[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-118821-en":3,"doc-seo-118821-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},118821,962075006959,"Anda","https://ap-avatar.wpscdn.com/avatar/e0002397efbe92a78e?_k=1776741047341049297",8,"Research & Report","Photovoltaic sizing using machine learning - Random forest is the best suited algorithm","Renewable energy is presented as a long-term solution to global electricity shortages, with solar power delivered through photovoltaic systems. Proper system sizing is emphasized as a decisive factor that prevents major energy losses and excessive costs, since improper design leads to inefficiency. Existing approaches are described as location-dependent optimization requiring local data. This study applies multiple machine learning models to enable a case-independent sizing model applicable across locations, with accuracy comparisons identifying random forest as the most suitable algorithm.","Available online [at www.sciencedirect.com](at www.sciencedirect.com)  \nScienceDirect  \nEnergy Reports 9 (2023) 512–518  \n[www.elsevier.com/locate/egyr](www.elsevier.com/locate/egyr)  \n7th International Conference on Renewable Energy and Conservation, ICREC 2022, November  \n18–20, 2022, Paris, France  \nPhotovoltaic sizing using machine learning  \nHaytham M. Dbouka ,∗, Mahdi Chehimib , Aya Khalafa  \na American University of Beirut, Beirut, Lebanon  \nb Virginia Tech, VA, United States of America  \nReceived 19 August 2023; accepted 3 September 2023  \nAvailable online 22 September 2023  \n\n| Abstract\u003Cbr>Renewable energy is the future of energy in the world. Solar energy is a major renewable energy source which addresses the energy deficiency problem in various countries. This endless energy source is captured using photovoltaic systems. However, in order to make the best out of photovoltaic systems, the size of the system must be optimized. Sizing has always been a critical issue that leads to huge losses once not properly designed. Existing methods consider sizing problem as a case dependent optimization problem that requires data from the place where the photovoltaic system is to be installed. This study introduces machine learning algorithms into the photovoltaic systems’ sizing problem for the first time. The proposed case-independent model automates the sizing process and is generalized to be applied at any location. Linear regression, polynomial regression, neural network, random forest, and decision tree were implemented and compared in terms of accuracy. Results show that random forest is the best suited algorithm for this application.\u003Cbr>© 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license ([http://creativecommons.org/licenses/by-nc-nd/4.0/](http://creativecommons.org/licenses/by-nc-nd/4.0/)).\u003Cbr>Peer-review under responsibility of the scientific committee of the 7th International Conference on Renewable Energy and Conservation, ICREC, 2022 .\u003Cbr>Keywords: Machine learning; Photovoltaic sizing; Linear regression; Polynomial regression; Neural network; Random forest; Decision tree; Energy optimization |\n| --- |\n| 1. Introduction\u003Cbr>Nowadays, the world is facing a global energy crisis affecting the provision of electricity for households, industries, and entire countries [1] . This is mainly due to the reliance on non-renewable energy sources, which poses environmental and energy security challenges. Furthermore, due to political and economic circumstances, various countries are facing shortages in conventional energy sources, which threatens their energy security. Lebanon is an exemplar of these countries since it has been suffering a serious energy deficiency problem over the past decades. Daily power cuts in state-provided electricity now last 22 h in some parts of the country [2] . In 2012, around 98% of the energy produced in such countries, e.g., Lebanon, was derived from using imported petroleum products and coal, while only 2% came from renewable energy [3] . Recently, renewable energy technologies, especially solar\u003Cbr>\u003Cbr>∗ Corresponding author.\u003Cbr>E-mail address: [hmd13@mail.aub.edu](hmd13@mail.aub.edu) (H.M. Dbouk) .\u003Cbr>[https://doi.org/10.1016/j.egyr.2023.09.025](https://doi.org/10.1016/j.egyr.2023.09.025)\u003Cbr>2352-4847/© 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license ([http:](http:)//[creativecommons.org/licenses/by-nc-nd/4.0/](creativecommons.org/licenses/by-nc-nd/4.0/)).\u003Cbr>Peer-review under responsibility of the scientific committee of the 7th International Conference on Renewable Energy and Conservation, ICREC, 2022 . |\n\nH.M. Dbouk, M. Chehimi and A. Khalaf Energy Reports 9 (2023) 512–518  \nenergy sources, have drawn greater global attention due to their capability to meet the growing energy demand [4] . Various suffering countries are rich in solar radiation, where the potential of photovoltai","cbCaia5t67Rf4Aw0","https://ap.wps.com/l/cbCaia5t67Rf4Aw0","pdf",525431,1,7,"English","en",105,"# Abstract\n# Introduction\n## Energy crisis context\n## Importance of photovoltaic system sizing\n## Load factor and energy loss mechanism","[{\"question\":\"Why is photovoltaic system sizing critical?\",\"answer\":\"Sizing strongly affects energy efficiency and cost. Improper sizing can cause significant energy losses and higher overall expenses.\"},{\"question\":\"What limitations do existing photovoltaic sizing methods have?\",\"answer\":\"They are described as case-dependent optimization problems that require data from the installation location.\"},{\"question\":\"Which machine learning algorithm performs best in the study?\",\"answer\":\"The results indicate that random forest is the best suited algorithm for photovoltaic sizing in this application.\"}]","Photovoltaic sizing using machine learning - Random forest is the best suited algorithm | PDF",1785720454,18,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"photovoltaic-sizing-using-machine-learning-random-forest-is-the-best-suited-algorithm","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/photovoltaic-sizing-using-machine-learning-random-forest-is-the-best-suited-algorithm/118821/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-03",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"Why is photovoltaic system sizing critical?","Question",{"text":75,"@type":76},"Sizing strongly affects energy efficiency and cost. Improper sizing can cause significant energy losses and higher overall expenses.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"What limitations do existing photovoltaic sizing methods have?",{"text":80,"@type":76},"They are described as case-dependent optimization problems that require data from the installation location.",{"name":82,"@type":73,"acceptedAnswer":83},"Which machine learning algorithm performs best in the study?",{"text":84,"@type":76},"The results indicate that random forest is the best suited algorithm for photovoltaic sizing in this application.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,119,122,127,130,134],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":21,"doc_module":4,"doc_module_name":46,"category_name":116,"show_sort_weight":117,"slug":118},"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":120,"slug":121},30,"research-report",{"id":123,"doc_module":4,"doc_module_name":46,"category_name":124,"show_sort_weight":125,"slug":126},9,"Religion & Spirituality",20,"religion-spirituality",{"id":125,"doc_module":4,"doc_module_name":46,"category_name":128,"show_sort_weight":125,"slug":129},"World Cup","world-cup",{"id":131,"doc_module":4,"doc_module_name":46,"category_name":132,"show_sort_weight":131,"slug":133},10,"Lifestyle","lifestyle",{"id":135,"doc_module":4,"doc_module_name":46,"category_name":136,"show_sort_weight":106,"slug":137},19,"General","general"]