A Novel GAN Architecture Reconstructed Using Bi-LSTM and Style Transfer for PV Temporal Dynamics Simulation
Xueqian Fu, Chunyu Zhang, Xiurong Zhang, Hongbin Sun
Abstract
The stochastic production simulation of photovoltaic (PV) power is crucial for the analysis of power balance in power planning, annual or monthly operational planning, and long-term transactions in the electricity market, especially in power systems with a high share of PVs. To model the uncertainty and temporal characteristics inherent in PV power, this letter introduces the style transfer and innovatively establishes bi-directional long short-term memory generative adversarial networks (GAN). Simulation results confirm the advantages of the proposed GAN over traditional convolutional neural network-based GANs in simulating the diversity and temporal characteristics of PV power.
Topics & Concepts
Dynamics (music)ArchitectureComputer scienceTransfer (computing)Style (visual arts)Artificial intelligenceComputer architectureParallel computingPhysicsVisual artsArtAcousticsHistoryArchaeologyPower Systems and Renewable EnergyPhotovoltaic System Optimization TechniquesSolar Radiation and Photovoltaics