Hybrid energy storage systems for photovoltaic storage microgrids power allocation and capacity determination based on adaptive Savitzky-Golay filtering and VMD-DTW

Hybrid energy storage systems for photovoltaic storage microgrids power allocation and capacity determination based on adaptive Savitzky-Golay filtering and VMD-DTW

In the photovoltaic storage microgrid, fluctuations in PV power generation are mitigated by the Hybrid Energy Storage System (HESS). However, excessive smoothing exacerbates storage burdens while meeting grid-connection standards, and improper power allocation within the storage system escalates cos...

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Bibliographic Details
Main Authors: Zengqiang Ma, Zejia Zhou, Tianming Mu, Cheng Wen
Format: Article
Language:English
Published: Elsevier 2025-09-01
Series:International Journal of Electrical Power & Energy Systems
Subjects:
Adaptive SG
VMD-DTW
Full life cycle
Power allocation
Capacity determination
Online Access:http://www.sciencedirect.com/science/article/pii/S014206152500393X
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Summary:In the photovoltaic storage microgrid, fluctuations in PV power generation are mitigated by the Hybrid Energy Storage System (HESS). However, excessive smoothing exacerbates storage burdens while meeting grid-connection standards, and improper power allocation within the storage system escalates costs. To address these challenges, an optimization model for Savitzky–Golay (SG) filtering parameters is formulated. An enhanced dung beetle optimization algorithm is employed to optimize this model, enabling adaptive parameter adjustments in SG filtering. This approach reduces energy storage burdens by trading off smoothing effects while adhering to grid-connection requirements. Upon obtaining the compensated power from HESS, a power allocation method based on Variational Modal Decomposition (VMD) and Dynamic Time Warping (DTW) is proposed. Additionally, a State of Charge (SOC) dynamic transformation model and a full life cycle-based HESS cost model are constructed to quantitatively assess the method’s efficacy and advantages. Simulations using PV power generation data from different seasons in a demonstration project in Hebei Province, China, confirm that this strategy effectively alleviates energy storage burdens and reduces system costs.
ISSN:0142-0615

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