Presentation Title ( Arial, Font size 28 ) AMI experience of Tata Power Date, Venue, etc..( Arial, Font size 18 )
1 Introduction • Tata Power is engaged in Supply of Electricity across Mumbai Licensed area. • The total spread of licensed area is 485 sq. km. and houses a population of approximately 1.45 crores • Customer base in the Mumbai licensed area is around three lakh. • Customers include Railways, Refineries, Mumbai Port Trust, BARC, Ordanance factory, Mumbai Municipal corporation, RCF etc • Tata Power has recently installed an Automatic Meter Reading system for customers in Industrial & commercial segment as well as for energy meters installed on Distribution Transformers.
1 Objective of AMR system • To fully automate the process of meter reading and billing without any human intervention. • Faster detection of metering abnormalities, theft and network faults. • Monitoring and profiling energy consumption of consumers. • Provide load profile data to key customers on Tata Power Customer Portal. • Facilitate accurate Load forecasting. • Facilitate Demand Response Initiatives.
1 Important design consideration • Meters installed for Industrial & commercial consumers are of different makes. It was decided not to replace existing meters for the purpose of AMR. • The meters are read using API provided by meter manufactures as per MIOS standards. • The modems installed for AMR are designed to have bidirectional communication and remote configuration features and work on GPRS technology. • To manage large amount of meter data ,a Meter Data Management System (MDM) is installed. The MDM system generates many MIS reports which help in faster detection of metering abnormalities /theft /tamper etc .
AMR system architecture AMR Data Centre HT/ LT customers Communication technology SAP PI MDM Middleware MDAS SAP Billing server Secured GPRS cloud Web server Internet Information to customer through internet
1 MDAS • Meter Data Acquisition System (MDAS) : • A common Meter Data Acquisition System is deployed to read all makes of meters. • MDA system acquires meter raw data stored in the Modem memory. • Raw files received from different types of meters are processed through the respective API utility tools and converted into XML file. • A Web Interface is provided for the MDA system. A client can access instantaneous data collected from meter at 15 minute intervals. • Also, health status of all the installed modems, communication logs and events can be seen on the web portal.
1 MDAS- Web Portal
1 MDAS- Instantaneous Data
1 MDAS- Alarms Reports
1 AMR equipment - MDMS • Meter Data Management System (MDMS) : • Itron Enterprise Edition (IEE) is used as Meter Data Management (MDM) System. • MDM is the central repository for meter data and maintains interval data, event logs , register data & outage history for all the connected meters. • The MDM system has a facility to upload meter data read through CMRI. This facility is used to manage the data of meters not covered under AMR. • MDM validates meter data as per predefined validation rules to ensure that only correct data is sent for billing. • The MDM system provides many useful MIS reports
1 Middleware • Middleware : • The SAP PI middleware is used for integrating MDAS, MDM and SAP billing system for seamless exchange of data. • The SAP PI system maps the meter CDF file with MDM system. • New meter creation or deletion is done in SAP system which is communicated to the MDM through the middleware.
1 MDMS • The MDM system has following functional elements • - Data collection, aggregation and analysis • - Validation, Editing & Estimation • - Report generation and status reporting • - Event list • - Customer Care • - Revenue Protection System Utility Operational and Back-office Systems Meter Data Management Customer Care Curtailment Manager Revenue Protection Suite Itron Enterprise Edition Platform Handheld AMR Solutions C&I Meter and Collection Systems AMI Multiple Data Collection Systems
1 Reports available from MDM • 1. Engineering Unit Report – • This report shows demand and consumption for a meter for a selected time range. The Maximum, Minimum and Average values are also displayed.
1 Reports available from MDM • 2. Coincident / Non Coincident peak demand report– • This report shows Coincident demand for a group of meters along with peak demands recorded by concerned meters individually.
1 Reports available from MDM • Coincident/Non Coincident peak Report– Cont.. • This report also shows the load factor, diversity factor and coincident factor.
1 Reports available from MDM • 3. Weekly Report for a meter– • This report shows demand or consumption data of a single channel for a period of one week. High, Low, and Sum of interval values for each day are available from this report.
1 Reports available from MDM • 4. Missing Interval Data Report – • This report shows the intervals for which the data is missing in a given date range The report can be generated for a single meter or multiple meters.
1 Event reports from MDM • 5. Events recorded by a meter – • This report provide details of events recorded by a meter for a given date range
1 Analytical Graphs from MDM. • Trending of load patterns ( Single channel) for a meter
1 Analytical Graphs from MDM • Trending of load patterns for a meter - multiple channels • (eg Kwh, Kvarh lag, Kvarh lead, Kvah)
1 Analytical Graphs from MDM • Comparison between load patterns of multiple meters:
Next steps To deploy AMR solution for cluster meters To deploy AMR solution for DLMS meters Enhance functionality of MDM Prepare a plan for deployment of smart metering solutions.
