(212h) Energy Price Index Framework and Tools – Five Years Later

EPIC (Energy PrICe index) framework was one of the very last scientific endeavors of Professor Christodoulos A. Floudas, who envisioned a systematic way to quantify what the unit price of energy is, and how it is affected by major events such as technological breakthroughs, political and social events, and changes in energy and monetary policies. Today, EPIC (Baratsas et al. 2021a) is a flexible, forecasting framework to calculate the average price of energy through the holistic consideration of energy pricing and demand-supply mechanisms at different granularity levels, i.e. state, multi-state, regional, national, of an energy landscape. At US national level, EPIC (Baratsas et al. 2021b) sets a benchmark for the price of energy across all end-use sectors, proportionally capturing the effects of all energy feedstocks and products. Applying state-of-the-art data analytics, deterministic optimization and machine learning techniques, the energy demands and prices of energy products can be predicted with high accuracy for a period up to four and one years respectively.

Taking advantage of these unique characteristics, EPIC can be also used as a quantitative framework to design, assess and optimize policy case studies of significant public interest. To this respect, the analysis of economic, social and fiscal effects of four case studies will be presented: i) crude oil tax hike, ii) renewable energy production targets and subsidies, iii) gasoline tax hike, iv) carbon tax. Moreover, a detailed comparison between EPIC and various widely-accepted economic indicators, financial metrics and energy benchmarks will be discussed. Finally, the development of a novel, holistic energy market index, the ESPIC (Energy Spot PrICe index), and its applications in trading on the financial markets will be presented.

References:

Baratsas, S. G., A. M. Niziolek, O. Onel, L. R. Matthews, C. A. Floudas, D. R. Hallermann, S. M. Sorescu and E. N. Pistikopoulos (2021a). "A framework to predict the price of energy for the end-users with applications to monetary and energy policies." Nature Communications 12(1): 18.

Baratsas, S. G., A. M. Niziolek, O. Onel, L. R. Matthews, C. A. Floudas, D. R. Hallermann, S. M. Sorescu and E. N. Pistikopoulos (2021b). "A novel quantitative forecasting framework in energy with applications in designing energy intelligent tax policies - the cases of federal gasoline and carbon tax in the United States." Applied Energy [Under Review].