The electrical energy (EE) price plays a significant role in the economic assessment of industrial processes. PSE/CAPE applications are often based on economic evaluations/optimizations where EE price and its possible dynamic evolution are important input data. Planning, scheduling, on-line optimization (dynamic) conceptual design, and feasibility studies are some of the applications where short-, medium-, and long-term predictions of EE quotations are involved. The paper discusses the main issues that contribute to EE quotations such as geographical, meteorological, seasonal, political, social, and financial terms. EE prices show a significant dependency on crude oil quotations with a time-delay of about a quarter/season. An econometric model comprising both linear and periodic components with an implicit stochastic term delivered by the reference component is first commented, then identified, and finally validated respect to real EE quotations. The paper provides also a discussion on how to forecast EE prices ranging from short- to long-term horizons.

Price model of electrical energy for PSE applications

MANCA, DAVIDE
2016-01-01

Abstract

The electrical energy (EE) price plays a significant role in the economic assessment of industrial processes. PSE/CAPE applications are often based on economic evaluations/optimizations where EE price and its possible dynamic evolution are important input data. Planning, scheduling, on-line optimization (dynamic) conceptual design, and feasibility studies are some of the applications where short-, medium-, and long-term predictions of EE quotations are involved. The paper discusses the main issues that contribute to EE quotations such as geographical, meteorological, seasonal, political, social, and financial terms. EE prices show a significant dependency on crude oil quotations with a time-delay of about a quarter/season. An econometric model comprising both linear and periodic components with an implicit stochastic term delivered by the reference component is first commented, then identified, and finally validated respect to real EE quotations. The paper provides also a discussion on how to forecast EE prices ranging from short- to long-term horizons.
2016
Crude oil quotations; Econometric model; Electrical energy price; Industrial processes; Price forecast; Short-, long-term predictions; Chemical Engineering (all); Computer Science Applications1707 Computer Vision and Pattern Recognition
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1011774
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