An Intelligent Source-Network-Load-Storage Configuration Method Based on Moth-Flame Optimization

The source-network-load-storage configuration of large-scale power systems plays an important role in the stability and efficiency of new power systems. Apply the Analytical Hierarchy Process to find a goal function with indices including the consumption amount of new energy, the proportion of annual consumption of new energy, the comprehensive utilization rate of new energy, the construction investment, and the emission of carbon, etc. Then use Moth-Flame Optimization to optimize the configuration. Compared to the conventional calculation method, Moth-Flame Optimization achieves the production simulation of source-network-load-storage integration and has a relatively high comprehensiveness of indices. Meanwhile, it can avoid the inconvenience of conventional methods, accelerate the solving speed, and improve the accuracy of the calculation results.

Authors

Publication Details

Published
2024-11-01
DOI
https://doi.org/10.1109/icei63732.2024.10917250
Citations
1
Primary Topic
Distributed and Parallel Computing Systems
Type
article
Field-Weighted Citation Impact
0.35
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

An Intelligent Source-Network-Load-Storage Configuration Method Based on Moth-Flame Optimization

Chuan Tong, Ran Duan, Liwei Zhang, Chao Gao et al.
1 citations
Distributed and Parallel Computing Systems
0.35
article

An Intelligent Source-Network-Load-Storage Configuration Method Based on Moth-Flame Optimization

Chuan Tong, Ran Duan, Liwei Zhang, Chao Gao, Te Li, Yan Liu, Litao Shi
article en
1 citations

Abstract

The source-network-load-storage configuration of large-scale power systems plays an important role in the stability and efficiency of new power systems. Apply the Analytical Hierarchy Process to find a goal function with indices including the consumption amount of new energy, the proportion of annual consumption of new energy, the comprehensive utilization rate of new energy, the construction investment, and the emission of carbon, etc. Then use Moth-Flame Optimization to optimize the configuration. Compared to the conventional calculation method, Moth-Flame Optimization achieves the production simulation of source-network-load-storage integration and has a relatively high comprehensiveness of indices. Meanwhile, it can avoid the inconvenience of conventional methods, accelerate the solving speed, and improve the accuracy of the calculation results.

Affordable and clean energy
Openalex Percentile: Top 33%
Distributed and Parallel Computing Systems
0.35
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.

An Intelligent Source-Network-Load-Storage Configuration Method Based on Moth-Flame Optimization — Chuan Tong, Ran Duan, et al. · (2024) | TGRS Research Map | TGRS