Optimal offering strategy for wind-storage systems under correlated wind production

This paper formulates the offering problem for a cluster of wind-storage systems in the day-ahead energy market using a risk-constrained stochastic programming approach that anticipates different operating conditions in the real-time energy market. Wind-storage systems can be jointly operated as a c...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:Applied energy Ročník 333; s. 120552
Hlavní autori: Dirin, Sepehr, Rahimiyan, Morteza, Baringo, Luis
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Elsevier Ltd 01.03.2023
Predmet:
ISSN:0306-2619
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Abstract This paper formulates the offering problem for a cluster of wind-storage systems in the day-ahead energy market using a risk-constrained stochastic programming approach that anticipates different operating conditions in the real-time energy market. Wind-storage systems can be jointly operated as a cluster so as to achieve higher profitability. However, a meaningful positive correlation among the production provided by wind farms located in the cluster results in a higher level of uncertainty that imposes additional risk. A key issue is how this correlation influences the operation of the cluster in the energy markets. In order to study this subject, this paper presents the uncertainties involved by means of a number of correlated scenarios including: (i) the correlated prices in the day-ahead and the real-time markets, and (ii) the correlated wind power production of multiple wind farms jointly generated using an innovative scenario generation methodology. The comparative statistical analysis validates the good accuracy of the method proposed in order to capture the spatio-temporal correlation among the wind farms. The results of a realistic case study are, moreover, compared with those obtained by considering that the scenarios are generated individually for each wind farm. Upon considering the latter, the variability of wind power production is underestimated, which has a negligible impact on the expected profit; however, the profit risk modeled using the conditional value-at-risk is significantly overestimated. The overestimation error particularly concerns a less risk-averse operator of the cluster in the case of low wind power production. •Correlated scenarios for wind production are jointly generated.•Individual uncertainty model of wind production cannot fully capture correlation.•Offering of wind-storage systems is compared using joint and individual models.•Conditional value-at-risk of profit is overestimated by individual uncertainty model.•If wind production is low, the higher-risk offering intensifies overestimation error.
AbstractList This paper formulates the offering problem for a cluster of wind-storage systems in the day-ahead energy market using a risk-constrained stochastic programming approach that anticipates different operating conditions in the real-time energy market. Wind-storage systems can be jointly operated as a cluster so as to achieve higher profitability. However, a meaningful positive correlation among the production provided by wind farms located in the cluster results in a higher level of uncertainty that imposes additional risk. A key issue is how this correlation influences the operation of the cluster in the energy markets. In order to study this subject, this paper presents the uncertainties involved by means of a number of correlated scenarios including: (i) the correlated prices in the day-ahead and the real-time markets, and (ii) the correlated wind power production of multiple wind farms jointly generated using an innovative scenario generation methodology. The comparative statistical analysis validates the good accuracy of the method proposed in order to capture the spatio-temporal correlation among the wind farms. The results of a realistic case study are, moreover, compared with those obtained by considering that the scenarios are generated individually for each wind farm. Upon considering the latter, the variability of wind power production is underestimated, which has a negligible impact on the expected profit; however, the profit risk modeled using the conditional value-at-risk is significantly overestimated. The overestimation error particularly concerns a less risk-averse operator of the cluster in the case of low wind power production. •Correlated scenarios for wind production are jointly generated.•Individual uncertainty model of wind production cannot fully capture correlation.•Offering of wind-storage systems is compared using joint and individual models.•Conditional value-at-risk of profit is overestimated by individual uncertainty model.•If wind production is low, the higher-risk offering intensifies overestimation error.
