order Drafting & Design CMMS Service Restoration OMS Network Analysis Planning & Engineering Maintenance & Construction WMS GIS AMI MDMS (MDM) Home Automation and Demand Response Schedule and Dispatch DMS Wireless Mobile Enablement Distribution Automation 7

8 Data Quality Survey and Results 8

9 EPRI GIS Data Quality Survey Phase 1 Thirteen utilities participated in the survey. Outage management and engineering analysis are the most common uses of GIS data. Integration and dependencies vary widely. No correlation between integration of the GIS and data quality. User are generally confident in the data. Utilities are doing a better job at completeness than accuracy of data. Benefits of good data are seen, but repercussions of bad data are not. 9

10 Who Owns GIS? Each, 8% Operations, 8% IT, 42% Other, 17% Engineering, 17% 10 Shared Services, 8%

11 Who Maintains GIS? IT, 8% Each, 25% Shared Services, 8% Engineering, 17% Operations, 25% Other, 17% 11

12 GIS Market Share Other, 8% Intergraph, 31% ESRI, 69% GE Smallworld, 23% 12

13 Data Dependencies of GIS OMS DMS Engineering Analysis CMMS CIS 13

14 Data Inputs to GIS

15 Direct Users of GIS Data

16 GIS Functionality 70% 60% 50% 40% 30% 20% 10% 0% 16

17 Utilities' Expressed Level of Data Quality 70% 60% 50% 40% 30% Data Accuracy Data Completeness 20% 10% 0% Worse than 50% 50% - 75% 75% - 90% Better than 90% 17

18 EPRI GIS Data Quality Survey Phase 1 Of the thirteen utilities that participated in the survey: 36% store all distribution data in GIS, but 66% make use of an asset management system. 66% have unique asset IDs, only 27% physically tag the asset in the field. 54% felt that data accuracy was 75-90% (64% user confidence in data). 63% felt that data completeness was 75-90% (72% user confidence in data). Only 9% of utilities have experienced a catastrophic problem due to data, but 56% have enjoyed a benefit of good data. While 91% have programs to improve data, only 54% have dedicated staff. 73% have automated quality assurance. 91% have not seen quality deterioration over time. 18

19 Cost Benefit Model for GIS Functions Benefits 19

20 Cost/Benefit Analysis Guiding Documents Methodological Approach, published Jan, 2010 Jointly funded by DOE and EPRI Provides framework for estimating benefits & costs Provides definitions, concepts and data sources Publicly available: Product ID CBA Guidebook, Volume 1: Measuring Impacts, published May, 2011 provides a manual for practical application with step by step instruction provides guidance for documenting the project in detail and approach to perform a CBA, includes templates for working through the process. Publicly available: Product ID

21 Overview of Smart Grid Evaluation Process Smart Grid Assets Smart Grid Functions Determine Impacts (physical measures) Determine Benefits (monetized) Functions Functions SG Assets Benefits Tables 4-4 and 4-8 in Methodological Approach and Tables 5-1 and 5-2 in CBA Guidebook 21

22 CBA Terminology: Impacts, Metrics, and Benefits Measure Calculate (algorithms) Monetize System (Program, Project, Sub-Project) Project1 Device1 Project3 Device3 Project2 Device2 Device4 Project4 Function 1 Function 2 Function 3 Application System Configuration & Operation Location Connection Direction of Influence Point of Impact Intended Use Market Environment Market versus Integrated Utility Regulatory conditions Impacts Impacts Impacts Metrics Metrics Metrics Costs/ Benefits Costs/ Benefits Costs/ Benefits Systems: Combination of Devices and Software Functions: Physical Capabilities Application: Use of System in its Environment Impacts: Measurable Physical Changes Metrics: Calculated from Impacts Costs/Benefits: Monetized Impacts An Application is a selection of functions for a given configuration and system context. Impacts are measurable physical changes within the bounds of the system under study. Impacts are differences between a measured quantity and its baseline measurement. Benefits are monetary products of impacts. Some may be negative, i.e., costs. In short: We measure impacts, calculate metrics, monetize costs and benefits. 22

23 Expected Impacts of Improved Data Reduction in the overall cost of operations as a whole - Sloppy data may be easier and cheaper to maintain, but yields poor engineering decisions; Increase efficiencies in implementing and troubleshooting Smart Grid communications issues; OMS and DMS improvement Outage and distribution management systems are heavily reliant on the accuracy of the connected model. As connectivity and switching increase in accuracy outages can be isolated and repaired more quickly resulting in reduced outage duration, metrics and cost; Improved crew efficiencies - Improved distribution system representation allows crews to locate field assets more quickly, to drive less and have correct replacement parts; 23 Improved load forecasting and system planning effectiveness; Reduced work order creation, construction, and close out process time Designs are posted to the GIS more quickly such that staff have maps which actually reflect the as-built; Improved material management and forecasting efficiency; Enabled information exchange with internal and external agencies; and Improved safety due to more accurate facilities records Crews should never rely solely on mapped information to protect their health and safety.

