Proceedings of the 2025 4th International Conference on Public Service, Economic Management and Sustainable Development (PESD 2025)

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Virtual Inertia Optimization of Wind Power System and Its Significance for Sustainable Development

Authors
Biyao Liu1, *
1School of International Education, Guangdong University of Technology, Guangdong, 510006, China
*Corresponding author. Email: lby6812025@163.com
Corresponding Author
Biyao Liu
Available Online 22 December 2025.
DOI
10.2991/978-94-6463-916-2_30How to use a DOI?
Keywords
Wind Power System; Virtual Inertia Optimization; Improved Deep Q Network; Particle Swarm Optimization
Abstract

A virtual inertia optimization framework based on improved deep Q network (DQN) is proposed to solve inertia attenuation and frequency instability problems caused by high proportion wind power grid integration. By integrating dynamic perception and decision-making mechanism of deep reinforcement learning, the model maps power grid state information (frequency deviation, inertia gap and tie-line power) into virtual inertia parameter adjustment instructions, and optimizes the training process by using competition architecture, L1 regularization and multi-level experience playback. simulation result show that that improved DQN algorithm has significant effect on the RMS value of frequency fluctuation (0.12 Hz, 42.9% lower than PSO, 36.8% lower than ACO), response time (0.86 seconds, 36.3%-43.4% increase) and absolute value of power fluctuation (0.08 pu) are significantly better than particle swarm optimization (PSO) and ant colony algorithm (ACO), especially in load mutation scenarios, showing stronger robustness and real-time adjustment ability, providing key technical support for stable operation of high permeability new energy grid.

Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2025 4th International Conference on Public Service, Economic Management and Sustainable Development (PESD 2025)
Series
Advances in Economics, Business and Management Research
Publication Date
22 December 2025
ISBN
978-94-6463-916-2
ISSN
2352-5428
DOI
10.2991/978-94-6463-916-2_30How to use a DOI?
Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Biyao Liu
PY  - 2025
DA  - 2025/12/22
TI  - Virtual Inertia Optimization of Wind Power System and Its Significance for Sustainable Development
BT  - Proceedings of the 2025 4th International Conference on Public Service, Economic Management and Sustainable Development (PESD 2025)
PB  - Atlantis Press
SP  - 258
EP  - 264
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-916-2_30
DO  - 10.2991/978-94-6463-916-2_30
ID  - Liu2025
ER  -