A convex multi-objective distributionally robust optimization for embedded electricity and natural gas distribution networks under smart electric vehicle fleets
Convex optimization; Distributionally robust optimization; Electricity distribution network; Electricity vehicle; Integrated energy systems; Natural gas system; Convex optimisation; Electrical distribution networks; Electricity distribution networks; Gas distribution network; Multi objective; Natural gas systems; Robust optimization; Renewable Energy, Sustainability and the Environment; Environmental Science (all); Strategy and Management; Industrial and Manufacturing Engineering; General Environmental Science; Building and Construction
Résumé :
[en] The indisputable environmental concerns have forced the imminent proliferation of renewable energy sources (RES) and electric vehicles (EV). However, the high penetration of such uncertain and variable sources, can pose significant challenges for maintaining supply–demand balance in electrical distribution networks (EDNs). To address these challenges, this paper presents a distributionally robust optimization (DRO) method for multi-objective scheduling in integrated electricity and natural gas distribution networks (IENGDNs). The proposed approach aims to minimize environmental-economic objectives while taking into account the high penetration of EVs and RESs. The impact of a smart EV charging strategy is evaluated to reduce operating costs and maximize the use of RESs. Additionally, demand response programs (DRPs) are used in the EDN to prevent overlapping of peak load hours between the EDN and natural gas distribution network (NGDN). Linepack technology is also used to store natural gas in NGDN pipelines, which increases the short-term flexibility of the entire IENGDNs. The proposed problem is mathematically structured as a second-order conical programming (SOCP) model to benefit from the reliable and efficient convex optimization solution. The simulations were conducted on a 123-EDN and a 40-NGDN systems. Different simulation cases show that the proposed economic-environmental framework can bring down the total emissions by 10.02%.
Disciplines :
Ingénierie électrique & électronique
Auteur, co-auteur :
Nasiri, Nima ; Resilient Smart Grids Research Lab, Electrical Engineering Department, Azarbaijan Shahid Madani University, Tabriz, Iran
Zeynali, Saeed; SnT, University of Luxembourg, Luxembourg, Luxembourg
KUBLER, Sylvain ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SerVal
Le Traon, Yves; SnT, University of Luxembourg, Luxembourg, Luxembourg
Co-auteurs externes :
yes
Langue du document :
Anglais
Titre :
A convex multi-objective distributionally robust optimization for embedded electricity and natural gas distribution networks under smart electric vehicle fleets
This work was supported by the Luxembourg National Research Fund (FNR) LightGridSEED Project, ref. C21/IS/16215802/LightGridSEED . and in fulfilment of the obligations arising from the grant agreement, the author has applied a Creative Commons Attribution 4.0 International (CC BY 4.0) license to any Author Accepted Manuscript version arising from this submission.
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