Risk-Constrained Optimal Chiller Loading Strategy Using Information Gap Decision Theory
This paper presents a novel framework for economic cooling load dispatch in conventional water-cooled chillers. Moreover, information gap decision theory (IGDT) is applied to the optimal chiller loading (OCL) problem to find the optimum operating point of the test system in three decision-making mod...
Gespeichert in:
| Veröffentlicht in: | Applied sciences Jg. 9; H. 9; S. 1925 |
|---|---|
| Hauptverfasser: | , , , , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
Basel
MDPI AG
01.05.2019
|
| Schlagworte: | |
| ISSN: | 2076-3417, 2076-3417 |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| Abstract | This paper presents a novel framework for economic cooling load dispatch in conventional water-cooled chillers. Moreover, information gap decision theory (IGDT) is applied to the optimal chiller loading (OCL) problem to find the optimum operating point of the test system in three decision-making modes: (a) risk-neutral approach, (b) risk-aversion or robustness approach, and (c) risk-taker or opportunistic approach. In the robustness mode of the IGDT-based OCL problem, the system operator enters a desired energy cost value in order to find the most appropriate loading points for the chillers so that the total electricity procurement cost over the study horizon is smaller than or equal to this critical value. Meanwhile, the cooling load increase is maximized to the highest possible level to find the most robust performance of the benchmark grid with respect to the overestimated load. Similarly, the risk-taker optimization method finds the on/off status and the partial load ratio (PLR) of the chillers in order to keep the total energy cost as low as the given cost function. In addition, the minimum value of cooling load decrease can be found while satisfying the refrigeration capacity of the chiller and the load-generation balance constraint. Thus, a mixed-integer non-linear programming problem is solved using the branch and reduce optimization (BARON) tool of the generalized algebraic mathematical modeling system (GAMS) for a five-chiller plant, to demonstrate that IGDT is able to find a good solution in robustness/risk-taker OCL problem. |
|---|---|
| AbstractList | This paper presents a novel framework for economic cooling load dispatch in conventional water-cooled chillers. Moreover, information gap decision theory (IGDT) is applied to the optimal chiller loading (OCL) problem to find the optimum operating point of the test system in three decision-making modes: (a) risk-neutral approach, (b) risk-aversion or robustness approach, and (c) risk-taker or opportunistic approach. In the robustness mode of the IGDT-based OCL problem, the system operator enters a desired energy cost value in order to find the most appropriate loading points for the chillers so that the total electricity procurement cost over the study horizon is smaller than or equal to this critical value. Meanwhile, the cooling load increase is maximized to the highest possible level to find the most robust performance of the benchmark grid with respect to the overestimated load. Similarly, the risk-taker optimization method finds the on/off status and the partial load ratio (PLR) of the chillers in order to keep the total energy cost as low as the given cost function. In addition, the minimum value of cooling load decrease can be found while satisfying the refrigeration capacity of the