Optimal Energy Scheduling of Load Demand with Two-Level Multi-objective Functions in Smart Electrical Grid

• Published in: Operations Research Forum Vol. 6; no. 2; p. 66
• Main Authors: Du, T. X., Jorshary, Kamilia Mehrabi, Seyedrezaei, Mirali, Uglu, Valisher Sapayev Odilbek
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 01.06.2025; Springer Nature B.V
• Subjects: Alternative energy; Applications of Mathematics; Brief Report; Business and Management; Consumers; Cost control; Demand; Demand side management; Electricity; Energy consumption; Energy management; Linear programming; Load shifting; Math Applications in Computer Science; Mathematical and Computational Engineering; Multidimensional methods; Multiple objective analysis; Operating costs; Operations Research/Decision Theory; Optimization; Optimization algorithms; Prices; Reliability; Scheduling; Smart grid; Topical Collection on Quantitative Methods for Sustainable Engineering and Environmental Management; Power prices; Demand management approaches; Multi-level optimization approach; Multi-objective functions
• ISSN: 2662-2556; 2662-2556
• DOI: 10.1007/s43069-025-00462-9

In this paper, electrical grid scheduling with hybrid demand management via a multi-level optimization approach is implemented. At the upper level, demand management approaches are implemented, and at the lower level, multi-objective functions are optimized. The implementation of demand management approaches, including load shifting and interruption approaches, is carried out. These approaches are optimized subject to power prices in the upstream grid. The multi-objectives like reliability index and operation costs are optimized subject to demand management approaches at the upper level. By using the linear programming technique for the multidimensional analysis of preference (LINMAP) and fuzzy methods, the optimal solution in Pareto solutions for multi-objectives is selected. The performance of the approach is analyzed on the 69-bus network by employing power scheduling and integrating results from mathematical modeling through several case studies. With the implementation of the demand management approaches in optimal power consumption, the reliability index is improved by 0.6% and operating costs are minimized by 2.43% compared to the lack of demand management.