Degradation-aware PSO–MPC energy management for second-life battery prosumer microgrids

Abstract The growing retirement of electric vehicle lithium-ion batteries has created significant opportunities for their reuse in stationary energy storage systems. However, integrating second-life batteries (SLBs) into residential photovoltaic (PV)-based prosumer microgrids remains challenging due to heterogeneous initial state-of-health (SoH) conditions, accelerated degradation behavior, and uncertain remaining useful life. This paper proposes a degradation-aware energy management framework for SLB-integrated prosumer microgrids based on the joint use of particle swarm optimization (PSO) and model predictive control (MPC). The proposed framework consists of four coordinated stages: PSO-based capacity sizing, hybrid AI-based forecasting of PV generation, electricity prices, and load demand, SoH-aware adaptive battery management within the MPC layer, and net present value (NPV)-based battery replacement decision-making. Within the control layer, the adaptive battery management mechanism updates state-of-charge limits, C-rate constraints, and degradation penalty coefficients according to real-time SoH evolution, thereby mitigating excessive capacity fade while preventing economically inefficient underutilization. In addition, a three-stage replacement strategy is developed to determine whether continued operation, SLB, or fresh battery replacement yields the highest long-term economic benefit. The proposed method is evaluated through long-horizon simulations using 2024 meteorological, market, and demand data for five residential prosumers in Antalya, Türkiye. The results show that the framework achieves a fleet-average self-consumption ratio of 71.8%, a renewable energy penetration factor of 37.6%, and a cost of energy of 0.0722 $/kWh, while sustaining battery utilization and enabling lifecycle-aware operation under realistic uncertainty. These findings demonstrate that the proposed PSO–MPC framework provides a computationally tractable approach that achieved stable convergence and feasible MPC solve times (2.1–3.4 s per 72-hour horizon) across all 20 simulated years under the five-prosumer Antalya configuration for degradation-aware energy management of SLB-based microgrids.

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Publication Details

Journal
Scientific Reports
Published
2026-07-27
DOI
https://doi.org/10.1038/s41598-026-61586-4
Primary Topic
Advanced Battery Technologies Research
Type
article
Field-Weighted Citation Impact
0.00

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article

Degradation-aware PSO–MPC energy management for second-life battery prosumer microgrids

Erdin Gökalp, Ümit Cali, Alpaslan Demirci, Musa Terkeş et al.
Scientific Reports
Advanced Battery Technologies Research
article

Degradation-aware PSO–MPC energy management for second-life battery prosumer microgrids

Erdin Gökalp, Ümit Cali, Alpaslan Demirci, Musa Terkeş, Idriss Dagal
article en

Abstract

Abstract The growing retirement of electric vehicle lithium-ion batteries has created significant opportunities for their reuse in stationary energy storage systems. However, integrating second-life batteries (SLBs) into residential photovoltaic (PV)-based prosumer microgrids remains challenging due to heterogeneous initial state-of-health (SoH) conditions, accelerated degradation behavior, and uncertain remaining useful life. This paper proposes a degradation-aware energy management framework for SLB-integrated prosumer microgrids based on the joint use of particle swarm optimization (PSO) and model predictive control (MPC). The proposed framework consists of four coordinated stages: PSO-based capacity sizing, hybrid AI-based forecasting of PV generation, electricity prices, and load demand, SoH-aware adaptive battery management within the MPC layer, and net present value (NPV)-based battery replacement decision-making. Within the control layer, the adaptive battery management mechanism updates state-of-charge limits, C-rate constraints, and degradation penalty coefficients according to real-time SoH evolution, thereby mitigating excessive capacity fade while preventing economically inefficient underutilization. In addition, a three-stage replacement strategy is developed to determine whether continued operation, SLB, or fresh battery replacement yields the highest long-term economic benefit. The proposed method is evaluated through long-horizon simulations using 2024 meteorological, market, and demand data for five residential prosumers in Antalya, Türkiye. The results show that the framework achieves a fleet-average self-consumption ratio of 71.8%, a renewable energy penetration factor of 37.6%, and a cost of energy of 0.0722 $/kWh, while sustaining battery utilization and enabling lifecycle-aware operation under realistic uncertainty. These findings demonstrate that the proposed PSO–MPC framework provides a computationally tractable approach that achieved stable convergence and feasible MPC solve times (2.1–3.4 s per 72-hour horizon) across all 20 simulated years under the five-prosumer Antalya configuration for degradation-aware energy management of SLB-based microgrids.

Scientific Reports
American University of Sharjah (AE), Norwegian University of Science and Technology (NO), Yıldız Technical University (TR), University of York (GB), Beykent University (TR)
Türkiye Bilimsel ve Teknolojik Araştırma Kurumu
Affordable and clean energy
Openalex Percentile: Top 15%
Advanced Battery Technologies Research
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