chiller and the load-generation balance constraint. Thus, a mixed-integer non-linear programming problem is solved using the branch and reduce optimization (BARON) tool of the generalized algebraic mathematical modeling system (GAMS) for a five-chiller plant, to demonstrate that IGDT is able to find a good solution in robustness/risk-taker OCL problem. [...]the economic operation of electrical air conditioners is important to reduce the energy demand of interconnected power systems. The variable climatic conditions affect the building cooling demand, the optimum value of the partial load ratios (PLRs), and the cooling capability of the chillers, as well as their power consumption [7]. [...]the uncertainties associated with the cooling load should be modeled by short-term scheduling of electrical air conditioners [8,9]. According to Equation (6), the robust optimization problem is formulated with an aim to maximize the uncertainty variable, α , while the energy cost is less than the given cost, Fk . [...]the minimum value of the cooling load decrease, which reduces the energy cost to predefined values Fw , must be found by solving the optimization problem (Equations (1)–(5), (13) and (14)). |
| Author | Mohammadi-ivatloo, Behnam Mohammadpourfard, Mousa Jabari, Farkhondeh Shi, Er Anvari-Moghaddam, Amjad |
| Author_xml | – sequence: 1 givenname: Er surname: Shi fullname: Shi, Er – sequence: 2 givenname: Farkhondeh surname: Jabari fullname: Jabari, Farkhondeh – sequence: 3 givenname: Amjad orcidid: 0000-0002-5505-3252 surname: Anvari-Moghaddam fullname: Anvari-Moghaddam, Amjad – sequence: 4 givenname: Mousa orcidid: 0000-0002-6098-924X surname: Mohammadpourfard fullname: Mohammadpourfard, Mousa – sequence: 5 givenname: Behnam orcidid: 0000-0002-0255-8353 surname: Mohammadi-ivatloo fullname: Mohammadi-ivatloo, Behnam |
| BookMark | eNptUU1Lw0AQXUTBWnvxFwS8CdH9SLO7R4laC4WCtnhcJptNuzXNxt300H9v0iqKOJeZN7x5PN5coNPa1QahK4JvGZP4DppGYkkkHZ-gAcU8jVlC-Omv-RyNQtjgriRhguABenux4T3OXB1aD7Y2RTRvWruFKsrWtqqMj2YOCluvoteO0JrVPlqGHk7r0vkttNbV0QSa6MFoG3qwWBvn95forIQqmNFXH6Ll0-Mie45n88k0u5_FmqWkjYGOJU1ZSiEnBHiRMl7qgpdsXGjCmQBBcpJoEIaneUm1wEzTnAJmXFPNgQ3R9KhbONioxnfW_V45sOqwcH6lwLdWV0YVGkupsUhpzhKWUKmFFqQsBOES50J2WtdHrca7j50Jrdq4na87-4oySoSgCRUdCx9Z2rsQvCmVtu0hhz7BShGs-m-on290Jzd_Tr6N_kP-BD6ei5Q |
| CitedBy_id | crossref_primary_10_1016_j_enbuild_2020_110058 crossref_primary_10_3233_JIFS_240283 crossref_primary_10_3390_app9204451 crossref_primary_10_3390_app10113829 crossref_primary_10_3390_su12125089 crossref_primary_10_1007_s11814_019_0392_x crossref_primary_10_1109_ACCESS_2020_2981697 crossref_primary_10_1080_02286203_2020_1843935 crossref_primary_10_1016_j_scs_2019_101991 crossref_primary_10_1016_j_cie_2020_106425 crossref_primary_10_1016_j_jclepro_2019_118393 crossref_primary_10_1016_j_jobe_2020_101263 crossref_primary_10_1016_j_compeleceng_2020_106550 crossref_primary_10_1109_ACCESS_2020_2998845 crossref_primary_10_3390_en13153760 crossref_primary_10_3390_en15239187 |
| Cites_doi | 10.1007/978-3-319-22732-0 10.1016/j.enbuild.2004.06.002 10.1016/j.rse.2014.08.012 10.1016/j.enbuild.2005.12.009 10.1016/j.applthermaleng.2005.02.010 10.1016/j.sbspro.2014.03.704 10.1016/j.energy.2005.10.018 10.1016/j.apenergy.2019.01.170 10.1016/j.enbuild.2017.10.040 10.1016/j.enconman.2008.08.036 10.1016/j.applthermaleng.2018.11.122 10.1016/j.gloenvcha.2008.12.003 10.1007/978-3-319-62350-4 10.1016/j.matcom.2018.04.013 10.18280/mmep.050311 10.1016/j.enbuild.2018.03.077 10.1016/j.enconman.2004.10.012 10.1016/j.enbuild.2013.04.030 10.1016/j.enbuild.2012.11.030 10.1016/j.enbuild.2017.12.020 10.1016/j.energy.2012.10.058 10.1016/j.enbuild.2018.04.046 10.1016/j.energy.2014.07.060 10.1016/j.jobe.2018.05.018 10.3390/en80910504 10.1016/j.apenergy.2009.05.004 10.1016/j.applthermaleng.2016.02.114 10.1007/978-3-319-75097-2 10.1016/j.enbuild.2010.10.028 10.3390/app7080784 |
