Mechanical characterization of polyhydroxyalkanoate and poly (lactic acid) blends

In this work, the mechanical behavior of polyhyroxyalkanoate (PHA)/poly(lactic acid) (PLA) blends is investigated in a wide range of compositions. The mechanical properties can be optimized by varying the PHA contents of the blend. The flexural and tensile properties were estimated by different models: the rule of mixtures, Kerner–Uemura–Takayanagi (KUT) model, Nicolai–Narkis model and Béla–Pukánsky model. This study was aimed at investigating the adhesion between the two material phases. The results anticipate a good adhesion between both phases. Nevertheless, for low levels of incorporation of PHA (up to 30%), where PLA is expectantly the matrix, the experimental data seem to deviate from the perfect adhesion models, suggesting a decrease in the adhesion between both polymeric phases when PHA is the disperse phase. For the tensile modulus, a linear relationship is found, following the rules of mixtures (or a KUT model with perfect adhesion between phases) denoting a good adhesion between the phases over the composition range. The incorporation of PHA in the blend leads to a decrease in the flexural modulus but, at the same time, increases the tensile modulus. The impact energy of the blends varies more than 157% over the entire composition. For blends with PHA weight fraction lower than 50%, the impact strength of the blend is higher than the pure base polymers. The highest synergetic effect is found when the PLA is the matrix and the PHA is the disperse phase for the blend PHA/PLA of 30/70. The second maximum is found for the inverse composition of 70/30. PLA has a heat-deflection temperature (HDT) substantially lower than PHA. For the blends, the HDT increases with the increment in the percentage of the incorporation of PHA. With up to 50% PHA (PLA as matrix), the HDT is practically constant and equal to PLA value. Above this point (PHA matrix), the HDT of the polymer blends increases linearly with the percentage of addition of PHA.

Quantum-based Particle Swarm Optimization Application to Studies of Aggregated Consumption Shifting and Generation Scheduling in Smart Grids

Demand response programs and models have been developed and implemented for an improved performance of electricity markets, taking full advantage of smart grids. Studying and addressing the consumers’ flexibility and network operation scenarios makes possible to design improved demand response models and programs. The methodology proposed in the present paper aims to address the definition of demand response programs that consider the demand shifting between periods, regarding the occurrence of multi-period demand response events. The optimization model focuses on minimizing the network and resources operation costs for a Virtual Power Player. Quantum Particle Swarm Optimization has been used in order to obtain the solutions for the optimization model that is applied to a large set of operation scenarios. The implemented case study illustrates the use of the proposed methodology to support the decisions of the Virtual Power Player in what concerns the duration of each demand response event.