ArticleNumber 120552
Author Baringo, Luis
Dirin, Sepehr
Rahimiyan, Morteza
Author_xml – sequence: 1
  givenname: Sepehr
  surname: Dirin
  fullname: Dirin, Sepehr
  email: sepehr.dirin@gmail.com
  organization: Faculty of Electrical Engineering, Shahrood University of Technology, 3619995161 Shahrood, Iran
– sequence: 2
  givenname: Morteza
  orcidid: 0000-0002-2423-1861
  surname: Rahimiyan
  fullname: Rahimiyan, Morteza
  email: morteza.rahimiyan@shahroodut.ac.ir
  organization: Faculty of Electrical Engineering, Shahrood University of Technology, 3619995161 Shahrood, Iran
– sequence: 3
  givenname: Luis
  orcidid: 0000-0002-8678-3258
  surname: Baringo
  fullname: Baringo, Luis
  email: Luis.Baringo@uclm.es
  organization: Department of Electrical Engineering, Universidad de Castilla-La Mancha, Campus Universitario s/n, 13071 Ciudad Real, Spain
BookMark eNqFkMtOwzAQRb0oEm3hF5B_IMF2UqeRWIAqXlKlLoC15diTyFVqR2MX1L8npbBh09Us5p6rmTMjEx88EHLDWc4Zl7fbXA_gAbtDLpgQORdssRATMmUFk5mQvL4ksxi3jDEx7qbkbTMkt9M9DW0L6HxHY0KdoDvQNiD9ct5mMQXUHdB4iAl2ke69BaQmIEI_Ru1Pig4Y7N4kF_wVuWh1H-H6d87Jx9Pj--olW2-eX1cP68yIUqQMoCqt0LUtAOqmLCrT6LYAW1tWVkvWNFVdSF1pWHIpm6VkWpqS83qhrbClZsWc3J16DYYYEVplXNLHC8YXXK84U0cpaqv-pKijFHWSMuLyHz7gqAIP58H7Ewjjc58OUEXjwBuwDsEkZYM7V_ENw0mHMA
CitedBy_id crossref_primary_10_1016_j_renene_2024_121769
crossref_primary_10_1016_j_epsr_2023_110039
crossref_primary_10_1016_j_ijepes_2025_110795
crossref_primary_10_1016_j_egyr_2023_08_027
crossref_primary_10_1016_j_apenergy_2024_124380
crossref_primary_10_1016_j_est_2025_117313
crossref_primary_10_1016_j_ijepes_2025_110492
crossref_primary_10_1016_j_energy_2023_130009
crossref_primary_10_3389_fenrg_2023_1094970
Cites_doi 10.1016/j.apenergy.2020.115973
10.1109/TSTE.2020.2965521
10.1016/j.epsr.2020.106745
10.1016/j.renene.2019.02.064
10.1016/j.ijhydene.2018.09.179
10.1287/opre.2013.1174
10.1109/TSTE.2018.2819137
10.1109/TPWRS.2015.2411332
10.1109/TPWRS.2016.2521177
10.1016/j.apenergy.2012.12.077
10.1002/we.1597
10.1016/j.apenergy.2018.03.082
10.1109/TPWRS.2018.2794541
10.1016/j.ijepes.2021.106955
10.35833/MPCE.2020.000935
10.1016/j.renene.2020.04.057
10.1002/we.2095
10.1109/TIA.2018.2828379
10.1109/TEC.2003.821865
10.1023/A:1021805924152
10.1016/j.ijepes.2020.106343
10.1016/j.apenergy.2009.09.022
10.1016/j.ijepes.2020.105931
10.1109/TPWRS.2015.2483781
10.1109/TSTE.2018.2806444
10.1016/j.renene.2015.07.104
10.1109/TPWRS.2013.2273276
10.1109/TPWRS.2013.2262502
10.1109/TSTE.2020.2967860
10.1109/TPWRS.2015.2477466
10.1109/TSTE.2019.2895332
10.1016/j.epsr.2019.105986
ContentType Journal Article
Copyright 2022 Elsevier Ltd
Copyright_xml – notice: 2022 Elsevier Ltd
DBID AAYXX
CITATION
DOI 10.1016/j.apenergy.2022.120552
DatabaseName CrossRef
DatabaseTitle CrossRef
DatabaseTitleList
DeliveryMethod fulltext_linktorsrc
Discipline Engineering
Environmental Sciences
ExternalDocumentID 10_1016_j_apenergy_2022_120552
S0306261922018098
GroupedDBID --K
--M
.~1
0R~
1B1
1~.
1~5
23M
4.4
457
4G.
5GY
5VS
7-5
71M
8P~
9JN
AABNK
AACTN
AAEDT
AAEDW
AAHBH
AAHCO
AAIKJ
AAKOC
AALRI
AAOAW
AAQFI
AARJD
AAXKI
AAXUO
ABJNI
ABMAC
ACDAQ
ACGFS
ACRLP
ADBBV
ADEZE
ADTZH
AEBSH
AECPX
AEKER
AENEX
AFJKZ
AFKWA
AFTJW
AGHFR
AGUBO
AGYEJ
AHHHB
AHIDL
AHJVU
AIEXJ
AIKHN
AITUG
AJOXV
AKRWK
ALMA_UNASSIGNED_HOLDINGS
AMFUW
AMRAJ
AXJTR
BELTK
BJAXD
BKOJK
BLXMC
CS3
EBS
EFJIC
EO8
EO9
EP2
EP3
FDB
FIRID
FNPLU
FYGXN
G-Q
GBLVA
IHE
J1W
JARJE
JJJVA
KOM
LY6
M41
MO0
N9A
O-L
O9-
OAUVE
OZT
P-8
P-9
P2P
PC.
