Complementary Intelligent Optimization Operation Strategy of Wind-Solar-Hydro Multi-energy Power System

Abstract

For high-ratio renewable energy access to the grid, the utilization of wind-solar-hydro complementary power generation can provide a smooth and stable power supply. This paper proposed a short-term optimal operation method based on stochastic programming for the windsolar-hydro multi-energy power system, using big data and artificial intelligence technology. Firstly, based on the variational autoencoder (VAE), a renewable energy scenarios generation method was proposed, which can generate diverse scenarios that meet the characteristics of renewable energy output and accurately describe the correlation of renewable energy output. Secondly, based on the scenarios method, a short-term optimization operation model of wind-solar-hydro was established and a piecewise linearization method was used to transform various nonlinear constraints into linear constraints, which can achieve fast solution while ensuring the accuracy of the model. Finally, through the simulation of the wind-solarhydro power system in downstream of the Yalong River, it demonstrates the effectiveness of the intelligent optimization operation strategy proposed in this paper.

Keywords

• power system
• complementation of windsolar-hydro
• scenarios generation
• variational autoencoder
• optimal operation