Renewable energy resources are steadily being important options in the microgrids power systems, energy storage technology become required to manage intermittent of power supply, battery storage can be use in small scale to support the power need, but the cost and lifetime of the battery one of the challenges in utilizing battery storage system in the microgrids. Also, the thermal storage system become desirable due to ability to hold greatly variable quantities of energy at the unchanged temperature. This paper studies a microgrid which supplies solar and wind energy to a single building with both electric load and thermal load. The aim is to investigate the potential benefit of using lower-cost thermal storage to assist in managing renewable power fluctuations, which is appropriate when significant thermal loads are present. Hourly electrical consumption and demand hot water profiles are developed from historical meter data. Model Predictive Control (MPC) has been used to dispatch the power between microgrid component. Renewable energy penetration and renewable energy curtailment are the performance measured. Modeling results indicate that storage balance among battery and thermal storage increasing renewable penetration by 15% and decrease renewable curtailment by 30%.
This paper discusses the probability of detection enhancement at the fusion area scanned by two radars. The improvement is implemented by three techniques, scan rate modulation, scan-to-scan processing, and applying the probability of detection rules (AND, OR) to make a decision. The simulation results reveal that using AND rules with precalculation of the threshold is better at enhancing the probability of detection and reducing the probability of false alarm. Furthermore, scan-to-scan processing has a considerable influence on reducing false alarms. Moreover, scan rate modulation increases the probability of detection and maintains the probability of false alarm within a permissible limit.