TensorConvolutionPlus: A python package for distribution system flexibility area estimation

TL;DR

TensorConvolutionPlus is an open-source Python package that enables power system operators and researchers to estimate distribution system flexibility areas using multiple algorithms, aiding in managing uncertainty and variable resources.

Contribution

The paper introduces TensorConvolutionPlus, the first open-source Python package for flexibility area estimation in distribution systems, integrating multiple algorithms and features for practical operational use.

Findings

Provides a user-friendly tool for flexibility estimation

Supports multiple algorithms including TensorConvolution+ and power flow-based methods

Facilitates adaptation to different operating conditions and flexibility providers

Abstract

Power system operators need new, efficient operational tools to use the flexibility of distributed resources and deal with the challenges of highly uncertain and variable power systems. Transmission system operators can consider the available flexibility in distribution systems (DSs) without breaching the DS constraints through flexibility areas. However, there is an absence of open-source packages for flexibility area estimation. This paper introduces TensorConvolutionPlus, a user-friendly Python-based package for flexibility area estimation. The main features of TensorConvolutionPlus include estimating flexibility areas using the TensorConvolution+ algorithm, the power flow-based algorithm, an exhaustive PF-based algorithm, and an optimal power flow-based algorithm. Additional features include adapting flexibility area estimations from different operating conditions and including flexibility service providers offering discrete setpoints of flexibility. The TensorConvolutionPlus package facilitates a broader adaptation of flexibility estimation algorithms by system operators and power system researchers.