Duck curve leveling in renewable energy integrated grids using internet of relays
Power grids are undergoing deregulation, privatization, and decentralization worldwide. The smart grid allows the integration of clean power renewable energy technologies to the utility grid through mini, micro, and nano grids. Conventional centralized power grids used to rely on fossil fuel-fired p...
Saved in:
| Published in: | Journal of cleaner production Vol. 294; p. 126294 |
|---|---|
| Main Authors: | , , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Elsevier Ltd
20.04.2021
|
| Subjects: | |
| ISSN: | 0959-6526, 1879-1786 |
| Online Access: | Get full text |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Abstract | Power grids are undergoing deregulation, privatization, and decentralization worldwide. The smart grid allows the integration of clean power renewable energy technologies to the utility grid through mini, micro, and nano grids. Conventional centralized power grids used to rely on fossil fuel-fired power plants which are being replaced worldwide with solar, wind, small hydro, geothermal, biomass, wave, and alternative energy technologies. Installed solar and wind power generation capacity has surpassed 1300 GW in 2020. Solar and wind powers rise during the day and fall during the evening. Consumer demand increases steadily during the evening and peaks after sunset when solar generation becomes zero and wind power falls substantially. Decentralized smart grid faces duck curve limitation on the integration of renewable energy technologies as centralized utilities used to face the peak-hours issue. Smart grid operators have no effective solution of load peaking after sundown except keeping fossil fuel-fired plants on standby to ride through the duck curve. We present a solution to the duck curve problem by integrating smart load shedding devices in micro and nano grids to adjust their demand frugally during peak hours to support the national grid. Information and communication (ICT) technologies that enabled the internet of things (IoT) have been attempted to facilitate smart load shedding in nano grids. ICT enabled voltage transformers (VT) and current transformers (CT) supply signals to heuristic rules based multifunction smart relaying system. Smart meters, instrument transformers, and status monitoring field devices generate a massive amount of data. The research designed an IoT and LabVIEW based software platform to carry out demand-side management. Under frequency (UF) and under-voltage (UV) relaying functions were used to conduct load shedding in nano grids. This nanoscale demand-side management experiment paves the way to ride through utility-scale duck curve setback. This PT/CT data based economic solution performs at nanoscale same as ABB PML 630 load shedding controller. This UF and UV relaying based multifunction relay starts shedding loads when frequency falls below <1% and voltage below 10% of rated values. Our load shedding scheme has successfully functioned on nanoscale 5 kW system. The future study section proposes to integrate big data technologies in-home energy management system (HEMS) through extract, transform and load (ETL) pipeline to import data from PT/CT and circuit breakers (CB) integrated smart meter to transform it according to requirement by loading data into Hadoop “big data” processing platforms for utility-scale load management with help of day-ahead load and weather-dependent renewable power generation forecasting techniques. |
|---|---|
| AbstractList | Power grids are undergoing deregulation, privatization, and decentralization worldwide. The smart grid allows the integration of clean power renewable energy technologies to the utility grid through mini, micro, and nano grids. Conventional centralized power grids used to rely on fossil fuel-fired power plants which are being replaced worldwide with solar, wind, small hydro, geothermal, biomass, wave, and alternative energy technologies. Installed solar and wind power generation capacity has surpassed 1300 GW in 2020. Solar and wind powers rise during the day and fall during the evening. Consumer demand increases steadily during the evening and peaks after sunset when solar generation becomes zero and wind power falls substantially. Decentralized smart grid faces duck curve limitation on the integration of renewable energy technologies as centralized utilities used to face the peak-hours issue. Smart grid operators have no effective solution of load peaking after sundown except keeping fossil fuel-fired plants on standby to ride through the duck curve. We present a solution to the duck curve problem by integrating smart load shedding devices in micro and nano grids to adjust their demand frugally during peak hours to support the national grid. Information and communication (ICT) technologies that enabled the internet of things (IoT) have been attempted to facilitate smart load shedding in nano grids. ICT enabled voltage transformers (VT) and current transformers (CT) supply signals to heuristic rules based multifunction smart relaying system. Smart meters, instrument