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The PHOTOPUR project aims to develop a photocatalytic process as a type of AOPs (Advanced Oxidation Processes) for the elimination of plant protection products (PPP) of the cleaning water used to wash sprayers. At INES a PV based energy supply for the photocatalytic cleaning system was developed within the framework of two bachelor theses and assembled as a demonstration unit. Then the system was step by step extended with further process automation features and pushed to a remote operating device. The final system is now available as a mobile unit mounted on a lab table. The latest step was the photocatalytic reactor module which completed the first PHOTOPUR prototype. The system is actually undergoing an intensive testing phase with performance checks at the consortium partners. First results give an overview about the successful operation.
This paper presents the use of model predictive control (MPC) based
approach for peak shaving application of a battery in a Photovoltaic (PV) battery
system connected to a rural low voltage gird. The goals of the MPC are to shave
the peaks in the PV feed-in and the grid power consumption and at the same
time maximize the use of the battery. The benefit to the prosumer is from the
maximum use of the self-produced electricity. The benefit to the grid is from the
reduced peaks in the PV feed-in and the grid power consumption. This would
allow an increase in the PV hosting and the load hosting capacity of the grid.
The paper presents the mathematical formulation of the optimal control problem
along with the cost benefit analysis. The MPC implementation scheme in the
laboratory and experiment results have also been presented. The results show
that the MPC is able to track the deviation in the weather forecast and operate
the battery by solving the optimal control problem to handle this deviation.
Model-based analysis of Electrochemical Pressure Impedance Spectroscopy (EPIS) for PEM Fuel Cells
(2019)
Electrochemical impedance spectroscopy (EIS) is a widely-used diagnostic technique to characterize electrochemical processes. It is based on the dynamic analysis of two electrical observables, that is, current and voltage. Electrochemical cells with gaseous reactants or products, in particular fuel cells, offer an additional observable, that is, the gas pressure. The dynamic coupling of current or voltage with gas pressure gives rise to a number of additional impedance definitions, for which we have previously introduced the term electrochemical pressure impedance spectroscopy (EPIS) [1,2]. EPIS shows a particular sensitivity towards transport processes of gas-phase or dissolved species, in particular, diffusion coefficients and transport pathway lengths. It is as such complementary to standard EIS, which is mainly sensitive towards electrochemical processes. First EPIS experiments on PEM fuel cells have recently been shown [3].
We present a detailed modeling and simulation analysis of EPIS of a PEM fuel cell. We use a 1D+1D continuum model of a fuel/air channel pair with GDL and MEA. Backpressure is dynamically varied, and the resulting simulated oscillation in cell voltage is evaluated to yield the ▁Z_( V⁄p_ca ) EPIS signal. Results are obtained for different transport situations of the fuel cell, giving rise to very complex EPIS shapes in the Nyquist plot. This complexity shows the necessity of model-based interpretation of the complex EPIS shapes. Based on the simulation results, specific features in the EPIS spectra can be assigned to different transport domains (gas channel, GDL, membrane water transport).
Cell lifetime diagnostics and system be-havior of stationary LFP/graphite lithium-ion batteries
(2018)
Modelling detailed chemistry in lithium-ion batteries: Insight into performance, ageing and safety
(2018)
In the dual membrane fuel cell (DM-Cell), protons formed at the anode and oxygen ions formed at the cathode migrate through their respective dense electrolytes to react and form water in a porous composite layer called dual membrane (DM). The DM-Cell concept was experimentally proven (as detailed in Part I of this paper). To describe the electrochemical processes occurring in this novel fuel cell, a mathematical model has been developed which focuses on the DM as the characteristic feature of the DM-Cell. In the model, the porous composite DM is treated as a continuum medium characterized by effective macro-homogeneous properties. To simulate the polarization behavior of the DM-Cell, the potential distribution in the DM is related to the flux of protons and oxygen ions in the conducting phases by introducing kinetic and transport equations into charge balances. Since water pressure may affect the overall formation rate, water mass balances across the DM and transport equations are also considered. The satisfactory comparison with available experimental results suggests that the model provides sound indications on the effects of key design parameters and operating conditions on cell behavior and performance.
The uncertain and time-variant nature of renewable energy results in the need to deal with peaks in the production of energy. One approach is to achieve a load shift and thereby help balancing the grid by using thermally Activated Building Systems (TABS). Control systems currently in place do not exploit the full potential of TABS. This paper reviews how Model Predictive Control can possibly reduce the fluctuations of the demand and supply of (renewable) energy as it enables the TABS to react to the dynamics of weather and its impact on the grid at any time.
Die Veränderungen in der Energieversorgung führen zu einer neuen Systemarchitektur der Stromversorgung, die nur durch einen massiven Einsatz von Informations- und Kommunikationstechnologien (IKT) bewältigt werden kann und meist als „Smart Grid“ bezeichnet wird. Während es bereits umfangreiche Forschungsarbeiten und Demonstrationsprojekte zu einzelnen technologischen Komponenten gibt, existieren noch wenige Überlegungen, in welchen technologischen Schritten eine Migration hin zu Smart Grids durchgeführt werden sollte, die sowohl betriebstechnisch zukunftssicher ist, als auch marktgetriebene Innovationen begünstigt. Der Beitrag veranschaulicht die Herleitung solcher Migrationspfade im Rahmen eines schrittweisen Vorgehens. Zunächst werden Zukunftsszenarien für das Jahr 2030 konstruiert, um die maßgeblichen, oft auch nichttechnischen Einflussfaktoren auf das Smart Grid zu identifizieren. Darauf aufbauend werden die wesentlichen IKT-bezogenen Technologiefelder und ihre Zuordnung zu den Domänen der Energiewirtschaft beschrieben. Für jedes Technologiefeld werden die in den nächsten zwei Jahrzehnten denkbaren Entwicklungsstufen ermittelt und deren Abhängigkeit untereinander analysiert. Die gemeinsame Betrachtung von Szenarien, der Entwicklungsstufen der Technologiefelder und deren Interdependenzen führen schließlich zu einer Roadmap, welche die Migrationspfade in das Smart Grid beschreiben. Es lassen sich drei Entwicklungsphasen erkennen: Die Konzeptionsphase, die Integrationsphase und die Fusionsphase. Die präsentierten Ergebnisse entstammen dem Projekt „Future Energy Grid – Migrationspfade ins Internet“, welches vom Bundesministerium für Wirtschaft und Technologie im Rahmen des E-Energy-Programms (Förderkennzeichen 01ME10012A und 01ME10013) gefördert wurde.