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Impact of multi-annual renewable energy variability on the optimal sizing of off-grid systems
Shanghai Jiao Tong University, China.
Wrocław University of Science and Technology, Poland.
Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
Universidad de la Costa, Colombia.
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2023 (English)In: Renewable & sustainable energy reviews, ISSN 1364-0321, E-ISSN 1879-0690, Vol. 183, article id 113514Article in journal (Refereed) Published
Abstract [en]

It remains a significant technical and economic challenge to fully power large-scale grids with intermittent renewable energy (RE). Meanwhile, due to the rapid decrease in the cost of RE power generation technologies in recent years, the number of real-world implementations and studies dedicated to the optimal capacity sizing of renewable off-grid systems has increased. However, a common approach in the literature is to rely on typical single-year meteorological and demand data. A negative effect of this assumption is that it does not consider the RE inter-annual variability, which might cause blackouts or oversizing the system and large curtailments. This study employs 43 years of hourly solar, wind, and demand data, coupled with different microgrid configurations, to evaluate the impact of diverse simulation periods on the total system cost, optimal RE mix, and system reliability. Our findings indicate that extended simulation periods considerably increased renewable energy systems (RES) reliability and that the resulting configurations can be up to 94% more robust than those obtained using a single year of data. Additionally, the optimal energy storage requirements increased when considering longer simulation periods, indicating that short simulation periods could underestimate energy storage capacities in off-grid systems. The overestimations or underestimations resulting from optimizations based on single-year data directly affect the long-term sustainability, reliability, and cost-effectiveness of the RES.

Place, publisher, year, edition, pages
Elsevier Ltd , 2023. Vol. 183, article id 113514
Keywords [en]
Battery storage, Long-term modeling horizons, Mixed integer linear programming, Off-grid, Pumped hydro storage, Variable renewable energy, Digital storage, Electric batteries, Integer programming, Pumped storage power plants, Reliability, Renewable energy resources, Integer Linear Programming, Long-term modeling horizon, Long-term models, Mixed integer linear, Off-grids, Renewable energies, Variable renewable energies, Cost effectiveness
National Category
Energy Engineering
Identifiers
URN: urn:nbn:se:mdh:diva-63888DOI: 10.1016/j.rser.2023.113514ISI: 001034878300001Scopus ID: 2-s2.0-85164250811OAI: oai:DiVA.org:mdh-63888DiVA, id: diva2:1783146
Available from: 2023-07-19 Created: 2023-07-19 Last updated: 2023-08-23Bibliographically approved

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Guezgouz, Mohammad

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