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Mathematics
Volume 13
Issue 24
10.3390/math13243964
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This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

Adaptive Iterative Algorithm for Optimizing the Load Profile of Charging Stations with Restrictions on the State of Charge of the Battery of Mining Dump Trucks

by
Nikita V. Martyushev
1,*,
Boris V. Malozyomov
2,
Vitaliy A. Gladkikh
3,
Anton Y. Demin
1,
Alexander V. Pogrebnoy
1,
Elizaveta E. Kuleshova
1 and
Yulia I. Karlina
3
1
Department of Information Technology, Tomsk Polytechnic University, 634050 Tomsk, Russia
2
Department of Electrotechnical Complexes, Novosibirsk State Technical University, 630073 Novosibirsk, Russia
3
Scientific Research and Testing Center “Stroytest”, Moscow State University of Civil Engineering, 129337 Moscow, Russia
*
Author to whom correspondence should be addressed.
Mathematics 2025, 13(24), 3964; https://doi.org/10.3390/math13243964
Submission received: 13 November 2025 / Revised: 8 December 2025 / Accepted: 9 December 2025 / Published: 12 December 2025
(This article belongs to the Special Issue Intelligent Optimization and Control Modeling in Power and Energy System)
Versions Notes

Abstract

The development of electric quarry transport puts a significant strain on local power grids, leading to sharp peaks in consumption and degradation of power quality. Existing methods of peak smoothing, such as generation control, virtual power plants, or intelligent load management, have limited efficiency under the conditions of stochastic and high-power load profiles of industrial charging stations. A new strategy for direct charge and discharge management of a system for integrated battery energy storage (IBES) is based on dynamic iterative adjustment of load boundaries. The mathematical apparatus of the method includes the formalization of an optimization problem with constraints, which is solved using a nonlinear iterative filter with feedback. The key elements are adaptive algorithms that minimize the network power dispersion functionality (i.e., the variance of Pgrid(t) over the considered time interval) while respecting the constraints on the state of charge (SOC) and battery power. Numerical simulations and experimental studies demonstrate a 15 to 30% reduction in power dispersion compared to traditional constant power control methods. The results confirm the effectiveness of the proposed approach for optimizing energy consumption and increasing the stability of local power grids of quarry enterprises.
Keywords: optimal control; mathematical modeling; load peak smoothing; integrated battery energy storage system; dynamic optimization; iterative algorithms; nonlinear filtering; constrained problem; real-time control; adaptive systems; numerical methods optimal control; mathematical modeling; load peak smoothing; integrated battery energy storage system; dynamic optimization; iterative algorithms; nonlinear filtering; constrained problem; real-time control; adaptive systems; numerical methods

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MDPI and ACS Style

Martyushev, N.V.; Malozyomov, B.V.; Gladkikh, V.A.; Demin, A.Y.; Pogrebnoy, A.V.; Kuleshova, E.E.; Karlina, Y.I. Adaptive Iterative Algorithm for Optimizing the Load Profile of Charging Stations with Restrictions on the State of Charge of the Battery of Mining Dump Trucks. Mathematics 2025, 13, 3964. https://doi.org/10.3390/math13243964

AMA Style

Martyushev NV, Malozyomov BV, Gladkikh VA, Demin AY, Pogrebnoy AV, Kuleshova EE, Karlina YI. Adaptive Iterative Algorithm for Optimizing the Load Profile of Charging Stations with Restrictions on the State of Charge of the Battery of Mining Dump Trucks. Mathematics. 2025; 13(24):3964. https://doi.org/10.3390/math13243964

Chicago/Turabian Style

Martyushev, Nikita V., Boris V. Malozyomov, Vitaliy A. Gladkikh, Anton Y. Demin, Alexander V. Pogrebnoy, Elizaveta E. Kuleshova, and Yulia I. Karlina. 2025. "Adaptive Iterative Algorithm for Optimizing the Load Profile of Charging Stations with Restrictions on the State of Charge of the Battery of Mining Dump Trucks" Mathematics 13, no. 24: 3964. https://doi.org/10.3390/math13243964

APA Style

Martyushev, N. V., Malozyomov, B. V., Gladkikh, V. A., Demin, A. Y., Pogrebnoy, A. V., Kuleshova, E. E., & Karlina, Y. I. (2025). Adaptive Iterative Algorithm for Optimizing the Load Profile of Charging Stations with Restrictions on the State of Charge of the Battery of Mining Dump Trucks. Mathematics, 13(24), 3964. https://doi.org/10.3390/math13243964

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