No abstract

This work assesses the performance of a solar tower power plant based on liquid sodium as heat transfer fluid and supercritical CO 2 cycles. The adoption of liquid sodium as heat transfer fluid allows maximum temperatures up to 750 °C and higher heat fluxes on the receiver with respect to molten salts (both Solar Salts and KCl-MgCl 2 ) also considered as reference. The assessment is carried out through detailed modeling of the solar to electricity conversion processes accounting for detail optical, thermal and power block models. Results at design conditions show that plants using sodium as HTF in the receiver can achieve overall efficiency above 25%, whereas the use of Solar Salts at 565 °C and KCl-MgCl 2 at 750 °C reach 21.5% and 24% respectively. The higher efficiency is consequence of the higher thermal efficiency of sodium which is achieved increasing the concentration ratio. Considering a yearly analysis, the overall efficiency of sodium reduces to 20.5% and 19.3% in Seville and Las Vegas respectively which is 7-9% higher than using KCl-MgCl 2 and 11% with respect to Solar Salts. Outcomes of this work are the importance of (i) coupling higher temperatures with higher allowable fluxes on the receiver and (ii) defining the system operating conditions on overall yearly efficiency rather than design point.

No abstract

Microgrids represent a flexible way to integrate renewable energy sources with programmable generators and storage systems. In this regard, a synergic integration of those sources is crucial to minimize the operating cost of the microgrid by efficient storage management and generation scheduling. The forecasts of renewable generation can be used to attain optimal management of the controllable units by predictive optimization algorithms. This paper introduces the implementation of a two-layer hierarchical energy management system for islanded photovoltaic microgrids. The first layer evaluates the optimal unit commitment, according to the photovoltaic forecasts, while the second layer deals with the power-sharing in real time, following as close as possible the daily schedule provided by the upper layer while balancing the forecast errors. The energy management system is experimentally tested at the Multi-Good MicroGrid Laboratory under three different photovoltaic forecast models: (i) day-ahead model, (ii) intraday corrections and (iii) nowcasting technique. The experimental study demonstrates the capability of the proposed management system to operate an islanded microgrid in safe conditions, even with inaccurate day-ahead photovoltaic forecasts.

No abstract