Development and analysis of a multi-node dynamic model for the simulation of stratified thermal energy storage

To overcome non-programmability issues that limit the market penetration of renewable energies, the use of thermal energy storage has become more and more significant in several applications where there is a need for decoupling between energy supply and demand. The aim of this paper is to present a multi-node physics-based model for the simulation of stratified thermal energy storage, which allows the required level of detail in temperature vertical distribution to be varied simply by choosing the number of nodes and their relative dimensions. Thanks to the chosen causality structure, this model can be implemented into a library of components for the dynamic simulation of smart energy systems. Hence, unlike most of the solutions proposed in the literature, thermal energy storage can be considered not only as a stand-alone component, but also as an important part of a more complex system. Moreover, the model behavior has been analyzed with reference to the experimental results from the literature. The results make it possible to conclude that the model is able to accurately predict the temperature distribution within a stratified storage tank typically used in a district heating network with limitations when dealing with small storage volumes and high flow rates

Nonlinear model predictive control of an Organic Rankine Cycle for exhaust waste heat recovery in automotive engines

Energy recovery from exhaust gas waste heat can be regarded as an effective way to improve the energy efficiency of automotive powertrains, thus reducing CO2 emissions. The application of Organic Rankine Cycles (ORCs) to waste heat recovery is a solution that couples effectiveness and reasonably low technological risks. On the other hand, ORC plants are rather complex to design, integrate and control, due to the presence of heat exchangers operating with phase changing fluid, and several control devices to regulate the thermodynamic states of the systems. Furthermore, the power output and efficiency of ORC systems are extremely sensitive to the operating conditions, requiring precise control of the evaporator pressure and superheat temperature. This paper presents an optimization and control design study for an Organic Rankine Cycle plant for automotive engine waste heat recovery. The analysis has been developed using a detailed Moving Boundary Model that predicts mass and energy flows through the heat exchangers, valves, pumps and expander, as well as the system performance. Starting from the model results, a nonlinear model predictive controller is designed to optimize the transient response of the ORC system. Simulation results for an acceleration-deceleration test illustrate the benefits of the proposed control strategy

Am J Prev Med

CC999999/Intramural CDC HHS/United States2017-02-19T00:00:00Z26456878PMC531651

Hybridization methodology based on DP algorithm for hydraulic mobile machinery — Application to a middle size excavator

Fuel consumption and pollutant emission reduction are and will continue to be the most important drivers in the improvement of mobile machinery hydraulic system. Many different solutions and options are proposed in the literature to improve the machinery fuel efficiency, and many of these are based on hybrid solutions. The aim of this paper is to present a hybridization methodology which allows to compare different system layouts, to dimension the energy storage devices, to define the optimal control policies, and finally to determine the more effective hybrid system layout. The proposed methodology takes advantage of the dynamic programming (DP) algorithm. The machinery mathematical model and information about working cycle have to be known “a priori” in order to take advantage of the presented methodology. The hybridization methodology has been applied to a hydraulic excavator as a guideline example, and the results are reported in the last section of the paper

New insight into the role of the metal oxidation state in controlling the selectivity of the Cr-(SNS) ethylene trimerization catalyst

The tri- and divalent complexes of the 2,6-bis(RSCH2)pyridine [R = Ph, Cy] ligands have been prepared. Upon activation with MAO, both species are catalysts for ethylene oligomerization of moderate activity. However, while the trivalent catalysts produced only 1-hexene, the divalent species gave a statistical distribution of oligomers. This clear difference in catalytic behavior indicates that the two oxidation states are not interconnected during the catalytic cycle as it happens instead with other oligomerization catalytic systems. The trivalent precursor is not reduced and the divalent is not oxidized. Treatment of the trivalent catalyst precursors with either MAO or other R3Al species afforded intractable materials. Instead, similar reactions with the divalent complexes gave new cationic species, which have been characterized by X-ray analysis. These complexes have preserved the divalent state of chromium during the reaction and still produce, upon further activation, a statistical distribution of oligomers. This reiterates the non-interconvertibility of the di- and trivalent oxidation states and the different degree of selectivity for which they are responsible