Reversible solid oxide cells can provide efficient and cost-effective scheme for electrical-energy storage applications. However, this technology faces many challenges from material development to system-level operational parameters , which should be tackle for practical purposes. Accordingly, this study focuses on developing novel robust artificial intelligence-based blackbox models to optimize operational variables of the system. A genetic-programming algorithm is used for Pareto modeling of reversible solid oxide cells in a multi-objective fashion based on experimental input-output data. The robustness of the obtained optimal model evaluated using Monte Carlo simulations technique. An optimization study adopted to optimize the operating parameters, such as temperature and fuel composition using a differential evolution algorithm. The objective functions that have been considered for Pareto multi-objective modeling process are training error and model complexity. In addition, the discrepancy between maximum and minimum output voltage in the whole operation of the system is chosen as the optimization process objective function. The robustness of the optimal trade-off model is shown in terms of statistical indices for varied uncertainty levels from 1 to 10%. The optimized operational condition based on the suggested model reveals optimal intermediate temperature of 762 °C and fuel mixture of about 29% H 2 , 25% H 2 O, and 14% CO.
A simulation study of daylight autonomy in perimeter office rooms at high latitudes is presented where the following variables are studied: Glazing-to-wall ratios (GWR), climate, orientation, inner surface reflectance, glazing visual transmittance, Venetian blind management and electric lighting dimming and switching systems. Based on daylight utilisation alone, the results indicate an optimal GWR ranging between 20% and 40%, with a North orientation requiring a larger GWR (40%), a South orientation a smaller GWR (20%) and an East/West orientation an intermediate GWR (30%). The reflectance of inner surfaces has a significant effect on daylight autonomy and the use of low transmittance glazing demands a larger GWR (60%) to achieve the same daylight autonomy as 20% GWR with high transmittance glazing. Also, the results indicate that the choice of electric lighting dimming and switching systems has a more significant impact on electricity use than the GWR, orientation and the other variables examined.
An important measure for climate change mitigation is reduction of energy use in buildings worldwide. In 2010 Skanska Sverige AB began designing an office building in the southern parts of Sweden, aiming towards a Net zero energy building (Net ZEB) balance. The construction work started in the middle of 2011.In the beginning of 2012 Sveriges Centrum fö r Nollenergihus/the Swedish Centre for Zero-energy buildings (SCNH) published a Swedish definition for a zero-energy building in the Swedish climate. In short; the Swedish definition of a zero-energy building demands fulfilment of the passive house criteria, and that a zero energy balance must be reached over a year based on import/exported balance.This study summarises the overall design ideas, constructions, installations, energy balance of the office building and investigates whether the building reaches the zero energy-building definition according to SCNH. The simulations show that a Net ZEB balance may be reached. However, the passive house criterion is not reached. The study discusses pros and cons in the Swedish definition of "zero-energy building"/Net ZEB and suggests clarifications needed and possible amendment that may be implemented in an updated version of the definition.
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