A Methodology for Building Generation Trajectories to Balance Continuous-Time Load Profiles

In power systems, maintaining a balance between generation and load is crucial. Traditional discrete-time dispatch methods often fall short, as they do not account for continuous-time changes in the load profiles throughout the time span. This oversight can lead to inaccuracies in tracing load profiles and even cause ramping resource shortages. In this paper, we propose the idea of continuous-time generation trajectories as dispatch results, to align with continuous-time load profiles. To ensure the solvability of the continuous-time dispatch, we propose an iterative dispatch methodology, which includes two stages: trajectory construction and constraint verification. In the trajectory construction stage, we use a parametric programming model to divide the continuous-time load profiles into multiple segments. Subsequently, we build the generation trajectories for each segment using parametric solutions. In the constraint verification stage, we specifically check the continuous-time ramping constraints. This stage identifies the infeasible trajectories, which will be updated during the next iteration. We repeat this iterative process until each unit has a feasible continuous-time generation trajectory throughout the time span. The effectiveness of our methodology is demonstrated in an illustrative 5-bus system and an actual 661-bus system.

Authors

Institutions

Publication Details

Journal
IEEE Transactions on Power Systems
Published
2024-08-23
DOI
https://doi.org/10.1109/tpwrs.2024.3449078
Primary Topic
Vibration and Dynamic Analysis
Type
article
Field-Weighted Citation Impact
0.00

Funders

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

A Methodology for Building Generation Trajectories to Balance Continuous-Time Load Profiles

Mingxu Xiang, Yue Zhou, Zhifang Yang, Wenyuan Li et al.
IEEE Transactions on Power Systems
Vibration and Dynamic Analysis
article

A Methodology for Building Generation Trajectories to Balance Continuous-Time Load Profiles

Mingxu Xiang, Yue Zhou, Zhifang Yang, Wenyuan Li, Menghan Zhang, Juan Yu
article en

Abstract

In power systems, maintaining a balance between generation and load is crucial. Traditional discrete-time dispatch methods often fall short, as they do not account for continuous-time changes in the load profiles throughout the time span. This oversight can lead to inaccuracies in tracing load profiles and even cause ramping resource shortages. In this paper, we propose the idea of continuous-time generation trajectories as dispatch results, to align with continuous-time load profiles. To ensure the solvability of the continuous-time dispatch, we propose an iterative dispatch methodology, which includes two stages: trajectory construction and constraint verification. In the trajectory construction stage, we use a parametric programming model to divide the continuous-time load profiles into multiple segments. Subsequently, we build the generation trajectories for each segment using parametric solutions. In the constraint verification stage, we specifically check the continuous-time ramping constraints. This stage identifies the infeasible trajectories, which will be updated during the next iteration. We repeat this iterative process until each unit has a feasible continuous-time generation trajectory throughout the time span. The effectiveness of our methodology is demonstrated in an illustrative 5-bus system and an actual 661-bus system.

IEEE Transactions on Power SystemsVol. 40(2)
Chongqing University (CN), Cardiff University (GB)
National Natural Science Foundation of China
Openalex Percentile: Top 85%
Vibration and Dynamic Analysis
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.