The present paper aims at defining a simplified but effective model of a thermal network that links the thermal power generation with the resulting temperature time profile in a heated or refrigerated environment. For this purpose, an equivalent electric circuit is proposed together with an experimental procedure to evaluate its input parameters. The paper also highlights the simplicity of implementation of the proposed model into a microgrid Energy Management System. This allows the optimal operation of the thermal network to be achieved on the basis of available data (desired temperature profile) instead of a less realistic basis (such as the desired thermal power profile). The validation of the proposed model is performed on the Savona Campus Smart Polygeneration Microgrid (SPM) with the following steps: (i) identification of the parameters involved in the equivalent circuit (performed by minimizing the difference between the temperature profile, as calculated with the proposed mode... [more]

When dealing with sustainable design concepts in new construction or in retrofitting existing buildings, it is useful to define both economic and environmental performance indicators, in order to select the optimal technical solutions. In most of the cases, the definition of the optimal strategy is not trivial because it is necessary to solve a multi-objective problem with a high number of the variables subjected to nonlinear constraints. In this study, a powerful multi-objective optimization genetic algorithm, NSGAII (Non-dominated Sorting Genetic Algorithm-II), is used to derive the Pareto optimal solutions, which can illustrate the whole trade-off relationship between objectives. A method is then proposed, to introduce uncertainty evaluation in the optimization procedure. A new university building is taken as a case study to demonstrate how each step of the optimization process should be performed. The results achieved turn out to be reliable and show the suitableness of this proced... [more]

In recent years, bioenergy has become a promising renewable energy source that can potentially reduce the greenhouse emissions and generate economic growth in rural areas. Gaining understanding and controlling biomass chemical composition contributes to an efficient biofuel generation. This paper presents a principal component analysis (PCA) that shows the influence and relevance of selected controllable factors over the chemical composition of switchgrass and, therefore, in the generation of biofuels. The study introduces the following factors: (1) storage days; (2) particle size; (3) wrap type; and (4) weight of the bale. Results show that all the aforementioned factors have an influence in the chemical composition. The number of days that bales have been stored was the most significant factor regarding changes in chemical components due to its effect over principal components 1 and 2 (PC1 and PC2, approximately 80% of the total variance). The storage days are followed by the particl... [more]

Heat sources, such as power electronics for offshore power, could be cooled passively—mainly by conduction and natural convection. The obvious advantage of this strategy is its high reliability. However, it must be implemented in an efficient manner (i.e., the area needs to be kept low to limit the construction costs). In this study, the placement of multiple heat sources mounted on a vertical plate was studied experimentally for optimization purposes. We chose a regular distribution, as this is likely to be the preferred choice in the construction process. We found that optimal spacing can be determined for a targeted source density by tuning the vertical and horizontal spacing between the heat sources. The optimal aspect ratio was estimated to be around two.