Multistage Optimization of a Petroleum Production System with Material Balance Model

Adaptive Relaxations for Multistage Robust Optimization

Multistage robust optimization problems can be interpreted as two-person zero-sum games between two players. We exploit this game-like nature and utilize a game tree search in order to solve quantified integer programs (QIPs). In this algorithmic environment relaxations are repeatedly called to asses the quality of a branching variable and for the generation of bounds. A useful relaxation, however, must be well balanced with regard to its quality and its computing time. We present two relaxations that incorporate scenarios from the uncertainty set, whereby the considered set of scenarios is co…

基于Wasserstein重心的情景树缩减方法

Scenario Tree Reduction via Wasserstein Barycenters

本文针对Kovacevic和Pichler情景树缩减算法中大规模线性问题求解瓶颈，提出利用Wasserstein重心和最优传输技术加速计算，实验表明在8阶段、78 125情景、97 656节点的情景树上速度提升达八倍。

Multi-stage Stochastic Alternating Current Optimal Power Flow with Storage: Bounding the Relaxation Gap

We propose a generic multistage stochastic model for the Alternating Current Optimal Power Flow (AC OPF) problem for radial distribution networks, to account for the random electricity production of renewable energy sources and dynamic constraints of storage systems. We consider single-phase radial networks. Radial three-phase balanced networks (medium-voltage distribution networks typically have this structure) reduce to the former case. This induces a large scale optimization problem, which, given the non-convex nature of the AC OPF, is generally challenging to solve to global optimality. We…