Q38
ROL
RPZ
SDF
SDG
SES
SPC
SPCBC
SSR
SST
SSZ
T5K
TN5
~02
~G-
9DU
AAQXK
AATTM
AAYWO
AAYXX
ABEFU
ABFNM
ABWVN
ABXDB
ACLOT
ACNNM
ACRPL
ACVFH
ADCNI
ADMUD
ADNMO
AEIPS
AEUPX
AFPUW
AGQPQ
AIGII
AIIUN
AKBMS
AKYEP
ANKPU
APXCP
ASPBG
AVWKF
AZFZN
CITATION
EFKBS
EFLBG
EJD
FEDTE
FGOYB
G-2
HVGLF
HZ~
R2-
SAC
SEW
WUQ
ZY4
~HD
ID FETCH-LOGICAL-c242t-ee74d2a9d3ee9b437cbaf3ed9d04780bb7936a7ae8166b860a6c41195ad2d4a03
ISICitedReferencesCount 14
ISICitedReferencesURI http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000925252900001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN 0306-2619
IngestDate Sat Nov 29 07:21:41 EST 2025
Tue Nov 18 22:19:32 EST 2025
Tue Dec 03 03:45:02 EST 2024
IsPeerReviewed true
IsScholarly true
Keywords Conditional value-at-risk
Wind-storage systems
Offering strategy
Correlated scenarios
Stochastic programming
Language English
LinkModel OpenURL
MergedId FETCHMERGED-LOGICAL-c242t-ee74d2a9d3ee9b437cbaf3ed9d04780bb7936a7ae8166b860a6c41195ad2d4a03
ORCID 0000-0002-2423-1861
0000-0002-8678-3258
ParticipantIDs crossref_citationtrail_10_1016_j_apenergy_2022_120552
crossref_primary_10_1016_j_apenergy_2022_120552
elsevier_sciencedirect_doi_10_1016_j_apenergy_2022_120552
PublicationCentury 2000
PublicationDate 2023-03-01
2023-03-00
PublicationDateYYYYMMDD 2023-03-01
PublicationDate_xml – month: 03
  year: 2023
  text: 2023-03-01
  day: 01
PublicationDecade 2020
PublicationTitle Applied energy
PublicationYear 2023
Publisher Elsevier Ltd
Publisher_xml – name: Elsevier Ltd
References Baringo, Conejo (b5) 2016; 31
Louie (b2) 2014; 17
Malvaldi, Weiss, Infield, Browell, Leahy, Foley (b3) 2017; 20
Nguyen, Le, Wang (b17) 2018; 54
Conejo, Carrión, Morales (b1) 2010
GAMS. 2022, Available at
Papavasiliou, Oren (b35) 2013; 61
Baeyens, Bitar, Khargonekar, Poolla (b8) 2013; 28
Zhang, Jiang, Li, Li, Chen, Li (b18) 2020; 11
Arjmand, Rahimiyan (b36) 2016; 86
Attarha, Amjady, Dehghan, Vatani (b14) 2018; 9
Windy: Wind map and weather forecast. 2022, Available at
Han, Kardakos, Hug (b6) 2019; 177
Wang (b32) 1996
Tan, Wu, Zhang, Wei, Hatziargyriou, Liu (b23) 2021; 130
ILOG CPLEX. 2022, Available at
Wu, Zhou, Wang, Du, Zhang, Li (b19) 2020; 11
Xu, Hu, Cao, Huang, Liu, Liu (b16) 2020; 156
Heitsch, Römisch (b38) 2003; 24
Tanga, Wangb, Xua, Suna, Zhang (b26) 2018; 221
Rahimiyan, Baringo (b31) 2016; 31
Morales, Mínguez, Conejo (b22) 2010; 87
Seok, Chen (b11) 2019; 138
ISO New England, US. 2022, Available at
NREL. Wind integration national dataset toolkit. 2022, Available at
Han, Hug (b15) 2020; 189
Ghavidel, Ghadi, Azizivahed, Aghaei, Li, Zhang (b13) 2020; 11
Damousis, Alexiadis, Theocharis, Dokopoulos (b28) 2004; 19
Hosseini, Toubeau, Grève, Vallée (b7) 2020; 280
Nguyen, Le (b10) 2018; 9
.
