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Polyhedral Risk Measures and Lagrangian Relaxation in Electricity Portfolio Optimization Eichhorn, Andreas Römisch, Werner Wegner, Isabel Stochastic Programming Mean-Risk Optimization Risk Measure Lagrangian Relaxation Electricity; We present a multistage stochastic programming model for mean-risk optimization of electricity portfolios containing physical components and energy derivative products. Stochasticity enters the model via the uncertain (time-dependent) prices and electricity demand. The objective is to maximize the expected overall revenue and, simultaneously, to minimize a multiperiod risk measure, i.e., a risk measure that takes into account the intermediate time cash values. We compare the effect of different multiperiod risk measures taken from the class of polyhedral risk measures which was suggested in our earlier work. Furthermore, we discuss how such a mean-risk optimization problem can be solved by dual decomposition techniques (Lagrangian relaxation). Schloss Dagstuhl – Leibniz-Zentrum für Informatik Andreas Eichhorn and Werner Römisch and Isabel Wegner 2005 Is Part Of Dagstuhl Seminar Proceedings, Volume 5031, Algorithms for Optimization with Incomplete Information (2005) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/DagSemProc.05031.23 urn:nbn:de:0030-drops-574 https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.05031.23 eng https://creativecommons.org/licenses/by/4.0/legalcode