Rolling Multi-Stage Stochastic Planning for Rural Distribution Networks Under Flexible Transformation Process of Distributed Photovoltaic

With the continuous increase in the grid-connected capacity of distributed photovoltaics in rural distribution networks, it has become extremely urgent to achieve the flexible transformation of distributed photovoltaics, enabling them to be measurable, adjustable, and controllable. Based on this backdrop, this paper proposes a rolling approximate dynamic programming (ADP) model for rural distribution networks under the process of distributed photovoltaic flexible transformation. Firstly, taking into account the process of distributed photovoltaic flexible transformation, based on the concept of “multi-stage planning and first-stage implementation”, a rolling multi-stage stochastic programming (MSSP) model for rural distribution networks is established. The MSSP model comprehensively considers various factors such as the construction progress of distributed photovoltaics and the dynamic changes in power demand in rural areas at different stages. Secondly, using the ADP algorithm based on the Markov decision process (MDP) as the core, a rolling ADP algorithm is developed. This algorithm can iteratively optimize the decision-making process in each stage, thereby realizing the rolling solution of the proposed planning model. Through this approach, the model can adapt to the changing scenarios in the process of rural distribution network planning and distributed photovoltaic development. Finally, the improved IEEE 33-bus typical system is employed to validate the proposed model and algorithm. The simulation results demonstrate that the proposed model can effectively address the challenges in the process of distributed photovoltaic flexible transformation in rural distribution networks. It can obtain an optimal configuration plan that not only offers better economic benefits but also exhibits a stronger ability to handle the continuously emerging long-term uncertainties.