E3S Web Conf.
Volume 238, 2021100RES 2020 – Applied Energy Symposium (ICAE), 100% RENEWABLE: Strategies, Technologies and Challenges for a Fossil Free Future
|Number of page(s)||6|
|Published online||16 February 2021|
Robust design optimization of a renewable-powered demand with energy storage using imprecise probabilities
University of Mons, Thermal Engineering and Combustion Unit, 7000 Mons, Belgium
2 Vrije Universiteit Brussel, Fluid and Thermal Dynamics, 1050 Brussels, Belgium
3 Université Catholique de Louvain, Institute of Mechanics, Materials and Civil Engineering, 1348 Louvain-la-Neuve, Belgium
* Corresponding author: firstname.lastname@example.org
During renewable energy system design, parameters are generally fixed or characterized by a precise distribution. This leads to a representation that fails to distinguish between uncertainty related to natural variation (i.e. future, aleatory uncertainty) and uncertainty related to lack of data (i.e. present, epistemic uncertainty). Consequently, the main driver of uncertainty and effective guidelines to reduce the uncertainty remain undetermined. To assess these limitations on a grid-connected household supported by a photovoltaic-battery system, we distinguish between present and future uncertainty. Thereafter, we performed a robust design optimization and global sensitivity analysis. This paper provides the optimized designs, the main drivers of the variation in levelized cost of electricity and the effect of present uncertainty on these drivers. To reduce the levelized cost of electricity variance for an optimized photovoltaic array and optimized photovoltaic-battery design, improving the determination of the electricity price for every specific scenario is the most effective action. For the photovoltaic-battery robust design, the present uncertainty on the prediction accuracy of the electricity price should be addressed first, before the most effective action to reduce the levelized cost of electricity variance can be determined. Future work aims at the integration of a heat demand and hydrogen-based energy systems.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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