Low-carbon generation expansion planning considering uncertainty of renewable energy at multi-time scales

With the development of carbon electricity, achieving a low-carbon economy has become prevailing and inevitable trend. Improving expansion generation planning is critical for emission mitigation low- economy. In this paper, two-layer approach considering uncertainty renewable energy at multiple time scales proposed. First, sequences in are generated based on Copula function probability distribution energy. Second, model trading capture technology established. Specifically, upper layer optimizes investment decision monthly scale, lower one scheduling peak shaving an hourly scale flexibility 15-minute scale. Finally, results different influence factors compared provincial power grid, which demonstrate effectiveness proposed model.