This paper provides an overview of tasks and activities of world energy regulatory authorities, through their regional associations. Regulatory practices are investigated when looking at federal, state and national author-ities' replies to two surveys on electricity and gas markets. Empirical results show that the implementation of the energy regulation can be context-specific. Indeed, regulators' powers and tools show diversity, even among groups of regulators belonging to the same regional associations and then expected to act homogeneously. To inspect the similarity across regulators, a statistical index and an unsupervised statistical learning technique are proposed. The usage of these two methods is recommended to inspect the status of the regulatory harmonization, and to inspect if uniformed and coordinated energy policy actions are achieved in view of global resolutions towards a low carbon transition, and delineated environmental and sustainable goals.

A worldwide analysis of the energy regulatory tasks and activities through the lenses of entropy and unsupervised statistical learning / Gianfreda, A; Scandolo, G. - In: ENERGY. - ISSN 0360-5442. - ELETTRONICO. - 271:(2023), pp. 126969-126986. [10.1016/j.energy.2023.126969]

A worldwide analysis of the energy regulatory tasks and activities through the lenses of entropy and unsupervised statistical learning

Scandolo, G
2023

Abstract

This paper provides an overview of tasks and activities of world energy regulatory authorities, through their regional associations. Regulatory practices are investigated when looking at federal, state and national author-ities' replies to two surveys on electricity and gas markets. Empirical results show that the implementation of the energy regulation can be context-specific. Indeed, regulators' powers and tools show diversity, even among groups of regulators belonging to the same regional associations and then expected to act homogeneously. To inspect the similarity across regulators, a statistical index and an unsupervised statistical learning technique are proposed. The usage of these two methods is recommended to inspect the status of the regulatory harmonization, and to inspect if uniformed and coordinated energy policy actions are achieved in view of global resolutions towards a low carbon transition, and delineated environmental and sustainable goals.
2023
271
126969
126986
Gianfreda, A; Scandolo, G
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1313095
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