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https://doi.org/10.1109/eem.20...
Article . 2018 . Peer-reviewed
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An Exact MILP Model for the Clearing of a Zonal Electricity Market with Uniform Purchase Price: Results and Comparison with Existing Approaches

Authors: Siface, Dario; Pisciella, Paolo; Davo, Federica; Vespucci, Maria Teresa;

An Exact MILP Model for the Clearing of a Zonal Electricity Market with Uniform Purchase Price: Results and Comparison with Existing Approaches

Abstract

The Italian day-ahead electricity market is a zonal market with a national uniform purchase price, called PUN (in Italian “Prezzo Unico Nazionale”). The clearing of such a market is based on linear programming techniques, where primal variables represent quantities of traded energy and dual variables represent prices. Since the PUN cannot be expressed as a linear combination of primal or dual variables only, up to now the above clearing problem could be solved exclusively using heuristic techniques and/or approximations. The authors of this paper have developed an exact mixed integer linear programming model, capable to clear the Italian day-ahead electricity market. In this paper, this new model is compared with the existing, non-exact, market solvers in terms of numerical results and computational costs. In particular, numerical results are perfectly adherent with the ones published by the Italian Market Operator, while the computational costs are of the order of few seconds on a PC.

Keywords

Mixed Integer Linear Programming; Optimization; Power System Economics; Power System Management; Marketing; Energy Engineering and Power Technology; Fuel Technology

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Average
Top 10%
Average
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