Abstract
Solar thermal power technologies require storage systems to mitigate the natural variability of solar irradiation. Packed bed thermal storage systems (PBTES) offer a cost-effective solution using air as heat transfer fluid and rocks as a storage medium. Compared to its alternatives, however, PBTES presents a limited flexibility of operation due to the conventional unidirectional flow, which involves the progressive reduction of the outlet temperature during discharge and thus lowers the thermodynamic efficiency of the power cycle. The present study summarizes the progress on the design and optimal operation of a novel multi-extraction PBTES, a project that aims at mitigating its typically poor operational flexibility for solar power applications. To this end, a one-dimensional model with a high spatial resolution of a PBTES was developed, which includes four intermediate outlet points along the axial direction to investigate the benefits of optimal extraction operation. In order to reduce the computational burden, a coarser model of the storage system is used in combination with non-linear model predictive control (NLMPC). Through the optimal manipulation of the extraction valves, the output temperature is maintained close to a prescribed temperature throughout the discharge. The control admits not only constant temperature targets, but also time-varying scheduled profiles. This work describes the limitation of such a design and control approach and sets the direction for the future, more detailed analyses needed to demonstrate its applicability.
Highlights
Packed bed systems are considered a promising energy storage option to overcome the variability of renewable energy sources in applications like solar-thermal power generation [1,2,3,4,5] or wind power [6]
Following the example of other authors, a series of assumptions to reduce its complexity has been considered: variables depend on time and space in the axial coordinate; wall effects are neglected since D/dp > 40, following [4], after [18]; the intraparticle temperature gradient effect is non-negligible (Bi < 0.1), but its effect is simplified following [3], after [19], using a corrected number of transfer units (NTU) value; the inertial term in the energy balance for the fluid phase is neglected, following [20]; particles are considered in mono-dispersed and in homogeneous distributions [4]; no deformation or leakage [4] is considered; air thermal conductivity is independent from pressure, following [4], after [21]
The partial differential equation (PDE) system developed by Schuman [22] and modified by other authors yields, after simplification, a system of differential algebraic equations (DAE), as described in [4]
Summary
Packed bed systems are considered a promising energy storage option to overcome the variability of renewable energy sources in applications like solar-thermal power generation [1,2,3,4,5] or wind power [6]. While the heat transfer mechanisms that take place within current designs of bedrock storage systems are well understood, and there is little uncertainty in the response of the system given the usual uniaxial character of a constant airflow, this may not be the case when the airflow is intentionally modified in terms of direction and quantity This is the starting point of a preliminary assessment of a novel control scheme that uses optimization tools to manipulate the flow of a multi-extraction packed bed storage system. The paper closes with some conclusions and an outline of future work (Section 6)
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