Data Analytics for Advanced Metering Infrastructure : A Guidance Note for South Asian Power Utilities
The power industry in South Asia is on the cusp of a transformation driven by technological advances, decreasing energy intensity, heightened environmental awareness, and evolving customer expectations. Governments in most South Asian countries are...
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| Format: | Report |
| Language: | English |
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World Bank, Washington, DC
2019
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| Online Access: | http://documents.worldbank.org/curated/en/307611570532208645/Data-Analytics-for-Advanced-Metering-Infrastructure-A-Guidance-Note-for-South-Asian-Power-Utilities http://hdl.handle.net/10986/32549 |
| Summary: | The power industry in South Asia is on
the cusp of a transformation driven by technological
advances, decreasing energy intensity, heightened
environmental awareness, and evolving customer expectations.
Governments in most South Asian countries are helping
utilities by implementing various schemes to improve their
power sectors. In particular, the widespread and successful
adoption of smart metering in advanced economies over the
last decade has encouraged South Asian policy makers to take
an increasing interest in smart metering systems in hope
that they can address some of the chronic issues. Now, with
high-level policies in place and utilities keen to adopt
smart metering, funding requirement and implementation
challenges remain the bottlenecks to mass deployment. A
recent World Bank–funded study for South Asian Utilities,
carried out in 2018, developed guidance, based on user
experience, on the deployment and operation of advanced
metering infrastructure (AMI) and analytics systems by
electricity distribution utilities in India and other South
Asian countries. The guidance is intended for the ready
reference of policy makers and utility managers. This report
has two main parts as follows: Chapter 1 provides an
overview of the use of data analytics by power utilities,
including conceptual architecture for system deployment,
meter data flow in metering, billing and collection (MBC)
processes, and data analytics systems; and Chapter 2
describes the transition phase utilities go through while
adopting data analytics systems, including an explanation of
procurement and implementation models for data analytics systems. |
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