An Optimal Scenario-Based Scheduling Method for an SOP-included Active Distribution Network Considering Uncertainty of Load and Renewable Generations

Abstract

The high penetration of renewable Distributed Generators (DGs) in the Active Distribution Network (ADN) in addition to its advantages brings great challenges for the ADN, due to their intermittent and uncertain generations. Increasing network flexibility using Soft Open Points (SOPs) is an effective solution to overcome these challenges. However, an SOP-based ADN may contain various renewable or Controllable DGs (CDGs), and autonomous interconnected Microgrids (MGs). Accordingly, the uncertainty of load and renewable generation makes its scheduling more complex. In this paper, a novel optimal scenario-based framework is proposed to schedule an SOP-included ADN with multi-interconnected microgrids, based on the forecasted scenarios of demand and renewable DGs generation. In the proposed framework, all technical constraints, such as AC load flow equations, SOP's operational limitations, and DG's production range, are modeled in a Second-Order Cone (SOC) programming format. The energy transaction between the ADN and the other agents, i.e., MGs, and Upstream Network (UN) is also considered. This model can be optimally solved in an acceptable time. To show the effectiveness of the proposed method, it is implemented on the IEEE 33-bus distribution network. The simulation results confirm its high accuracy and speed.