MDM Enhancement IEE Revenue Protection Suite Customer Care
RPS Focuses on Commercial Losses Theft Administrative Loss Mis-metered Commercial Loss Taxes Technical Loss Financial Costs Un-metered / Unbilled Profitability Energy Purchased Depreciation O&M Commercial Losses Theft from known accounts: Purposeful diversion of consumption to avoid accurate Billing by customers known to the utility, which includes: • Unauthorized consumption • Self-reconnect • Stopped meters
IEE Revenue Protection RPS Daily Workflow Data Upload Analytics application that helps utility Revenue Assurance teams identify tamper and theft • Correlates tamper events, field work orders, weather data, and customer usage to identify suspects • Includes workflow to trigger field work and track investigation status • Includes robust statistical model to compute customer baseline usage levels Revenue Analysis Task Candidates • The expected benefits of RPS are: • Quicker investigation and recovery of abnormal metering cases • Increases revenue recovery for unbilled electricity. • Improves operational efficiency of revenue investigation / Vigilance teams. • Reduces dependence on field staff to visually inspect meters. First Suspect List Final Suspect List Investigation
RPS Application Architecture • Monthly Consumption • Baseline Model • Deviations Actual / • Predicted Consumptions • Other Estimation Models • Average Demand • Tamper Counts • Coincident Tamper Flags • Service Orders • Investigation Information IEE RPS Data Mart - Readings Data - Interval Data - SIC/NAICS - Tamper Events - Service Orders - User Defined Attributes - Account Status - Meter Status - Daily Consumption - Occupancy Change - Meter Change-out AMI, AMR Data Collection Systems Daily feed Weather Data Utility In-House Data Suspect List RPS Application Initiate Investigation
Detailed View • The RPS Data mart stores only monthly consumption data. IEE stores all the data. RPS can calculate weekly and daily consumption values on-the-fly. • These values can be calculated for the drill down. • Daily and Weekly Consumption for Interval and Daily Register Reads • End of Month consumption for Monthly Register Reads Daily Weekly
Suspect Account Consumption dropped and tamper flags occur. No explanation for this behavior Suspect account .
Evolving Customer Service Goals Complete Automation/ Control Personalized, Optimized Recommendations Alerts, Online Energy Education Interactive Tools/Services, Real-time system info Online Bill Pay Online Information Paper Bill Auto Pay Technological Sophistication
C&I - Load Analysis • View daily and average weekly and monthly load profiles. • Identify operational and scheduling anomalies • Load variations by month, week, season and day type • TOU summary statistics • Rank peak loads View average hourly consumption levels and load duration curve. View load duration curve for weekday, weekend, and all days
C&I - Usage Analysis • View usage for selected time period • View summary statistics such as load factor; average, min, and max demand • Compare to prior periods • Display results aggregated to different levels (day/week/month)
Usage Portlet – Day View http://oak-dmo-mmcc.itron.dmz/CustomerCare/MMCC/Usage/Usage.aspx
Usage Portlet – Week View http://oak-dmo-mmcc.itron.dmz/CustomerCare/MMCC/Usage/Usage.aspx
Usage Portlet - Month View http://oak-dmo-mmcc.itron.dmz/CustomerCare/MMCC/Usage/Usage.aspx
Usage Port let - Highlights • Configurable notes built around a list of variables • Optionally, associate icons with notes. Conditional text formatting Total use increased 1%. On-peak use decreased 2% Average Temperature decreased 3°F CO2 Consumption was 795 lbs.
Distribution Asset Analysis & Design • How do actual rather than estimated loads affect distribution asset analysis and design? • How do automated design tools impact design quality and enforcement of engineering standards? • Are my transformers over-loaded? Under-loaded? • Can I reduce O&M expense and / or capital expenditures? Asset Management – Better Data Means Better Results Asset Management Distribution Asset Monitoring & Control • Can I use the AMI infrastructure to monitor distribution circuits and automate distribution operations? • What are my distribution circuit loads • Can I remotely monitor and control capacitor banks? • Can I monitor power quality? Asset Management Portal Sample Asset management using IEE • Provide simple Transformer Load Management overloaded tx calculations • Aggregate usage to transformer • Compare against transformer name plate rating • Calculate overload % • Provide list, sorted by % overloaded, color coded
Future Road Map First Steps towards Smart Grid
1 Smart Metering solution • Pilot on Smart Grid: • It is proposed to install one pilot towards implementation of Smart Grid initiatives. This would include smart metering, Home Area Network (HAN) with energy gateway which can be used for following functions: • - Demand Response Signaling. • - Provision of Customer Energy Usage Information to In-Home Displays. • - Control Activation/Deactivation of HAN Appliances. • - Remote connection/disconnection. • - Real time pricing signals
Pilot project Agenda Pilot Project Objectives AMI Pilot Project Scope AMI Customer Benefits
Pilot Project Objectives To enhance business case for a full rollout of Smart metering solution based on experience of Pilot project with current AMI technology. To understand customers’ interests in and concerns about AMI through personal contact. To study the meter data collected by the meter data management system and determine its value for various customers and operational purposes as below flexible rates demand response mechanisms transformer load management outage detection
Pilot Project Objectives To evaluate the potential value of remote equipment control, thermostats, and other energy conservation features To evaluate electricity meters with a load limiting/disconnect switch To evaluate customer interest & experience in Home Area Display Units
AMI Pilot Scope Trials for following communication technologies - GPRS - RF Mesh / Zigbee - Power Line Carrier Install MDAS for above technologies Integration of multiple MDAS with MDMS Revenue Protection Transformer Load Management Customer Care Applications
Targeted Customer Benefits Convenience- customer has access to their own data - accurate timely meter reads without intrusion in their property Consumption and Demand Response Control- interval data for time of use rates- smart thermostats- load limiting disconnect switch Reliability- reduced outage times- proactive load and voltage data