transformers, and status monitoring field devices generate a massive amount of data. The research designed an IoT and LabVIEW based software platform to carry out demand-side management. Under frequency (UF) and under-voltage (UV) relaying functions were used to conduct load shedding in nano grids. This nanoscale demand-side management experiment paves the way to ride through utility-scale duck curve setback. This PT/CT data based economic solution performs at nanoscale same as ABB PML 630 load shedding controller. This UF and UV relaying based multifunction relay starts shedding loads when frequency falls below <1% and voltage below 10% of rated values. Our load shedding scheme has successfully functioned on nanoscale 5 kW system. The future study section proposes to integrate big data technologies in-home energy management system (HEMS) through extract, transform and load (ETL) pipeline to import data from PT/CT and circuit breakers (CB) integrated smart meter to transform it according to requirement by loading data into Hadoop “big data” processing platforms for utility-scale load management with help of day-ahead load and weather-dependent renewable power generation forecasting techniques. Power grids are undergoing deregulation, privatization, and decentralization worldwide. The smart grid allows the integration of clean power renewable energy technologies to the utility grid through mini, micro, and nano grids. Conventional centralized power grids used to rely on fossil fuel-fired power plants which are being replaced worldwide with solar, wind, small hydro, geothermal, biomass, wave, and alternative energy technologies. Installed solar and wind power generation capacity has surpassed 1300 GW in 2020. Solar and wind powers rise during the day and fall during the evening. Consumer demand increases steadily during the evening and peaks after sunset when solar generation becomes zero and wind power falls substantially. Decentralized smart grid faces duck curve limitation on the integration of renewable energy technologies as centralized utilities used to face the peak-hours issue. Smart grid operators have no effective solution of load peaking after sundown except keeping fossil fuel-fired plants on standby to ride through the duck curve. We present a solution to the duck curve problem by integrating smart load shedding devices in micro and nano grids to adjust their demand frugally during peak hours to support the national grid. Information and communication (ICT) technologies that enabled the internet of things (IoT) have been attempted to facilitate smart load shedding in nano grids. ICT enabled voltage transformers (VT) and current transformers (CT) supply signals to heuristic rules based multifunction smart relaying system. Smart meters, instrument transformers, and status monitoring field devices generate a massive amount of data. The research designed an IoT and LabVIEW based software platform to carry out demand-side management. Under frequency (UF) and under-voltage (UV) relaying functions were used to conduct load shedding in nano grids. This nanoscale demand-side management experiment paves the way to ride through utility-scale duck curve setback. This PT/CT data based economic solution performs at nanoscale same as ABB PML 630 load shedding controller. This UF and UV relaying based multifunction relay starts shedding loads when frequency falls below <1% and voltage below 10% of rated values. Our load shedding scheme has successfully functioned on nanoscale 5 kW system. The future study section proposes to integrate big data technologies in-home energy management system (HEMS) through extract, transform and load (ETL) pipeline to import data from PT/CT and circuit breakers (CB) integrated smart meter to transform it according to requirement by loading data into Hadoop “big data” processing platforms for utility-scale load management with help of day-ahead load and weather-dependent renewable power generation forecasting techniques. |
| ArticleNumber | 126294 |
| Author | Stojcevski, Alex Khan, Nasrullah Abas, Naeem Seyedmahmoudian, Mehdi Rauf, Shoaib Kalair, Ali Raza |
| Author_xml | – sequence: 1 givenname: Ali Raza surname: Kalair fullname: Kalair, Ali Raza organization: Department of Telecommunications, Electrical, Robotics and Biomedical Engineering, Swinburne University, Australia – sequence: 2 givenname: Naeem orcidid: 0000-0002-7214-2986 surname: Abas fullname: Abas, Naeem email: naeemkalair@uog.edu.pk organization: Department of Electrical Engineering Department, University of Gujrat, Hafiz Hayat Campus, Pakistan – sequence: 3 givenname: Mehdi surname: Seyedmahmoudian fullname: Seyedmahmoudian, Mehdi organization: Department of Telecommunications, Electrical, Robotics and Biomedical Engineering, Swinburne University, Australia – sequence: 4 givenname: Shoaib surname: Rauf fullname: Rauf, Shoaib organization: Department of Electrical Engineering Department, University of Gujrat, Hafiz Hayat Campus, Pakistan – sequence: 5 givenname: Alex surname: Stojcevski fullname: Stojcevski, Alex organization: Department of Telecommunications, Electrical, Robotics and Biomedical Engineering, Swinburne University, Australia – sequence: 6 givenname: Nasrullah surname: Khan fullname: Khan, Nasrullah organization: Department of Electrical Engineering Department, COMSATS University Islamabad, Pakistan |
