A Cloud-edge Cooperative Dispatching Method for Distribution Networks Considering Photovoltaic Generation Uncertainty

With the increasing penetration of renewable energy generation, uncertainty and randomness pose great challenges for optimal dispatching in distribution networks. We propose a cloud-edge cooperative dispatching (CECD) method to exploit the new opportunities offered by Internet of Things (IoT) technology. To alleviate the huge pressure on the modeling and computing of large-scale distribution system, the method deploys edge nodes in small-scale transformer areas in which robust optimization subproblem models are introduced to address the photovoltaic (PV) uncertainty. Considering the limited communication and computing capabilities of the edge nodes, the cloud center in the distribution automation system (DAS) establishes a utility grid master problem model that enforces the consistency between the solution at each edge node with the utility grid based on the alternating direction method of multipliers (AD-MM). Furthermore, the voltage constraint derived from the linear power flow equations is adopted for enhancing the operation security of the distribution network. We perform a cloud-edge system simulation of the proposed CECD method and demonstrate a dispatching application. The case study is carried out on a modified 33-node system to verify the remarkable performance of the proposed model and method.