Title
Data-based Distributionally Robust Stochastic Optimal Power Flow, Part I: Methodologies.
Abstract
We propose a data-based method to solve a multi-stage stochastic optimal power flow (OPF) problem based on limited information about forecast error distributions. The framework explicitly combines multi-stage feedback policies with any forecasting method and historical forecast error data. The objective is to determine power scheduling policies for controllable devices in a power network to balance operational cost and conditional value-at-risk of device and network constraint violations. These decisions include both nominal power schedules and reserve policies, which specify planned reactions to forecast errors in order to accommodate fluctuating renewable energy sources. Instead of assuming that the uncertainties across the networks follow prescribed probability distributions, we consider <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ambiguity sets</italic> of distributions centered around a finite training dataset. By utilizing the Wasserstein metric to quantify differences between the empirical data-based distribution and the real unknown data-generating distribution, we formulate a multi-stage distributionally robust OPF problem to compute control policies that are robust to both forecast errors and sampling errors inherent in the dataset. Two specific data-based distributionally robust stochastic OPF problems are proposed for distribution networks and transmission systems.
Year
DOI
Venue
2018
10.1109/TPWRS.2018.2878385
IEEE Transactions on Power Systems
Keywords
Field
DocType
Stochastic processes,Optimization,Training,Uncertainty,Security,Linear programming,Optimal control
Mathematical optimization,Optimal control,Nominal power (photovoltaic),Scheduling (computing),Schedule,Probability distribution,Transmission system,Wasserstein metric,Mathematics,CVAR
Journal
Volume
Issue
ISSN
abs/1804.06388
2
0885-8950
Citations 
PageRank 
References 
1
0.43
7
Authors
5
Name
Order
Citations
PageRank
Yi Guo1163.05
Kyri Baker2155.55
Emiliano Dall'Anese336038.11
Zechun Hu48014.70
Tyler H. Summers524130.84