| BookMark | eNqFkF1LwzAUhoNMcJv-BKGX3rQmaZq2eCEyP2Eggl6HNDkdmVk6k3Syf29Hd-XNrs7h8D4vnGeGJq5zgNA1wRnBhN-us7WysPVdRjElGaGc1uwMTUlV1ikpKz5BU1wXdcoLyi_QLIQ1xqTEJZuij8defSeq9ztILOzAGrdKjEs8OPiVjYVkWPxqP9wirLyMoJOVNzokfRijEbyDmHTtwFi5D5fovJU2wNVxztHX89Pn4jVdvr-8LR6WqcoZjWkjqZSqkRhD3nAGdcWamuZFy2rNMK6kxLrSRJOWUwKY5RQ0q4GxUknOWZPP0c3YOzz-00OIYmOCAmulg64PghaU0QJXjA_RYowq34XgoRVbbzbS7wXB4qBQrMVRoTgoFKPCgbv7xykTZTSdi14ae5K-H2kYLOwMeBGUAadAGw8qCt2ZEw1_FwOTjg |
| CitedBy_id | crossref_primary_10_1007_s10668_022_02252_3 crossref_primary_10_1016_j_egyr_2025_01_006 crossref_primary_10_1016_j_apenergy_2021_117608 crossref_primary_10_1016_j_enconman_2024_118326 crossref_primary_10_1016_j_egyr_2021_10_060 crossref_primary_10_1016_j_eneco_2024_107806 crossref_primary_10_1016_j_seta_2024_103720 crossref_primary_10_1016_j_suscom_2023_100897 crossref_primary_10_1016_j_apenergy_2024_123378 crossref_primary_10_1016_j_applthermaleng_2025_125421 crossref_primary_10_1016_j_rineng_2025_104001 crossref_primary_10_1016_j_enbuild_2024_114414 crossref_primary_10_1007_s13198_023_01929_w crossref_primary_10_1016_j_energy_2022_123701 |
| Cites_doi | 10.3844/ajassp.2009.317.327 10.3390/app9153192 10.1038/s41558-019-0622-6 10.1016/j.comcom.2013.09.004 10.1016/j.jclepro.2020.120747 10.3390/en10030326 10.1016/j.apenergy.2017.07.073 10.1109/JIOT.2019.2935189 10.1109/ACCESS.2015.2389659 10.1049/iet-gtd:20080210 10.1016/j.bdr.2015.03.003 10.1109/59.336128 10.1016/j.rser.2015.12.288 10.1016/j.epsr.2019.106054 10.1109/TIA.2017.2740832 10.1016/j.comcom.2015.05.015 10.1016/j.tej.2012.09.010 10.1109/19.893254 10.1109/TPWRS.2010.2059715 10.1109/JPROC.2017.2696878 10.1049/iet-gtd.2015.0277 |
| ContentType | Journal Article |
| Copyright | 2021 Elsevier Ltd |
| Copyright_xml | – notice: 2021 Elsevier Ltd |
| DBID | AAYXX CITATION 7S9 L.6 |
| DOI | 10.1016/j.jclepro.2021.126294 |
| DatabaseName | CrossRef AGRICOLA AGRICOLA - Academic |
| DatabaseTitle | CrossRef AGRICOLA AGRICOLA - Academic |
| DatabaseTitleList | AGRICOLA |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Engineering |
| EISSN | 1879-1786 |
| ExternalDocumentID | 10_1016_j_jclepro_2021_126294 S095965262100514X |
| GroupedDBID | --K --M ..I .~1 0R~ 1B1 1RT 1~. 1~5 4.4 457 4G. 5GY 5VS 7-5 71M 8P~ 9JM 9JN AABNK AACTN AAEDT AAEDW AAHCO AAIAV AAIKJ AAKOC AALRI AAOAW AAQFI AARJD AAXUO ABFYP ABJNI ABLST ABMAC ABYKQ ACDAQ ACGFS ACRLP ADBBV ADEZE AEBSH AEKER AENEX AFKWA AFTJW AFXIZ AGHFR AGUBO AGYEJ AHEUO AHHHB AHIDL AIEXJ AIKHN AITUG AJOXV AKIFW ALMA_UNASSIGNED_HOLDINGS AMFUW AMRAJ AXJTR BELTK BKOJK BLECG BLXMC CS3 DU5 EBS EFJIC EFLBG EO8 EO9 EP2 EP3 FDB FIRID FNPLU FYGXN G-Q GBLVA IHE J1W JARJE K-O KCYFY KOM LY9 M41 MO0 MS~ N9A O-L O9- OAUVE OZT P-8 P-9 P2P PC. Q38 RNS ROL RPZ SCC SDF SDG SDP SES SPC SPCBC SSJ SSR SSZ T5K ~G- 29K 9DU AAHBH AAQXK AATTM AAXKI AAYWO AAYXX ABFNM ABWVN ABXDB ACLOT ACRPL ACVFH ADCNI ADHUB ADMUD ADNMO AEGFY AEIPS AEUPX AFJKZ AFPUW AGQPQ AIGII AIIUN AKBMS AKRWK AKYEP ANKPU APXCP ASPBG AVWKF AZFZN CITATION D-I EFKBS EJD FEDTE FGOYB G-2 HMC HVGLF HZ~ R2- SEN SEW WUQ ZY4 ~HD 7S9 L.6 |
| ID | FETCH-LOGICAL-c342t-ba2aacba00e3b64e984b9235f49d4008aa0d8d1d1f621e0432ed49e447ca664b3 |
| ISICitedReferencesCount | 21 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000629035100001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 0959-6526 |
| IngestDate | Wed Oct 01 14:36:06 EDT 2025 Sat Nov 29 07:06:55 EST 2025 Tue Nov 18 21:00:01 EST 2025 Fri Feb 23 02:41:39 EST 2024 |
| IsPeerReviewed | true |
| IsScholarly | true |
| Keywords | Renewable energy Smart grid Nanogrids Demand side management (DSM) Demand response (DR) IoT |
| Language | English |
| LinkModel | OpenURL |
| MergedId | FETCHMERGED-LOGICAL-c342t-ba2aacba00e3b64e984b9235f49d4008aa0d8d1d1f621e0432ed49e447ca664b3 |
| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
| ORCID | 0000-0002-7214-2986 |
| PQID | 2524250846 |
| PQPubID | 24069 |
| ParticipantIDs | proquest_miscellaneous_2524250846 crossref_primary_10_1016_j_jclepro_2021_126294 crossref_citationtrail_10_1016_j_jclepro_2021_126294 elsevier_sciencedirect_doi_10_1016_j_jclepro_2021_126294 |
| PublicationCentury | 2000 |
| PublicationDate | 2021-04-20 |
| PublicationDateYYYYMMDD | 2021-04-20 |
| PublicationDate_xml | – month: 04 year: 2021 text: 2021-04-20 day: 20 |
| PublicationDecade | 2020 |
| PublicationTitle | Journal of cleaner production |
| PublicationYear | 2021 |
| Publisher | Elsevier Ltd |
| Publisher_xml | – name: Elsevier Ltd |
