The DOI matches its Crossref record; 104 of the 104 references it cites were found in a registry or an index.
Formalizing best practice for energy system optimization modelling
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Cites
Klüppel, H.-J. (2005) · The International Journal of Life Cycle Assessment · doi:10.1065/lca2005.03.001 · Cited by 4,639
Uncertainty and Quality in Science for Policy
Funtowicz, S. O., & Ravetz, J. R. (1990) · doi:10.1007/978-94-009-0621-1 · Cited by 1,575
Scenario planning: a tool for strategic thinking
(1995) · Long Range Planning · doi:10.1016/0024-6301(95)91604-0 · Cited by 1,502
Scenario types and techniques: Towards a user's guide
Börjeson, L., Höjer, M., Dreborg, K.-H., Ekvall, T., & Finnveden, G. (2006) · Futures · doi:10.1016/j.futures.2005.12.002 · Cited by 1,421
Multi-stage stochastic optimization applied to energy planning
Pereira, M. V. F., & Pinto, L. M. V. G. (1991) · Mathematical Programming · doi:10.1007/bf01582895 · Cited by 1,361
Scenarios and Policy Aggregation in Optimization Under Uncertainty
Rockafellar, R. T., & Wets, R. J.-B. (1991) · Mathematics of Operations Research · doi:10.1287/moor.16.1.119 · Cited by 1,340
Shaping the Next One Hundred Years: New Methods for Quantitative, Long-Term Policy Analysis
Lempert, R., Popper, S., & Bankes, S. (2003) · RAND Corporation eBooks · doi:10.7249/mr1626 · Cited by 1,244
The origins and evolution of scenario techniques in long range business planning
Bradfield, R., Wright, G., Burt, G., Cairns, G., & Van Der Heijden, K. (2005) · Futures · doi:10.1016/j.futures.2005.01.003 · Cited by 1,204
Energy systems modeling for twenty-first century energy challenges
Pfenninger, S., Hawkes, A., & Keirstead, J. (2014) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2014.02.003 · Cited by 1,164
Indicated, N. (2010) · Joint Research Centre (European Commission) · doi:10.2788/38479 · Cited by 1,038
Cited by
Empirically grounded technology forecasts and the energy transition
Way, R., Ives, M. C., Mealy, P., & Farmer, J. D. (2022) · Joule · doi:10.1016/j.joule.2022.08.009 · Cited by 607
Thormeyer, C., Sasse, J.-P., & Trutnevyte, E. (2020) · Renewable Energy · doi:10.1016/j.renene.2019.06.017 · Cited by 61
Self-citation
Metadata
- Authors
- DeCarolis, J., Daly, H., Dodds, P., Keppo, I., Li, F., McDowall, W., Pye, S., Strachan, N., Trutnevyte, E., Usher, W., Winning, M., Yeh, S., & Zeyringer, M.
- Venue
- Applied Energy
- Publisher
- Elsevier BV
- Published
- 2017-05
- Volume
- 194
- Pages
- 184-198
- ISSN
- 0306-2619 (ISSN-L)
- OpenAlex
- W2593076975
- Cited by
- 389
- References
- 104
- FWCI
- 11.52
- Type
- journal article
- Language
- en
- Open access
- bronze
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- The paper
- DeCarolis, J., Daly, H., Dodds, P., Keppo, I., Li, F., McDowall, W., Pye, S., Strachan, N., Trutnevyte, E., Usher, W., Winning, M., Yeh, S., & Zeyringer, M. (2017). Formalizing best practice for energy system optimization modelling. Applied Energy. https://doi.org/10.1016/j.apenergy.2017.03.001
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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.
