Demand Side Management for Enhanced Grid Stability based on Model Predictive Control

In order to enhance grid stability and improve energy utilization efficiency, it is essential to explore effective demand side management strategies. This paper focuses on minimizing peak load fluctuations and improving the flexibility of power systems by considering the dynamic characteristics of userside loads. Model predictive control (MPC) is employed to design a real-time demand response framework. The main contributions are as follows: A typical demand side management model is constructed, incorporating controllable loads, user behavior models. A model predictive control-based optimization strategy is proposed, and the objective function and constraints are formulated. Finally, a case study was conducted based on the park scenario to validate the effectiveness of the proposed method.

Authors

Institutions

Publication Details

Published
2025-08-22
DOI
https://doi.org/10.1109/pges66344.2025.11193633
Primary Topic
Power Systems and Renewable Energy
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Demand Side Management for Enhanced Grid Stability based on Model Predictive Control

Yuhang Sun, Xun Suo, Caixia Hu, Zhukui Tan et al.
Power Systems and Renewable Energy
article

Demand Side Management for Enhanced Grid Stability based on Model Predictive Control

Yuhang Sun, Xun Suo, Caixia Hu, Zhukui Tan, Bin Liu
article en

Abstract

In order to enhance grid stability and improve energy utilization efficiency, it is essential to explore effective demand side management strategies. This paper focuses on minimizing peak load fluctuations and improving the flexibility of power systems by considering the dynamic characteristics of userside loads. Model predictive control (MPC) is employed to design a real-time demand response framework. The main contributions are as follows: A typical demand side management model is constructed, incorporating controllable loads, user behavior models. A model predictive control-based optimization strategy is proposed, and the objective function and constraints are formulated. Finally, a case study was conducted based on the park scenario to validate the effectiveness of the proposed method.

Guizhou Electric Power Design and Research Institute (CN), Guizhou Institute of Technology (CN), Zhejiang University (CN)
Openalex Percentile: Top 67%
Power Systems and Renewable Energy
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.