Artificial Intelligence Assisted Consumer Privacy and Electrical Energy Management
Keywords:
AI, smart metering, privacy, scheduling, virtual power bank, adjusted-average daily demand
Abstract
Smart metering infrastructure brings unique benefits for Utility Companies as well as consumers, however, massive consumer data collected and transmitted by the smart meters have raised consumers2019; privacy concerns. This paper presents a novel solution that is based on Artificial Intelligence Agent that continuously computes the gap between 201C;Average Daily Demand201D; and 201C;Instantaneous Demand201D; of a consumer, and allows the Battery Banks to discharge just enough to fill the gaps and eliminate kinks in the energy usage graph to mask the energy usage. This novel approach offers several benefits, such as, it conceals the utility usage patterns and thus ensures privacy, eliminates excessive discharging and charging of batteries that lifts operational constraints of the batteries, employs scheduling that renders utility bill reduction as an add-on.
Downloads
- Article PDF
- TEI XML Kaleidoscope (download in zip)* (Beta by AI)
- Lens* NISO JATS XML (Beta by AI)
- HTML Kaleidoscope* (Beta by AI)
- DBK XML Kaleidoscope (download in zip)* (Beta by AI)
- LaTeX pdf Kaleidoscope* (Beta by AI)
- EPUB Kaleidoscope* (Beta by AI)
- MD Kaleidoscope* (Beta by AI)
- FO Kaleidoscope* (Beta by AI)
- BIB Kaleidoscope* (Beta by AI)
- LaTeX Kaleidoscope* (Beta by AI)
How to Cite
Published
2020-01-15
Issue
Section
License
Copyright (c) 2020 Authors and Global Journals Private Limited

This work is licensed under a Creative Commons Attribution 4.0 International License.