El precio spot de la electricidad y la inclusión de energía renovable no convencional: evidencia para Colombia (The Electricity Spot Price and Inclusion of Non-Conventional Renewable Energies: Evidence for Colombia)

This study aims to explore the relationship between renewable energies and the electric power spot price of the Japan Electric Power Exchange (JEPX). By using panel data analysis and proxy modeling, this work attempts to estimate how renewable energies (displayed through the proxies) and other factors influence the electric power spot price in Japan. Based on an analysis of the estimations, some policy implications have been proposed, such as to incorporate weather information into the price forecast, or to provide a guide to more effectively transact on the JEPX.

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High Frequency Electricity Spot Price Dynamics: An Intra-Day Markets Approach

SSRN Electronic Journal ◽

10.2139/ssrn.367760 ◽

2003 ◽

Cited By ~ 4

Author(s):

Graeme A. Guthrie ◽

Steen Videbeck

Keyword(s):

High Frequency ◽

Spot Price ◽

Price Dynamics ◽

Electricity Spot Price

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

Fluctuation and Noise Letters ◽

10.1142/s0219477515500406 ◽

2015 ◽

Vol 14 (04) ◽

pp. 1550040 ◽

Cited By ~ 1

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.

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

Sustainability ◽

10.3390/su12104267 ◽

2020 ◽

Vol 12 (10) ◽

pp. 4267 ◽

Cited By ~ 1

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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