  In this work we propose a heuristic clearing method of day-ahead electricity
markets. In the first part of the process, a computationally less demanding
problem is solved using an approximation of the cumulative demand and supply
curves, which are derived via the aggregation of simple bids. Based on the
outcome of this problem, estimated ranges for the clearing prices of individual
periods are determined. In the final step, the clearing for the original bid
set is solved, taking into account the price ranges determined previously as
constraints. Adding such constraints reduces the feasibility region of the
clearing problem. By removing simple bids whose acceptance or rejection is
already determined by the assumed price range constraints, the size of the
problem is also significantly reduced. Via simple examples, we show that due to
the possible paradox rejection of block bids the proposed bid-aggregation based
approach may result in a suboptimal solution or in an infeasible problem, but
we also point out that these pitfalls of the algorithm may be avoided by using
different aggregation patterns. We propose to construct multiple different
aggregation patterns and to use parallel computing to enhance the performance
of the algorithm. We test the proposed approach on setups of various problem
sizes, and conclude that in the case of parallel computing with 4 threads a
high success rate and a significant gain in computational speed may be
achieved.
