Uncertainty Analysis for Data-Driven Chance-Constrained Optimization

In this contribution our developed framework for data-driven chance-constrained optimization is extended with an uncertainty analysis module. The module quantifies uncertainty in output variables of rigorous simulations. It chooses the most accurate parametric continuous probability distribution model, minimizing deviation between model and data. A constraint is added to favour less complex models with a minimal required quality regarding the fit. The bases of the module are over 100 probability distribution models provided in the Scipy package in Python, a rigorous case-study is conducted selecting the four most relevant models for the application at hand. The applicability and precision of the uncertainty analyser module is investigated for an impact factor calculation in life cycle impact assessment to quantify the uncertainty in the results. Furthermore, the extended framework is verified with data from a first principle process model of a chloralkali plant, demonstrating the increased precision of the uncertainty description of the output variables, resulting in 25% increase in accuracy in the chance-constraint calculation.BMWi, 0350013A, ChemEFlex - Umsetzbarkeitsanalyse zur Lastflexibilisierung elektrochemischer Verfahren in der Industrie; Teilvorhaben: Modellierung der Chlor-Alkali-Elektrolyse sowie anderer Prozesse und deren Bewertung hinsichtlich Wirtschaftlichkeit und möglicher HemmnisseDFG, 414044773, Open Access Publizieren 2019 - 2020 / Technische Universität Berli

Optimal Control of Surfactant containing Multiphase Systems – Challenges and Solution Strategies for a stable Mini-Plant Operation

In this contribution, a model-based approach for the control and stable operation of a mini-plant for homogeneously catalysed reactions in microemulsions is presented. Within these systems, the control of the crucial reaction and phase separation steps is hindered by sensitive shifting operation windows and immeasurable concentrations. Combining the optical observation of the separation state and an underlying phase separation model, a soft-sensor is created to identify these relevant concentrations. Together with plant measurements, a moving horizon state estimation is used to calculate a consistent and validated state of the full plant model, which is then used in a dynamic optimization to calculate optimal trajectories for the mini-plant operation. Hereby, a stable separation is achieved for up to 200 h mini-plant campaigns, alongside an efficient reaction performance with up to 38 % yield and a chemoselectivity of 95 %.DFG, 56091768, TRR 63: Integrierte chemische Prozesse in flüssigen Mehrphasensysteme

Dynamic Modelling and Operation of the Chlor-Alkali Process

Chlorine it is commonly produced through the Chlor-alkali process, which is an electrochemical process – the process energy consumption dominates the production cost. Therefore, optimization of the process has become a major issue to achieve energy conservation and cost effective production. This study aims at investigating the transient and steady-state behavior of the chlorine production system through process modeling and simulation. Material balance and energy balance of the Chlor-alkali membrane process (electrolysis), brine pre-treatment, and chlorine handling are modelled and investigated using rigorous models. MOSAIC and MATLAB, are used to model and to simulate the process response when receiving dynamic input. For validation, the simulation result is compared to experimental data

Development of a State Estimation Environment for the Optimal Control of a Mini-plant for the Hydroformylation in Microemulsions

A state estimation framework for a surfactant containing multiphase process for the hydroformylation of longchained alkenes is presented. Firstly, available state estimation methods, such as the extended Kalman filter, the unscented Kalman filter and the particle filter are compared regarding their usability in processes with high model and measurement uncertainty. Subsequently, an MHE-based state estimation algorithm is introduced. This includes an approach, which handles the occurring multi-rate measurements by dividing the state estimation into two separate steps. Finally, the implementation is discussed regarding necessary requirements and the state estimation framework is applied within long-term real process operation in a mini-plant.DFG, 56091768, TRR 63: Integrierte chemische Prozesse in flüssigen Mehrphasensysteme

Towards demand-side management of the chlor-alkali electrolysis: Dynamic, pressure-driven modeling and model validation of the 1,2-dichloroethane synthesis

