Communication Delay based Response Control Method for Grid Dispatch in Virtual Power Plants

To address the issue of low reliability in Virtual Power Plants participating in rapid Grid dispatch operations, this paper proposes a communication delay based response control method. The proposed method use the end-to-end communication delay as a constraint for the Predictive Control scheduling model for VPPs, where the communication delay is predicted through the Long Short-Term Memory method and an improved Particle Swarm Optimization algorithm is then used. During the scheduling process, a confidence parameter <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\alpha$</tex> is introduced to control the strictness of the delay constraints. When the confidence parameter takes a small value, the performance of the proposed algorithm in terms of profit and reliability outperforms the traditional VPP algorithms. As the confidence parameter increases, the performance of the proposed algorithm will approach the traditional VPP algorithms. Therefore, the proposed method allows users to select an appropriate <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\alpha$</tex> to balance the profit and the reliability.

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Publication Details

Published
2024-11-22
DOI
https://doi.org/10.1109/sgee64306.2024.10865925
Primary Topic
Power Systems and Renewable Energy
Type
article
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article

Communication Delay based Response Control Method for Grid Dispatch in Virtual Power Plants

Wei Peng, Zhaohui Yang, Chuan Liu
Power Systems and Renewable Energy
article

Communication Delay based Response Control Method for Grid Dispatch in Virtual Power Plants

Wei Peng, Zhaohui Yang, Chuan Liu
article en

Abstract

To address the issue of low reliability in Virtual Power Plants participating in rapid Grid dispatch operations, this paper proposes a communication delay based response control method. The proposed method use the end-to-end communication delay as a constraint for the Predictive Control scheduling model for VPPs, where the communication delay is predicted through the Long Short-Term Memory method and an improved Particle Swarm Optimization algorithm is then used. During the scheduling process, a confidence parameter <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\alpha$</tex> is introduced to control the strictness of the delay constraints. When the confidence parameter takes a small value, the performance of the proposed algorithm in terms of profit and reliability outperforms the traditional VPP algorithms. As the confidence parameter increases, the performance of the proposed algorithm will approach the traditional VPP algorithms. Therefore, the proposed method allows users to select an appropriate <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\alpha$</tex> to balance the profit and the reliability.

State Grid Corporation of China (China) (CN), Huazhong University of Science and Technology (CN)
Affordable and clean energy
Openalex Percentile: Top 70%
Power Systems and Renewable Energy
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