scholarly journals FORECASTING THE COLOMBIAN ELECTRICITY SPOT PRICE UNDER A FUNCTIONAL APPROACH

2021 ◽  
Vol 11 (2) ◽  
pp. 67-74
Author(s):  
Santiago Gallón ◽  
Jorge Barriento
Keyword(s):  
Functional Approach ◽  
Spot Price ◽  
Electricity Spot Price

A Critical Empirical Study of Three Electricity Spot Price Models

2011 ◽  
Author(s):  
Fred Espen Benth ◽  
Ruediger Kiesel ◽  
Anna Nazarova
Keyword(s):  
Empirical Study ◽  
Spot Price ◽  
Electricity Spot Price

Permutation Min-Entropy and Statistical Complexity Analysis of Electricity Spot Price

2015 ◽  
Vol 14 (04) ◽  
pp. 1550040 ◽  
Author(s):  
Qingju Fan ◽  
Dan Li
Keyword(s):  
Temporal Dynamics ◽  
Complexity Analysis ◽  
Spot Price ◽  
Temporal Correlations ◽  
Price Series ◽  
Statistical Complexity ◽  
Electricity Spot Price ◽  
Insight Into ◽  
Refined Classification

In this study, we investigate the subtle temporal dynamics of California 1999–2000 spot price series based on permutation min-entropy (PME) and complexity-entropy causality plane. The dynamical transitions of price series are captured and the temporal correlations of price series are also discriminated by the recently introduced PME. Moreover, utilizing the CECP, we provide a refined classification of the monthly price dynamics and obtain an insight into the stochastic nature of price series. The results uncover that the spot price signal presents diverse temporal correlations and exhibits a higher stochastic behavior during the periods of crisis.

scholarly journals High-Resolution Electricity Spot Price Forecast for the Danish Power Market

2020 ◽  
Vol 12 (10) ◽  
pp. 4267 ◽  
Author(s):  
Jannik Schütz Roungkvist ◽  
Peter Enevoldsen ◽  
George Xydis
Keyword(s):  
Electricity Market ◽  
Thermal Power ◽  
Power Market ◽  
Power Production ◽  
Spot Price ◽  
Price Forecasting ◽  
Learning Approaches ◽  
Electricity Prices ◽  
Price Forecast ◽  
Electricity Spot Price

Energy markets with a high penetration of renewables are more likely to be challenged by price variations or volatility, which is partly due to the stochastic nature of renewable energy. The Danish electricity market (DK1) is a great example of such a market, as 49% of the power production in DK1 is based on wind power, conclusively challenging the electricity spot price forecast for the Danish power market. The energy industry and academia have tried to find the best practices for spot price forecasting in Denmark, by introducing everything from linear models to sophisticated machine-learning approaches. This paper presents a linear model for price forecasting—based on electricity consumption, thermal power production, wind production and previous electricity prices—to estimate long-term electricity prices in electricity markets with a high wind penetration levels, to help utilities and asset owners to develop risk management strategies and for asset valuation.

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