| ContentType | Journal Article |
| Copyright | 2019. This work is licensed under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. |
| Copyright_xml | – notice: 2019. This work is licensed under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. |
| DBID | AAYXX CITATION ABUWG AFKRA AZQEC BENPR CCPQU DWQXO PHGZM PHGZT PIMPY PKEHL PQEST PQQKQ PQUKI PRINS DOA |
| DOI | 10.3390/app9091925 |
| DatabaseName | CrossRef ProQuest Central (Alumni) ProQuest Central UK/Ireland ProQuest Central Essentials - QC ProQuest Central ProQuest One ProQuest Central ProQuest Central Premium ProQuest One Academic Publicly Available Content Database (ProQuest) ProQuest One Academic Middle East (New) ProQuest One Academic Eastern Edition (DO NOT USE) ProQuest One Academic (retired) ProQuest One Academic UKI Edition ProQuest Central China DOAJ Directory of Open Access Journals |
| DatabaseTitle | CrossRef Publicly Available Content Database ProQuest One Academic Middle East (New) ProQuest Central Essentials ProQuest One Academic Eastern Edition ProQuest Central (Alumni Edition) ProQuest One Community College ProQuest Central China ProQuest Central ProQuest One Academic UKI Edition ProQuest Central Korea ProQuest Central (New) ProQuest One Academic ProQuest One Academic (New) |
| DatabaseTitleList | CrossRef Publicly Available Content Database |
| Database_xml | – sequence: 1 dbid: DOA name: DOAJ Directory of Open Access Journals url: https://www.doaj.org/ sourceTypes: Open Website – sequence: 2 dbid: PIMPY name: Publicly Available Content Database url: http://search.proquest.com/publiccontent sourceTypes: Aggregation Database |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Engineering Sciences (General) |
| EISSN | 2076-3417 |
| ExternalDocumentID | oai_doaj_org_article_dc099c0862b343429c8c81fd81790b89 10_3390_app9091925 |
| GeographicLocations | Iran Switzerland |
| GeographicLocations_xml | – name: Switzerland – name: Iran |
| GroupedDBID | .4S 2XV 5VS 7XC 8CJ 8FE 8FG 8FH AADQD AAFWJ AAYXX ADBBV ADMLS AFFHD AFKRA AFPKN AFZYC ALMA_UNASSIGNED_HOLDINGS APEBS ARCSS BCNDV BENPR CCPQU CITATION CZ9 D1I D1J D1K GROUPED_DOAJ IAO IGS K6- K6V KC. KQ8 L6V LK5 LK8 M7R MODMG M~E OK1 P62 PHGZM PHGZT PIMPY PROAC TUS ABUWG AZQEC DWQXO PKEHL PQEST PQQKQ PQUKI PRINS |
| ID | FETCH-LOGICAL-c361t-a25926362ab11a7d637fcd7f35dc1738a81b14ca8e76bf2c803c2b2a037c2c7a3 |
| IEDL.DBID | BENPR |
| ISICitedReferencesCount | 19 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000469756000204&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 2076-3417 |
| IngestDate | Fri Oct 03 12:43:20 EDT 2025 Mon Jun 30 11:10:50 EDT 2025 Sat Nov 29 07:16:51 EST 2025 Tue Nov 18 21:41:32 EST 2025 |
| IsDoiOpenAccess | true |
| IsOpenAccess | true |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 9 |
| Language | English |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c361t-a25926362ab11a7d637fcd7f35dc1738a81b14ca8e76bf2c803c2b2a037c2c7a3 |
| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| ORCID | 0000-0002-5505-3252 0000-0002-0255-8353 0000-0002-6098-924X |
