2016
DOI: 10.1016/j.epsr.2016.06.019
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European day-ahead electricity market clearing model

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Cited by 51 publications
(27 citation statements)
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“…The model incorporates an iterative procedure, aiming to mitigate the nonconvexity of electricity prices, as a result of the different EUPHEMIA order types and conditions, such as the "fill or kill" condition of block orders, complex orders, and Prezzo Unico Nazionale (PUN) orders. Also, Chatzigiannis et al [18] developed a European day-ahead electricity market clearing model, which explicitly incorporates all the different types of market orders, besides Merit and PUN orders, that are available in European power exchanges, as well as the transmission constraints, containing elements of both the Flow Based (FB) and Available Transfer Capacity (ATC) network representations. The model incorporates an iterative algorithm for the efficient handling of Paradoxically Accepted Orders (PAO) and complex Minimum Income Conditions (MIC).…”
Section: Introductionmentioning
confidence: 99%
“…The model incorporates an iterative procedure, aiming to mitigate the nonconvexity of electricity prices, as a result of the different EUPHEMIA order types and conditions, such as the "fill or kill" condition of block orders, complex orders, and Prezzo Unico Nazionale (PUN) orders. Also, Chatzigiannis et al [18] developed a European day-ahead electricity market clearing model, which explicitly incorporates all the different types of market orders, besides Merit and PUN orders, that are available in European power exchanges, as well as the transmission constraints, containing elements of both the Flow Based (FB) and Available Transfer Capacity (ATC) network representations. The model incorporates an iterative algorithm for the efficient handling of Paradoxically Accepted Orders (PAO) and complex Minimum Income Conditions (MIC).…”
Section: Introductionmentioning
confidence: 99%
“…This term, defined by equation 4 l / f t,− l,ms need to be null and vice-versa. This decomposition is required to correctly model the real energy losses on such interconnectors [34] and limit the upper and lower bounds of temporary variable f t l,ms . Therefore, c l for all interconnectors are set to 0.001.…”
Section: Objective Functionmentioning
confidence: 99%
“…The loss coefficient loss l , f t,+ l and f t,− l are added in (6) to take into account the losses in the DC interconnectors and decompose the power flow into importing and exporting. Constraints (7)-(9) combined with the penalty term (4) give f t,+ l and f t,− l as in [34].…”
Section: Balancing Equationsmentioning
confidence: 99%
“…In the literature, algorithms to solve the market clearing problem in the presence of block orders are based on different techniques. Reference [26] formulates a mixed-integer linear program (MILP) to clear the market with an additional iterative process to handle PRBs. Reference [27] proposes a primal-dual formulation of the market clearing problem, where an improved Benders-like decomposition method is further introduced to strengthen the classical Benders cuts, which is extended in [28].…”
Section: Literature Reviewmentioning
confidence: 99%