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Evaluating an Interconnection Project: Do Strategic Interactions Matter?

Sébastien Debia, David Benatia, and Pierre-Olivier Pineau

Year: 2018
Volume: Volume 39
Number: Number 6
DOI: 10.5547/01956574.39.6.sdeb
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Abstract:
High-Voltage Direct Current (HVDC) merchant transmission lines allow trade across separate power markets and often in different countries. Flows on existing cross-border lines are often assessed as suboptimal, which may be due to the light regulation that often prevails in these cases. This paper studies the impact of market power on HVDC interconnections as a determinant of imperfect arbitrage. We assess the impact of Physical Transmission Rights (PTRs) allocation on the management of an HVDC interconnection between a thermal and a hydroelectricity market, assuming dynamic water management. We use a two-stage game formulated as an Equilibrium Problem with Equilibrium Constraints (EPEC) to model the strategic trade between the New York (US) and Quebec (Canada) systems. The numerical model is calibrated with public data. We find that although the interconnection can create wealth, a high concentration of PTRs can destroy value because of dumping strategies. The impact of trade on local price levels may be of concern and calls for the functional unbundling of traders and generators.



Reaching New Lows? The Pandemic’s Consequences for Electricity Markets

David Benatia and Samuel Gingras

Year: 2023
Volume: Volume 44
Number: Number 4
DOI: 10.5547/01956574.44.4.dben
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Abstract:
The COVID-19 crisis has disrupted electricity systems worldwide. This article disentangles the effects of the demand reductions, fuel price devaluation, and increased forecast errors on New York's day-ahead and real-time markets by combining machine learning and structural econometrics. From March 2020 to February 2021, statewide demand has decreased by 4.6 TWh (-3%) including 4 TWh (-8%) for New York City alone, and the day-ahead market has depreciated by $250 million (-6%). The real-time market has, however, appreciated by $15 million (+23%) because of abnormally large forecast errors which significantly undermined system efficiency.





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