Chance-constrained comfort-centric loss minimization in renewable distribution grids through mutual-interest approach

High penetration of distributed energy resources (DERs) motivates coordination mechanisms that reconcile individually preferred operation with mutual-interest performance in microgrids. Achieving mutual-interest objectives remains challenging due to the need for fair treatment of network-related responsibility. One of the most crucial mutual-interests of the power grids is network loss. Hence, proposing effective mechanisms that encourage loss reduction, and explicit representation of heterogeneous owner preferences in a fair manner is of vital importance. This paper develops a comfort-based market-clearing framework in which each DER owner is characterized by a monetary comfort value ($/MWh) that quantifies how strongly the owner weights the mutual-interest objective (network loss minimization) relative to their preferred operating schedule, while ensuring that all participants’ comfort preferences are satisfied. The main novelty is twofold: (i) embedding owner-specific comfort into the loss-related payment component so that loss responsibility becomes preference-aware across DERs, and (ii) solving the resulting comfort-based, network-constrained market-clearing problem in a decentralized manner to preserve privacy and enable scalability. Simulations on the IEEE 30-bus distribution test system demonstrate that the proposed framework reduces total network losses and improves voltage profiles, and illustrates how comfort values tune the trade-off between mutual-interest performance and individual operating preferences.

Authors

Publication Details

Journal
Applied Energy
Published
2026-04-07
DOI
https://doi.org/10.1016/j.apenergy.2026.127826
Primary Topic
Optimal Power Flow Distribution
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Chance-constrained comfort-centric loss minimization in renewable distribution grids through mutual-interest approach

Jamshid Aghaei, Reza Zamani, Mehran Moradi, Saeed Nasiri et al.
Applied Energy
Optimal Power Flow Distribution
article

Chance-constrained comfort-centric loss minimization in renewable distribution grids through mutual-interest approach

Jamshid Aghaei, Reza Zamani, Mehran Moradi, Saeed Nasiri, Mohammad Kazem Sheikh-El-Eslami
article en

Abstract

High penetration of distributed energy resources (DERs) motivates coordination mechanisms that reconcile individually preferred operation with mutual-interest performance in microgrids. Achieving mutual-interest objectives remains challenging due to the need for fair treatment of network-related responsibility. One of the most crucial mutual-interests of the power grids is network loss. Hence, proposing effective mechanisms that encourage loss reduction, and explicit representation of heterogeneous owner preferences in a fair manner is of vital importance. This paper develops a comfort-based market-clearing framework in which each DER owner is characterized by a monetary comfort value ($/MWh) that quantifies how strongly the owner weights the mutual-interest objective (network loss minimization) relative to their preferred operating schedule, while ensuring that all participants’ comfort preferences are satisfied. The main novelty is twofold: (i) embedding owner-specific comfort into the loss-related payment component so that loss responsibility becomes preference-aware across DERs, and (ii) solving the resulting comfort-based, network-constrained market-clearing problem in a decentralized manner to preserve privacy and enable scalability. Simulations on the IEEE 30-bus distribution test system demonstrate that the proposed framework reduces total network losses and improves voltage profiles, and illustrates how comfort values tune the trade-off between mutual-interest performance and individual operating preferences.

Applied EnergyVol. 414
Affordable and clean energy
Openalex Percentile: Top 27%
Optimal Power Flow Distribution
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.