Cooperative planning of renewable energy generation and multi-timescale flexible resources in active distribution networks

Large-scale integration of distributed renewable power sources into active distribution networks (ADNs) brings uncontrollability, randomness and volatility to the system. Configuring flexible resources with different response rates provides an effective way to improve power supply reliability and renewable consumption. To this end, a novel bi-level cooperative planning model targeted at renewable energy generations (REGs) and multi-timescale flexible resources (MTFRs) is proposed for ADNs, where the upper level aims to seek the optimal installation sizes, sites, and types of REGs and MTFRs by minimizing the annualized investment and operating costs, the lower level optimizes the operation strategy by regulating the flexible resources on different timescales. Furthermore, a model-free scenario generation method is introduced, which fully captures the characteristics of renewable energy output without relying on complicated explicit feature modeling. In the solution phase, the second-order cone relaxation is implemented to convert the original nonconvex nonlinear model into a readily solvable mixed-integer second-order cone programming formulation, which is finally solved using the CPLEX solver. Based on the simulation results on the PG&E 69-node distribution system, the proposed approach demonstrates superior performances in terms of renewable consumption, economy and voltage profile when compared to single timescale planning and individual planning approaches.