| OpenAccessLink | https://www.proquest.com/docview/2321882428?pq-origsite=%requestingapplication% |
| PQID | 2321882428 |
| PQPubID | 2032433 |
| ParticipantIDs | doaj_primary_oai_doaj_org_article_dc099c0862b343429c8c81fd81790b89 proquest_journals_2321882428 crossref_citationtrail_10_3390_app9091925 crossref_primary_10_3390_app9091925 |
| PublicationCentury | 2000 |
| PublicationDate | 2019-05-01 |
| PublicationDateYYYYMMDD | 2019-05-01 |
| PublicationDate_xml | – month: 05 year: 2019 text: 2019-05-01 day: 01 |
| PublicationDecade | 2010 |
| PublicationPlace | Basel |
| PublicationPlace_xml | – name: Basel |
| PublicationTitle | Applied sciences |
| PublicationYear | 2019 |
| Publisher | MDPI AG |
| Publisher_xml | – name: MDPI AG |
| References | Chang (ref_11) 2010; 87 Chang (ref_23) 2005; 25 Chang (ref_10) 2005; 46 Chang (ref_22) 2005; 37 Ho (ref_9) 2014; 154 Lin (ref_31) 2015; 8 Zheng (ref_1) 2019; 155 ref_32 Wang (ref_5) 2019; 238 Chang (ref_6) 2007; 39 ref_30 Cannistraro (ref_20) 2018; 5 Chang (ref_15) 2009; 50 ref_16 Cannistraro (ref_28) 2018; 19 Sulaiman (ref_2) 2014; 129 Saeedi (ref_26) 2019; 148 Chang (ref_13) 2006; 31 Coelho (ref_14) 2013; 59 Coelho (ref_17) 2014; 75 Huang (ref_8) 2018; 158 Zheng (ref_25) 2018; 161 Powell (ref_4) 2013; 50 Sohrabi (ref_19) 2018; 169 ref_21 Wang (ref_3) 2018; 172 Lee (ref_18) 2011; 43 ref_29 Lo (ref_24) 2016; 100 ref_27 Chen (ref_12) 2014; 68 Hallegatte (ref_7) 2009; 19 |
| References_xml | – ident: ref_16 doi: 10.1007/978-3-319-22732-0 – volume: 37 start-page: 147 year: 2005 ident: ref_22 article-title: Optimal chiller loading by genetic algorithm for reducing energy consumption publication-title: Energy Build. doi: 10.1016/j.enbuild.2004.06.002 – ident: ref_30 – volume: 154 start-page: 38 year: 2014 ident: ref_9 article-title: Mapping maximum urban air temperature on hot summer days publication-title: Remote Sens. Environ. doi: 10.1016/j.rse.2014.08.012 – volume: 39 start-page: 437 year: 2007 ident: ref_6 article-title: Optimal chiller loading by evolution strategy for saving energy publication-title: Energy Build. doi: 10.1016/j.enbuild.2005.12.009 – volume: 25 start-page: 2800 year: 2005 ident: ref_23 article-title: Genetic algorithm based optimal chiller loading for energy conservation publication-title: Appl. Therm. Eng. doi: 10.1016/j.applthermaleng.2005.02.010 – volume: 129 start-page: 483 year: 2014 ident: ref_2 article-title: A new swarm intelligence approach for optimal chiller loading for energy conservation publication-title: Procedia Soc. Behav. Sci. doi: 10.1016/j.sbspro.2014.03.704 – volume: 31 start-page: 1883 year: 2006 ident: ref_13 article-title: An innovative approach for demand side management—Optimal chiller loading by simulated annealing publication-title: Energy doi: 10.1016/j.energy.2005.10.018 – volume: 238 start-page: 1444 year: 2019 ident: ref_5 article-title: Online chiller loading strategy based on the near-optimal performance map for energy conservation publication-title: Appl. Energy doi: 10.1016/j.apenergy.2019.01.170 – volume: 158 start-page: 684 year: 2018 ident: ref_8 article-title: Optimal configuration of multiple-chiller plants under cooling load uncertainty for different climate effects and building types publication-title: Energy Build. doi: 10.1016/j.enbuild.2017.10.040 – volume: 50 start-page: 132 year: 2009 ident: ref_15 article-title: Evolution strategy based optimal chiller loading for saving energy publication-title: Energy Convers. Manag. doi: 10.1016/j.enconman.2008.08.036 – volume: 148 start-page: 