RHEIA: Robust design optimization of renewable Hydrogen
and dErIved energy cArrier systems

Coppitters, Diederik; Tsirikoglou, Panagiotis; Paepe, Ward De; Kyprianidis, Konstantinos; Kalfas, A. I.; Contino, Francesco

doi:10.21105/joss.04370

Cited by 11 publications

(9 citation statements)

References 14 publications

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“…Therefore, we adopted the computationally-efficient PCE surrogate modelling technique 45 . We used the Python package RHEIA, developed in our research group, to construct the PCEs 46 . While a concise overview of the Polynomial Chaos Expansion (PCE) method is presented in the subsequent paragraph, a comprehensive exposition of its various stages is available in Sudret 45 .…”

Section: Methodsmentioning

confidence: 99%

“…We developed the ADO framework in Python. Starting from the Python package RHEIA 46 that performs PCE-assisted RDO, the package has been modified in two main aspects to perform ADO: The NSGA-III optimization method has been integrated from the Python package DEAP 53 , and the specific objectives of the ADO framework were calculated on the distribution generated by the PCEs.…”

Section: Methodsmentioning

confidence: 99%

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Optimizing upside variability and antifragility in renewable energy system design

Coppitters

Contino

2023

Sci Rep

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Despite the considerable uncertainty in predicting critical parameters of renewable energy systems, the uncertainty during system design is often marginally addressed and consistently underestimated. Therefore, the resulting designs are fragile, with suboptimal performances when reality deviates significantly from the predicted scenarios. To address this limitation, we propose an antifragile design optimization framework that redefines the indicator to optimize variability and introduces an antifragility indicator. The variability is optimized by favoring upside potential and providing downside protection towards a minimum acceptable performance, while the skewness indicates (anti)fragility. An antifragile design primarily enhances positive outcomes when the uncertainty of the random environment exceeds initial estimations. Hence, it circumvents the issue of underestimating the uncertainty in the operating environment. We applied the methodology to the design of a wind turbine for a community, considering the Levelized Cost Of Electricity (LCOE) as the quantity of interest. The design with optimized variability proves beneficial in 81% of the possible scenarios when compared to the conventional robust design. The antifragile design flourishes (LCOE drops by up to 120%) when the real-world uncertainty is higher than initially estimated in this paper. In conclusion, the framework provides a valid metric for optimizing the variability and detects promising antifragile design alternatives.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Optimizing upside variability and antifragility in renewable energy system design

Coppitters

Contino

2023

Sci Rep

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“…Design variables encompass capacities of the PV array, wind farm, electrolyzer array, battery stack, and hydrogen storage. In alignment with established guidelines, specifically advocating for 10 population samples per design variable [25], we have chosen a population size of 50. Finally, the convergence of the Pareto front hypervolume serves as the stopping criterion for the optimization process.…”

Section: Multi-objective Optimizationmentioning

confidence: 99%

“…A high correlation exists between the impacts on the Climate change and Ocean acidification control variables (illustrated in Supplementary Information, S7), as the impact on these categories is driven by mainly the same elementary flows [16]. Therefore, the impact on Climate change -CO 2 concentration is selected as a first objective, The results of the multi-objective optimization using the Nondominated Sorting Genetic Algorithm [25] reveal a trade-off between minimizing the LCOH and the impact on the PB control variables for the various import pathways considered (Figure 4). Fig.…”

Section: Multi-objective Optimization Of the Planetary Boundary Contr...mentioning

confidence: 99%

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Towards importing renewable hydrogen within planetary boundaries

Coppitters,

Ghuys,

Verleysen

et al. 2024

Preprint

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In pursuit of reducing greenhouse gas emissions, the European Union plans to annually import ten million tonnes of renewable hydrogen. While the economic viability of hydrogen importation is established, environmental assessments are limited to comparisons and lack an evaluation of absolute sustainability. Therefore, we conducted a multi-objective optimization and absolute sustainability assessment with respect to planetary boundaries under current conditions and future scenarios, considering hydrogen, ammonia, and methane as energy carriers. Under current conditions, absolute sustainability is achievable under utilitarian sharing principles, utilizing hydrogen or ammonia as energy carrier, and relying on wind energy and storage at the source location. Looking ahead, cost-effective import pathways, powered by wind and solar energy, can achieve absolute sustainability from 2030 onward, when the world follows an optimistic sustainability pathway with ambitious climate mitigation targets. To attain absolute sustainability in other scenarios, improved practices and new materials in photovoltaic array design should be prioritized.

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Is waste heat recovery a promising avenue for the Carnot battery? Techno-economic optimisation of an electric booster-assisted Carnot battery integrated into different data centres

Laterre,

Dumont,

Lemort

et al. 2024

Energy Conversion and Management

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RHEIA: Robust design optimization of renewable Hydrogen and dErIved energy cArrier systems

Cited by 11 publications

References 14 publications

Optimizing upside variability and antifragility in renewable energy system design

Optimizing upside variability and antifragility in renewable energy system design

Towards importing renewable hydrogen within planetary boundaries

Is waste heat recovery a promising avenue for the Carnot battery? Techno-economic optimisation of an electric booster-assisted Carnot battery integrated into different data centres

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