{"corpus_id":110743566,"paper_sha":"bcd374e0f6099ee21341fc2bace89adedf375ed1","doi":"10.1016/J.EGYPRO.2011.10.103","arxiv_id":null,"pmid":null,"pmcid":null,"mag_id":2067718885,"dblp_id":null,"acl_id":null,"title":"A Review of Wind Power Forecasting Models","year":2011,"publication_date":null,"venue":"","journal":{"name":"Energy Procedia","pages":"770-778","volume":"12"},"journal_issn":null,"journal_title":null,"publication_types":["Review"],"pubmed_pub_types":null,"s2_fields_of_study":["Engineering","Environmental Science"],"reference_count":28,"citation_count":424,"influential_citation_count":10,"is_open_access":false,"arxiv_categories":null,"arxiv_license":null,"arxiv_journal_ref":null,"mesh_headings":null,"chemicals":null,"comments_corrections":null,"source_flags":1,"s2_open_access_pdf_url":null,"s2_open_access_landing_url":null,"s2_open_access_license":null,"s2_open_access_status":null,"pmc_open_access_pdf_url":null,"pmc_open_access_landing_url":null,"pmc_open_access_license":null,"pmc_open_access_status":null,"unpaywall_open_access_pdf_url":null,"unpaywall_open_access_landing_url":null,"unpaywall_open_access_license":null,"unpaywall_open_access_status":null,"abstract":"Abstract Rapid growth in wind power, as well as increase on wind generation, requires serious research in various fields. Because wind power is weather dependent, it is variable and intermittent over various time-scales. Thus accurate forecasting of wind power is recognized as a major contribution for reliable large-scale wind power integration. Wind power forecasting methods can be used to plan unit commitment, scheduling and dispatch by system operators, and maximize profit by electricity traders. In addition, a number of wind power models have been developed internationally, such as WPMS, WPPT, Prediktor, ARMINES, Previento, WPFS Ver1.0 etc. This paper provides a review on comparative analysis on the foremost forecasting models, associated with wind speed and power, based on physical methods, statistical methods, hybrid methods over different time-scales. Furthermore, this paper gives emphasis on the accuracy of these models and the source of major errors, thus problems and challenges associated with wind power prediction are presented.","claims":[{"public_id":"cl_14568339088843818b50442f14cc33a3","status":"active","text":"Comparative analysis is provided for major wind power forecasting models across physical, statistical, and hybrid methods and across different time-scales.","confidence":0.97,"contributors":[{"id":1,"public_id":"12632b8b5f","public_label":"Anonymous (12632b8b5f)","roles":["extraction"],"url":"https://sah.borca.ai/u/12632b8b5f"}],"url":"https://sah.borca.ai/claims/cl_14568339088843818b50442f14cc33a3"},{"public_id":"cl_accff8e21b87afb1b46f26f6541282f5","status":"active","text":"Model accuracy and the main sources of forecasting error are emphasized, along with the problems and challenges associated with wind power prediction.","confidence":0.93,"contributors":[{"id":1,"public_id":"12632b8b5f","public_label":"Anonymous 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