Optimal pressure control using switching solenoid valves

This paper presents the mathematical modeling and the design of an optimal pressure tracking controller for an often used setup in pneumatic applications. Two pneumatic chambers are connected with a pneumatic tube. The pressure in the second chamber is to be controlled using two switching valves connected to the first chamber and based on the pressure measurement in the first chamber. The optimal control problem is formulated and solved using the MPC framework. The designed controller shows good tracking quality, while fulfilling hard constraints, like maintaining the pressure below a given upper bound

Bridging granularity gaps to decarbonize large-scale energy systems - The case of power system planning

The comprehensive evaluation of strategies for decarbonizing large- scale energy systems requires insights from many different perspectives. In energy systems analysis, optimization models are widely used for this purpose. However, they are limited in incorporating all crucial aspects of such a complex system to be sustainably transformed. Hence, they differ in terms of their spatial, temporal, technological, and economic perspective and either have a narrow focus with high resolution or a broad scope with little detail. Against this background, we introduce the so- called granularity gaps and discuss two possibilities to address them: increasing the resolutions of the established optimization models, and the different kinds of model coupling. After laying out open challenges, we propose a novel framework to design power systems in particular. Our exemplary concept exploits the capabilities of power system optimization, transmission network simulation, distribution grid planning, and agent- based simulation. This integrated framework can serve to study the energy transition with greater comprehensibility and may be a blueprint for similar multi-model analyses

Analyse der Integration erneuerbarer Energien in Deutschland und Europa unter Berücksichtigung der Versorgungssicherheit und dezentraler Flexibilitäten

Das Vorhaben greift den Forschungsbedarf auf, der aus dem vorangehenden Vorhaben INTEEVER (FKZ 03ET4020) hervorgegangen ist. Dieser betrifft zum einen den Grad der Genauigkeit und der Differenzierung der modelltechnischen Abbildung von Verbrauchern und Erzeugern im deutschen und europäischen Stromsystem und damit insbesondere die Modelleingangsdaten, die einen relevanten Einfluss auf die Ergebnisse haben. Zum anderen wird eine enge Kopplung von Energiesystemmodellierung und Leistungsflusssimulation im europäischen Verbundnetz angestrebt

Optimal pressure control using switching solenoid valves

This paper presents the mathematical modeling and the design of an optimal pressure tracking controller for an often used setup in pneumatic applications. Two pneumatic chambers are connected with a pneumatic tube. The pressure in the second chamber is to be controlled using two switching valves connected to the first chamber and based on the pressure measurement in the first chamber. The optimal control problem is formulated and solved using the MPC framework. The designed controller shows good tracking quality, while fulfilling hard constraints, like maintaining the pressure below a given upper bound

Optimal pressure control using switching solenoid valves

This paper presents the mathematical modeling and the design of an optimal pressure tracking controller for an often used setup in pneumatic applications. Two pneumatic chambers are connected with a pneumatic tube. The pressure in the second chamber is to be controlled using two switching valves connected to the first chamber and based on the pressure measurement in the first chamber. The optimal control problem is formulated and solved using the MPC framework. The designed controller shows good tracking quality, while fulfilling hard constraints, like maintaining the pressure below a given upper bound

The impact of spatial resolution in energy system optimization models on AC-power flow convergence

Energy system optimization models (ESOMs) are often used to design future energy supply systems in terms of scenario development. However, the representation of power grids in ESOMs – due to these having a much broader scope than only grids – is simplified, e.g., by spatial aggregation and DC-power flow constraints. Such simplification is necessary to obtain optimization problems that can be solved in reasonable time. As a consequence, the level of detail of ESOMs is not suitable for the evaluation of concrete implementation projects (e.g. projects of common interest). Hence, grid operators need to use much more detailed power system models based on AC-power flow representations. In this paper, we first discuss two dimensions of the gap between ESOMs and transmission network modeling, namely the spatial resolution and mathematical formulation scales. Second, we propose a coupling framework to bridge the gap. The proposed method is applied to a study case using the German power network to analyze the correlation between spatial resolution and AC-feasibility. First results with 44, 84 and 134 spatial clusters, show that commonly used resolutions, e.g., 16 clusters for a federal state level in Germany, are insufficient to observe convergence. Even with 84 spatial clusters, more than 2000 feasibility violations occur. This is nearly avoided (in 99,6% of the time steps in year) at 134 clusters, while this resolution still allows for a reduction of computing time of about 90% compared to solving the fully resolved ESOM. The results also show that the overloading of the branches using a DC-power flow approach can not be used to predict AC-feasibility

Spectrum of Autoantibodies in Tunisian Psychiatric Inpatients

International audienceOne hundred and three psychiatric inpatients (74 men) were assessed for a wide spectrum of autoantibodies including antinuclear, antismooth muscle, antimitochondrial, antiDNA, anti-phospholipid, anti-cardiolipin IgG and IgM, antikeratin, rheumatoid factor, antithyroperoxydase, antigliadin IgA and IgG, antitransgutaminase, and antiendomysium antibodies. Four groups of patients were considered separately, including 47 with schizophrenia, 23 with schizoaffective disorder, 16 with bipolar disorder and 17 patients with other different psychiatric diagnosis. Forty one healthy, age-and sex-matched blood donors were used as a control group. There were no significant difference in the prevalence of the different autoantibodies between patients (N = 103) and controls except for antigliadin IgG (30.1 vs 9.8 respectively, p = 0.01). Presence of autoantibodies was influenced by age but not by sex or treatment. As for diagnosis categories, patients with bipolar disorder presented significantly more autoantibodies than the three other categories and controls. These results point out a possible autoimmune activation in at least a subgroup of psychiatric patients especially amongst those suffering from bipolar disorder

Bridging granularity gaps to decarbonize large-scale energy systems

The comprehensive evaluation of strategies for decarbonizing large-scale energy systems requires insights from many different perspectives. In energy systems analysis, optimization models are widely used for this purpose. However, they are limited in incorporating all crucial aspects of such a complex system to be sustainably transformed. Hence, they differ in terms of their spatial, temporal, technological and economic perspective and either have a narrow focus with high resolution or a broad scope with little detail. Against this background, we introduce the so-called granularity gaps and discuss two possibilities to address them: increasing the resolutions of the established optimization models, and the different kinds of model coupling. After laying out open challenges, we propose a novel framework to design power systems. Our exemplary concept exploits the capabilities of energy system optimization, transmission network simulation, distribution grid planning and agent-based simulation. This integrated framework can serve to study the energy transition with greater comprehensibility and may be a blueprint for similar multi-model analyses