Can electricity demand management drive the transition to clean and affordable energy in poor economies?
This project seeks to inform the design of dynamic pricing and automation programmes to increase the share of renewable energy on the electric grid and lower the average cost of supply.
In accordance with the Government of India’s target of installing 250 million smart meters by 2025, utilities are in the process of replacing traditional meter installations with smart meters across their customer bases. A cornerstone for power sector reforms, smart meters provide utilities and consumers with real-time data on meter-level electricity consumption, allow for various forms of dynamic electricity pricing, and have the potential to reduce aggregate technical and commercial (AT&C) losses by giving utilities the ability to remotely disconnect consumers who fail to pay their bills.
However, electricity regulators and policymakers require additional evidence to develop the policies enabled by this large investment in new infrastructure. By revealing both the scope for flexibility in intraday energy demand and the welfare cost of supply interruptions to residential consumers, this project seeks to inform the design of dynamic pricing and automation programmes, including the types of consumers these policies should target.
At present, a small fraction of utilities in low- and middle-income countries have installed Supervisory Control and Data Acquisition (SCADA), a computer-based system for gathering and analysing real-time data on various elements of the power distribution network, giving them the ability to manage electricity demand at an aggregated feeder level. However, utilities, electricity regulators, and policymakers are interested in developing programmes and tools that can leverage the flexibility that may exist at the consumer level to increase the share of renewable energy on the electric grid and lower the average cost of supply. This is the issue that our study aims to address.