Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/25590
Full metadata record
DC FieldValueLanguage
dc.contributor.authorMesa-Jiménez, JJ-
dc.contributor.authorTzianoumis, AL-
dc.contributor.authorStokes, L-
dc.contributor.authorYang, Q-
dc.contributor.authorLivina, VN-
dc.date.accessioned2022-12-06T11:41:50Z-
dc.date.available2022-12-06T11:41:50Z-
dc.date.issued2022-12-08-
dc.identifierORCiD: J.J. Mesa-Jiménez https://orcid.org/0000-0003-0822-2700-
dc.identifierORCiD: L. Stokes https://orcid.org/0000-0003-0702-6070-
dc.identifierORCiD: Qingping Yang https://orcid.org/0000-0002-2557-8752-
dc.identifierORCiD: V.N. Livina https://orcid.org/0000-0003-3759-9013-
dc.identifier.citationMesa-Jiménez, J.J. et al. (2022) 'Long-term wind and solar energy generation forecasts, and optimisation of Power Purchase Agreements', Energy Reports, 9, pp. 292 - 302. doi: 10.1016/j.egyr.2022.11.175.en_US
dc.identifier.urihttps://bura.brunel.ac.uk/handle/2438/25590-
dc.descriptionData availability: The authors do not have permission to share data.-
dc.description.abstractDue to more affordable solar and wind power, and the European Union regulations for decarbonisation of the economy, more than 40% of the Fortune 500 companies have targets related to green energy. This is one of the main reasons why multi-technology Power-Purchase Agreements (PPAs) are becoming increasingly important. However, there are risks associated with the uncertainty and variable generation patterns in wind speed and solar radiation. Moreover, there are challenges to predict intermittent wind and solar generation for the forecasting horizon required by PPAs, which is usually of several years. We propose a long-term wind and solar energy generation forecasts suitable for PPAs with cost optimisation in energy generation scenarios. We use Markov Chain Monte Carlo simulations with suitable models of wind and solar generation and optimise long-term energy contracts with purchase of renewable energy.-
dc.description.sponsorshipDepartment for Business, Energy and Industrial Strategy of the United Kingdom; Brunel University London.en_US
dc.description.sponsorshipDepartment for Business, Energy and Industrial Strategy of the United Kingdom; Engineering and Physical Sciences Research Council DTP of Brunel University London; National Physical Laboratory; Mitie.-
dc.format.extent292 - 302-
dc.format.mediumElectronic-
dc.language.isoen_USen_US
dc.publisherElsevieren_US
dc.rightsCopyright © 2022 The Authors. Published by Elsevier Ltd. under a Creative Commons license (https://creativecommons.org/licenses/by/4.0/).-
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/-
dc.subjectpower purchase agreementsen_US
dc.subjectMarkov Chain Monte Carloen_US
dc.subjectstochastic forecasten_US
dc.subjectrenewable energy optimisationen_US
dc.titleLong-term wind and solar energy generation forecasts, and optimisation of Power Purchase Agreementsen_US
dc.typeArticleen_US
dc.identifier.doihttps://doi.org/10.1016/j.egyr.2022.11.175-
dc.relation.isPartOfEnergy Reports-
pubs.publication-statusPublished-
pubs.volume9-
dc.identifier.eissn2352-4847-
dc.rights.licensehttps://creativecommons.org/licenses/by/4.0/legalcode.en-
dc.rights.holderThe Authors-
Appears in Collections:Dept of Mechanical and Aerospace Engineering Research Papers

Files in This Item:
File Description SizeFormat 
FullText.pdfCopyright © 2022 The Authors. Published by Elsevier Ltd. under a Creative Commons license (https://creativecommons.org/licenses/by/4.0/).2.46 MBAdobe PDFView/Open


This item is licensed under a Creative Commons License Creative Commons