Optimal offering strategies for generation companies operating in electricity spot markets

By Á. Baíllo, Mariano Ventosa, Michel M. Rivier, Andrés Ramos. IEEE Transactions on Power Systems, 2004

171 citations recorded by the source corpus.

Subfields: Electrical and Electronic Engineering, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/55ff54adbab318c06bc939b89d686924de2c3e79

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In Electrical and Electronic Engineering

In Management Science and Operations Research

Citations in the corpus

Strategic bidding under uncertainty: a binary expansion approach (2005, methodology): “1 In this context, one possible approach is to forecast the demand behavior of the day under study and use a clustering method to select past days sufficiently similar to this one, such as presented in [1].”
Electricity Producer Offering Strategies in Day-Ahead Energy Market With Step-Wise Offers (2007, background): “The Producer in this case, acts as a “leader” in a Stackelberg game, facing a “residual demand” function, obtained by the aggregation of the “follower”-competitors’ demand declarations and supply offers [4].”
Multimarket optimal bidding for a power producer (2005, background): “Within an electricity market framework, [9] models in detail the day-ahead market but not other markets, and [10] focuses on hydrodominated systems.”
Offering Strategy of Wind-Power Producer: A Multi-Stage Risk-Constrained Approach (2016, background): “Nevertheless, most of them focus on conventional producers [3]–[6], which cannot be directly applied by WPPs since WP production is uncertain at the time the offering strategy is decided.”
Risk-Constrained Bidding Strategy With Stochastic Unit Commitment (2007, methodology): “In [13] and [14], unit commitment decisions were not considered and assumed to be given.”
Optimal Demand-Side Bidding Strategies in Electricity Spot Markets (2012, methodology): “Mathematical programming techniques are the most frequently implemented as in [3], [4], [7], [8], [11], and [13]–[18].”
Optimal Offering Strategy of a Virtual Power Plant: A Stochastic Bi-Level Approach (2016, unknown): “Since this condition is nonlinear, an equivalent linear formulation is used [32] Qi1ts2 − Qi1ts′2 ≥ −xts2s′2 · Mq ∀ i ∈ I S , t ∈ T , s2, s′2 ∈ S2, s′2 > s2 (33) Qi1ts′2 − Qi1ts2 ≥ − ( 1 − xts2s′2 ) · Mq ∀ i ∈ I S , t ∈ T , s2, s′2 ∈ S2, s′2 > s2 (34) πi1ts2 − πi1ts′2 ≥ −xts2s′2 · Mp ∀ i ∈ I S , t ∈”
Short-Term Trading for a Wind Power Producer (2010, methodology): “For this purpose, variables representing the power traded in this market for each time period are made dependant on scenarios , as in [20] or [21], and the following constraints are added to model (16)–(21):”
Offering Strategy Via Robust Optimization (2011, background): “Stochastic programming approaches for deriving offering curves are provided in [17]–[19].”
Optimal Bidding Strategies for Hydro-Electric Producers: A Literature Survey (2014, background): “In non-game theoretic models, a competitor’s bidding behavior is represented via bidding scenarios and a revenue-maximization problem, under uncertainty, is solved for the price-maker agent [32], [33].”
Strategic generation with conjectured transmission price responses in a mixed transmission pricing system-part II: application (2004, background): “Inclusion of such a term has been interpreted as representing a generator’s concern with long-run profitability [2].”