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A robust operation-based scheduling optimization for smart distribution networks with multi-microgrids.

Authors :
Liu, Yixin
Guo, Li
Wang, Chengshan
Source :
Applied Energy. Oct2018, Vol. 228, p130-140. 11p.
Publication Year :
2018

Abstract

Highlights • An interactive mechanism is proposed for smart distribution networks with microgrids. • The interaction process is formulated as Stackelberg game under a market framework. • The uncertainty of microgrids is handled by two-stage robust method. • A collaborative strategy is established to promote the trading among microgrids. Abstract This paper proposes a two-level interactive mechanism to address the day-ahead scheduling optimization of smart distribution networks with multi-microgrids. Each microgrid realizes the economic dispatch in the lower level interactive model, where the uncertainties caused by renewable energy integration and loads as well as the coordination of controllable distributed generator, energy storage and demand response are handled through a two-stage robust model. In the upper level interactive model, the distribution network operator (DNO) guarantees the operational quality by considering the power flow constraints and decides the transaction price and quantity with each microgrid based on the solutions of the lower level problem, to minimize the operation cost. The interaction process is formulated as a Stackelberg game, in which the trading strategies of coupled microgrids, acted as followers, are influenced by price incentive mechanism of DNO and affect the decision of DNO in turn. A collaborative strategy promoting the internal power trading among microgrids is also presented to deal with the market power of DNO, such that the participating microgrids can benefit from the internal trading and further reduce the cost. Numerical cases on an improved IEEE 33-bus system show the effectiveness of the proposed model and solution strategy. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
03062619
Volume :
228
Database :
Academic Search Index
Journal :
Applied Energy
Publication Type :
Academic Journal
Accession number :
131731753
Full Text :
https://doi.org/10.1016/j.apenergy.2018.04.087