A promising application of demand-side management is the chlor-alkali electrolysis. However, storing the produced chlorine for flexibility should be avoided whenever possible. If PVC is produced from chlorine, storing the intermediate 1,2-dichloroethane resulting from direct chlorination of ethene is a better alternative as it is less toxic than chlorine and can be easily stored. Currently, no dynamic process models to study the process behavior or to develop optimal trajectories for the 1,2-dichloroethane production under different demand response scenarios are available. Hence, we formulate and solve a dynamic, pressure-driven model of the synthesis of 1,2-dichloroethane and validate it with real process data in this contribution. As part of this dynamic model, differentiable formulations for weeping and the flow over a weir of a distillation tray are presented, which are also valid whenever certain trays run dry.BMWi, 0350013A, Verbundvorhaben: ChemEFlex - Umsetzbarkeitsanalyse zur Lastflexibilisierung elektrochemischer Verfahren in der Industrie; Teilvorhaben: Modellierung der Chlor-Alkali-Elektrolyse sowie anderer Prozesse und deren Bewertung hinsichtlich Wirtschaftlichkeit und möglicher Hemmniss

Dynamic Model of Chloralkali Membrane Process

Chloralkali is one of the most important and energy intensive processes in the chemical industry. The process produces chlorine through electrochemical conversion. The process's energy consumption is a major production cost for the chloralkali industry. Since the demand for energy efficiency and environmentally friendly processes in industry increases, ion exchange membranes are used intensively in the process. One of the prospective energy sources for this process is renewable energy, which shows strong fluctuations and highly unpredictable behavior. Dynamic behavior of the process becomes important to measure and predict the feasibility of the process. Therefore, modelling of the process dynamics is required. Rigorous model of material balance and voltage balance of the process are developed and investigated in this paper. The material transport phenomena inside the electrolyser are modelled considering a number of driving forces. The developed model also predicts the voltage and current density of the cell. The process simulation result is compared to experimental data

A pressure-driven, dynamic model for distillation columns with smooth reformulations for flexible operation

Dynamic models for plants including the startup or shutdown phase are still scarce as the (dis-)appearence of phases or streams is challenging to implement. We present an approach to model a distillation column, in which these operation modes are also considered without exchanging equations. For this purpose, the well-known modeling equations for distillation columns are reformulated robustly to allow for the disappearance of the vapor phase without discontinuities. The reformulation does not depend on solving an optimization problem and could easily be applied to other column types or different unit operations. The proposed model is solved in two case studies with 10 and 40 trays, respectively. In these case studies, the influence of single phenomena on the obtained dynamic profiles is investigated, e.g., weeping, which are often neglected. The proposed modeling approach yields a dynamic model that can be solved without reinitialization for a realistically large number of trays.BMBF, 0350013A, Verbundvorhaben: ChemEFlex - Umsetzbarkeitsanalyse zur Lastflexibilisierung elektrochemischer Verfahren in der Industrie; Teilvorhaben: Modellierung der Chlor-Alkali-Elektrolyse sowie anderer Prozesse und deren Bewertung hinsichtlich Wirtschaftlichkeit und möglicher Hemmniss

Development of a Mobile Pilot Plant for the Evaluation of Novel Scrubbing Liquids for the Absorption of CO2 From Industrial Gases

Most available scrubbing liquids suffer from either high heating duties for the regeneration or vulnerability towards gas components. In order to increase the efficiency of the absorption process a novel scrubbing liquid has been developed by thyssenkrupp Industrial Solutions AG. For verifying relevance and feasibility of long-term operation of the new fluid assumptions for installation were created – conceptual design and detailed simulation of the process without detailed thermodynamic information

Dynamic Modeling and Operation of the Chlor-Alkali Process

Chlorine it is commonly produced through the Chlor-alkali process, which is an electrochemical process – the process energy consumption dominates the production cost. Therefore, optimization of the process has become a major issue to achieve energy conservation and cost effective production. This study aims at investigating the transient and steady-state behavior of the chlorine production system through process modeling and simulation. Material balance and energy balance of the Chlor-alkali membrane process (electrolysis), brine pre-treatment, and chlorine handling are modelled and investigated using rigorous models. MOSAIC and MATLAB, are used to model and to simulate the process response when receiving dynamic input. For validation, the simulation result is compared to experimental data

Dynamic Modeling and Operation of the Chlor-Alkali Process

Chlorine it is commonly produced through the Chlor-alkali process, which is an electrochemical process – the process energy consumption dominates the production cost. Therefore, optimization of the process has become a major issue to achieve energy conservation and cost effective production. This study aims at investigating the transient and steady-state behavior of the chlorine production system through process modeling and simulation. Material balance and energy balance of the Chlor-alkali membrane process (electrolysis), brine pre-treatment, and chlorine handling are modelled and investigated using rigorous models. MOSAIC and MATLAB, are used to model and to simulate the process response when receiving dynamic input. For validation, the simulation result is compared to experimental data