Joint planning and hierarchical optimization method of wind photovoltaic storage based on decomposition coordination

Abstract

The joint planning of wind photovoltaic storage can fully consider the characteristics of renewable energy resources, and the planning results are more scientific in a global perspective. In this paper, the medium-term and long-term time-series power balance is considered for joint planning of wind photovoltaic storage, and the planning results are more reasonable and reliable. The multi-region wind photovoltaic storage joint planning problem is essentially a high-dimensional complex stochastic planning problem with wide area multiple power sources, multiple variables and multiple time sections, which is very time-consuming to solve and even impossible to solve due to dimensional disasters. Based on this, a multi-region wind photovoltaic storage joint planning model is established, and a hierarchical optimization algorithm is proposed based on regional decomposition coordination in this paper, which decomposes the multi-region wind photovoltaic storage joint planning model into a two-layer problem. The configuration capacity of power sources and energy storage in each sub-region is determined in the lower-layer problem. The power sources in each sub-region are determined in the upper-layer problem according to the capacity planning scheme given by the lower-level problem operation. The two layers iterate with each other to coordinate and obtain the optimal capacity of wind photovoltaic storage in each region. Finally, the rationality and effectiveness of the proposed model and method are verified by the arithmetic case analysis.

Keywords

• renewable energy
• energy storage
• generation planning
• lagrangian relaxation
• decomposition coordination
• capacity allocation