A Robust Unit Combination Model For Multi-Resource Backup Coordination Optimization Of Source, Network And Storage Is Considered

The purpose of this study is to address the impact of the high proportion of new energy applications on the operation of traditional power grids and energy storage equipment, a robust unit combination model considering the multi-resource reserve coordination optimization of source-grid-load-storage is proposed. Firstly, the model to which the article belongs is based on the extraction of the characteristics of wind power generation prediction deviation from a time perspective. At the same time, quantile theory is applied to fit the numerical range of wind power generation prediction deviation based on the time perspective, which can better clarify the instability of wind power generation output. Secondly, considering the operational characteristics and reserve capabilities of various resources in the systems source-grid-load-storage, This article takes the daily running period as a case model and improves the robustness of the model through two stages, output, and reserve capacity coordination of all types of resources. This model employs nested column generation algorithms with constraints to solve the problem. Case studies have confirmed the effectiveness and advancement of this model in enhancing system operational flexibility and promoting the consumption of renewable energy, providing practical references and theoretical support for the determination of unit combination and reserve capacity schemes in new power systems under large scale consolidation of new energy.

Authors

Institutions

Publication Details

Published
2025-03-07
DOI
https://doi.org/10.1109/csnt64827.2025.10968504
Primary Topic
Distributed and Parallel Computing Systems
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Robust Unit Combination Model For Multi-Resource Backup Coordination Optimization Of Source, Network And Storage Is Considered

Peng Shu, Yahui Hou, Pan Guo, Yanyan Xu et al.
Distributed and Parallel Computing Systems
article

A Robust Unit Combination Model For Multi-Resource Backup Coordination Optimization Of Source, Network And Storage Is Considered

Peng Shu, Yahui Hou, Pan Guo, Yanyan Xu, Shutao Zhang
article en

Abstract

The purpose of this study is to address the impact of the high proportion of new energy applications on the operation of traditional power grids and energy storage equipment, a robust unit combination model considering the multi-resource reserve coordination optimization of source-grid-load-storage is proposed. Firstly, the model to which the article belongs is based on the extraction of the characteristics of wind power generation prediction deviation from a time perspective. At the same time, quantile theory is applied to fit the numerical range of wind power generation prediction deviation based on the time perspective, which can better clarify the instability of wind power generation output. Secondly, considering the operational characteristics and reserve capabilities of various resources in the systems source-grid-load-storage, This article takes the daily running period as a case model and improves the robustness of the model through two stages, output, and reserve capacity coordination of all types of resources. This model employs nested column generation algorithms with constraints to solve the problem. Case studies have confirmed the effectiveness and advancement of this model in enhancing system operational flexibility and promoting the consumption of renewable energy, providing practical references and theoretical support for the determination of unit combination and reserve capacity schemes in new power systems under large scale consolidation of new energy.

Tebian Electric Apparatus (China) (CN), Xinjiang New Energy Research Institute (China) (CN)
Research and Development
Openalex Percentile: Top 92%
Distributed and Parallel Computing Systems
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.