Dynamics Power Quality Cost Assessment Based on a Gradient Descent Method

Abstract

The escalating demand for power load is increasingly prone to triggering power quality (PQ) issues, leading to severe economic losses. Aiming at reducing the economic losses, this paper focuses on the coordinated relationship between PQ and economic costs. Firstly, a multilayer multiple linear stepwise regression method is employed to screen PQ indicators, identifying harmonic and voltage deviation as the primary influencing factors of PQ. Secondly, a gradient descent optimization algorithm based on the Least Absolute Shrinkage and Selection Operator (LASSO) is proposed, enabling rapid computation of the minimum PQ cost. Finally, through validations of two case studies, the results confirm that the proposed method can rapidly calculate the minimum PQ cost based on real-time load demands, enabling the dynamic adjustment of PQ cost to meet the evolving needs of power system development.

Comprehensive Power Quality Assessment Based on a Data-Driven Determinant-Valued Extension Hierarchical Analysis Approach

“…Each evaluation index in the system should be in line with the objective facts of power quality, and at the same time, the computational complexity and time should be considered. Considering the above factors, the assessment system in this study selects five main power quality indicators and constructs a data-driven power quality assessment system based on them, and Figure 1 shows the framework of the assessment system [24].…”