Multi-Objective Decision Support for Industrial Energy System Transformation: Exploring Near-Pareto-Optimal Design Alternatives
Computers & Chemical Engineering, vol. 211, pp. 109653
Abstract
The transformation of industrial energy systems to low-carbon systems is challenging due to conflicting decision-making criteria, overwhelming decision alternatives, and information overload. Multi-objective optimization identifies tradeoffs between conflicting objectives, while methods to explore near-optimal alternatives reveal decision flexibilities. This work combines multi-objective optimization with exploring near-optimal energy system design alternatives to analyze the objective and the design space of energy system design optimization problems. First, we identify Pareto-optimal design alternatives using the augmented epsilon-constraint method. Starting from selected Pareto-optimal design alternatives, we explore near-Pareto-optimal design spaces across the Pareto front using the Modeling All Alternatives method. We quantify the impact of objective relaxation in a sensitivity analysis to offer insights into the tradeoff between design flexibility and Pareto-optimality. To manage decision complexity, we introduce an interactive decision-support tool that enables decision-makers to explore design flexibilities and incorporate additional constraints in real time.
Authors 5
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Affiliation as printed
Institute of Technical Thermodynamics, RWTH Aachen University, Schinkelstr. 8, 52062 Aachen, Germany
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Affiliation as printed
Institute of Technical Thermodynamics, RWTH Aachen University, Schinkelstr. 8, 52062 Aachen, Germany
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Affiliation as printed
Institute of Technical Thermodynamics, RWTH Aachen University, Schinkelstr. 8, 52062 Aachen, Germany
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Affiliation as printed
Institute of Technical Thermodynamics, RWTH Aachen University, Schinkelstr. 8, 52062 Aachen, Germany
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Affiliation as printed
Institute of Technical Thermodynamics, RWTH Aachen University, Schinkelstr. 8, 52062 Aachen, Germany
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