A mixed-integer SDP solution to distributionally robust unit commitment with second order moment constraints

A power system unit commitment (UC) problem considering uncertainties of renewable energy sources is investigated in this paper, through a distributionally robust optimization approach. We assume that the first and second order moments of stochastic parameters can be inferred from historical data, a...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:CSEE Journal of Power and Energy Systems Jg. 6; H. 2; S. 374 - 383
Hauptverfasser: Xiaodong Zheng, Haoyong Chen, Yan Xu, Zhengmao Li, Zhenjia Lin, Zipeng Liang
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Beijing Chinese Society for Electrical Engineering Journal of Power and Energy Systems 01.06.2020
China electric power research institute
Schlagworte:
Algorithms
Feasibility
Integers
Optimization
Order parameters
Real time operation
Renewable energy sources
Robustness (mathematics)
Semidefinite programming
Unit commitment
ISSN:2096-0042, 2096-0042
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:A power system unit commitment (UC) problem considering uncertainties of renewable energy sources is investigated in this paper, through a distributionally robust optimization approach. We assume that the first and second order moments of stochastic parameters can be inferred from historical data, and then employed to model the set of probability distributions. The resulting problem is a two-stage distributionally robust unit commitment with second order moment constraints, and it can be recast as a mixed-integer semidefinite programming (MI-SDP) with finite constraints. The solution algorithm of the problem comprises solving a series of relaxed MI-SDPs and a subroutine of feasibility checking and vertex generation. Based on the verification of strong duality of the semidefinite programming (SDP) problems, we propose a cutting plane algorithm for solving the MI-SDPs; we also introduce an SDP relaxation for the feasibility checking problem, which is an intractable biconvex optimization. Experimental results on the IEEE 6-bus system are presented, showing that without any tuning of parameters, the real-time operation cost of distributionally robust UC method outperforms those of deterministic UC and two-stage robust UC methods in general, and our method also enjoys higher reliability of dispatch operation.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:2096-0042
2096-0042
DOI:10.17775/CSEEJPES.2019.00930