Improved Inner Approximation for Aggregating Power Flexibility in Active Distribution Networks and Its Applications

Concise and reliable modeling for the aggregated power flexibility of distributed energy resources (DERs) in active distribution networks (ADNs) is essential for coordinating transmission and distribution networks. Inner approximated aggregation models are desirable for power system operators because they ensure a safe dispatchable range for the distribution network. However, previous inner approximation methods often rely on experience and intuition due to the absence of an explicit expression of the exact aggregation model (EAM), leading to accuracy and computational efficiency challenges. This paper proposes a novel inner approximation method to overcome these challenges, leveraging the properties of our recently derived closed-form EAM. Specifically, we divide the process of inner approximation methods into two steps: defining a geometric prototype and calculating its parameters. The first step is accomplished by selecting a subset of all the coefficient vectors forming the EAM so as to improve accuracy. When calculating parameters, on the other hand, we exploit the regularity of these coefficient vectors to improve the computational efficiency. The inner approximated flexibility model of ADNs is further incorporated into the security-constrained unit commitment problem as an application, which helps improve the system’s economic benefits. Numerical simulations verify the effectiveness of the proposed method.