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Integration of Renewable Energy Sources in future power systems: The role of storage
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“Such systems use machine learning algorithms to forecast when the sun or wind will be available, and energy distribution is then appropriately re-allocated to ensure a constant supply and diminish the use of non-renewable energy sources43–45.”
From A decision-support framework for evaluating AI-enabled ESG strategies in the context of sustainable manufacturing systems (2025) · cites this paper as [44]
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Jacobson, M. Z., & Delucchi, M. A. (2010) · Energy Policy · doi:10.1016/j.enpol.2010.11.040 · Cited by 1,570
Energy system analysis of 100% renewable energy systems—The case of Denmark in years 2030 and 2050
Lund, H., & Mathiesen, B. V. (2008) · Energy · doi:10.1016/j.energy.2008.04.003 · Cited by 1,127
Budischak, C., Sewell, D., Thomson, H., Mach, L., Veron, D. E., & Kempton, W. M. (2012) · Journal of Power Sources · doi:10.1016/j.jpowsour.2012.09.054 · Cited by 531
Seasonal optimal mix of wind and solar power in a future, highly renewable Europe
Heide, D., von Bremen, L., Greiner, M., Hoffmann, C., Speckmann, M., & Bofinger, S. (2010) · Renewable Energy · doi:10.1016/j.renene.2010.03.012 · Cited by 518
Technical challenges associated with the integration of wind power into power systems
Georgilakis, P. S. (2006) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2006.10.007 · Cited by 405
Grid vs. storage in a 100% renewable Europe
Steinke, F., Wolfrum, P., & Hoffmann, C. (2012) · Renewable Energy · doi:10.1016/j.renene.2012.07.044 · Cited by 337
Heide, D., Greiner, M., von Bremen, L., & Hoffmann, C. (2011) · Renewable Energy · doi:10.1016/j.renene.2011.02.009 · Cited by 272
Least cost 100% renewable electricity scenarios in the Australian National Electricity Market
Elliston, B., MacGill, I. F., & Diesendorf, M. O. (2013) · Energy Policy · doi:10.1016/j.enpol.2013.03.038 · Cited by 265
Elliston, B., Diesendorf, M. O., & MacGill, I. F. (2012) · Energy Policy · doi:10.1016/j.enpol.2012.03.011 · Cited by 262
Storage and balancing synergies in a fully or highly renewable pan-European power system
Rasmussen, M. G., Andresen, G. B., & Greiner, M. (2012) · Energy Policy · doi:10.1016/j.enpol.2012.09.009 · Cited by 259
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“Therefore, the development of large-scale energy storage technologies is imperative for the effective integration of renewable energy sources, such as solar and wind, into the power sys-tem (Weitemeyer et al. 2015; Ji et al. 2024).”
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Metadata
- Authors
- Weitemeyer, S., Kleinhans, D., Vogt, T., & Agert, C.
- Affiliations
- Carl von Ossietzky Universität Oldenburg (DE)
- Corresponding author
- Weitemeyer, Stefan
- Venue
- Renewable Energy
- Publisher
- Elsevier BV
- Published
- 2015-03
- Volume
- 75
- Pages
- 14-20
- ISSN
- 0960-1481 (ISSN-L)
- OpenAlex
- W2058391473
- Cited by
- 514
- References
- 24
- Citations by year
- 2026: 27 · 2025: 41 · 2024: 43 · 2023: 44 · 2022: 48 · 2021: 49 · 2020: 67 · 2019: 58 · 2018: 46 · 2017: 41 · 2016: 30 · 2015: 20
- FWCI
- 16.12
- Type
- journal article
- Language
- en
- Open access
- green
- arxiv.org
- Locations
- Renewable Energy (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- arXiv (Cornell University)
- Funders
- German Federal Ministry of Education and Research (03SF0439A)
- Lower Saxony Ministry for Science and Culture (MWK)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Integrated Energy Systems Optimization
- Physical Sciences › Energy › Energy Engineering and Power Technology › Power Systems and Renewable Energy
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Electric Power System Optimization
- Keywords
- renewable energy integration, energy storage, storage efficiency, wind energy, solar energy, curtailment, flexible power plants, seasonal storage, power system modeling
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