Maximizing the benefits of AMR for theft detection through Data Analytics. Rajesh M Bansal

Transcription

1 Maximizing the benefits of AMR for theft detection through Data Analytics Rajesh M Bansal

2 Metering systems & meter data management BSES Delhi distributes electricity for almost 2/3 rd of Delhi population. In a span of five years AT&C losses were reduced drastically by more than 20 %. Reduction of AT&C loss in Delhi owes to having right metering & data management strategies. Enablers Right metering system Downloads of meter data thru hand held MRI & AMR Analysis of downloaded data

3 AMR Systems in BSES Delhi BSES has installed AMR modems for all premium consumers. Presently 15,000 consumers are covered through AMR. Plan to further extend AMR to 0.1 Million consumers AMR helped BSES in Add value by reduction in operating cost Detect & control theft in premium segment. Critical requirement Data analytics

4 Data analytics - Process This initiative was undertaken at Delhi, with the strategic intent of providing inputs on potential cases of theft to the Enforcement teams This initiative has been identified as one of the key drivers for AT&C loss reduction. Key Drivers Tamper Analysis Consumption Analysis Billing Database Analysis Secondary database Analysis

5 Data analytics - Process Around 0.1 Million consumers in the premium segment & high value segment were physically surveyed on following parameters. Activity of the consumer (Industrial/ commercial activity etc) Operating hours Premise type /area etc. All meters Including Single Phase are downloaded through AMR/ CMRI. Downloaded meter data are analyzed through inhouse developed software & the surveyed data to detect anomalies

6 Tamper analysis Tampers result in under recording of energy Various circuits inside the meter or wiring at the terminal box is manipulated Current circuit voltage circuit or Switching off power supply (SMPS) Tampers logged by meter along with load profile is analyzed to identify theft

7 Types Of Tamper Voltage Circuit tamper This is easily detectable Power supply switched off To check if there are periods of Power supply failure logged by meter beyond supply failure Current circuit tamper This is the trickiest one to detect due to issue of false alarms Load imbalance Certain current circuit tampers are not detected at times. Load imbalance comes handy at these times

8 Remote Operated Relays A very common methodology in Delhi This may not be detected when we check consumption using Accucheck Remote circuits are used in following ways: For opening or bypassing current circuit For altering voltage circuit For switching on and off power supply Can be detected from study of tamper events / load profile and instantaneous parameters

9 Remote operated relay - Photo

10 Electrostatic discharge (ESD) This is a novel method used to manipulate the electronic meters. When subjected to ESD, meter would get into sleep mode till the time it is waken up by a power supply interruption. We have identified symptoms in the data stored in the meter through which we detect such cases.

11 Consumption Analysis: Key Focus Surveyed consumers contributing to 60 % of company s revenue Nature of Activity Collected information to calculate their consumption Establishing benchmarks for different commercial / industry segments. Examples: Commercial Categories Fast Food joint: 10 units per month per Sq Ft Shopping Malls: 3.5 to 4.5 units per month per Sq Ft

12 Case Study: Hotels Hotels nailed based on Consumption Analysis We found some budget hotels consuming 200 units per A/C room per month.. If found low, We check on key parameters Room Tariff rate Occupancy Effectiveness of cooling in each case Ambience Facilities offered We could book more than 20 economy hotels for theft

13 Case Study: CNG Pumps Complete list of CNG outlets was taken up for Analysis from Secondary Source Many CNG outlets in Delhi consume 10,000 units (monthly). While CNG outlets in Mumbai typically consume upwards of 50,000 units This led us to infer that Most CNG outlets were involved in theft But our inference went wrong as most of the CNG outlets in Delhi operate on gas turbines. We decided to continue our drive for those CNG pumps that had not shifted to Gas Turbines. Subsequently we could book four CNG outlets.

