Adaptive Corridor-Based Control of a Lithium-Ion Battery Energy Storage System for Wind-Turbine Power Stabilisation and Reliability Improvement in Industrial Microgrids
The increasing penetration of wind generation into autonomous and weakly coupled industrial microgrids requires control strategies that can maintain power-supply reliability under stochastic generation and sharply variable loads. This paper proposes an adaptive corridor-based supervisory control algorithm for a lithium-ion battery energy storage system (BESS) integrated with a wind-turbine generator. The novelty of the method is not the general use of battery storage for power smoothing but a control law that maintains the generator within a predefined active-power corridor while transferring fast and medium-duration imbalances to the battery under state-of-charge, power-limit, and response-delay constraints. Unlike PI-based smoothing, model predictive control, or fixed rule-based switching, the proposed approach uses corridor retention as the primary operating criterion and relies only on directly measurable variables. The model was implemented in MATLAB/Simulink for a 2 MW wind-turbine generator coupled with a 444 kWh/1776 kW lithium-ion battery energy storage system. Field-measurement-based simulation validation was performed in MATLAB/Simulink using industrial load data measured at an autonomous oilfield power plant; the validation scenarios included extracted step disturbances, a real multi-peak load profile, prolonged deficit operation, and a scaled configuration scenario. The algorithm compensated for 86.3–87.4% of short-term load peaks, reduced the standard deviation of generator power from 467 to 98 kW, and decreased recovery time from 6.8 to 1.6 s.
Authors
- Yadviga Aleksandrovna Tynchenko (ORCID: https://orcid.org/0000-0001-8963-7830)
- Nikita V. Martyushev (ORCID: https://orcid.org/0000-0003-0620-9561)
- В С Тынченко (ORCID: https://orcid.org/0000-0002-3959-2969)
- Boris V. Malozyomov (ORCID: https://orcid.org/0000-0001-8686-9556)
- Rollan Nussipali
- Viktor A. Kukartsev
- Tatyana A. Panfilova
Institutions
- Bauman Moscow State Technical University (RU)
- Ministry of Water Resources and Irrigation (EG)
- National Research Tomsk State University (RU)
- Tomsk Polytechnic University (RU)
- Siberian Federal University (RU)
- Novosibirsk State Technical University (RU)
Publication Details
- Journal
- Electricity
- Published
- 2026-06-17
- DOI
- https://doi.org/10.3390/electricity7020056
- Primary Topic
- Microgrid Control and Optimization
- Type
- article
- Field-Weighted Citation Impact
- 0.00