Effective estimation of the state-of-charge of latent heat thermal energy storage for heating and cooling systems using non-linear state observers
Effective estimation of the state-of-charge of latent heat thermal energy storage for heating and cooling systems using non-linear state observers
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DOI：
10.1016/j.apenergy.2022.120448
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发表时间：
2022-12-09
期刊：
影响因子：
11.2
通讯作者：
Ugalde-Loo, Carlos E.
中科院分区：
文献类型：
--
作者：
Bastida, Hector;De la Cruz-Loredo, Ivan;Ugalde-Loo, Carlos E.
潜热热能储存（LHTES）单元吸收和提供的能量的有效量化对于最大限度地利用其在热力系统中至关重要。为了有效地控制这些单元的充电和放电过程，需要准确地估计荷电状态（SoC）。然而，直接和可靠的SoC估计需要结合内部传感器来监测相变材料（即存储介质）的温度梯度，从而导致更高的仪器成本和技术规格。这些问题可以通过采用状态观测器进行SoC估计来大大减少测量的数量来缓解。本文提出了一种新的和直接的方法来估计的SoC的LHTES单位，无论是加热和冷却应用，基于非线性状态观测器，弥补了这一差距。观测器是基于一个简单的一维动态模型的热存储和热物理性质的存储介质和传热流体，这通常是由制造商提供。这使得能够估计LHTES单元的内部温度，进而进行SoC计算。观测器的实现很简单，因为它只需要三个测量值作为输入变量（即质量流率以及传热流体的输入和输出温度）。SoC估计方法通过两个LHTES单元的动态模拟进行评估：一个用于加热应用，一个用于冷却应用。结果表明，与实验测量值相比，SoC的均方根和平均绝对误差分别小于4.6%和3.62%。
An effective quantification of the energy absorbed and supplied by latent heat thermal energy storage (LHTES) units is critical to maximise their use within thermal systems. An effective control of the charging and discharging processes of these units demands an accurate estimation of the state-of-charge (SoC). However, a direct and reliable SoC estimation requires incorporating internal sensors to monitor the temperature gradient of the phase change material (i.e. the storage medium), resulting in higher instrumentation costs and technical specifications. These issues may be relieved by adopting state observers for SoC estimation to drastically reduce the number of measurements. This paper bridges this gap by presenting a novel and direct method for estimating the SoC of LHTES units, both for heating and cooling applications, based on a non-linear state observer. The observer is based on a simple one-dimensional dynamic model of the thermal store and the thermophysical properties of the storage medium and the heat transfer fluid, which are usually provided by manufacturers. This enables the estimation of the internal temperatures of the LHTES unit and, in turn, SoC calculation. The observer implementation is simple as it requires three measurements only as input variables (i.e. the mass flow rate and the input and output temperatures of the heat transfer fluid). The SoC estimation approach is assessed through dynamic simulations of two LHTES units: one for a heating application and one for a cooling application. The results show that the SoC can be estimated with root mean square and mean absolute errors of less than 4.6% and 3.62%, respectively, compared with experimental measurements.