| References | Roy, Banninthaya, Prabhu, Koomar, Karnataki, Shankar (bib43) 2018 Rudez, Mihalic (bib44) 2011; 26 Omine, Hatta, Ueno (bib38) 2019 Munshi, Alqarni, Abdullah Almalki (bib37) 2020 Yadav, Prasad (bib57) 2019 Prasetijo, Lachs, Sutanto (bib40) 1994; 9 Tsado, Lund, Gamage (bib54) 2015; 71 Lindahl, Runvik, Stranne (bib31) 1997 Meneghello, Calore, Zucchetto, Polese, Zanella (bib35) 2019; 6 Kalair, Abas, Hasan, Seyedmahmoudian, Khan (bib24) 2020; 258 Ronen, Shamir (bib42) 2016 Sajedian, Rho (bib46) 2019; 6 Tao, Zhang, Nee (bib53) 2019 Hu, Li, Xu, Zhou, Cui (bib20) 2017; 10 Kezunovic, Xie, Grijalva (bib25) 2013 Ethan S, “Our Sun Is Lighter than Ever, and the Problem Is Getting Worse.,” Fadel, Ibrahim, Tamazin, Hamdy, Abdel-Khalik (bib15) 2019 Domenico Talia Paolo Trunfio Fabrizio Marozzo, Data Analysis in the Cloud Models, Techniques and Applications, 1st Ed. Elsevier. Zeng (bib58) 2019; 9 Gao, Li, Hong, Long (bib16) 2019; 9 . Mortaji, Ow, Moghavvemi, Almurib (bib36) 2017; 53 Elmore (bib12) 2003 Haes Alhelou, Hamedani Golshan, Njenda, Hatziargyriou (bib17) 2020; 179 Chelsea H, “The World’s Winds Are Speeding Up.,” Kul, Şen (bib29) 2017 Liu, Lv, Li (bib32) 2015 Bo, Li, Zheng (bib5) 2010 Kroposki, Basso, DeBlasio (bib28) 2008 Blaabjerg, Yang, Yang, Wang (bib4) 2017; 105 Shuvra, Chowdhury (bib49) 2019 Ancillotti, Bruno, Conti (bib3) 2013; 36 Aminifar (bib19) 2014; 2 Soliman, Abiodun, Hamouda, Zhou, Lung (bib50) 2013 Su, Wang (bib52) 2012; 25 Rudez, Mihalic (bib45) 2011 Sanaye-Pasand, Seyedi (bib62) 2009; 3 California Independent System Operator (bib7) 2012 Seyedi, Sanaye-Pasand (bib48) 2009; 6 Derafshian, Amjady, Dehghan (bib9) 2016; 10 Kraeling, Brogioli (bib27) 2019 Eclypse Z7 Hardware Reference Manual [Digilent Documentation] . Johns, Salman (bib23) 1995 Wang, Luo, Zhai, Yang, He (bib55) 2017 Khahro, Soomro, Tabbassum, Dong, Liao (bib26) 2013; 11 Händel (bib18) 2000; 49 Manur, Venkataramanan, Sehloff (bib33) 2018; 210 Marhaposan (bib34) 2016; 8 Raju, Swetha, Shruthi, Shruthi (bib41) 2020 Kulkarni, Patil, Suryavanshi (bib30) 2018 Pourbabak, Chen, Zhang, Su (bib39) 2017 Kalair, Abas, Khan (bib61) 2016; 59 Statista (bib51) Isomura, Yabiku, Tamashiro, Massingue, Senjyu (bib21) 2020 Alarbi, Strickland, Blanchard (bib1) 2019 D. Analytics, Big Data Analytics (Empowering Data Analytics Ecosystem) . Diamantoulakis, Kapinas, Karagiannidis (bib10) 2015; 2 Shuvra (10.1016/j.jclepro.2021.126294_bib49) 2019 10.1016/j.jclepro.2021.126294_bib11 10.1016/j.jclepro.2021.126294_bib59 10.1016/j.jclepro.2021.126294_bib13 Munshi (10.1016/j.jclepro.2021.126294_bib37) 2020 Hu (10.1016/j.jclepro.2021.126294_bib20) 2017; 10 Manur (10.1016/j.jclepro.2021.126294_bib33) 2018; 210 Blaabjerg (10.1016/j.jclepro.2021.126294_bib4) 2017; 105 California Independent System Operator (10.1016/j.jclepro.2021.126294_bib7) 2012 Khahro (10.1016/j.jclepro.2021.126294_bib26) 2013; 11 Kroposki (10.1016/j.jclepro.2021.126294_bib28) 2008 Diamantoulakis (10.1016/j.jclepro.2021.126294_bib10) 2015; 2 Su (10.1016/j.jclepro.2021.126294_bib52) 2012; 25 Isomura (10.1016/j.jclepro.2021.126294_bib21) 2020 Kalair (10.1016/j.jclepro.2021.126294_bib61) 2016; 59 Yadav (10.1016/j.jclepro.2021.126294_bib57) 2019 Prasetijo (10.1016/j.jclepro.2021.126294_bib40) 1994; 9 Statista (10.1016/j.jclepro.2021.126294_bib51) Johns (10.1016/j.jclepro.2021.126294_bib23) 1995 Aminifar (10.1016/j.jclepro.2021.126294_bib19) 2014; 2 Soliman (10.1016/j.jclepro.2021.126294_bib50) 2013 Derafshian (10.1016/j.jclepro.2021.126294_bib9) 2016; 10 Gao (10.1016/j.jclepro.2021.126294_bib16) 2019; 9 Kulkarni (10.1016/j.jclepro.2021.126294_bib30) 2018 Omine (10.1016/j.jclepro.2021.126294_bib38) 2019 10.1016/j.jclepro.2021.126294_bib8 Kezunovic (10.1016/j.jclepro.2021.126294_bib25) 2013 Seyedi (10.1016/j.jclepro.2021.126294_bib48) 2009; 6 Roy (10.1016/j.jclepro.2021.126294_bib43) 2018 Zeng (10.1016/j.jclepro.2021.126294_bib58) 2019; 9 Händel (10.1016/j.jclepro.2021.126294_bib18) 2000; 49 10.1016/j.jclepro.2021.126294_bib2 Tsado (10.1016/j.jclepro.2021.126294_bib54) 2015; 71 Wang (10.1016/j.jclepro.2021.126294_bib55) 2017 Bo (10.1016/j.jclepro.2021.126294_bib5) 2010 Marhaposan (10.1016/j.jclepro.2021.126294_bib34) 2016; 8 Liu (10.1016/j.jclepro.2021.126294_bib32) 2015 Sanaye-Pasand (10.1016/j.jclepro.2021.126294_bib62) 2009; 3 Haes Alhelou (10.1016/j.jclepro.2021.126294_bib17) 2020; 179 Elmore (10.1016/j.jclepro.2021.126294_bib12) 2003 Tao (10.1016/j.jclepro.2021.126294_bib53) 2019 Rudez (10.1016/j.jclepro.2021.126294_bib44) 2011; 26 Ronen (10.1016/j.jclepro.2021.126294_bib42) 2016 Kalair (10.1016/j.jclepro.2021.126294_bib24) 2020; 258 Lindahl (10.1016/j.jclepro.2021.126294_bib31) 1997 Alarbi (10.1016/j.jclepro.2021.126294_bib1) 2019 Sajedian (10.1016/j.jclepro.2021.126294_bib46) 2019; 6 Rudez (10.1016/j.jclepro.2021.126294_bib45) 2011 Fadel (10.1016/j.jclepro.2021.126294_bib15) 2019 Raju (10.1016/j.jclepro.2021.126294_bib41) 2020 Meneghello (10.1016/j.jclepro.2021.126294_bib35) 2019; 6 Kul (10.1016/j.jclepro.2021.126294_bib29) 2017 Pourbabak (10.1016/j.jclepro.2021.126294_bib39) 2017 Kraeling (10.1016/j.jclepro.2021.126294_bib27) 2019 Mortaji (10.1016/j.jclepro.2021.126294_bib36) 2017; 53 Ancillotti (10.1016/j.jclepro.2021.126294_bib3) 2013; 36 |
