Smart assessment of the unified power system efficiency in the context of smart grid: an ideal point–based multi-criteria method

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Authors: Iryna Bashynska, Viktoriia Kryvda, Vladyslav Suvorov, Liubov Niekrasova, Maksym Maksymov, Oleksii M. Maksymov
Cited by: 1
References: 14

Abstract

• Proposes a parameter-convolution method integrating supply volume, quality, and efficiency. • Uses an ideal-point distance (L1) to yield an interpretable, robust UPS efficiency indicator. • Detects real deficits/surpluses and frequency deviations on a daily schedule (±2.1–2.9%). • Interval I shows a 5.162 MVA·h deficit requiring 10% borrowing—evidence of economic inefficiency. • Provides policy-ready signals to target demand response, voltage control, and Smart Grid upgrades. This article proposes a unified approach for assessing the operational efficiency of a Unified Power System (UPS) within the evolving Smart Grid environment. The method is based on an ideal-point evaluation framework that integrates the analysis of electricity supply volume, quality, and efficiency into a single generalized performance criterion. Instead of the previously used parameter convolution, the study employs a weighted L 1 norm–based distance to the ideal point, ensuring mathematical rigor and comparability with modern multi-criteria optimization techniques. The approach enables a comprehensive assessment of key performance indicators, including supply reliability, voltage stability, and consumption efficiency. The paper also provides numerical examples that illustrate the applicability of the proposed model and demonstrate its sensitivity to system-level parameters. The results confirm that the developed method can support decision-making for enhancing UPS operational efficiency and guiding Smart Grid modernization toward sustainable and resilient energy development.

Fields of Study & Subjects

Smart Grid Energy Management Power System Reliability and Maintenance Electric Power System Optimization

Publication details

Journal / source
International Journal of Electrical Power & Energy Systems
Publisher
Elsevier BV
Volume
175
Pages
111644–111644
Publication date
1 February 2026
Language
EN