9 research outputs found
Revisiting minimum profit conditions in uniform price day-ahead electricity auctions
We examine the problem of clearing day-ahead electricity market auctions
where each bidder, whether a producer or consumer, can specify a minimum profit
or maximum payment condition constraining the acceptance of a set of bid curves
spanning multiple time periods in locations connected through a transmission
network with linear constraints. Such types of conditions are for example
considered in the Spanish and Portuguese day-ahead markets. This helps
describing the recovery of start-up costs of a power plant, or analogously for
a large consumer, utility reduced by a constant term. A new market model is
proposed with a corresponding MILP formulation for uniform locational price
day-ahead auctions, handling bids with a minimum profit or maximum payment
condition in a uniform and computationally-efficient way. An exact
decomposition procedure with sparse strengthened Benders cuts derived from the
MILP formulation is also proposed. The MILP formulation and the decomposition
procedure are similar to computationally-efficient approaches previously
proposed to handle so-called block bids according to European market rules,
though the clearing conditions could appear different at first sight. Both
solving approaches are also valid to deal with both kinds of bids
simultaneously, as block bids with a minimum acceptance ratio, generalizing
fully indivisible block bids, are but a special case of the MP bids introduced
here. We argue in favour of the MP bids by comparing them to previous models
for minimum profit conditions proposed in the academic literature, and to the
model for minimum income conditions used by the Spanish power exchange OMIE
A new formulation of the European day-ahead electricity market problem and its algorithmic consequences
A new formulation of the optimization problem implementing European market rules for non- convex day-ahead electricity markets is presented, that avoids the use of complementarity constraints to express market equilibrium conditions, and also avoids the introduction of auxiliary binary variables to linearise these constraints. Instead, we rely on strong duality theory for linear or convex quadratic optimization problems to recover equilibrium constraints imposed by most of European power exchanges facing indivisible orders. When only so-called stepwise preference curves are considered to describe continuous bids, the new formulation allows to take full advantage of state-of-the-art solvers, and in most cases, an optimal solution together with market clearing prices can be computed for large-scale instances without any further algorithmic work. The new formulation also suggests a very competitive Benders-like decomposition procedure, which helps to handle the case of interpolated preference curves that yield quadratic primal and dual objective functions, and consequently a dense quadratic constraint. This procedure essentially consists in strengthening classical Benders cuts locally. Computational experiments on real data kindly provided by main European power exchanges (Apx-Endex, Belpex and Epex spot) show that in the linear case, both approaches are very efficient, while for quadratic instances, only the decomposition procedure is tractable and shows very good results. Finally, when most orders are block orders, and instances are combinatorially very hard, the new MILP approach is substantially more efficient