The DOI matches its Crossref record; 99 of the 99 references it cites were found in a registry or an index.
Optimization methods applied to renewable and sustainable energy: A review
Open accessAbstract
Energy is a vital input for social and economic development. As a result of the generalization of agricultural, industrial and domestic activities the demand for energy has increased remarkably, especially in emergent countries. This has meant rapid grower in the level of greenhouse gas emissions and the increase in fuel prices, which are the main driving forces behind efforts to utilize renewable energy sources more effectively, i.e. energy which comes from natural resources and is also naturally replenished. Despite the obvious advantages of renewable energy, it presents important drawbacks, such as the discontinuity of generation, as most renewable energy resources depend on the climate, which is why their use requires complex design, planning and control optimization methods. Fortunately, the continuous advances in computer hardware and software are allowing researchers to deal with these optimization problems using computational resources, as can be seen in the large number of optimization methods that have been applied to the renewable and sustainable energy field. This paper presents a review of the current state of the art in computational optimization methods applied to renewable and sustainable energy, offering a clear vision of the latest research advances in this field.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Genetic algorithms in search, optimization, and machine learning
(1989) · Choice Reviews Online · doi:10.5860/choice.27-0936 · Cited by 49,010
(1979) · Cited by 43,841
Genetic Algorithms in Search, Optimization and Machine Learning
Goldberg, D. E., & Robson, D. (1988) · Cited by 18,391
The method of moving asymptotes—a new method for structural optimization
Svanberg, K. (1987) · International Journal for Numerical Methods in Engineering · doi:10.1002/nme.1620240207 · Cited by 5,573
(2003) · International Series in Operations Research & Management Science · doi:10.1007/b101874 · Cited by 3,430
Production of first and second generation biofuels: A comprehensive review
Naik, S. N., Goud, V. V., Rout, P. K., & Dalai, A. K. (2010) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2009.10.003 · Cited by 3,264
Review on multi-criteria decision analysis aid in sustainable energy decision-making
Wang, J.-J., Jing, Y.-Y., Zhang, C.-F., & Zhao, J.-H. (2009) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2009.06.021 · Cited by 2,346
Application of multi-criteria decision making to sustainable energy planning—A review
Pohekar, S. D., & Ramachandran, M. (2004) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2003.12.007 · Cited by 1,938
(2010) · International Series in Operations Research & Management Science · doi:10.1007/978-1-4419-1665-5 · Cited by 1,642
Connolly, D., Lund, H., Mathiesen, B. V., & Leahy, M. (2010) · Applied Energy · doi:10.1016/j.apenergy.2009.09.026 · Cited by 1,631
Cited by
A review on simulation-based optimization methods applied to building performance analysis
Nguyen, A.-T., Reiter, S., & Rigo, P. (2014) · Applied Energy · doi:10.1016/j.apenergy.2013.08.061 · Cited by 1,379
All you need to know about model predictive control for buildings
Drgoňa, J., Arroyo, J., Cupeiro Figueroa, I., Blum, D., Arendt, K., Kim, D., Ollé, E. P., Oravec, J., Wetter, M., Vrabie, D. L., et al. (2020) · Annual Reviews in Control · doi:10.1016/j.arcontrol.2020.09.001 · Cited by 1,020
Ringkjøb, H.-K., Haugan, P. M., & Solbrekke, I. M. (2018) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2018.08.002 · Cited by 760
A review of urban energy system models: Approaches, challenges and opportunities
Keirstead, J., Jennings, M., & Sivakumar, A. (2012) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2012.02.047 · Cited by 641
Solar assisted sea water desalination: A review
Li, C., Goswami, Y., & Stefanakos, E. (2013) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2012.04.059 · Cited by 490
Metadata
- Authors
- Baños, R., Manzano-Agugliaro, F., Montoya, F. G., Gil, C., Alcayde, A., & Gómez, J.
- Venue
- Renewable and Sustainable Energy Reviews
- Publisher
- Elsevier BV
- Published
- 2011-05
- Volume
- 15
- Issue
- 4
- Pages
- 1753-1766
- ISSN
- 1364-0321 (ISSN-L)
- OpenAlex
- W2003948968
- Cited by
- 1,646
- References
- 99
- FWCI
- 63.06
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Optimization methods applied to renewable and sustainable energy: A review. https://app.cochat.ai/papers/10.1016/j.rser.2010.12.008
- The paper
- Baños, R., Manzano-Agugliaro, F., Montoya, F. G., Gil, C., Alcayde, A., & Gómez, J. (2011). Optimization methods applied to renewable and sustainable energy: A review. Renewable and Sustainable Energy Reviews. https://doi.org/10.1016/j.rser.2010.12.008
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
