Literature DB >> 33398000

A framework to predict the price of energy for the end-users with applications to monetary and energy policies.

Stefanos G Baratsas1,2, Alexander M Niziolek1,2, Onur Onel1,2, Logan R Matthews1,2, Christodoulos A Floudas1,2, Detlef R Hallermann3, Sorin M Sorescu3, Efstratios N Pistikopoulos4,5.   

Abstract

Energy affects every single individual and entity in the world. Therefore, it is crucial to precisely quantify the "price of energy" and study how it evolves through time, through major political and social events, and through changes in energy and monetary policies. Here, we develop a predictive framework, an index to calculate the average price of energy in the United States. The complex energy landscape is thoroughly analysed to accurately determine the two key factors of this framework: the total demand of the energy products directed to the end-use sectors, and the corresponding price of each product. A rolling horizon predictive methodology is introduced to estimate future energy demands, with excellent predictive capability, shown over a period of 174 months. The effectiveness of the framework is demonstrated by addressing two policy questions of significant public interest.

Entities:  

Year:  2021        PMID: 33398000     DOI: 10.1038/s41467-020-20203-2

Source DB:  PubMed          Journal:  Nat Commun        ISSN: 2041-1723            Impact factor:   14.919


  3 in total

Review 1.  Energy supply chain optimization of hybrid feedstock processes: a review.

Authors:  Josephine A Elia; Christodoulos A Floudas
Journal:  Annu Rev Chem Biomol Eng       Date:  2014-03-12       Impact factor: 11.059

2.  Paris Agreement climate proposals need a boost to keep warming well below 2 °C.

Authors:  Joeri Rogelj; Michel den Elzen; Niklas Höhne; Taryn Fransen; Hanna Fekete; Harald Winkler; Roberto Schaeffer; Fu Sha; Keywan Riahi; Malte Meinshausen
Journal:  Nature       Date:  2016-06-30       Impact factor: 49.962

3.  Optimal Design of Energy Systems Using Constrained Grey-Box Multi-Objective Optimization.

Authors:  Burcu Beykal; Fani Boukouvala; Christodoulos A Floudas; Efstratios N Pistikopoulos
Journal:  Comput Chem Eng       Date:  2018-02-21       Impact factor: 3.845

  3 in total

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