| References_xml | – volume: 26 start-page: 839 year: 2011 end-page: 846 ident: bib44 article-title: Monitoring the first frequency derivative to improve adaptive underfrequency load-shedding schemes publication-title: IEEE Trans. Power Syst. – volume: 25 start-page: 45 year: 2012 end-page: 60 ident: bib52 article-title: Energy management systems in microgrid operations publication-title: Electr. J. – reference: Chelsea H, “The World’s Winds Are Speeding Up.,” – volume: 11 year: 2013 ident: bib26 article-title: Assessment of wind power potential at Hawksbay, Karachi Sindh, Pakistan publication-title: TELKOMNIKA Indones. J. Electr. Eng. – year: 2019 ident: bib49 article-title: “ publication-title: Load Management System and Control Strategies of Distributed Energy Resources in an Islanded Microgrid,” in – year: 2017 ident: bib39 article-title: Control and energy management system in microgrids publication-title: , – volume: 71 start-page: 34 year: 2015 end-page: 49 ident: bib54 article-title: Resilient communication for smart grid ubiquitous sensor network: state of the art and prospects for next generation publication-title: Comput. Commun. – reference: D. Analytics, Big Data Analytics (Empowering Data Analytics Ecosystem) . – reference: Domenico Talia Paolo Trunfio Fabrizio Marozzo, Data Analysis in the Cloud Models, Techniques and Applications, 1st Ed. Elsevier. – year: 2018 ident: bib30 article-title: IOT based PV assisted EV charging station for Confronting duck curve publication-title: , CTEMS – year: 2020 ident: bib41 article-title: IoT Based Demand Side Management Using Arduino and MATLAB – volume: 105 start-page: 1311 year: 2017 end-page: 1331 ident: bib4 article-title: Distributed power-generation systems and protection publication-title: Proceedings of the IEEE – year: 2013 ident: bib50 article-title: Smart home: integrating internet of things with web services and cloud computing publication-title: , CloudCom – year: 2017 ident: bib29 article-title: “Energy Saving IoT-Based Advanced Load Limiter,” in – year: 2019 ident: bib27 article-title: Internet of Things At-A-Glance – volume: 3 start-page: 99 year: 2009 end-page: 114 ident: bib62 article-title: New centralised adaptive load-shedding algorithms to mitigate power system blackouts publication-title: IET Gener. Transm. Distrib. – year: 2019 ident: bib53 article-title: Digital twin and cloud, fog, edge computing publication-title: Digital Twin Driven Smart Manufacturing – volume: 36 start-page: 1665 year: 2013 end-page: 1697 ident: bib3 article-title: The role of communication systems in smart grids: architectures, technical solutions and research challenges publication-title: Comput. Commun. – volume: 8 start-page: 43 year: 2016 end-page: 54 ident: bib34 article-title: The load current and voltage estimation using interpolation method in electrical power monitoring system based on microcontroller atmega 8535 and pc publication-title: Bull. Math. – volume: 10 year: 2017 ident: bib20 article-title: A chance-constrained economic dispatch model in wind-thermal-energy storage system publication-title: Energies – volume: 210 start-page: 748 year: 2018 end-page: 763 ident: bib33 article-title: Simple electric utility platform: a hardware/software solution for operating emergent microgrids publication-title: Appl. Energy – year: 2003 ident: bib12 article-title: Protective relaying theory and applicantions publication-title: Protective Relaying Theory and Applications – volume: 258 year: 2020 ident: bib24 article-title: Demand side management in hybrid rooftop photovoltaic integrated smart nano grid publication-title: J. Clean. Prod. – volume: 59 start-page: 1653 year: 2016 end-page: 1675 ident: bib61 article-title: Comparative study of HVAC and HVDC transmission systems publication-title: Renew. Sustain. Energy Rev. – volume: 53 start-page: 5155 year: 2017 end-page: 5163 ident: bib36 article-title: Load shedding and smart-direct load control using internet of things in smart grid demand response management publication-title: IEEE Trans. Ind. Appl. – year: 2019 ident: bib15 publication-title: “IoT-Based Power Management for DC Microgrids,” in – volume: 6 year: 2019 ident: bib46 article-title: Accurate and instant frequency estimation from noisy sinusoidal waves by deep learning publication-title: Nano Converg. – reference: Ethan S, “Our Sun Is Lighter than Ever, and the Problem Is Getting Worse.,” – year: 2012 ident: bib7 article-title: What the Duck Curve Tells Us about Managing a Green Grid,” Calif. ISO, Shap. A Renewed Futur., – volume: 9 year: 2019 ident: bib16 article-title: Short-term forecasting of power production in a large-scale photovoltaic plant based on LSTM publication-title: Appl. Sci. – volume: 49 start-page: 1189 year: 2000 end-page: 1193 ident: bib18 article-title: Properties of the IEEE-STD-1057 four-parameter sine wave fit algorithm publication-title: IEEE Trans. Instrum. Meas. – year: 2018 ident: bib43 article-title: Smart IoT based energy metering system for microgrids with load management algorithm publication-title: , ICCMC – year: 2020 ident: bib37 article-title: DDOS attack on IOT devices publication-title: ICCAIS 2020 - 3rd International Conference on Computer Applications and Information Security, – year: 1995 ident: bib23 article-title: Digital Protection for Power Systems – year: 2019 ident: bib57 article-title: IOT devices for control applications: a review publication-title: , ICECA – year: 2019 ident: bib1 article-title: