Energy system optimization is vital for tackling climate change and ensuring quality of life. This study examines how uncertainties in technology costs impact optimization results. Using stochastic optimization with probability distributions, it demonstrates that scenario optimization overestimates system costs based on expected expenses. A German energy model, encompassing electricity, heating, and transport, is used. Stochastic optimization with distributions is robust, enhancing confidence amidst cost assumption disagreements and unforeseen input variations.
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Energy system optimization is vital for tackling climate change and ensuring quality of life. This study examines how uncertainties in technology costs impact optimization results. Using stochastic optimization with probability distributions, it demonstrates that scenario optimization overestimates system costs based on expected expenses. A German energy model, encompassing electricity, heating, and transport, is used. Stochastic optimization with distributions is robust, enhancing confidence am...
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