Distributed Model Predictive Load Frequency Control for Virtual Power Plants with Novel Event-Based Low-Delay Technique Under Cloud-Edge-Terminal Framework

Kai Kang, Nian Shi, Si Cai, Liang Zhang, Xinan Shao, Haohao Cao, Mingjin Fei, Shisen Zhou and Xiongbo Wan ()
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Kai Kang: PowerChina Hubei Engineering Co., Ltd., Wuhan 430040, China
Nian Shi: PowerChina Hubei Electric Engineering Co., Ltd., Wuhan 430040, China
Si Cai: PowerChina Hubei Electric Engineering Co., Ltd., Wuhan 430040, China
Liang Zhang: PowerChina Hubei Electric Engineering Co., Ltd., Wuhan 430040, China
Xinan Shao: PowerChina Hubei Electric Engineering Co., Ltd., Wuhan 430040, China
Haohao Cao: PowerChina Hubei Electric Engineering Co., Ltd., Wuhan 430040, China
Mingjin Fei: PowerChina Hubei Electric Engineering Co., Ltd., Wuhan 430040, China
Shisen Zhou: School of Automation, China University of Geosciences, Wuhan 430074, China
Xiongbo Wan: School of Automation, China University of Geosciences, Wuhan 430074, China

Energies, 2025, vol. 18, issue 6, 1-18

Abstract: In this paper, the distributed model predictive load frequency control problem for virtual power plants (VPPs) under the cloud-edge-terminal framework is addressed, where the data packets are transmitted under a novel dynamic event-triggered mechanism (DETM) with hybrid variables. The proposed DETM has the ability to flexibly manage packet releases and reduce network congestion, thus decreasing the communication delay of the VPP. A method of the DETM-based distributed model predictive control (DMPC) is proposed, which can shorten the data processing time and further decrease the communication delay. The DMPC problem is described as a “min-max” optimization problem (OP) with hard constraints on the system state. By utilizing a Lyapunov function with an internal dynamic variable, an auxiliary OP with matrix inequalities constraints is proposed to optimize the controller gain and the weighting matrix of the DETM. The effectiveness and superiority of the designed DETM and dynamic event-based DMPC algorithm are demonstrated through a case study on two-area VPPs.

Keywords: load frequency control; dynamic event-triggered mechanism; distributed model predictive control; cloud-edge-terminal; virtual power plant (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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