24 CBA Compares Two or More Alternatives In our demonstration framework, the reference case can be called the Baseline Scenario. If Do nothing is a viable alternative, then the project is discretionary. Do nothing is the Baseline Scenario. CBA compares incremental costs and benefits relative to the Baseline Do nothing scenario. If Do nothing is not a viable alternative, then action is imperative: i.e., there is a problem that must be solved. The least-cost solution forms the Baseline Scenario. CBA determines the least-cost solution. Remaining alternatives are discretionary projects that may layer over the Baseline Scenario. CBA compares incremental costs and benefits of each layer. 24

25 Layering of Alternatives to Isolate Impacts Interdependent projects layer on the baseline scenario. Impacts should pair with the investments that produce them. Discretionary Project 3 Measurements CBA3 Incremental Cost of Project 3 Discretionary Project 2 Measurements CBA2 Incremental Cost of Project 2 Incremental Cost of Project 1 Discretionary Project 1 Baseline Scenario (includes obligatory investments) Measurements Baseline Measurements CBA1 25

26 Layering of Alternatives Mutually exclusive alternatives may necessitate multiple paths through various layers of projects. Measurements Discretionary Project 3 Discretionary Project 3 Measurements Measurements Discretionary Project 1 Incr $ Incr $ Discretionary Project 2 Measurements Incr $ Baseline Scenario Incr $ (includes obligatory investments) Baseline Measurements 26

27 Examples of EPRI GIS Data Improvement Projects 27

28 Automating Phase Identification Using AMI Data SCADA Voltage Data Correlating Voltage AMI Voltage Data Customer Phase ID 28

29 Phase Identification Example 29

30 Field Force Data Visualization Inexpensive to deploy Inexpensive to maintain Applications: GIS data improvement Asset maintenance manuals Storm damage assessment Asset information access Switching communications Work-order information flow Real-time system status validation Visualizing faults in the field Field Work Becomes Easier and More Efficient 30

31 LineView Automated Asset Recognition Uses images from: Google street view Utility aerial images Utility ground images Pattern recognition utilizing neural networks Automated way of completing GIS 31

32 The Cost Benefit Model Functions Benefits 32

33 Systems (Costs) for the CBA Parameter Description Area Primary Objective Data creation Time/effort for process of data creation Clean-up Utility Operational Efficiency Data maintenance Reduced effort for maintenance Clean-up Utility Operational Efficiency Current data assessment Required understanding of existing data limitations Clean-up Utility Operational Efficiency Staff/Retirees/Vendor Time Actual time for clean-up process Clean-up Utility Operational Efficiency QA Team equipment Computers, Monitors, Space Clean-up Utility Operational Efficiency Software Licenses Additional seats for GIS Clean-up Utility Operational Efficiency Awareness of Inaccuracies Increased awareness of current state of data Clean-up Utility Operational Efficiency Automated Routines Programming time Clean-up Utility Operational Efficiency Vehicles Light-trucks for field survey Field Survey Other Staff Time or Contractor Field resources knowledgable in electrical system Field Survey Other Data Input Additional staff time or responsibility for input and oversight Field Survey Other Data acceptance review Staff time and training Field Survey Other Equipment Mobile devices and office equipment, GPS Field Survey Other Historical Inaccuracies in Rate Base Potential to discover rate base has been miscalculated Field Survey Other Programming Develop interfaces between GIS and other systems Integration Other Staff Testing and Acceptance Time Interface testing and quality control Integration Other Licenses For any COTS solutions Integration Other Software Cost Costs for interfaces or bus Integration Other Interface Maintenance Ongoing maintenance of interfaces and service bus Integration Other Process Change Workshops Development of necessary business process change to support data quality improvement Training Other Change Management Training Staff training workshops Training Other Data Use Training Reduction of costs associated with intuitive data, processes and systems Training Other 33

