Stochastic dominant-subordinate-interactive scheduling optimization for interconnected microgrids with considering wind-photovoltaic-based distributed generations under uncertainty

Yizhong Chen, Li He and Jing Li

Energy, 2017, vol. 130, issue C, 581-598

Abstract: This study develops a dominant-subordinate-interactive stochastic programming (DSISP) model for the wind-photovoltaic-based distributed energy resource systems in Lize Financial Business District of Beijing, China. During the synergistic optimization process with 24-h prediction outputs of solar and wind power as constraints, the dominant level puts more emphasis on renewable energy utilization, while the minimization both of pollutant emissions and system cost are modeled as a multi-objective programming (MOP) problem placed at the subordinate level. Results indicate that: (a) renewable energy technologies would exert an increasing paramount role in power systems, with an average share of 15.54% through a whole year; (b) a higher violation risk would lead to a decreased strictness of the constraints for facility capacity availabilities, and then to a higher system cost, more green electricity generation, and lower non-renewable electricity generation. As a consequence, thermal supplies especially in winner days would depend strongly on gas-fired boiler, which would result in more pollutant emissions as a violation risk increases. Moreover, the performance of the DSISP model is enhanced by comparing with three single-objective programs and the MOP approach. Results demonstrate that the DSISP model can provide much comprehensive and systematic strategies as considering the bi-level structure within the systems.

Keywords: Stochastic; Distributed energy resource; Green electricity generation; Pollutant emissions; Bi-level structure (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (11)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0360544217305522
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:130:y:2017:i:c:p:581-598

DOI: 10.1016/j.energy.2017.03.172

Access Statistics for this article

Energy is currently edited by Henrik Lund and Mark J. Kaiser

More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().