Ding, Pinson, Hu, Song (b12) 2016; 31
Pandz̆ić, Morales, Conejo, Kuzle (b21) 2013; 105
Chen, Wang, Kirschen, Zhang (b27) 2018; 33
Guerrero-Mestre, de la Nieta, Contreras, Catalão (b9) 2016; 31
Windguru–Maui (north shore). 2022, Available at
Rashidizadeh-Kermani, Vahedipour-Dahraie, Shafie-Khah, Siano (b20) 2021; 124
Qiu, Li, Pan, Yang, Chen (b24) 2019; 44
Tu, Miao, Yao, Li, Yin, Han (b25) 2021; 9
Abedi, Rahimiyan (b29) 2020; 120
Baringo, Conejo (b4) 2013; 28
Attarha (10.1016/j.apenergy.2022.120552_b14) 2018; 9
Ghavidel (10.1016/j.apenergy.2022.120552_b13) 2020; 11
Chen (10.1016/j.apenergy.2022.120552_b27) 2018; 33
Rashidizadeh-Kermani (10.1016/j.apenergy.2022.120552_b20) 2021; 124
Xu (10.1016/j.apenergy.2022.120552_b16) 2020; 156
Baringo (10.1016/j.apenergy.2022.120552_b4) 2013; 28
Han (10.1016/j.apenergy.2022.120552_b15) 2020; 189
Wu (10.1016/j.apenergy.2022.120552_b19) 2020; 11
Tu (10.1016/j.apenergy.2022.120552_b25) 2021; 9
Han (10.1016/j.apenergy.2022.120552_b6) 2019; 177
Guerrero-Mestre (10.1016/j.apenergy.2022.120552_b9) 2016; 31
Baeyens (10.1016/j.apenergy.2022.120552_b8) 2013; 28
Nguyen (10.1016/j.apenergy.2022.120552_b17) 2018; 54
Arjmand (10.1016/j.apenergy.2022.120552_b36) 2016; 86
10.1016/j.apenergy.2022.120552_b30
Damousis (10.1016/j.apenergy.2022.120552_b28) 2004; 19
Tan (10.1016/j.apenergy.2022.120552_b23) 2021; 130
10.1016/j.apenergy.2022.120552_b33
Pandz̆ić (10.1016/j.apenergy.2022.120552_b21) 2013; 105
10.1016/j.apenergy.2022.120552_b34
Wang (10.1016/j.apenergy.2022.120552_b32) 1996
Papavasiliou (10.1016/j.apenergy.2022.120552_b35) 2013; 61
10.1016/j.apenergy.2022.120552_b37
Baringo (10.1016/j.apenergy.2022.120552_b5) 2016; 31
Nguyen (10.1016/j.apenergy.2022.120552_b10) 2018; 9
Malvaldi (10.1016/j.apenergy.2022.120552_b3) 2017; 20
Hosseini (10.1016/j.apenergy.2022.120552_b7) 2020; 280
Rahimiyan (10.1016/j.apenergy.2022.120552_b31) 2016; 31
10.1016/j.apenergy.2022.120552_b39
Heitsch (10.1016/j.apenergy.2022.120552_b38) 2003; 24
Seok (10.1016/j.apenergy.2022.120552_b11) 2019; 138
Tanga (10.1016/j.apenergy.2022.120552_b26) 2018; 221
Morales (10.1016/j.apenergy.2022.120552_b22) 2010; 87
Louie (10.1016/j.apenergy.2022.120552_b2) 2014; 17
Conejo (10.1016/j.apenergy.2022.120552_b1) 2010
Ding (10.1016/j.apenergy.2022.120552_b12) 2016; 31
Qiu (10.1016/j.apenergy.2022.120552_b24) 2019; 44
Abedi (10.1016/j.apenergy.2022.120552_b29) 2020; 120
Zhang (10.1016/j.apenergy.2022.120552_b18) 2020; 11
10.1016/j.apenergy.2022.120552_b40
References_xml – volume: 33
  start-page: 3265
  year: 2018
  end-page: 3275
  ident: b27
  article-title: Model-free renewable scenario generation using generative adversarial networks
  publication-title: IEEE Trans Power Syst
– volume: 20
  start-page: 1315
  year: 2017
  end-page: 1329
  ident: b3
  article-title: A spatial and temporal correlation analysis of aggregate wind power in an ideally interconnected Europe
  publication-title: Wind Energy
– volume: 189
  year: 2020
  ident: b15
  article-title: A distributionally robust bidding strategy for a wind-storage aggregator
  publication-title: Electr Power Syst Res
– volume: 28
  start-page: 4645
  year: 2013
  end-page: 4654
  ident: b4
  article-title: Strategic offering for a wind power producer
  publication-title: IEEE Trans Power Syst
– volume: 61
  start-page: 578
  year: 2013
  end-page: 592
  ident: b35
  article-title: Multiarea stochastic unit commitment for high wind penetration in a transmission constrained network
  publication-title: Oper Res
– volume: 105
  start-page: 282
  year: 2013
  end-page: 292
  ident: b21
  article-title: Offering model for a virtual power plant based on stochastic programming
  publication-title: Appl Energy
– volume: 44
  start-page: 5162
  year: 2019
  end-page: 5170
  ident: b24
  article-title: A scenario generation method based on the mixture vine copula and its application in the power system with wind/hydrogen production
  publication-title: Int J Hydrog Energy
– volume: 31
  start-page: 2688
  year: 2016
  end-page: 2700
  ident: b9
  article-title: Optimal bidding of a group of wind farms in day-ahead markets through an external agent
  publication-title: IEEE Trans Power Syst
– reference: Windguru–Maui (north shore). 2022, Available at
– volume: 120
  year: 2020
  ident: b29
  article-title: Day-ahead energy and reserve scheduling under correlated wind power production
