一种多阶段DRO-SDDP方法用于高渗透率可再生能源电力系统中多类型储能与柔性资源规划

With the widespread integration of renewable energy (RE) into the power systems, the inherent fluctuations of renewable energy present formidable challenges to the temporal and spatial power and energy balances. Load-side flexible resources (FRs), along with battery energy storage systems (ESSs), can make significant contribution to balance the intra-day power generation and load demand. On the other hand, ESSs with longer discharging duration like pumped hydro storage and hydrogen storage, compressed air energy storage, can balance inter-day and even inter-month power supply and demand. To consider the complementary characteristics of multiple FRs and ESSs in the planning stage, firstly a joint planning model is built. Considering that the uncertain information reveals stage by stage after the periodical decision-making process, the planning model is formulated as a multi-stage stochastic programming problem (MSSP), where decisions are made sequentially based solely on the information available at the present stage. Subsequently, to deal with the uncertainties across multiple stages, a distributionally robust stochastic dual dynamic programming (DRO-SDDP) approach is employed to solve the proposed model. To accelerate the algorithm, dynamic sampling, dynamic cut generation and parallel computing are adopted. Finally, simulations and sensitivity analyses are conducted on the modified HRP-38 system. Simulation results verify the effectiveness of the proposed method.