  The imbalance costs incurred by a stochastic power producer due to forecast
production errors have a significant impact on its total profit and therefore,
such an impact needs to be taken into account when evaluating investment
decisions. In this paper, we propose a modeling framework to analyze the effect
of these imbalance costs on optimal generating expansion decisions of
stochastic units. The proposed model is cast as a mathematical program with
equilibrium constraints, which allows the explicit representation of both the
day-ahead and balancing market-clearing mechanisms. We use the proposed
framework to investigate the effect of two paradigmatic market designs on
investment decisions: a day-ahead market that is cleared following a
conventional cost merit-order principle, and an ideal market-clearing procedure
that determines day-ahead dispatch decisions accounting for their impact on
balancing operation costs. The variability throughout the planning horizon of
the expected stochastic power production and demand level in the day-ahead
market is modeled via a scenario set. Likewise, the uncertainty pertaining to
their corresponding forecast errors, which are to be settled in the balancing
market, is also characterized through scenarios. The main features and results
of the proposed models are discussed using an illustrative two-node example and
a more realistic 24-node case study.
