Distributed Economic Dispatch Algorithm With Quantized Communication Mechanism

doi:10.1109/TASE.2024.3487214

Distributed Economic Dispatch Algorithm With Quantized Communication Mechanism

2024-01-01

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DOI：10.1109/TASE.2024.3487214

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Due to the limited bandwidth and energy of communication channels among agents in practical applications, the communication-efficient distributed optimization method has emerged as a pressing research topic in recent years. The distributed economic dispatch problem with restricted data communication/finite communication bandwidth is investigated in this study, where the communication among agents can be described as a strongly connected directed network. For this purpose, a robust push-pull distributed optimization algorithm with a dynamic scaling quantization mechanism is developed based on the gradient tracking technique. A novel surplus variable is designed to prevent the accumulation of quantization errors, and then, a heavy-ball momentum is introduced to speed up convergence performance. In addition, a linear convergence rate of the developed approach is deduced for the strongly convex and Lipschitz smooth cost function. Finally, we offer two instances for illustration.

Keyword:

Convergence

Quantization (signal)

Heuristic algorithms

Cost function

Bandwidth

Costs

Smart grids

Optimization methods

Graph theory

Energy Internet

Distributed economic dispatch

gradient tracking

heavy-ball momentum

limited communication bandwidth

smart grid

Distributed Economic Dispatch Algorithm With Quantized Communication Mechanism

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