AI concepts for demand side shedding management in Libya publication-title: , ICRERA – volume: 10 start-page: 341 year: 2016 end-page: 351 ident: bib9 article-title: “Special protection scheme against voltage collapse,” publication-title: Transm. Distrib. – start-page: 2016 year: 2016 ident: bib42 article-title: Extended functionality attacks on IoT devices: the case of smart lights publication-title: , EURO S and – year: 2020 ident: bib21 article-title: Unit Commitment using advanced direct load control publication-title: , APPEEC – volume: 6 start-page: 317 year: 2009 end-page: 327 ident: bib48 article-title: Design of new load shedding special protection schemes for a double area power system publication-title: Am. J. Appl. Sci. – year: 2017 ident: bib55 article-title: “Algorithm for Sine Wave Cure Fit Based on Frequency Precise Estimation,” in – volume: 2 start-page: 94 year: 2015 end-page: 101 ident: bib10 article-title: Big data analytics for dynamic energy management in smart grids publication-title: Big Data Research – year: 1997 ident: bib31 article-title: Operational experience of load shedding and new requirements on frequency relays,” publication-title: IEE Conference Publication – year: 2008 ident: bib28 article-title: “Microgrid Standards and Technologies,” in – volume: 9 start-page: 1371 year: 1994 end-page: 1378 ident: bib40 article-title: A new load shedding scheme for limiting under frequency publication-title: IEEE Trans. Power Syst. – year: 2011 ident: bib45 article-title: “Forecast of the system frequency response for underfrequency load shedding publication-title: 2011 IEEE PES Trondheim PowerTech: the Power of Technology for a Sustainable Society, POWERTECH – volume: 2 start-page: 1607 year: 2014 end-page: 1628 ident: bib19 article-title: Synchrophasor measurement technology in power systems: Panorama and State-of-the-Art publication-title: IEEE Access. – reference: Eclypse Z7 Hardware Reference Manual [Digilent Documentation] . – volume: 6 start-page: 8182 year: 2019 end-page: 8201 ident: bib35 article-title: IoT: internet of threats? A Survey of practical security Vulnerabilities in real IoT devices publication-title: ” IEEE Internet Things J. – volume: 9 start-page: 979 year: 2019 end-page: 985 ident: bib58 article-title: A reversal in global terrestrial stilling and its implications for wind energy production publication-title: Nat. Clim. Change – reference: . – year: 2019 ident: bib38 article-title: “A proposal of demand response program for Suppressing duck-curve’s ramp rate with large penetration of photovoltaic generation systems,” publication-title: IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT – volume: 179 year: 2020 ident: bib17 article-title: An Overview of UFLS in conventional, modern, and future smart power systems: challenges and Opportunities publication-title: Elec. Power Syst. Res. – ident: bib51 article-title: “iot-number-of-connected-devices-worldwide.” [Online]. Available: – year: 2013 ident: bib25 article-title: The role of big data in improving power system operation and protection publication-title: , IREP – year: 2010 ident: bib5 article-title: Energy management of hybrid DC and AC bus linked microgrid publication-title: , PEDG – year: 2015 ident: bib32 article-title: Application of high sampling rate data in merging unit for relay protection publication-title: , DRPT – volume: 6 start-page: 317 year: 2009 ident: 10.1016/j.jclepro.2021.126294_bib48 article-title: Design of new load shedding special protection schemes for a double area power system publication-title: Am. J. Appl. Sci. doi: 10.3844/ajassp.2009.317.327 – ident: 10.1016/j.jclepro.2021.126294_bib8 – year: 2013 ident: 10.1016/j.jclepro.2021.126294_bib50 article-title: Smart home: integrating internet of things with web services and cloud computing – start-page: 2016 year: 2016 ident: 10.1016/j.jclepro.2021.126294_bib42 article-title: Extended functionality attacks on IoT devices: the case of smart lights – year: 2018 ident: 10.1016/j.jclepro.2021.126294_bib43 article-title: Smart IoT based energy metering system for microgrids with load management algorithm – volume: 6 issue: 27 year: 2019 ident: 10.1016/j.jclepro.2021.126294_bib46 article-title: Accurate and instant frequency estimation from noisy sinusoidal waves by deep learning publication-title: Nano Converg. – volume: 9 issue: 15 year: 2019 ident: 10.1016/j.jclepro.2021.126294_bib16 article-title: Short-term forecasting of power production in a large-scale photovoltaic plant based on LSTM publication-title: Appl. Sci. doi: 10.3390/app9153192 – volume: 9 start-page: 979 year: 2019 ident: 10.1016/j.jclepro.2021.126294_bib58 article-title: A reversal in global terrestrial stilling and its implications for wind energy production publication-title: Nat. Clim. Change doi: 10.1038/s41558-019-0622-6 – volume: 36 start-page: 1665 issue: 17–18 year: 2013 ident: 10.1016/j.jclepro.2021.126294_bib3 article-title: The role of communication systems in smart grids: architectures, technical solutions and research challenges publication-title: Comput. Commun. doi: 10.1016/j.comcom.2013.09.004 – volume: 