A Data-Driven Bidding Model for a Cluster of Price-Responsive Consumers of Electricity

Javier Saez Gallego, Juan Miguel Morales González, Marco Zugno, Henrik Madsen

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This paper deals with the market-bidding problem of a cluster of price-responsive consumers of electricity. We develop an inverse optimization scheme that, recast as a bilevel programming problem, uses price-consumption data to estimate the complex market bid that best captures the price-response of the cluster. The complex market bid is defined as a series of marginal utility functions plus some constraints on demand, such as maximum pick-up and drop-off rates. The proposed modeling approach also leverages information on exogenous factors that may influence the consumption behavior of the cluster, e.g., weather conditions and calendar effects. We test the proposed methodology for a particular application: forecasting the power consumption of a small aggregation of households that took part in the Olympic Peninsula project. Results show that the price-sensitive consumption of the cluster of flexible loads can be largely captured in the form of a complex market bid, so that this could be ultimately used for the cluster to participate in the wholesale electricity market.
Original languageEnglish
JournalIEEE Transactions on Power Systems
Issue number6
Pages (from-to)5001-5011
Publication statusPublished - 2016


  • Smart grid
  • Demand response
  • Electricity markets
  • Inverse optimization
  • Bilevel programming


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