1081 year: 2019 ident: ref_26 article-title: Robust optimization based optimal chiller loading under cooling demand uncertainty publication-title: Appl. Ther. Eng. doi: 10.1016/j.applthermaleng.2018.11.122 – volume: 19 start-page: 240 year: 2009 ident: ref_7 article-title: Strategies to adapt to an uncertain climate change publication-title: Glob. Environ. Chang. doi: 10.1016/j.gloenvcha.2008.12.003 – ident: ref_32 doi: 10.1007/978-3-319-62350-4 – volume: 155 start-page: 227 year: 2019 ident: ref_1 article-title: Optimal chiller loading by improved artificial fish swarm algorithm for energy saving publication-title: Math. Comput. Simul. doi: 10.1016/j.matcom.2018.04.013 – volume: 5 start-page: 205 year: 2018 ident: ref_20 article-title: Testing a dual-source heat pump publication-title: Math. Model. Eng. Probl. doi: 10.18280/mmep.050311 – volume: 169 start-page: 245 year: 2018 ident: ref_19 article-title: Optimal chiller loading for saving energy by exchange market algorithm publication-title: Energy Build. doi: 10.1016/j.enbuild.2018.03.077 – ident: ref_29 – volume: 46 start-page: 2158 year: 2005 ident: ref_10 article-title: Optimal chiller sequencing by branch and bound method for saving energy publication-title: Energy Convers. Manag. doi: 10.1016/j.enconman.2004.10.012 – volume: 68 start-page: 364 year: 2014 ident: ref_12 article-title: Applying smart models for energy saving in optimal chiller loading publication-title: Energy Build. doi: 10.1016/j.enbuild.2013.04.030 – volume: 59 start-page: 273 year: 2013 ident: ref_14 article-title: Improved firefly algorithm approach applied to chiller loading for energy conservation publication-title: Energy Build. doi: 10.1016/j.enbuild.2012.11.030 – volume: 161 start-page: 80 year: 2018 ident: ref_25 article-title: Optimal chiller loading by improved invasive weed optimization algorithm for reducing energy consumption publication-title: Energy Build. doi: 10.1016/j.enbuild.2017.12.020 – volume: 50 start-page: 445 year: 2013 ident: ref_4 article-title: Optimal chiller loading in a district cooling system with thermal energy storage publication-title: Energy doi: 10.1016/j.energy.2012.10.058 – volume: 172 start-page: 1 year: 2018 ident: ref_3 article-title: Evaluation of operation performance of a multi-chiller system using a data-based chiller model publication-title: Energy Build. doi: 10.1016/j.enbuild.2018.04.046 – volume: 75 start-page: 237 year: 2014 ident: ref_17 article-title: Optimal chiller loading for energy conservation using a new differential cuckoo search approach publication-title: Energy doi: 10.1016/j.energy.2014.07.060 – volume: 19 start-page: 295 year: 2018 ident: ref_28 article-title: New sol-gel deposition technique in the Smart-Windows–Computation of possible applications of Smart-Windows in buildings publication-title: J. Build. Eng. doi: 10.1016/j.jobe.2018.05.018 – volume: 8 start-page: 10504 year: 2015 ident: ref_31 article-title: Optimal energy reduction schedules for ice storage air-conditioning systems publication-title: Energies doi: 10.3390/en80910504 – volume: 87 start-page: 1096 year: 2010 ident: ref_11 article-title: Economic dispatch of chiller plant by gradient method for saving energy publication-title: Appl. Energy doi: 10.1016/j.apenergy.2009.05.004 – volume: 100 start-page: 1140 year: 2016 ident: ref_24 article-title: Economic dispatch of chiller plant by improved ripple bee swarm optimization algorithm for saving energy publication-title: Appl. Therm. Eng. doi: 10.1016/j.applthermaleng.2016.02.114 – ident: ref_21 doi: 10.1007/978-3-319-75097-2 – volume: 43 start-page: 599 year: 2011 ident: ref_18 article-title: Optimal chiller loading by differential evolution algorithm for reducing energy consumption publication-title: Energy Build. doi: 10.1016/j.enbuild.2010.10.028 – ident: ref_27 doi: 10.3390/app7080784 |
