论文标题
混合整数线性程序模型,用于优化氧化钒氧化还原流量电池的调度,其效率可变,容量淡出和电解质维护
Mixed Integer Linear Program model for optimized scheduling of a vanadium redox flow battery with variable efficiencies, capacity fade, and electrolyte maintenance
论文作者
论文摘要
氧化还原流量电池是大规模固定能量存储的有前途选择。由于其化学稳定性和性能,钒氧化还原流量电池是最广泛的商业化系统。这项工作旨在优化钒流量电池的调度,该电池存储可再生电厂产生的能量,并考虑到电池性能的彻底表征,并具有可变的效率和容量的淡出效果。与使用较简单的模型获得的结果相比,电池性能的详细表征可改善与电池使用相关的最佳周期和收入的计算,这些结果考虑到恒定的效率和无容量的淡入效果。提出的问题是由于电池效率的功能而非线性的,该功能取决于充电和排放功率以及与非线性,非凸相关性的充电状态。该问题是使用凸壳线性化的。优化计划还可以计算由于未经想的二级电化学反应以及通过定期维护对能力恢复的经济影响,因此渐进的电池容量逐渐消失。最终问题被解决为混合企业线性程序(MILP),以确保线性化问题的全局最优性。提出的优化模型已应用于两个不同的案例研究:一种能量套利的案例和一个载荷转移案例。优化结果已与恒定电池效率模型获得的优化结果进行了比较,而电池效率模型不考虑容量褪色效果。结果表明,如果不考虑电池的降解模型,则更简单的型号高估了电池的最佳循环和收入最高15%,如果电池的降级模型分别高达32%和42%,如果电池的恒定效率也是如此。
Redox Flow Batteries are a promising option for large-scale stationary energy storage. The vanadium redox flow battery is the most widely commercialized system thanks to its chemical stability and performance. This work aims to optimize the scheduling of a vanadium flow battery that stores energy produced by a renewable power plant, keeping into account a thorough characterization of the battery performance, with variable efficiencies and capacity fade effects. A detailed characterization of the battery performance improves the calculation of the optimal number of cycles and revenue associated with the battery use if compared to the results obtained using simpler models, which take into account constant efficiencies and no capacity fade effects. The presented problem is nonlinear due to the functions of the battery efficiency, which depend upon charging and discharging powers and state of charge with nonlinear, non-convex correlations. The problem is linearized using convex hulls. The optimization program also calculates the progressive battery capacity fade due to undesired secondary electrochemical reactions and the economic impact of capacity restoration through periodic maintenance. The final problem is solved as a Mixed-Integer Linear Program (MILP) to guarantee the global optimality of the linearized problem. The proposed optimization model has been applied to two different case studies: a case of energy arbitrage and a case of load-shifting. The optimization results have been compared to those obtained with constant battery efficiency models, which do not consider the capacity fade effects. Results show that simpler models overestimate the optimal number of cycles of the battery and the revenue by up to 15% if they do not take into account the degradation model of the battery, and respectively up to 32% and 42% if they also assume constant efficiency for the battery.