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A Stochastic Programming Model for a Day-Ahead Electricity Market With Real-Time Reserve Shortage Pricing

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3 Author(s)
Jichen Zhang ; Department of Management Sciences, Faculty of Engineering, University of Waterloo, Waterloo, Canada ; J. David Fuller ; Samir Elhedhli

We present a multi-period stochastic mixed integer programming model for power generation scheduling in a day-ahead electricity market. The model considers various scenarios and integrates the idea of reserve shortage pricing in real time. Instead of including all the possible scenarios, we parsimoniously select a certain number of scenarios to limit the size of the model. As realistic size models are still intractable for exact methods, we propose a heuristic solution methodology based on scenario-rolling that is capable of finding good quality feasible solutions within reasonable computation time.

Published in:

IEEE Transactions on Power Systems  (Volume:25 ,  Issue: 2 )