Ricerc@Sapienza

The transition towards energy systems characterized by high share of weather dependent renewable energy sources poses the problem of balancing the mismatch between inflexible production and inelastic demand with appropriate solutions, which should be feasible from the techno-economic as well as from the environmental point of view. Temporal and spatial decoupling of supply and demand is an important element to be considered for the evolution of built environment, especially when creating sectorial level planning strategies and policies.

Smart multi-energy systems based on distributed polygeneration power plants have gained increasing attention for having shown the capability of significant primary energy savings and reduced CO2 pollutant emissions due to the high renewable energy sources penetration. Compared to the traditional power plants, the large variability in the end-user demands (electricity, heat and cold energy), coupled with the uncertainty in the solar and wind energy availability, require the adoption of energy storage systems for dampening the intermittency problems and for performing peak shaving.

In the current paper, the behavior of zinc oxide/SAE50 nano lubricant as a part of the new generation of coolants and lubricants is examined using response surface method (RSM). The data used in this study were viscosity at dissimilar volume concentrations (0-1.5%) and temperatures (5-50 °C) for dissimilar shear rate values. Therefore, sensitivity analysis based on variation of nanoparticle (NP) concentration and temperature was also implemented. The findings revealed that enhancing the volume fraction (φ) exacerbates the viscosity sensitivity to temperature.

A novel energy management system (EMS) synthesis procedure based on adaptive neurofuzzy inference systems (ANFISs) by hyperplane clustering is investigated in this paper. In particular, since it is known that clustering input–output samples in hyperplane space does not consider clusters’ separability in the input space, a Min–Max classifier is applied to properly cut and update those hyperplanes defined on scattered clusters in order to refine the ANFIS membership functions.