Adaptive Robust Optimization Approach for Energy System Optimization Models
IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT Europe), pp. 1–5
Abstract
Climate policy goals require massive expansion of renewable energy plants as well as transmission capacities and sector-coupling technologies. Although this requires a fundamental transformation, the energy system must be able to reliably supply future energy demand, especially for electricity and gas. In this context, Energy System Optimization Models (ESOMs) provide recommendations on future energy system designs. However, these models rely on deterministic assumptions about future developments. This reduces the robustness and validity of their findings in the context of uncertainty, especially with respect to future energy demands. To address this issue, Robust Optimization methods offer promising approaches to enhance the resilience of the optimized energy system designs by explicitly accounting for uncertainty in model inputs.In this context, this paper introduces an Adaptive Robust Optimization framework to consider uncertainty in future energy demands and applies it to a state-of-the art ESOM. The resulting model can be used to identify robust capacity expansions of generation and transmission infrastructures, that protect against the uncertainty across various scenarios.
Authors 3
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Affiliation as printed
RWTH Aachen University,Institute of High Voltage Equipment and Grids, Digitalization and Energy Economics (IAEW),Aachen,Germany
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Affiliation as printed
RWTH Aachen University,Institute of High Voltage Equipment and Grids, Digitalization and Energy Economics (IAEW),Aachen,Germany
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Affiliation as printed
RWTH Aachen University,Institute of High Voltage Equipment and Grids, Digitalization and Energy Economics (IAEW),Aachen,Germany
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