Practical Day‐Ahead Gas Generator Dispatch Optimisation for Enhancing the Reserved Capacity

ABSTRACT In order to reduce carbon dioxide emissions, traditional coal‐fired power generation has been strictly limited in China recently, which has led to the problem of reserved capacity shortage. As one of the critical east provinces of China, Zhejiang province also suffers from the shortage of reserved capacity, whereas gas power generation is commonly utilised to mitigate this problem. However, the gas generator dispatch plan is still made manually at the current stage, which is quite time‐consuming and has the space to optimise. Therefore, this paper first proposes a practical day‐ahead gas generator dispatch optimisation (GGDO) model to maximise the daily minimum reserve capacity. Besides, several constraints related to the system operation and natural gas limitations are given. Finally, the data of three typical days in Zhejiang province are employed for demonstration, which shows the strength of the proposed GGDO model.

Authors

Institutions

Publication Details

Journal
IET Smart Energy Systems
Published
2026-04-11
DOI
https://doi.org/10.1049/ses2.70026
Primary Topic
Integrated Energy Systems Optimization
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Practical Day‐Ahead Gas Generator Dispatch Optimisation for Enhancing the Reserved Capacity

Shengyuan Liu, Bin Feng, W. K. Sun, Yicheng Jiang et al.
IET Smart Energy Systems
Integrated Energy Systems Optimization
article

Practical Day‐Ahead Gas Generator Dispatch Optimisation for Enhancing the Reserved Capacity

Shengyuan Liu, Bin Feng, W. K. Sun, Yicheng Jiang, Gang Huang, Wei Gu, Yunchu Wang
article en

Abstract

ABSTRACT In order to reduce carbon dioxide emissions, traditional coal‐fired power generation has been strictly limited in China recently, which has led to the problem of reserved capacity shortage. As one of the critical east provinces of China, Zhejiang province also suffers from the shortage of reserved capacity, whereas gas power generation is commonly utilised to mitigate this problem. However, the gas generator dispatch plan is still made manually at the current stage, which is quite time‐consuming and has the space to optimise. Therefore, this paper first proposes a practical day‐ahead gas generator dispatch optimisation (GGDO) model to maximise the daily minimum reserve capacity. Besides, several constraints related to the system operation and natural gas limitations are given. Finally, the data of three typical days in Zhejiang province are employed for demonstration, which shows the strength of the proposed GGDO model.

IET Smart Energy Systems
State Grid Corporation of China (China) (CN), Shanghai Electric (China) (CN), Zhejiang University (CN)
Openalex Percentile: Top 21%
Integrated Energy Systems Optimization
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.