Abstract
Abstract The benefits of thermal storage in hybrid energy systems (HESs) are multiple, being among others the enhancement of flexibility of the network and of the efficiency in the energy resources use, by also reducing the overall cost of the energy system. Choosing the capacity of TSS to minimize the operational cost of the HES is not a trivial task, depending on several variables existing at both supply and demand sides. The contribution of this paper is to present the experimental validation of an innovative optimization model aiming to identify the optimal capacity of TSS in HESs that maximizes the economic performances. The optimization model is based on a mixed-integer linear programming approach and allows determining the optimal hourly operating strategies of the system components as well as the optimal capacity of the TSS, while minimizing the total daily energy costs. The optimized hourly operation schedule of the HES was simulated experimentally by using one of the systems from the TSS laboratory of ENEA Portici Research Center. The experimental results demonstrated the practical applicability of the proposed optimization model. In fact, a good overlap was found between the results obtained from the implementation of the optimization model with those obtained from the experimental simulation, both considering energy and economic data.
Published Version
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