Energy management in smart distribution networks: Synergizing network reconfiguration, energy storage, and electric vehicles with disjunctive convex hull relaxation

Efficient energy management is critical for modern distribution networks integrating renewable energy, storage systems, and electric vehicles. This paper introduces a novel approach combining network reconfiguration with disjunctive convex hull relaxation to optimize power flow, minimize energy losses, and enhance grid stability. Case studies on 33-node and 84-node networks showcase the model’s effectiveness, reducing energy losses to 0.939 MWh and 7.214 MWh, respectively, outperforming Big-M and McCormick methods. Additionally, the approach achieved a 78 % efficiency improvement, enhanced emissions control, and improved voltage regulation, demonstrating superior renewable energy integration. These results highlight the model's potential to provide a more efficient and sustainable energy management solution, addressing the challenges of modern power grids.

Authors

Institutions

Publication Details

Journal
Energy Reports
Published
2024-12-01
DOI
https://doi.org/10.1016/j.egyr.2024.11.085
Citations
3
Primary Topic
Optimal Power Flow Distribution
Type
article
Field-Weighted Citation Impact
0.63
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Energy management in smart distribution networks: Synergizing network reconfiguration, energy storage, and electric vehicles with disjunctive convex hull relaxation

Nasrin Salehi Dehno, Mojtaba Vahedi, Mahmoud Samiei Moghaddam, Mohamad Hoseini Abardeh et al.
3 citations
Energy Reports
Optimal Power Flow Distribution
0.63
article

Energy management in smart distribution networks: Synergizing network reconfiguration, energy storage, and electric vehicles with disjunctive convex hull relaxation

Nasrin Salehi Dehno, Mojtaba Vahedi, Mahmoud Samiei Moghaddam, Mohamad Hoseini Abardeh, Hadi Tavalaei
article en
3 citations

Abstract

Efficient energy management is critical for modern distribution networks integrating renewable energy, storage systems, and electric vehicles. This paper introduces a novel approach combining network reconfiguration with disjunctive convex hull relaxation to optimize power flow, minimize energy losses, and enhance grid stability. Case studies on 33-node and 84-node networks showcase the model’s effectiveness, reducing energy losses to 0.939 MWh and 7.214 MWh, respectively, outperforming Big-M and McCormick methods. Additionally, the approach achieved a 78 % efficiency improvement, enhanced emissions control, and improved voltage regulation, demonstrating superior renewable energy integration. These results highlight the model's potential to provide a more efficient and sustainable energy management solution, addressing the challenges of modern power grids.

Energy ReportsVol. 12
Islamic Azad University, Shahrood (IR), Islamic Azad University, Damghan Branch (IR)
Affordable and clean energy
Openalex Percentile: Top 30%
Optimal Power Flow Distribution
0.63
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Energy management in smart distribution networks: Synergizing network reconfiguration, energy storage, and electric vehicles with disjunctive convex hull relaxation — Nasrin Salehi Dehno, Mojtaba Vahedi, et al. · Energy Reports (2024) | TGRS Research Map | TGRS