R-Infra carries out rigorous meter reading of over 2.6 mn customers in
Mumbai— month after month. This process is highly person dependent, and unless
tightly controlled, can lead to delay in meter reading cycle-time; increase in
customer complaints and queries; rise in cases where meters cannot be read and
hence leading to billing, based on estimation and delay in revenue collection,
specially for high-value customers.
In a survey carried out by the company, it was identified that the customers
appreciate accurate meter reading and billing in a timely and transparent
manner. Similarly the premium customers aspire for personalized and technology
driven services. They are on the look out for ways and means where the utility
company can help them be aware of their consumption patterns so that they can
control their energy consumption and also pro-actively plan to arrange for
payment of monthly energy bills.
Q What were the challenges and business problems that led to this Q What were the key benefits gained in meter data management after Q How do you plan to enhance it in future? |
R-Infra was also looking for appropriate technologies that could enable their
Energy Auditing process that could help accurate accounting of T&D losses and
enable resulting improvements. In order to increase operational efficiency,
enhance process capabilities and address all the above mentioned issues,
automated meter reading (AMR) solution was envisaged.
Technologies used
The company deployed CDMA-based modems, serially attached to the digital meters
for 4,916 substations/distribution transformers, 2,687 streetlights, 12,590
high-value customers and 57 receiving stations/grid stations. These modems are
installed at the customer premises and installation details are captured. They
are then verified through a remote software to check the connectivity with the
remote server. An AMR modem configuration software was developed to assign the
IP addresses to individual modems to be deployed. A forward and backward
integration of AMR server with the existing platforms such as SAP-ISU server and
SAP-Billing server (for consumer billing) was done to provide an end to end
solution.
Company Scenario |
Before Deployment |
|
After Deployment |
|
Deployment challenges
The following were the key technical challenges faced while implementing the
project:
- Poor signal strength of the CDMA network
- Large pool of IP addresses to be configured on modems
- Remotely identify and cross verify modem connectivity to the meters
- Conduct audits of modems installed on the field
- Identifying the exact energy parameters from the XML file downloaded from
the meter for the billing server - Devising the process of providing the power supply to the modem without
disturbing the meter connection
Benefits to company
R-Infra maintains the meter reading cycle time to 30 days in a sustainable
manner — month after month. The accuracy of these meter readings is maintained
to over 99.7%. The following are other benefits that have been accrued by
Reliance Infrastructure after deployment of the project
1. Optimum utilization of manpower: The manpower deployed for the monthly
meter reading activity is relieved which has led to savings in 5680 man hours
per month. Also, the reduction in transport costs for Meter reading has been by
40% per month.
2. Reduced customer service costs: During the manual meter reading
process the meters which could not be covered were billed on the basis of
assessed bills. These bills lead to major consumer complaints which required
manpower to address the complaints. The meter automation reduced the customer
service costs of R-Infra. The assessment periodicity for customers has reduced
by 50%. The loss calculation process has been speeded-up and this helped in
achieving a loss reduction of over 1% in one year, which translates to approx Rs
60 cr of revenue.
3. Reduction in commercial and technical losses: The meter data captured
is used for analysis purpose to identify the commercial and technical losses in
the system. The data helps in identifying meter tampering events, meter OFF
events, energy consumption pattern of the consumer exceeding the contract
demand, etc. Some 53 cases of power theft were reported through AMRs during 4th
quarter of last FY.