Carnegie Mellon University
Browse

Real-Time Predictive Analytics, Big Data & Energy Market Efficiency: Key to Efficient Markets and Lower Prices for Consumers

Download (504.06 kB)
journal contribution
posted on 2025-04-25, 20:52 authored by Benjamin Schmidt, Patrick Flannery, Mark DeSantisMark DeSantis
The combination of evolving deregulation of the US and EU energy markets together with recent advances in data analytics and so called 'Big Data' technologies now offers an unprecedented opportunity for optimal real-time energy pricing for buyers and sellers alike. The main challenge to date for optimal pricing has been optimal real-time bidding and variety of traditional data analysis tools have been applied to this challenge. Yet inefficiencies remain due to the volatile nature of the real-time market. Energy data science is the best solution to protect consumers against the electricity market's inefficiencies. This field is the meeting point between computer programming, machine learning, big data, quantitative analysis and economics. Energy data science is used to help the consumer predict what price they should offer to buy at each hour and closes gaps in the electric markets.

History

Date

2015-02-04

Usage metrics

    Categories

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC