Optimal microgrid operation considering battery degradation using stochastic dual dynamic programming

Per Aaslid, M. Belsnes, O. Fosso
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引用次数: 10

Abstract

Intermittent energy sources demand temporal storages to balance generation and load, and batteries stand out as an alternative. However, the lifetime is limited, and cycling depth affects the battery degradation rate. Current stochastic multi-stage methods lack proper representation of battery degradation. This paper proposes a stochastic multi-stage model for optimizing battery operation in a microgrid considering battery degradation with a piece-wise linear cost function with uncertain wind power production and load. The model is solved using Stochastic Dual Dynamic Programming (SDDP) and is demonstrated on a 4-bus test case with limited import and export capacity to illustrate the battery degradation cost's impacts on the battery cycling strategy. The results show that the importance of a stochastic method is more pronounced when battery degradation is modelled.
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考虑电池退化的随机双动态规划微电网优化运行
间歇性能源需要临时存储来平衡发电和负荷,而电池作为一种替代方案脱颖而出。但其寿命有限,且循环深度会影响电池的降解率。目前的随机多阶段方法缺乏电池退化的适当表示。本文提出了一种考虑电池退化的随机多阶段模型,该模型具有分段线性成本函数,风电产量和负荷不确定。采用随机双动态规划(SDDP)方法求解该模型,并在进出口能力有限的4总线测试案例中进行了验证,以说明电池退化成本对电池循环策略的影响。结果表明,在对电池退化进行建模时,随机方法的重要性更为明显。
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