  publication-title: Int J Electr Power Energy Syst
– volume: 24
  start-page: 187
  year: 2003
  end-page: 206
  ident: b38
  article-title: Scenario reduction algorithms in stochastic programming
  publication-title: Comput Optim Appl
– volume: 9
  start-page: 1921
  year: 2018
  end-page: 1934
  ident: b10
  article-title: Sharing profit from joint offering of a group of wind power producers in day ahead markets
  publication-title: IEEE Trans Sustain Energy
– volume: 138
  start-page: 1134
  year: 2019
  end-page: 1142
  ident: b11
  article-title: An intelligent wind power plant coalition formation model achieving balanced market penetration growth and profit increase
  publication-title: Renew Energy
– year: 1996
  ident: b32
  article-title: A Course in Fuzzy Systems and Control
– reference: NREL. Wind integration national dataset toolkit. 2022, Available at
– volume: 28
  start-page: 3774
  year: 2013
  end-page: 3784
  ident: b8
  article-title: Coalitional aggregation of wind power
  publication-title: IEEE Trans Power Syst
– reference: ILOG CPLEX. 2022, Available at
– volume: 177
  year: 2019
  ident: b6
  article-title: A distributionally robust bidding strategy for a wind power plant
  publication-title: Electr Power Syst Res
– volume: 11
  start-page: 2545
  year: 2020
  end-page: 2555
  ident: b18
  article-title: Coordinated bidding strategy of wind farms and power-to-gas facilities using a cooperative game approach
  publication-title: IEEE Trans Sustain Energy
– volume: 31
  start-page: 1420
  year: 2016
  end-page: 1429
  ident: b5
  article-title: Offering strategy of wind-power producer: A multi-stage risk-constrained approach
  publication-title: IEEE Trans Power Syst
– volume: 280
  year: 2020
  ident: b7
  article-title: An advanced day-ahead bidding strategy for wind power producers considering confidence level on the real-time reserve provision
  publication-title: Appl Energy
– reference: GAMS. 2022, Available at
– volume: 156
  start-page: 47
  year: 2020
  end-page: 56
  ident: b16
  article-title: Scheduling of wind-battery hybrid system in the electricity market using distributionally robust optimization
  publication-title: Renew Energy
– volume: 9
  start-page: 837
  year: 2021
  end-page: 848
  ident: b25
  article-title: Forecasting scenario generation for multiple wind farms considering time-series characteristics and spatial-temporal correlation
  publication-title: J Mod Power Syst Clean Energy
– volume: 19
  start-page: 352
  year: 2004
  end-page: 361
  ident: b28
  article-title: A fuzzy model for wind speed prediction and power generation in wind parks using spatial correlation
  publication-title: IEEE Trans Energy Convers
– reference: ISO New England, US. 2022, Available at
– volume: 221
  start-page: 348
  year: 2018
  end-page: 357
  ident: b26
  article-title: Efficient scenario generation of multiple renewable power plants considering spatial and temporal correlations
  publication-title: Appl Energy
– volume: 11
  start-page: 457
  year: 2020
  end-page: 466
  ident: b13
  article-title: Risk-constrained bidding strategy for a joint operation of wind power and CAES aggregators
  publication-title: IEEE Trans Sustain Energy
– volume: 31
  start-page: 4755
  year: 2016
  end-page: 4764
  ident: b12
  article-title: Optimal offering and operating strategies for wind-storage systems with linear decision rules
  publication-title: IEEE Trans Power Syst
– reference: .
– volume: 86
  start-page: 216
  year: 2016
  end-page: 227
  ident: b36
  article-title: Impact of spatio–temporal correlation of wind production on clearing outcomes of a competitive pool market
  publication-title: Renew Energy
– volume: 54
  start-page: 3044
  year: 2018
  end-page: 3055
  ident: b17
  article-title: A bidding strategy for virtual power plants with the intraday demand response exchange market using the stochastic programming
  publication-title: IEEE Trans Ind Appl
– volume: 87
  start-page: 843
  year: 2010
  end-page: 855
  ident: b22
  article-title: A methodology to generate statistically dependent wind speed scenarios
  publication-title: Appl Energy
– volume: 9
  start-page: 1659
  year: 2018
  end-page: 1671
  ident: b14
  article-title: Adaptive robust self-scheduling for a wind producer with compressed air energy storage