14 Database Query Logic - Examples Units Consumed (Monthly) / Maximum Demand Recorded Units Consumed (Monthly) / Sanctioned Load is another parameter on which we can analyze Often this is due to premise not being used Residential load greater than 15 KWatts in low income locations or > 30 KWatts at any location Above will be suspect for tariff misuse Faulty / Burnt meters that have been replaced Drop in consumption

15 Effectiveness of Database Queries Querying database has proved to be effective in analyzing mass segment consumers. Intelligent use of few queries resulted in opening a large bucket of tampered meters in mass segment (Single phase meters). Thousands of tampered single phase meters have been identified. The hit rate in this segment ranges from 50% to 80% depending on the logics used. (i.e. 5 to 8 cases were found to have tampered of the 10 cases investigated based on these logics).

16 Secondary database query Secondary data collected from various sources. The data available in the secondary data are reconciled in billing database to conclude unbilled cases. For example, through internet sites of Reserve bank of India & all other banks operating in India, list of all bank branches operating in our service area was obtained. This list was reconciled with the billing database to confirm that all bank branches were being billed. To our surprise we found around 1% of the bank branches were not in the billing net.

17 Removed meter analysis at lab Another process which helped in improving the data analytics is analysis of meters removed from site at the Meter testing lab. Deliverables of this analysis at lab. Detect new types of tampers & impact of tamper on meters data. Ascertain reason for failure to improve specification parameters/ Quality of the meters. Retrieve not readable meter data for billing

18 Analysis using HV Energy Audit Reports Feeder to Transformer Reports ( Feeders with HT Consumers & SPDs)

19 Analysis using HV Energy Audit Reports Definition of Gap Gap = {Sum ( Input Energy from 11 kv Feeder)- Sum (DT + HT + SPD + HVDS Energy) of Feeder Network Gap % = {Gap / Sum(11 kv Input Energy )}*100 Gap is taken for a study period where network changes has not happened Study Period is preferred Minimum for one week

20 Analysis using HV Energy Audit Reports Methodology Grid Substation M1 11 kv Feeder Feeding to DTs and HT Consumers M2 DT 1 M4 HT Consumer M3 DT 2

21 Analysis using HV Energy Audit Reports Observations 1 : Feeders with acceptable Gap, Sample Cases Summary of Feeder to DT + HT Reports S. No. Division Feeder Name Feeder Energy Sum of DT/HT Energy Gap (Units) Gap (%) 1 Nehru Place S/S NO. 6 OKHLA PH-III Nehru Place O/G TELEPHONE EXCHANGE

22 Analysis using HV Energy Audit Reports Observations 1 : Feeders with acceptable Gap, Load Curves Study Period 17 July to 22 July 1400 Feeder & (DT+HT) Energy Curves Feeder : SS No 6, Okh Ph III Load (KW) Jul 0:00 17-Jul 12:00 Feeders input -1,75,782 DT Energy -1,70,974, HT Energy 4,399 Total 1,75,373 Gap (0.23%), Unit Gap (408) 18-Jul 0:00 18-Jul 12:00 19-Jul 0:00 19-Jul 12:00 20-Jul 0:00 20-Jul 12:00 21-Jul 0:00 21-Jul 12:00 22-Jul 0:00

23 Analysis using HV Energy Audit Reports Observations 1 : Feeders with acceptable Gap, Load Curves FEEDER ENERGY Study Period 1 July to 8 July DT-HT ENERGY 1600 Feeder & (DT+HT) Energy Curves Feeder : Telephone Exchange Jul 12:00 01-Jul 00:00 01-Jul 12:00 02-Jul 00:00 02-Jul 12:00 03-Jul 00:00 03-Jul 12:00 04-Jul 00:00 04-Jul 12:00 05-Jul 00:00 05-Jul 12:00 06-Jul 00:00 06-Jul 12:00 07-Jul 00:00 07-Jul 12:00 08-Jul 00:00 Load (KW) Feeders input -2,77,284 DT Energy -1,10,736, HT Energy 1,63,207, Total -2,73,944 Gap (1.2%) Unit Gap (339)

