变环境温度下含强制冷却的全钒液流电池系统多变量动态优化研究

Vanadium redox battery (VRB)-based peak shaving is playing a leading role in the context of the smart energy revolution. Under different storage dispatch strategy and ambient temperature conditions, VRB’s overall efficiency varies in a wide range, i.e., from nearly 90% to below 60%. This project thus aims to provide an optimization framework to address this varying-ambient-temperature, multi-variable optimization problem, by elaborating the complex relationships among different variables, clarifying their impacts on VRB’s overall efficiency, and establishing a dynamic, multi-variable optimization approach. This project intends to study the coupling relationship among ambient temperature, demand profile and demand target, and reveal the coupling relationship between ambient temperature and VRB’s (dis-)charge current; then to develop a semi-empirical, dynamic electro-thermal model for VRB and its forced cooling system as a whole, by using which, the project intends to investigate the impacts of the electrolyte and the coolant flow rates on the electrolyte temperature, VRB’s energy efficiency, and pump losses, so as to reveal the overall impacts of the flow rates on VRB’s overall efficiency under different ambient temperature conditions; and finally develop two dynamic optimization models that maximize VRB’s profit and overall efficiency, respectively. The study could provide a novel approach to optimally dispatch flow batteries under varying ambient conditions, and lay a theoretical foundation for the storage-based smart energy system practice.

全钒液流电池（简称钒电池）用于需求侧调峰，是智慧能源系统的重要研究课题之一。随着环境温度和钒电池系统运行参数的变化，其效率可由理想效率（接近90%）降低至60%以下。为了解决变环境温度下钒电池相互关联的多变量优化问题，本项目拟通过细化变量间的复杂依变关系，分别厘清不同变量对于钒电池系统效率的作用机理和影响规律，建立变环境温度下的多变量动态优化新方法。本项目拟研究环境温度与负荷曲线、调峰目标的耦合关系，揭示环境温度与钒电池充放电电流的耦合规律；拟建立半经验的含强制冷却的钒电池全系统动态热模拟模型，厘清电解液和冷却剂流速与电解液温度、电池效率、泵耗能之间的变化关系，揭示电解液和冷却剂流速对钒电池系统效率的影响规律；最后建立变环境温度下分别使得经济效益最优和系统效率最优的两个动态优化模型。为变环境温度下的液流电池的运行优化提供新思路，为基于储能的智慧能源系统的实现奠定理论基础。

全钒液流电池用于需求侧调峰，是智慧能源系统的重要研究课题之一。随着环境温度和全钒液流电池系统运行参数的变化，其效率可由理想效率（接近90%）降低至60%以下。本项目为解决全钒液流电池在变工况（变充放电功率、荷电状态和环境温度）下系统效率较低和实际可用容量衰减等关键问题，通过建立全钒液流电池全系统（含电解液储罐）的瞬态多物理场耦合模型和实验平台，研究总结了电池温度变化的基本规律：电池的平均温度主要受电流密度和电解液流速的影响，随电流密度的增大而增大，随流量的增大先减小后增大；电池温度的波动幅度主要受电池充放电深度的影响，在环境温度基本稳定的工作条件下，电堆温度的波动幅度和充放电深度大致呈正比。环境温度通过影响电解液的粘度和电导率影响电池产热，随着温度的升高流动产热减小，旁路电流产热增大，总体而言，低温环境下比高温环境下电池热效应更加显著。据此，本项目建立了变环境温度下分别使得经济效益最优和系统效率最优的全钒液流电池电解液流量和充放电电流动态优化模型，能够将全钒液流电池变工况充放电过程中的系统效率维持在87%以上、实际可用容量提高10%以上、最高温升降低约4℃；设计了新型流道结构，可提高大尺度电极中活性物质的分布均匀性，保障动态优化策略在实际应用场景中的有效性。为变环境温度下、变工况下全钒液流电池的运行优化提供新思路，为基于储能的智慧能源系统的实现奠定理论基础。