  publication-title: IEEE Trans Sustain Energy
– volume: 17
  start-page: 793
  year: 2014
  end-page: 810
  ident: b2
  article-title: Correlation and statistical characteristics of aggregate wind power in large transcontinental systems
  publication-title: Wind Energy
– year: 2010
  ident: b1
  publication-title: Decision Making under Uncertainty in Electricity Markets
– volume: 124
  year: 2021
  ident: b20
  article-title: A stochastic short-term scheduling of virtual power plants with electric vehicles under competitive markets
  publication-title: Int J Electr Power Energy Syst
– volume: 130
  year: 2021
  ident: b23
  article-title: Wind power scenario generation with non-separable spatio–temporal covariance function and fluctuation-based clustering
  publication-title: Int J Electr Power Energy Syst
– volume: 11
  start-page: 2606
  year: 2020
  end-page: 2616
  ident: b19
  article-title: Profit-sharing mechanism for aggregation of wind farms and concentrating solar power
  publication-title: IEEE Trans Sustain Energy
– reference: Windy: Wind map and weather forecast. 2022, Available at
– volume: 31
  start-page: 2676
  year: 2016
  end-page: 2687
  ident: b31
  article-title: Strategic bidding for a virtual power plant in the day-ahead and real-time markets: A price-taker robust optimization approach
  publication-title: IEEE Trans Power Syst
– volume: 280
  year: 2020
  ident: 10.1016/j.apenergy.2022.120552_b7
  article-title: An advanced day-ahead bidding strategy for wind power producers considering confidence level on the real-time reserve provision
  publication-title: Appl Energy
  doi: 10.1016/j.apenergy.2020.115973
– volume: 11
  start-page: 2545
  issue: 4
  year: 2020
  ident: 10.1016/j.apenergy.2022.120552_b18
  article-title: Coordinated bidding strategy of wind farms and power-to-gas facilities using a cooperative game approach
  publication-title: IEEE Trans Sustain Energy
  doi: 10.1109/TSTE.2020.2965521
– ident: 10.1016/j.apenergy.2022.120552_b30
– volume: 189
  year: 2020
  ident: 10.1016/j.apenergy.2022.120552_b15
  article-title: A distributionally robust bidding strategy for a wind-storage aggregator
  publication-title: Electr Power Syst Res
  doi: 10.1016/j.epsr.2020.106745
– volume: 138
  start-page: 1134
  year: 2019
  ident: 10.1016/j.apenergy.2022.120552_b11
  article-title: An intelligent wind power plant coalition formation model achieving balanced market penetration growth and profit increase
  publication-title: Renew Energy
  doi: 10.1016/j.renene.2019.02.064
– volume: 44
  start-page: 5162
  issue: 11
  year: 2019
  ident: 10.1016/j.apenergy.2022.120552_b24
  article-title: A scenario generation method based on the mixture vine copula and its application in the power system with wind/hydrogen production
  publication-title: Int J Hydrog Energy
  doi: 10.1016/j.ijhydene.2018.09.179
– volume: 61
  start-page: 578
  year: 2013
  ident: 10.1016/j.apenergy.2022.120552_b35
  article-title: Multiarea stochastic unit commitment for high wind penetration in a transmission constrained network
  publication-title: Oper Res
  doi: 10.1287/opre.2013.1174
– volume: 9
  start-page: 1921
  issue: 4
  year: 2018
  ident: 10.1016/j.apenergy.2022.120552_b10
  article-title: Sharing profit from joint offering of a group of wind power producers in day ahead markets
  publication-title: IEEE Trans Sustain Energy
  doi: 10.1109/TSTE.2018.2819137
– volume: 31
  start-page: 1420
  issue: 2
  year: 2016
  ident: 10.1016/j.apenergy.2022.120552_b5
  article-title: Offering strategy of wind-power producer: A multi-stage risk-constrained approach
  publication-title: IEEE Trans Power Syst
  doi: 10.1109/TPWRS.2015.2411332
– volume: 31
  start-page: 4755
  issue: 6
  year: 2016
  ident: 10.1016/j.apenergy.2022.120552_b12
  article-title: Optimal offering and operating strategies for wind-storage systems with linear decision rules
  publication-title: IEEE Trans Power Syst
  doi: 10.1109/TPWRS.2016.2521177
– volume: 105
  start-page: 282
  year: 2013
  ident: 10.1016/j.apenergy.2022.120552_b21
  article-title: Offering model for a virtual power plant based on stochastic programming
  publication-title: Appl Energy
  doi: 10.1016/j.apenergy.2012.12.077
– volume: 17
  start-page: 793
  issue: 6
  year: 2014
