Academic Journal
RL-ADN: A high-performance Deep Reinforcement Learning environment for optimal Energy Storage Systems dispatch in active distribution networks
العنوان: | RL-ADN: A high-performance Deep Reinforcement Learning environment for optimal Energy Storage Systems dispatch in active distribution networks |
---|---|
المؤلفون: | Hou, Shengren, Gao, Shuyi, Xia, Weijie, Salazar Duque, Edgar Mauricio, Palensky, Peter, Vergara, Pedro P. |
المساهمون: | National Natural Science Foundation of China, Nederlandse Organisatie voor Wetenschappelijk Onderzoek |
المصدر: | Energy and AI ; volume 19, page 100457 ; ISSN 2666-5468 |
بيانات النشر: | Elsevier BV |
سنة النشر: | 2025 |
المجموعة: | ScienceDirect (Elsevier - Open Access Articles via Crossref) |
نوع الوثيقة: | article in journal/newspaper |
اللغة: | English |
DOI: | 10.1016/j.egyai.2024.100457 |
الاتاحة: | https://doi.org/10.1016/j.egyai.2024.100457 https://api.elsevier.com/content/article/PII:S266654682400123X?httpAccept=text/xml https://api.elsevier.com/content/article/PII:S266654682400123X?httpAccept=text/plain |
Rights: | https://www.elsevier.com/tdm/userlicense/1.0/ ; https://www.elsevier.com/legal/tdmrep-license ; http://creativecommons.org/licenses/by/4.0/ |
رقم الانضمام: | edsbas.178A74C9 |
قاعدة البيانات: | BASE |
ResultId |
1 |
---|---|
Header |
edsbas BASE edsbas.178A74C9 1057 3 Academic Journal academicJournal 1056.5498046875 |
PLink |
https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&scope=site&db=edsbas&AN=edsbas.178A74C9&custid=s6537998&authtype=sso |
FullText |
Array
(
[Availability] => 0
)
Array ( [0] => Array ( [Url] => https://doi.org/10.1016/j.egyai.2024.100457# [Name] => EDS - BASE [Category] => fullText [Text] => View record in BASE [MouseOverText] => View record in BASE ) ) |
Items |
Array
(
[Name] => Title
[Label] => Title
[Group] => Ti
[Data] => RL-ADN: A high-performance Deep Reinforcement Learning environment for optimal Energy Storage Systems dispatch in active distribution networks
)
Array ( [Name] => Author [Label] => Authors [Group] => Au [Data] => <searchLink fieldCode="AR" term="%22Hou%2C+Shengren%22">Hou, Shengren</searchLink><br /><searchLink fieldCode="AR" term="%22Gao%2C+Shuyi%22">Gao, Shuyi</searchLink><br /><searchLink fieldCode="AR" term="%22Xia%2C+Weijie%22">Xia, Weijie</searchLink><br /><searchLink fieldCode="AR" term="%22Salazar+Duque%2C+Edgar+Mauricio%22">Salazar Duque, Edgar Mauricio</searchLink><br /><searchLink fieldCode="AR" term="%22Palensky%2C+Peter%22">Palensky, Peter</searchLink><br /><searchLink fieldCode="AR" term="%22Vergara%2C+Pedro+P%2E%22">Vergara, Pedro P.</searchLink> ) Array ( [Name] => Author [Label] => Contributors [Group] => Au [Data] => National Natural Science Foundation of China<br />Nederlandse Organisatie voor Wetenschappelijk Onderzoek ) Array ( [Name] => TitleSource [Label] => Source [Group] => Src [Data] => Energy and AI ; volume 19, page 100457 ; ISSN 2666-5468 ) Array ( [Name] => Publisher [Label] => Publisher Information [Group] => PubInfo [Data] => Elsevier BV ) Array ( [Name] => DatePubCY [Label] => Publication Year [Group] => Date [Data] => 2025 ) Array ( [Name] => Subset [Label] => Collection [Group] => HoldingsInfo [Data] => ScienceDirect (Elsevier - Open Access Articles via Crossref) ) Array ( [Name] => TypeDocument [Label] => Document Type [Group] => TypDoc [Data] => article in journal/newspaper ) Array ( [Name] => Language [Label] => Language [Group] => Lang [Data] => English ) Array ( [Name] => DOI [Label] => DOI [Group] => ID [Data] => 10.1016/j.egyai.2024.100457 ) Array ( [Name] => URL [Label] => Availability [Group] => URL [Data] => https://doi.org/10.1016/j.egyai.2024.100457<br />https://api.elsevier.com/content/article/PII:S266654682400123X?httpAccept=text/xml<br />https://api.elsevier.com/content/article/PII:S266654682400123X?httpAccept=text/plain ) Array ( [Name] => Copyright [Label] => Rights [Group] => Cpyrght [Data] => https://www.elsevier.com/tdm/userlicense/1.0/ ; https://www.elsevier.com/legal/tdmrep-license ; http://creativecommons.org/licenses/by/4.0/ ) Array ( [Name] => AN [Label] => Accession Number [Group] => ID [Data] => edsbas.178A74C9 ) |
RecordInfo |
Array
(
[BibEntity] => Array
(
[Identifiers] => Array
(
[0] => Array
(
[Type] => doi
[Value] => 10.1016/j.egyai.2024.100457
)
)
[Languages] => Array
(
[0] => Array
(
[Text] => English
)
)
[Titles] => Array
(
[0] => Array
(
[TitleFull] => RL-ADN: A high-performance Deep Reinforcement Learning environment for optimal Energy Storage Systems dispatch in active distribution networks
[Type] => main
)
)
)
[BibRelationships] => Array
(
[HasContributorRelationships] => Array
(
[0] => Array
(
[PersonEntity] => Array
(
[Name] => Array
(
[NameFull] => Hou, Shengren
)
)
)
[1] => Array
(
[PersonEntity] => Array
(
[Name] => Array
(
[NameFull] => Gao, Shuyi
)
)
)
[2] => Array
(
[PersonEntity] => Array
(
[Name] => Array
(
[NameFull] => Xia, Weijie
)
)
)
[3] => Array
(
[PersonEntity] => Array
(
[Name] => Array
(
[NameFull] => Salazar Duque, Edgar Mauricio
)
)
)
[4] => Array
(
[PersonEntity] => Array
(
[Name] => Array
(
[NameFull] => Palensky, Peter
)
)
)
[5] => Array
(
[PersonEntity] => Array
(
[Name] => Array
(
[NameFull] => Vergara, Pedro P.
)
)
)
[6] => Array
(
[PersonEntity] => Array
(
[Name] => Array
(
[NameFull] => National Natural Science Foundation of China
)
)
)
[7] => Array
(
[PersonEntity] => Array
(
[Name] => Array
(
[NameFull] => Nederlandse Organisatie voor Wetenschappelijk Onderzoek
)
)
)
)
[IsPartOfRelationships] => Array
(
[0] => Array
(
[BibEntity] => Array
(
[Dates] => Array
(
[0] => Array
(
[D] => 01
[M] => 01
[Type] => published
[Y] => 2025
)
)
[Identifiers] => Array
(
[0] => Array
(
[Type] => issn-locals
[Value] => edsbas
)
[1] => Array
(
[Type] => issn-locals
[Value] => edsbas.oa
)
)
[Titles] => Array
(
[0] => Array
(
[TitleFull] => Energy and AI ; volume 19, page 100457 ; ISSN 2666-5468
[Type] => main
)
)
)
)
)
)
)
|
IllustrationInfo |