Robust policy optimization for the pathway towards a sustainable whole-energy system using a hierarchical multi-objective reinforcement learning approach
immc | Louvain-la-Neuve
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Robust policy optimization for the pathway towards a sustainable whole-energy system using a hierarchical multi-objective reinforcement learning approach
05 Oct
The transition towards carbon-neutrality of a whole-energy system (i.e. including all streams of energy carriers and demands) is uncertain. Therefore, instead of establishing single-shot plans towards 2050 (and beyond), i.e. perfect foresight, policy makers rather go through multiple rolling-horizon short-term decisions, i.e. myopic approach.
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Robust policy optimization for the pathway towards a sustainable whole-energy system using a hierarchical multi-objective reinforcement learning approach
05 Oct
The transition towards carbon-neutrality of a whole-energy system (i.e. including all streams of energy carriers and demands) is uncertain. Therefore, instead of establishing single-shot plans towards 2050 (and beyond), i.e. perfect foresight, policy makers rather go through multiple rolling-horizon short-term decisions, i.e. myopic approach.