  ident: 10.1016/j.apenergy.2022.120552_b2
  article-title: Correlation and statistical characteristics of aggregate wind power in large transcontinental systems
  publication-title: Wind Energy
  doi: 10.1002/we.1597
– volume: 221
  start-page: 348
  year: 2018
  ident: 10.1016/j.apenergy.2022.120552_b26
  article-title: Efficient scenario generation of multiple renewable power plants considering spatial and temporal correlations
  publication-title: Appl Energy
  doi: 10.1016/j.apenergy.2018.03.082
– ident: 10.1016/j.apenergy.2022.120552_b34
– volume: 33
  start-page: 3265
  issue: 3
  year: 2018
  ident: 10.1016/j.apenergy.2022.120552_b27
  article-title: Model-free renewable scenario generation using generative adversarial networks
  publication-title: IEEE Trans Power Syst
  doi: 10.1109/TPWRS.2018.2794541
– volume: 130
  year: 2021
  ident: 10.1016/j.apenergy.2022.120552_b23
  article-title: Wind power scenario generation with non-separable spatio–temporal covariance function and fluctuation-based clustering
  publication-title: Int J Electr Power Energy Syst
  doi: 10.1016/j.ijepes.2021.106955
– volume: 9
  start-page: 837
  issue: 4
  year: 2021
  ident: 10.1016/j.apenergy.2022.120552_b25
  article-title: Forecasting scenario generation for multiple wind farms considering time-series characteristics and spatial-temporal correlation
  publication-title: J Mod Power Syst Clean Energy
  doi: 10.35833/MPCE.2020.000935
– volume: 156
  start-page: 47
  year: 2020
  ident: 10.1016/j.apenergy.2022.120552_b16
  article-title: Scheduling of wind-battery hybrid system in the electricity market using distributionally robust optimization
  publication-title: Renew Energy
  doi: 10.1016/j.renene.2020.04.057
– volume: 20
  start-page: 1315
  issue: 8
  year: 2017
  ident: 10.1016/j.apenergy.2022.120552_b3
  article-title: A spatial and temporal correlation analysis of aggregate wind power in an ideally interconnected Europe
  publication-title: Wind Energy
  doi: 10.1002/we.2095
– volume: 54
  start-page: 3044
  issue: 4
  year: 2018
  ident: 10.1016/j.apenergy.2022.120552_b17
  article-title: A bidding strategy for virtual power plants with the intraday demand response exchange market using the stochastic programming
  publication-title: IEEE Trans Ind Appl
  doi: 10.1109/TIA.2018.2828379
– volume: 19
  start-page: 352
  issue: 2
  year: 2004
  ident: 10.1016/j.apenergy.2022.120552_b28
  article-title: A fuzzy model for wind speed prediction and power generation in wind parks using spatial correlation
  publication-title: IEEE Trans Energy Convers
  doi: 10.1109/TEC.2003.821865
– year: 1996
  ident: 10.1016/j.apenergy.2022.120552_b32
– volume: 24
  start-page: 187
  issue: 2–3
  year: 2003
  ident: 10.1016/j.apenergy.2022.120552_b38
  article-title: Scenario reduction algorithms in stochastic programming
  publication-title: Comput Optim Appl
  doi: 10.1023/A:1021805924152
– volume: 124
  year: 2021
  ident: 10.1016/j.apenergy.2022.120552_b20
  article-title: A stochastic short-term scheduling of virtual power plants with electric vehicles under competitive markets
  publication-title: Int J Electr Power Energy Syst
  doi: 10.1016/j.ijepes.2020.106343
– volume: 87
  start-page: 843
  year: 2010
  ident: 10.1016/j.apenergy.2022.120552_b22
  article-title: A methodology to generate statistically dependent wind speed scenarios
  publication-title: Appl Energy
  doi: 10.1016/j.apenergy.2009.09.022
– volume: 120
  year: 2020
  ident: 10.1016/j.apenergy.2022.120552_b29
  article-title: Day-ahead energy and reserve scheduling under correlated wind power production
  publication-title: Int J Electr Power Energy Syst
  doi: 10.1016/j.ijepes.2020.105931
– ident: 10.1016/j.apenergy.2022.120552_b37
– volume: 31
  start-page: 2676
  issue: 4
  year: 2016
  ident: 10.1016/j.apenergy.2022.120552_b31
  article-title: Strategic bidding for a virtual power plant in the day-ahead and real-time markets: A price-taker robust optimization approach
  publication-title: IEEE Trans Power Syst
  doi: 10.1109/TPWRS.2015.2483781
– ident: 10.1016/j.apenergy.2022.120552_b39
– volume: 9
  start-page: 1659
  issue: 4
  year: 2018
  ident: 10.1016/j.apenergy.2022.120552_b14
  article-title: Adaptive robust self-scheduling for a wind producer with compressed air energy storage
  publication-title: IEEE Trans Sustain Energy
