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Optimal scheduling of home energy systems considering battery aging and CO2 emissions

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  • de Lima, Tayenne Dias
  • Faria, Pedro
  • Vale, Zita

Abstract

Battery energy storage systems (BESS) play a critical role in enhancing the flexibility, reliability, and efficiency of residential energy management. Optimized scheduling of BESS is essential to maximize operational benefits while mitigating carbon emissions. Consequently, investigations addressing the enhanced operation of BESS in energy management systems are highly relevant. From this perspective, it is important to consider operational patterns that preserve the long-term performance and lifespan of batteries. This paper presents a mixed integer linear programming model for the optimal scheduling of home energy systems supported by solar generation and battery systems. After optimization, the model calculates battery degradation, considering both cycle and calendar aging effects. Additionally, a carbon emissions penalty was incorporated into the objective function to address environmental impacts. The model was coded in Python and solved through the CBC solver. The model was tested under different battery SOC limits and seasonal conditions (winter and summer), highlighting the role of BESS in reducing energy costs, emissions, and grid dependency while evidencing the impact of operational strategies on battery aging.

Suggested Citation

  • de Lima, Tayenne Dias & Faria, Pedro & Vale, Zita, 2026. "Optimal scheduling of home energy systems considering battery aging and CO2 emissions," Applied Energy, Elsevier, vol. 409(C).
    • Handle: RePEc:eee:appene:v:409:y:2026:i:c:s0306261926000851
    DOI: 10.1016/j.apenergy.2026.127433
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