Optimal Offering Strategies for Generation Companies Operating in Electricity Spot Markets

Baı́llo, Álvaro; Ventosa, Mariano; Rivier, Michel; Ramos, Andrés

doi:10.1109/tpwrs.2003.821429

Cited by 153 publications

(94 citation statements)

References 15 publications

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“…In addition, [42] discusses a methodology for generation companies to provide hourly offers by considering a series of possible residual inverse demand curves. These are selected from recent days similar to the considered day in terms of hourly demand, and are thus based on historical offers submitted by competing players.…”

Section: Literature Reviewmentioning

confidence: 99%

Price-based unit commitment electricity storage arbitrage with piecewise linear price-effects

Brijs

Geth

Siddiqui

et al. 2016

Journal of Energy Storage

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Electricity storage plants can be used for many applications, with one of the most studied applications being arbitrage in the day-ahead market. Terms of use: Documents inAlthough the arbitrage value is related to the presence of price spreads, it also depends on the effect of (dis)charge actions on prices, as arbitrage generally reduces price spreads by increasing off-peak prices when charging and decreasing peak prices when discharging. As such, there are two important assumptions in price-based unit commitment arbitrage models: first, whether the storage operator is assumed to have perfect knowledge of future prices, and second, whether they recognize that their (dis)charge actions may affect those prices, i.e., the price-taking or pricemaking assumption. This article proposes a comprehensive formulation of the arbitrage problem including detailed operating constraints, and focuses on relaxing the price-taking assumption by considering real-world price-effect data, published in the form of hourly piecewise linear relationships between quantity and price based on submitted bids, which are referred to as "market resilience functions". These can be used to (1) evaluate the price-taking and price-making assumptions based on simplified price-effects, and to (2) provide an upper limit to the arbitrage value under the assumption that prices and price-effects are known at the decision stage. In addition, a stepwise approximation to the piecewise linear functions is developed to reduce computation time, i.e., from mixed-integer nonconvex quadratic programming to mixed-integer linear programming, while providing lower-and upper bound approximations to the arbitrage value. The developed models are applied to the Belgian day-ahead market for 2014, and show that the price-effect has a strong impact on the operation and arbitrage value of large-scale storage.

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Section: Literature Reviewmentioning

confidence: 99%

Price-based unit commitment electricity storage arbitrage with piecewise linear price-effects

Brijs

Geth

Siddiqui

et al. 2016

Journal of Energy Storage

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“…Bajo estas condiciones se logran reducir costos de generación en la operación de corto plazo [2], consecuentemente mejoras en los precios spot dentro de un gran sistema de generación interconectado [3].…”

Section: Planteamiento De Problemaunclassified

Maximización de la eficiencia a cargas parciales de una central hidroeléctrica multigrupo integrada al sistema interconectado nacional

Chávez

Maximiliano

Coquil³

2015

TEC

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“…Earlier studies use the residual demand in strategic price bidding in day ahead market [1,2] and forward market [3]. Reference [4] provides a residual demand model to forecast electricity prices.…”

Section: Introductionmentioning

confidence: 99%

Demand and residual demand modelling using quantile regression

Catherine

Hagfors

Lin

et al. 2016

Renew. Energy Environ. Sustain.

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Abstract. Residual demand, the difference between demand and solar and wind production, is an important variable in predicting the future price and storage requirements. However, little is known about predicting the residual demand itself as well as its quantiles. Therefore, we model both demand and residual demand using both ordinary and quantile regression and compare the results for the hourly electricity consumption in Germany. We find that the residual demand is less predictable than demand. The effect is visible for all hours, and is higher for the lower than the upper quantiles.

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Optimal Offering Strategies for Generation Companies Operating in Electricity Spot Markets

Cited by 153 publications

References 15 publications

Price-based unit commitment electricity storage arbitrage with piecewise linear price-effects

Price-based unit commitment electricity storage arbitrage with piecewise linear price-effects

Maximización de la eficiencia a cargas parciales de una central hidroeléctrica multigrupo integrada al sistema interconectado nacional

Demand and residual demand modelling using quantile regression

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