2015/06/22 by Javier Saez-Gallego, Saez-Gallego, Javier, Juan M. Morales +5 · 2 citations
Energy · Engineering · #Electric Power System Optimization #Energy, Environment, and Transportation Policies #FOS: Mathematics #Optimization and Control (math.OC) #Smart Grid Energy Management
paper · pdf · doi:10.48550/arxiv.1506.06587
openalex publication_date 2015/06/22 · openalex created_date 2022/10/03 · openalex updated_date 2026/07/28
This paper deals with the market-bidding problem of a cluster of\nprice-responsive consumers of electricity. We develop an inverse optimization\nscheme that, recast as a bilevel programming problem, uses price-consumption\ndata to estimate the complex market bid that best captures the price-response\nof the cluster. The complex market bid is defined as a series of marginal\nutility functions plus some constraints on demand, such as maximum pick-up and\ndrop-off rates. The proposed modeling approach also leverages information on\nexogenous factors that may influence the consumption behavior of the cluster,≠.g., weather conditions and calendar effects. We test the proposed methodology\nfor a particular application: forecasting the power consumption of a small\naggregation of households that took part in the Olympic Peninsula project.\nResults show that the price-sensitive consumption of the cluster of flexible\nloads can be largely captured in the form of a complex market bid, so that this\ncould be ultimately used for the cluster to participate in the wholesale\nelectricity market.\n