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Estimating the Volatility of Wholesale Electricity Spot Prices in the US

Lester Hadsell, Achla Marathe and Hany A. Shawky

Year: 2004
Volume: Volume 25
Number: Number 4
DOI: 10.5547/ISSN0195-6574-EJ-Vol25-No4-2
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Abstract:
This paper examines the volatility of wholesale electricity prices for five US markets. Using data covering the period from May 1996 to September 2001, for the California-Oregon Border, Palo Verde, Cinergy, Entergy, and Pennsylvania-New Jersey-Maryland markets, we examine the volatility of electricity wholesale prices over time and across markets. We estimate volatility using a TARCH model to study the differences among markets and the seasonal characteristics of each market. For all markets, we find strong evidence for a downward trend in the ARCH term and a significant negative asymmetric effect over the sample period. We also document important differences among the regional electricity markets not only with respect to wholesale price volatility and seasonal variations, but also with respect to asymmetric properties and persistence of volatility.



Space-time modeling of electricity spot prices

Girum Dagnachew Abate and Niels Haldrup

Year: 2017
Volume: Volume 38
Number: Number 5
DOI: https://doi.org/10.5547/01956574.38.5.gaba
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Abstract:
Using data for the Nord Pool power grid, we derive a space-time Durbin model for electricity spot prices with both temporal and spatial lags. Joint modeling of temporal and spatial adjustment effects is necessarily important when prices and loads are determined in a network grid. By using different spatial weight matrices, statistical tests show significant spatial dependence in the spot price dynamics across areas. In fact, estimation of the model shows that the spatial dependence is as important as the temporal dependence in describing the spot price dynamics. We decompose price impacts into direct and indirect effects and demonstrate how price effects transmit to neighboring markets and decline with distance. A forecasting comparison with a non-spatial model shows that the space-time model improves forecasting performance for 7 and 30 days ahead forecasts. A model with time-varying parameters is estimated for an expanded sample period and it is found that the spatial correlation within the power grid has increased over time. We interpret this to indicate an increasing degree of market integration within the sample period.



The Impact of Renewable Energy Generation on the Spot Market Price in Germany: Ex-Post Analysis using Boosting Method

Alexander Ryota Keeley, Ken’ichi Matsumoto, Kenta Tanaka, Yogi Sugiawan, and Shunsuke Managi

Year: 2020
Volume: Volume 41
Number: Special Issue
DOI: 10.5547/01956574.41.SI1.akee
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Abstract:
This study combines regression analysis with machine learning analysis to study the merit order effect of renewable energy focusing on German market, the largest market in Europe with high renewable energy penetration. The results show that electricity from wind and solar sources reduced the spot market price by 9.64 €/MWh on average during the period from 2010 to 2017. Wind had a relatively stable impact across the day, ranging from 5.88 €/MWh to 8.04 €/MWh, while the solar energy impact varied greatly across different hours, ranging from 0.24 €/MWh to 11.78 €/MWh and having a stronger impact than wind during peak hours. The results also show characteristics of the interactions between renewable energy and spot market prices, including the slightly diminishing merit order effect of renewable energy at high generation volumes. Finally, a scenario-based analysis illustrates how different proportions of wind and solar energies affect the spot market price.





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