24 Analysis using HV Energy Audit Reports Observations 2 : Feeders with Un-acceptable Gap, Sample Cases Summary of Feeder to DT + HT Reports S. No. Division Feeder Name Feeder Energy Sum of DT/HT Energy Gap (Units) Gap (%) 1 Nehru Place O/G S/STN-5 NHP Nehru Place O/G BLDG NO 37 NHP

25 Analysis using HV Energy Audit Reports Observations 2 : Feeders with Un-acceptable Gap, Details A. O/G S/STN-5 NHP - HT (1) + DT (2) Gap ( 39.82%) Units Gap (51797) HT Consumer 1 Y1 B. O/G BLDG NO 37 NHP- HT (2) + DT (5) Gap ( 8.44%) Units Gap (12824) HT Consumer 1 Y2 HT Consumer 2 Y3

26 Load Balance Report Feeder : X 3, Study Period: 1st July'07 to 15th July' /07/2007 0:30 01/07/ :00 02/07/2007 1:30 02/07/ :00 03/07/2007 2:30 03/07/ :00 04/07/2007 3:30 04/07/ :00 05/07/2007 4:30 05/07/ :00 06/07/2007 5:30 06/07/ :00 07/07/2007 6:30 07/07/ :00 08/07/2007 7:30 08/07/ :00 09/07/2007 8:30 09/07/ :00 10/07/2007 9:30 10/07/ :00 11/07/ :30 11/07/ :00 12/07/ :30 KW 13/07/2007 0:00 13/07/ :30 14/07/2007 1:00 Analysis using HV Energy Audit Reports Observations 2 : Feeders with Un-acceptable Gap, Load Curves Study Period 1 July to 14 July Feeders input 1,30,074 DT Energy - 45,377, HT Energy 32,900, Total 78,277 DATE & TIME Gap (39.82 %), Unit Gap (51,797) Feeder Energy DT & HT Energy

27 Analysis using HV Energy Audit Reports Observations 2 : Feeders with Un-acceptable Gap, Load Curves Study Period 1 July to 8 July 1400 Feeder & (DT+HT) Energy Curves Feeder :Bldg. No. 37 Nehru Place Feeder Energy DT & HT Energy Jul 00:30 01-Jul 12:30 02-Jul 00:30 02-Jul 12:30 03-Jul 00:30 03-Jul 12:30 04-Jul 00:30 04-Jul 12:30 05-Jul 00:30 05-Jul 12:30 06-Jul 00:30 06-Jul 12:30 07-Jul 00:30 07-Jul 12:30 08-Jul 00:30 Load (KW) Feeders input 1,52,022 DT Energy - 1,10,377, HT Energy 28,820, Total 1,39,197 Gap (8.44%), Unit Gap (12,824)

28 Analysis using HV Energy Audit Reports Comparison With conventional Method of Metering Installation Testing Cost of Metering installation Testing = INR 8000/- per Consumer (Unit) Out put = 2-3 Installation per day Cost of AMR system & Analysis = INR 6000/- Reporting = Consumer Per Month

29 Future plans Few pockets in Delhi supply area are prone to direct theft even at high value consumers segment. Catching direct theft red handed is critical to establish a theft case in court of law. AMR will help in cracking this. Plan to install intelligent modem based AMR-SMS communication system at consumer s end. Working closely with the meter vendors to provide few additional features.

30 AT&C Loss Reduction Performance (FY to FY ) BSES Yamuna BSES Rajdhani Year analytics initiative was started Attained Incentive Bid Attained Incentive Bid

31 AT&C Loss Reduction Performance (FY to FY ) BSES Yamuna BSES Rajdhani Year O7~08, in BYPL expected reduction is 10% Attained Incentive Bid Attained Incentive Bid

32 Our Analytics team is thankful to Communication service providers Modem vendors Energy audit consultants Energy meter vendors

33 Thanks