258 year: 2020 ident: 10.1016/j.jclepro.2021.126294_bib24 article-title: Demand side management in hybrid rooftop photovoltaic integrated smart nano grid publication-title: J. Clean. Prod. doi: 10.1016/j.jclepro.2020.120747 – issue: 2nd year: 2003 ident: 10.1016/j.jclepro.2021.126294_bib12 article-title: Protective relaying theory and applicantions publication-title: Protective Relaying Theory and Applications – ident: 10.1016/j.jclepro.2021.126294_bib13 – year: 2019 ident: 10.1016/j.jclepro.2021.126294_bib49 article-title: “ – volume: 10 issue: 3 year: 2017 ident: 10.1016/j.jclepro.2021.126294_bib20 article-title: A chance-constrained economic dispatch model in wind-thermal-energy storage system publication-title: Energies doi: 10.3390/en10030326 – ident: 10.1016/j.jclepro.2021.126294_bib59 – volume: 210 start-page: 748 year: 2018 ident: 10.1016/j.jclepro.2021.126294_bib33 article-title: Simple electric utility platform: a hardware/software solution for operating emergent microgrids publication-title: Appl. Energy doi: 10.1016/j.apenergy.2017.07.073 – year: 2018 ident: 10.1016/j.jclepro.2021.126294_bib30 article-title: IOT based PV assisted EV charging station for Confronting duck curve – volume: 6 start-page: 8182 issue: 5 year: 2019 ident: 10.1016/j.jclepro.2021.126294_bib35 article-title: IoT: internet of threats? A Survey of practical security Vulnerabilities in real IoT devices publication-title: ” IEEE Internet Things J. doi: 10.1109/JIOT.2019.2935189 – year: 2017 ident: 10.1016/j.jclepro.2021.126294_bib39 article-title: Control and energy management system in microgrids – volume: 2 start-page: 1607 year: 2014 ident: 10.1016/j.jclepro.2021.126294_bib19 article-title: Synchrophasor measurement technology in power systems: Panorama and State-of-the-Art publication-title: IEEE Access. doi: 10.1109/ACCESS.2015.2389659 – year: 2019 ident: 10.1016/j.jclepro.2021.126294_bib15 – volume: 3 start-page: 99 year: 2009 ident: 10.1016/j.jclepro.2021.126294_bib62 article-title: New centralised adaptive load-shedding algorithms to mitigate power system blackouts publication-title: IET Gener. Transm. Distrib. doi: 10.1049/iet-gtd:20080210 – year: 2019 ident: 10.1016/j.jclepro.2021.126294_bib1 article-title: AI concepts for demand side shedding management in Libya – year: 2019 ident: 10.1016/j.jclepro.2021.126294_bib57 article-title: IOT devices for control applications: a review – year: 2008 ident: 10.1016/j.jclepro.2021.126294_bib28 – year: 2020 ident: 10.1016/j.jclepro.2021.126294_bib37 article-title: DDOS attack on IOT devices – volume: 2 start-page: 94 issue: 3 year: 2015 ident: 10.1016/j.jclepro.2021.126294_bib10 article-title: Big data analytics for dynamic energy management in smart grids publication-title: Big Data Research doi: 10.1016/j.bdr.2015.03.003 – year: 2019 ident: 10.1016/j.jclepro.2021.126294_bib27 – year: 2020 ident: 10.1016/j.jclepro.2021.126294_bib21 article-title: Unit Commitment using advanced direct load control – ident: 10.1016/j.jclepro.2021.126294_bib51 – volume: 11 issue: 7 year: 2013 ident: 10.1016/j.jclepro.2021.126294_bib26 article-title: Assessment of wind power potential at Hawksbay, Karachi Sindh, Pakistan publication-title: TELKOMNIKA Indones. J. Electr. Eng. – year: 2010 ident: 10.1016/j.jclepro.2021.126294_bib5 article-title: Energy management of hybrid DC and AC bus linked microgrid – year: 1995 ident: 10.1016/j.jclepro.2021.126294_bib23 – ident: 10.1016/j.jclepro.2021.126294_bib2 – year: 2019 ident: 10.1016/j.jclepro.2021.126294_bib38 article-title: “A proposal of demand response program for Suppressing duck-curve’s ramp rate with large penetration of photovoltaic generation systems,” – volume: 9 start-page: 1371 issue: 3 year: 1994 ident: 10.1016/j.jclepro.2021.126294_bib40 article-title: A new load shedding scheme for limiting under frequency publication-title: IEEE Trans. Power Syst. doi: 10.1109/59.336128 – volume: 59 start-page: 1653 year: 2016 ident: 10.1016/j.jclepro.2021.126294_bib61 article-title: Comparative study of HVAC and HVDC transmission systems publication-title: Renew. Sustain. Energy Rev. doi: 10.1016/j.rser.2015.12.288 – ident: 10.1016/j.jclepro.2021.126294_bib11 – volume: 179 year: 2020 ident: 10.1016/j.jclepro.2021.126294_bib17 article-title: An Overview of UFLS in conventional, modern, and future smart power systems: challenges and Opportunities publication-title: Elec. Power Syst. Res. doi: 10.1016/j.epsr.2019.106054 – year: 2020 ident: 10.1016/j.jclepro.2021.126294_bib41 – year: 2012 ident: 10.1016/j.jclepro.2021.126294_bib7 – year: 1997 ident: 10.1016/j.jclepro.2021.126294_bib31 article-title: Operational experience of load shedding and new requirements on frequency relays,” – volume: 53 start-page: 5155 issue: 6 year: 2017 ident: 10.1016/j.jclepro.2021.126294_bib36 article-title: Load shedding and smart-direct load control using internet of things in smart grid demand response management publication-title: IEEE Trans. Ind. Appl. doi: 10.1109/TIA.2017.2740832 – volume: 71 start-page: 34 year: 2015 ident: 10.1016/j.jclepro.2021.126294_bib54 article-title: Resilient communication for smart grid ubiquitous