Learning-Aided Optimal Power Flow Based Fast Total Transfer Capability Calculation

Ji’Ang Liu,Xiao Shao,Gao Qiu,Youbo Liu

doi:10.3390/en15041320

Abstract

Total transfer capability (TTC) is a vital security indicator for power exchange among areas. It characterizes time-variants and transient stability dynamics, and thus is challenging to evaluate efficiently, which can jeopardize operational safety. A leaning-aided optimal power flow method is proposed to handle the above challenges. At the outset, deep learning (DL) is utilized to globally establish real-time transient stability estimators in parametric space, such that the dimensionality of dynamic simulators can be reduced. The computationally intensive transient stability constraints in TTC calculation and their sensitivities are therewith converted into fast forward and backward processes. The DL-aided constrained model is finally solved by nonlinear programming. The numerical results on the modified IEEE 39-bus system demonstrate that the proposed method outperforms several model-based methods in accuracy and efficiency.

Highlights

Power systems are currently operated near their stability boundary with the significant proliferation of interconnected grids and renewable penetration [1]
The above studies show that LAM can speed up solving optimization problems. Because it is a data-mechanism hybrid-driven method rather than an utterly data-driven method, it performs better in terms of fidelity. By prioritizing both merits of physics- and data-driven modeling, this paper proposed a learning-aided optimal power flow based fast total transfer capability (TTC) calculation methods with the following features: Deep belief network (DBN) is advocated to surrogate computationally intensive and high-dimensional time-domain based transient stability modelling
M5 applies NNs to learn the mapping between system state variables and TTC values

Summary

Introduction

Power systems are currently operated near their stability boundary with the significant proliferation of interconnected grids and renewable penetration [1]. Total transfer capability (TTC), defined as maximum power exchange allowed to withstand multifarious security contingencies, is a widespread metric to quantify such a security margin. Limited by this issue, dispatchers generally use a conservative constant of offline TTC to decide online operations. Dispatchers generally use a conservative constant of offline TTC to decide online operations Such TTC values can incur the unwanted waste of line capacity and incorrect estimation to security margin. To untie these knots, the essence is to accelerate TTC calculation

Methods

Results

Conclusion