Comparison of distributed and Centralized control for partial shading in PV parallel based on Particle Swarm Optimization Algorithm

Jumpasri, Nattawat; Pinsuntia, Kittapas; Woranetsuttikul, Kaweepoj; Nilsakorn, Taywin; Khan-ngern, W.

doi:10.1109/ieecon.2014.6925921

Cited by 4 publications

(1 citation statement)

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“…Early distributed optimization problems were mainly solved by centralized optimization algorithms. The feature of a centralized optimization algorithm is that all agents have a central node that centrally stores all of the information to address the optimization problem [12,13]. However, centralized optimization algorithms are unsuitable for large-scale networks, because collecting information from all agents in the network requires a lot of communication and computational overhead, and there will be the single point of failure problem.…”

Section: Introductionmentioning

confidence: 99%

Distributed Optimization for Resource Allocation Problem with Dynamic Event-Triggered Strategy

Guo

Chen

Ming

et al. 2023

Entropy

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This study aims to unravel the resource allocation problem (RAP) by using a consensus-based distributed optimization algorithm under dynamic event-triggered (DET) strategies. Firstly, based on the multi-agent consensus approach, a novel one-to-all DET strategy is presented to solve the RAP. Secondly, the proposed one-to-all DET strategy is extended to a one-to-one DET strategy, where each agent transmits its state asynchronously to its neighbors. Furthermore, it is proven that the proposed two types of DET strategies do not have Zeno behavior. Finally, numerical simulations are provided to validate and illustrate the effectiveness of the theoretical results.

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Section: Introductionmentioning

confidence: 99%