Artificial Intelligence & Machine Learning would be leveraged to analyse data generated through smart meters to detect the theft cases – Union Power & NRE Minister R. K. Singh

Line losses in electrical networks are predominantly due to ohmic (heat) loss. Illegal electricity connections and theft of power leads to commercial loss which affects the financial health of the distribution companies with consequential effects like poor quality of power. The Aggregate Technical & Commercial (AT&C) loss is one of the key indicators of DISCOMs performance, which includes impact of power theft also.

As per the ‘Report on Performance of Power Utilities’ for the years 2018-19 to 2020-21 published by Power Finance Corporation Ltd. (PFC), Aggregate Technical and Commercial (AT&C) Losses of distribution utilities during FY 2016-17 to FY 2020-21 are given below-

*Provisional figures.

The State-wise and Utility-wise details of AT&C Losses are given at Annexure.

The pilferage of electricity is one of the several reasons for AT&C losses of the power distribution utilities. It is the prime responsibility of respective Distribution Utilities to take adequate measures to stop power theft. However, Govt. of India supplements the efforts of States/ distribution utilities by providing funding for the purpose under various schemes launched from time to time. Under RDSS Prepaid Smart meters including System metering are important interventions in reducing distribution losses in the Utilities and in facilitating automatic measurement of energy flows and energy accounting as well as auditing without any human intervention. Along with installation of prepaid Smart metering and the associated Advanced Metering Infrastructure (AMI), System metering at Feeder and Distribution Transformer level with communicating feature would also be taken up to facilitate proper energy accounting every month for identification of defaulting consumers, theft prone pockets and high loss areas. Under the scheme, advanced ICT like Artificial Intelligence & Machine Learning (AI/ML) would be leveraged to analyse data generated through smart meters to detect the theft cases and to prepare actionable MIS from system generated energy accounting reports so as to enable the DISCOMs to take informed decisions on power theft along with loss reduction.

Under Aatma Nirbhar Bharat Abhiyan, Government of India have taken a policy decision to privatize the distribution functions in the Power Departments / Utilities in the Union Territories. This is an important policy decision of the Government, taken with the objectives of providing better services to consumers and improvement in operational and financial efficiency of Distribution sector which currently is beset with inefficiencies. This will also provide a model for emulation by other Utilities across the country.

Further, there are specific provisions in the Electricity Act, 2003 (Section 126 and Sections 135 to 140) relating to theft and unauthorized use of electricity, including stringent penal provisions and speedy trial for such offences by Special Courts (Part XV of the Electricity Act, 2003). As per Electricity (Rights of Consumers) Rules, 2020, the distribution licensee shall arrange to display on its website feeder-wise outage data, efforts made for minimizing outages, prevention of theft or unauthorized use of electricity or tampering, distress or damage to electrical plant, electric lines or meter and results obtained during the year. Also, Tariff Policy 2016 envisages that in order to reduce theft of power, the distribution companies should have enabling feature like distribution SCADA with distribution management system and energy audit functions.