sensor network: state of the art and prospects for next generation publication-title: Comput. Commun. doi: 10.1016/j.comcom.2015.05.015 – volume: 25 start-page: 45 issue: 8 year: 2012 ident: 10.1016/j.jclepro.2021.126294_bib52 article-title: Energy management systems in microgrid operations publication-title: Electr. J. doi: 10.1016/j.tej.2012.09.010 – volume: 49 start-page: 1189 issue: 6 year: 2000 ident: 10.1016/j.jclepro.2021.126294_bib18 article-title: Properties of the IEEE-STD-1057 four-parameter sine wave fit algorithm publication-title: IEEE Trans. Instrum. Meas. doi: 10.1109/19.893254 – volume: 26 start-page: 839 year: 2011 ident: 10.1016/j.jclepro.2021.126294_bib44 article-title: Monitoring the first frequency derivative to improve adaptive underfrequency load-shedding schemes publication-title: IEEE Trans. Power Syst. doi: 10.1109/TPWRS.2010.2059715 – volume: 105 start-page: 1311 issue: 107 year: 2017 ident: 10.1016/j.jclepro.2021.126294_bib4 article-title: Distributed power-generation systems and protection publication-title: Proceedings of the IEEE doi: 10.1109/JPROC.2017.2696878 – volume: 8 start-page: 43 issue: 1 year: 2016 ident: 10.1016/j.jclepro.2021.126294_bib34 article-title: The load current and voltage estimation using interpolation method in electrical power monitoring system based on microcontroller atmega 8535 and pc publication-title: Bull. Math. – year: 2011 ident: 10.1016/j.jclepro.2021.126294_bib45 article-title: “Forecast of the system frequency response for underfrequency load shedding – year: 2013 ident: 10.1016/j.jclepro.2021.126294_bib25 article-title: The role of big data in improving power system operation and protection – year: 2017 ident: 10.1016/j.jclepro.2021.126294_bib29 – volume: 10 start-page: 341 issue: 2 year: 2016 ident: 10.1016/j.jclepro.2021.126294_bib9 article-title: “Special protection scheme against voltage collapse,” IET Gener publication-title: Transm. Distrib. doi: 10.1049/iet-gtd.2015.0277 – year: 2019 ident: 10.1016/j.jclepro.2021.126294_bib53 article-title: Digital twin and cloud, fog, edge computing – year: 2015 ident: 10.1016/j.jclepro.2021.126294_bib32 article-title: Application of high sampling rate data in merging unit for relay protection – year: 2017 ident: 10.1016/j.jclepro.2021.126294_bib55 |
| SSID | ssj0017074 |
| Score | 2.4391708 |
| Snippet | Power grids are undergoing deregulation, privatization, and decentralization worldwide. The smart grid allows the integration of clean power renewable energy... |
| SourceID | proquest crossref elsevier |
| SourceType | Aggregation Database Enrichment Source Index Database Publisher |
| StartPage | 126294 |
| SubjectTerms | biomass computer software consumer demand decentralization Demand response (DR) Demand side management (DSM) electric potential difference electrical equipment fossil fuels Internet IoT management systems Nanogrids power generation privatization Renewable energy Smart grid wind wind power |
| Title | Duck curve leveling in renewable energy integrated grids using internet of relays |
| URI | https://dx.doi.org/10.1016/j.jclepro.2021.126294 https://www.proquest.com/docview/2524250846 |
| Volume | 294 |
| WOSCitedRecordID | wos000629035100001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| journalDatabaseRights | – providerCode: PRVESC databaseName: Elsevier SD Freedom Collection Journals 2021 customDbUrl: eissn: 1879-1786 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0017074 issn: 0959-6526 databaseCode: AIEXJ dateStart: 19950101 isFulltext: true titleUrlDefault: https://www.sciencedirect.com providerName: Elsevier |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1Lj9MwELZKlwMcEE-xLCAjcYtSEtd5-FihRcCh4rFIvUWT2KGpssmqaapdbvvPGcd5lMKy7IFLVFmx43Q-T-Y9hLwGJhPXd7idci9EBQVcG1DTspMppNovKNQ0bppNBPN5uFiIT6PRZZcLs82DogjPz8XZfyU1jiGxdersDcjdL4oD-BuJjlckO17_ifC66bOV1OutsnIdEdQnraAA3eRJqS7dry0UIa3v60xWVl2ZW7WJUDUBAjrR5aK6Qn7FxwKupCO8pClB2zNvyCEzTbLzzPoCP3rWP4tN_tgcVGsybkKNL5Q8heVpWWuwNiZatZTZ4IKqm8qRX5clZPGumYK52uPCnD17o--Z9PiO9TLBd5iny_x24De-bkwMq8kK3w1fa6KfMBnu_7WO9t73rY867ALaVlG7TKSXicwyt8gBCzwRjsnB7MPx4mPvigocU8q72_-QBvbmj_u5SsDZ-9Q38svJfXKvJRydGcA8ICNVPCR3d8pRPiKfNXRoAx3aQYdmBe2hQw106AAd2kCHNtChHXRomVIDncfk27vjk7fv7bblBh5OzjZ2DAwgicFx8Iz6XImQx6gCeCkXErl9CODIULrSTX3mKl3OUUkuFOdBAr7P4-kTMi7KQj0lVNdSm6JyEALKuChmC1eAgET6yvMCnsAh4d3_FCVtPXrdFiWP_kqnQzLpp52ZgizXTQg7IkStVGmkxQjBdd3UVx3RIuS62pWGB6usq4h5WlV3UHh_dtP9HJE7w_l4Tsabda1ekNvJdpNV65ct-n4C54upRA |
| linkProvider | Elsevier |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Duck+curve+leveling+in+renewable+energy+integrated+grids+using+internet+of+relays&rft.jtitle=Journal+of+cleaner+production&rft.au=Kalair%2C+Ali+Raza&rft.au=Abas%2C+Naeem&rft.au=Seyedmahmoudian%2C+Mehdi&rft.au=Rauf%2C+Shoaib&rft.date=2021-04-20&rft.issn=0959-6526&rft.volume=294&rft.spage=126294&rft_id=info:doi/10.1016%2Fj.jclepro.2021.126294&rft.externalDBID=n%2Fa&rft.externalDocID=10_1016_j_jclepro_2021_126294 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0959-6526&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0959-6526&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0959-6526&client=summon |