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
| Parent link: | Mathematics.— .— Basel: MDPI AG Vol. 13, iss. 24.— 2025.— Article number 3964, 13 p. |
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| מחברים אחרים: | , , , , , , |
| סיכום: | 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
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 Текстовый файл |
| שפה: | אנגלית |
| יצא לאור: |
2025
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| נושאים: | |
| גישה מקוונת: | https://doi.org/10.3390/math13243964 |
| פורמט: | אלקטרוני Book Chapter |
| KOHA link: | https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=683769 |
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| 200 | 1 | |a 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 |f Nikita V. Martyushev, Boris V. Malozyomov, Vitaliy A. Gladkikh [et al.] | |
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| 330 | |a 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 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 | ||
| 336 | |a Текстовый файл | ||
| 461 | 1 | |t Mathematics |c Basel |n MDPI AG | |
| 463 | 1 | |t Vol. 13, iss. 24 |v Article number 3964, 13 p. |d 2025 | |
| 610 | 1 | |a optimal control | |
| 610 | 1 | |a mathematical modeling | |
| 610 | 1 | |a load peak smoothing | |
| 610 | 1 | |a integrated battery energy storage system | |
| 610 | 1 | |a dynamic optimization | |
| 610 | 1 | |a iterative algorithms | |
| 610 | 1 | |a nonlinear filterin | |
| 610 | 1 | |a constrained problem | |
| 610 | 1 | |a real-time control | |
| 610 | 1 | |a adaptive systems | |
| 610 | 1 | |a numerical method | |
| 610 | 1 | |a труды учёных ТПУ | |
| 610 | 1 | |a электронный ресурс | |
| 701 | 1 | |a Martyushev |b N. V. |c specialist in the field of material science |c Associate Professor of Tomsk Polytechnic University, Candidate of technical sciences |f 1981- |g Nikita Vladimirovich |9 16754 | |
| 701 | 1 | |a Malozemov |b B. V. |g Boris Vitaljevich | |
| 701 | 1 | |a Gladkikh |b V. A. |g Vitaly Aleksandrovich | |
| 701 | 1 | |a Demin |b A. Yu. |c specialist in the field of Informatics and computer engineering |c Associate Professor of Tomsk Polytechnic University, candidate of technical sciences |f 1973- |g Anton Yurievich |9 17327 | |
| 701 | 1 | |a Pogrebnoy |b A. V. |c specialist in the field of Informatics and computer engineering |c Associate Professor of Tomsk Polytechnic University, candidate of technical sciences |f 1973- |g Aleksandr Vladimirovich |9 17310 | |
| 701 | 1 | |a Kuleshova |b E. E. |g Elizaveta Evgenjevna | |
| 701 | 1 | |a Karlina |b Yu. I. |g Yuliya Igorevna | |
| 801 | 0 | |a RU |b 63413507 |c 20251217 | |
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| 856 | 4 | |u https://doi.org/10.3390/math13243964 |z https://doi.org/10.3390/math13243964 | |
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