  doi: 10.1109/TSTE.2018.2806444
– volume: 86
  start-page: 216
  year: 2016
  ident: 10.1016/j.apenergy.2022.120552_b36
  article-title: Impact of spatio–temporal correlation of wind production on clearing outcomes of a competitive pool market
  publication-title: Renew Energy
  doi: 10.1016/j.renene.2015.07.104
– ident: 10.1016/j.apenergy.2022.120552_b33
– ident: 10.1016/j.apenergy.2022.120552_b40
– volume: 28
  start-page: 4645
  issue: 4
  year: 2013
  ident: 10.1016/j.apenergy.2022.120552_b4
  article-title: Strategic offering for a wind power producer
  publication-title: IEEE Trans Power Syst
  doi: 10.1109/TPWRS.2013.2273276
– volume: 28
  start-page: 3774
  issue: 4
  year: 2013
  ident: 10.1016/j.apenergy.2022.120552_b8
  article-title: Coalitional aggregation of wind power
  publication-title: IEEE Trans Power Syst
  doi: 10.1109/TPWRS.2013.2262502
– volume: 11
  start-page: 2606
  issue: 4
  year: 2020
  ident: 10.1016/j.apenergy.2022.120552_b19
  article-title: Profit-sharing mechanism for aggregation of wind farms and concentrating solar power
  publication-title: IEEE Trans Sustain Energy
  doi: 10.1109/TSTE.2020.2967860
– year: 2010
  ident: 10.1016/j.apenergy.2022.120552_b1
– volume: 31
  start-page: 2688
  issue: 4
  year: 2016
  ident: 10.1016/j.apenergy.2022.120552_b9
  article-title: Optimal bidding of a group of wind farms in day-ahead markets through an external agent
  publication-title: IEEE Trans Power Syst
  doi: 10.1109/TPWRS.2015.2477466
– volume: 11
  start-page: 457
  issue: 1
  year: 2020
  ident: 10.1016/j.apenergy.2022.120552_b13
  article-title: Risk-constrained bidding strategy for a joint operation of wind power and CAES aggregators
  publication-title: IEEE Trans Sustain Energy
  doi: 10.1109/TSTE.2019.2895332
– volume: 177
  year: 2019
  ident: 10.1016/j.apenergy.2022.120552_b6
  article-title: A distributionally robust bidding strategy for a wind power plant
  publication-title: Electr Power Syst Res
  doi: 10.1016/j.epsr.2019.105986
SSID ssj0002120
Score 2.467571
Snippet This paper formulates the offering problem for a cluster of wind-storage systems in the day-ahead energy market using a risk-constrained stochastic programming...
SourceID crossref
elsevier
SourceType Enrichment Source
Index Database
Publisher
StartPage 120552
SubjectTerms Conditional value-at-risk
Correlated scenarios
Offering strategy
Stochastic programming
Wind-storage systems
Title Optimal offering strategy for wind-storage systems under correlated wind production
URI https://dx.doi.org/10.1016/j.apenergy.2022.120552
Volume 333
WOSCitedRecordID wos000925252900001&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
  issn: 0306-2619
  databaseCode: AIEXJ
  dateStart: 19950101
  customDbUrl:
  isFulltext: true
  dateEnd: 99991231
  titleUrlDefault: https://www.sciencedirect.com
  omitProxy: false
  ssIdentifier: ssj0002120
  providerName: Elsevier
link http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1LT9wwELZa4AAHRHmIt3zoDQWydrKJjwht1VYVrQpIe4vs2BFBEFabXVj49YxfSWgRlEMvURRlHO_O58mMM_MNQp9T3eitKIqgH3IIUHphGIg0VEFERC6IoAksKdNsIjk9TYdD9svlz9emnUBSVelsxkb_VdVwDZStS2ffoe5mULgA56B0OILa4fhPiv8JRuDGuJiFoRk8qC0Brc3MvIcYPNAZkTpXx9I416YX7vgg1406rvnEJKQb-gBDBusV56lqnduqTNFg4weXY0tGcKZG6rJJ-P3NL8ub8sFuspq83sd2A4Dr2Zmd2h_T8tn2A6Ft_pUvuwr7gQ7DuiaVUtoxij0Sxpam9i97bbcOrg75yM4aAnZCDluB5wTZf7y4mnRCn6l2lflxMj1OZsf5iOZJEjMwefPH3wbD782LmjjWTv8LOgXkL8_oZd-l44-cr6BlF0jgYwuAT-iDqlbRUodechVtDNoqRrjVmfF6DZ05jGCPEewxggEjuIsR7DCCDUZwixFzF24xso4uvgzOT74GrrtGkINbNgmUSiJJOJNUKSYimuSCF1RJJjVhUygEWO4-T7jSX5ZFCmu5n0eaIJBLIiMe0g00V91WahPhuCejomAgAc6OjFOWqJ5uuyo1vT_N6RaK_f-W5Y56XndAuc5e19wWOmrkRpZ85U0J5tWSORfSuoYZIO4N2e13P20HLbZLYhfNTcZTtYcW8rtJWY_3HdyeABTfmhE
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=Optimal+offering+strategy+for+wind-storage+systems+under+correlated+wind+production&rft.jtitle=Applied+energy&rft.au=Dirin%2C+Sepehr&rft.au=Rahimiyan%2C+Morteza&rft.au=Baringo%2C+Luis&rft.date=2023-03-01&rft.issn=0306-2619&rft.volume=333&rft.spage=120552&rft_id=info:doi/10.1016%2Fj.apenergy.2022.120552&rft.externalDBID=n%2Fa&rft.externalDocID=10_1016_j_apenergy_2022_120552
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0306-2619&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0306-2619&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0306-2619&client=summon