Logo eprints

A multi-stage stochastic optimization approach to optimal bidding on energy markets

Puglia, Laura and Bernardini, Daniele and Bemporad, Alberto A multi-stage stochastic optimization approach to optimal bidding on energy markets. In: Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference (CDC-ECC). IEEE, 1509 -1514. ISBN 978-1-61284-800-6 (2011)

Full text not available from this repository.


One of the most challenging tasks for an energy producer is represented by the optimal bidding on energy markets. Each eligible plant has to submit bids for the spot market one day before the delivery time and bids for the ancillary services provision. Allocating the optimal amount of energy, jointly minimizing the risk and maximizing profits is not a trivial task, since one has to face several sources of stochasticity, such as the high volatility of energy prices and the uncertainty of the production, due to the deregulation and to the growing importance of renewable sources. In this paper the optimal bidding problem is formulated as a multi-stage optimization problem to be solved in a receding horizon fashion, where at each time step a risk measure is minimized in order to obtain optimal quantities to bid on the day ahead market, while reserving the remaining production to the ancillary market. Simulation results show the optimal bid profile for a trading day, based on stochastic models identified from historical data series from the Italian energy market.

Item Type: Book Section
Identification Number: 10.1109/CDC.2011.6161169
Additional Information: This work was partially supported by the HYCON2: Highly-complex and networked control systems, Network of Excellence, FP7-IST contract no. 257462 and by the European project E-PRICE: Price-based Control of Electrical Power Systems, FP7-IST contract no. 249096
Uncontrolled Keywords: Biological system modeling , Contracts , Electricity , Modeling , Optimization , Production , Stochastic processes
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
T Technology > TJ Mechanical engineering and machinery
Research Area: Computer Science and Applications
Depositing User: Ms T. Iannizzi
Date Deposited: 05 Mar 2012 11:06
Last Modified: 04 Apr 2012 09:21
URI: http://eprints.imtlucca.it/id/eprint/1212

Actions (login required)

Edit Item Edit Item