34 Impacts (Benefits) for the CBA Description Area Primary Objective Prevent orphan database Data Creation Utility Operational Efficiency Provide correlation between databases Data Creation Utility Operational Efficiency Assets are correctly referenced to real world location Data Creation Utility Operational Efficiency Not St or Street Data Creation Utility Operational Efficiency Staff don t draw and re-draw designs Data Creation Utility Operational Efficiency Data reflects the as-built more quickly Data Creation Utility Operational Efficiency Reduce data entry Data Creation Utility Operational Efficiency Efficiency in office Data Creation Utility Operational Efficiency Design correctly the first time Data Creation Utility Operational Efficiency More users have ability to edit basic attributes Data Maintenance Utility Operational Efficiency Documentation for future changes Data Maintenance Utility Operational Efficiency Time savings Data Maintenance Utility Operational Efficiency Time savings Data Maintenance Utility Operational Efficiency Balance storage and creation efficiency Data Maintenance Utility Operational Efficiency Accurate routing and problem location identification Operations Utility Operational Efficiency Reduce no address calls Operations Utility Operational Efficiency Bring correct replacement materials, no need to measure conductor size Operations Utility Operational Efficiency Less drive time Operations Utility Operational Efficiency Better understanding of existing plant Operations Utility Operational Efficiency Maps reflect the as-built field condition Operations Utility Operational Efficiency More eyes on the data, shared ownership Operations Utility Operational Efficiency Access to customer/premise information Operations Utility Operational Efficiency Reduce export time and effort to OMS Operations Utility Operational Efficiency Staff acceptance and use of data Operations Utility Operational Efficiency Good data will obviate other sources and files which have been necessary to supplement bad data Engineering/ Analytics Utility Operational Efficiency Model accuracy Planning Utility Operational Efficiency Greater confidence in analysis Planning Utility Operational Efficiency Savings due to data quality improvements Planning Utility Operational Efficiency Better metrics and visibility in real-time data quality Planning Utility Operational Efficiency Able to find/analyze assets (San Bruno Explosion) Operations Utility Asset Efficiency Designs are electrically connected to model Data Creation System Operational Efficiency System integration and data sharing Data Maintenance System Operational Efficiency Connected model from substation to transformer to customer Operations System Operational Efficiency Precision for smart grid devices Operations System Operational Efficiency Powerline Loss Engineering/ Analytics System Operational Efficiency Balance loading to three phases Engineering/ Analytics System Operational Efficiency List of impacts of improved GIS data quality There is a factor of the likelihood of the user achieve the impact that was obtained from the second EPRI survey The user will assign the monetary value based on their unique situation Identify opportunities for efficiency or excess capacity Planning System Operational Efficiency Prevent unplanned outage Operations Reliability SAIDI, CAIDI, SAIFI improvement Engineering/ Analytics Reliability Certainty of existing system Planning Reliability Provide accurate information to crews Operations Other Theft Engineering/ Analytics Other Statistic and Metric accuracy Engineering/ Analytics Other Goodwill and headline avoidance Planning Other Less negative publicity Planning Other Goodwill with important/large customers Planning Other Confidence in company direction and management Planning Other Confidence and goodwill of regulatory agency/board Planning Other Workplace satisfaction and dedication Planning Other Efficiency with replacements, i.e. PCB phase-out Planning Other Accuracy and completeness, i.e. number of poles Planning Other Assets are added and capitalized more quickly Planning Other Pay the correct district Planning Other Recover lost revenue Planning Other Reduction of Unknown third party attachments Planning Other Potential revenue from sale of quality data Planning Other Eased data sharing Planning Other Methodology and consulting services Planning Other 34

35 Net Present Value NPV is calculated by summing the dollar-valued benefits and then subtracting all of the dollarvalued costs, with discounting applied to both benefits and costs as appropriate. A CBA will yield a positive NPV if the benefits exceed the costs. NPV n ( Benefits Costs) = t = 0 t (1 + r) Where: r = discount rate t = year n = analytic horizon (in years) t 35

36 Internal Rate of Return Net Present Value NPV irr = NPV cash in NPV cash out Internal Rate of Return - IRR Discount Rate 36

37 Together Shaping the Future of Electricity Thanks: Jeff Roark Tom Short Jared Green Jerry Gray Matt Olearczyk Boreas Group 37