Demand response (DR) can compensate for imbalances in variable renewable energy supplies. This possibility is particularly interesting for electrochemical processes, due to their high energy intensity. To determine the technical feasibility and economic viability of DR, we chose the chlor-alkali process with subsequent polyvinyl chloride production, including intermediate storage for ethylene dichloride. We estimate the maximum possible cost savings of implementing load flexibility measures. A process model is set up to determine the system characteristic. Subsequent optimizations result in the facility's best possible dispatch depending on additional and minimum power load, storage volume, and cost of a load change. Real plant data are used to specify model parameters and validate the system characteristic and the plant dispatch. An economic evaluation reveals the economic advantages of efficiency and flexibility. The approach can be used to analyze the DR potential of other chlorine value chains or facilities with high electricity demand in general.
Renewable sources of energy supply an increasing share to the electricity mix although they show much more fluctuations than conventional energy sources. Hence, net stability and availability represent very large challenges. Demand response can positively contribute to the solution of this issue as large electricity consumers adapt their consumption to the available electricity. In the past, chloralkali electrolysis has been suggested as such a large consumer. Unfortunately, its main product, chlorine, cannot be easily stored in large amounts, so that downstream processes have to operate based on a fluctuating feed. This work reviews the processes within the chlorine value chain, determines the most promising ones for flexibilisation based on their chlorine consumption, and analyses these processes in more detail to assign them to one of four flexibility categories. It is shown that 45 % of the theoretical potential could be used for demand response right away. Highlights: • A novel approach to evaluate the flexibility of chemical processes is proposed. • The flexibility potential of the whole chlorine value chain is assessed. • The chlorine-consuming processes relevant for demand response are identified. • Subsequent processes limit demand response potential of chloralkali process. • The dichloroethane and the chloroacetic acid route have the highest potential.
Demand response is
a viable concept to deal with and benefit from
fluctuating electricity prices and is of growing interest to the electrochemical
industry. To assess the flexibility potential of such processes, a
generic, interdisciplinary methodology is required. We propose such
a methodology, in which the electrochemical fundamentals and the theoretical
potential are determined first by analyzing strengths, weaknesses,
opportunities, and threats. Afterward, experiments are conducted to
determine selectivity and yield under varying loads and to assess
the additional long-term costs associated with flexible operation.
An industrial-scale electrochemical process is assessed regarding
its technical, economic, and practical potential. The required steps
include a flow sheet analysis, the formulation and solution of a simplified
model for operation scheduling under various business options, and
a dynamic optimization based on rigorous, dynamic process models.
We apply the methodology to three electrochemical processes of different
technology readiness levelsthe syntheses of hydrogen peroxide,
adiponitrile, and 1,2-dichloroethane via chloralkali electrolysisto
illustrate the individual steps of the proposed methodology.
State-of-the-art thermodynamic simulation of energy conversion processes requires proprietary software. This article is an attempt to refute this statement. Based on object-oriented programming a simulation and exergy analysis of a combined cycle gas turbine is carried out in a free and open-source framework. Relevant basics of a thermodynamic analysis with exergy-based methods and necessary fluid property models are explained. Thermodynamic models describe the component groups of a combined heat and power system. The procedure to transform a physical model into a Python-based simulation program is shown. The article contains a solving algorithm for a precise gas turbine model with sophisticated equations of state. As an example, a system analysis of a combined cycle gas turbine with district heating is presented. Herein, the gas turbine model is validated based on literature data. The exergy analysis identifies the thermodynamic inefficiencies. The results are graphically presented in a Grassmann chart. With a sensitivity analysis a thermodynamic optimization of the district heating system is discussed. Using the exergy destruction rate in heating condensers or the overall efficiency as the objective function yields to different results.
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