| SSID | ssj0000913810 |
| Score | 2.222534 |
| Snippet | This paper presents a novel framework for economic cooling load dispatch in conventional water-cooled chillers. Moreover, information gap decision theory... [...]the economic operation of electrical air conditioners is important to reduce the energy demand of interconnected power systems. The variable climatic... |
| SourceID | doaj proquest crossref |
| SourceType | Open Website Aggregation Database Enrichment Source Index Database |
| StartPage | 1925 |
| SubjectTerms | Decision making Decision theory Electricity Energy conservation Energy consumption Genetic algorithms information gap decision theory (IGDT) Integer programming Linear programming Load mixed-integer non-linear programming problem (MINLP) optimal chiller loading (OCL) Optimization algorithms Optimization techniques uncertain cooling demand Variables |
| SummonAdditionalLinks | – databaseName: DOAJ Directory of Open Access Journals dbid: DOA link: http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrZ1LSwMxEMeDFA96EFsVq1UCerCHxWazu0mOvqqHUkUUe1uyeUCxtqWtgt_eSTatCwpevC5hH5PJ5D_s5DcInWaGGG4SHlGQ01FCbBoVNtORFlY7uIy00tP1e6zf54OBeKi0-nI1YSUeuDTcuVagYZQT3gVNKERPxRUnVnOHliq4P7oHqqeSTPkYLIhDV5U8Ugp5vfsfLOCqcD2xKzuQB_X_iMN-c-luo62gCvFF-TZ1tGbGDbRZYQU2UD2swjk-C6jo9g56eRzOXyPXdNO3ejAa30MIeINbOWTxyMxwb-KL5HGg0H5iXyOAwykkNyv4Vk7xdWi1g8uz-rvouXvzdHUXhVYJkaIZWUQSspg4g81IFoRIpjPKrNLM0lQrwiiXoE5JoiQ3LCtsrHiHqriIZYcyFSsm6R6qjSdjs4-wEiKV2qZcpJAqSi6pSZlIjUhilYnUNlF7ab5cBY64-8ZRDvmEM3X-beomOlmNnZb0jF9HXbpZWI1wxGt_AfwgD36Q_-UHTdRazmEeluE8B7lIIIWAFOvgP55xiDZAL4my3rGFaovZuzlC6-pjMZzPjr0HfgHHad81 priority: 102 providerName: Directory of Open Access Journals |
| Title | Risk-Constrained Optimal Chiller Loading Strategy Using Information Gap Decision Theory |
| URI | https://www.proquest.com/docview/2321882428 https://doaj.org/article/dc099c0862b343429c8c81fd81790b89 |
| Volume | 9 |
| WOSCitedRecordID | wos000469756000204&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: PRVAON databaseName: DOAJ Directory of Open Access Journals customDbUrl: eissn: 2076-3417 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0000913810 issn: 2076-3417 databaseCode: DOA dateStart: 20110101 isFulltext: true titleUrlDefault: https://www.doaj.org/ providerName: Directory of Open Access Journals – providerCode: PRVHPJ databaseName: ROAD: Directory of Open Access Scholarly Resources customDbUrl: eissn: 2076-3417 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0000913810 issn: 2076-3417 databaseCode: M~E dateStart: 20110101 isFulltext: true titleUrlDefault: https://road.issn.org providerName: ISSN International Centre – providerCode: PRVPQU databaseName: ProQuest Central customDbUrl: eissn: 2076-3417 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0000913810 issn: 2076-3417 databaseCode: BENPR dateStart: 20110101 isFulltext: true titleUrlDefault: https://www.proquest.com/central providerName: ProQuest – providerCode: PRVPQU databaseName: Publicly Available Content Database customDbUrl: eissn: 2076-3417 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0000913810 issn: 2076-3417 databaseCode: PIMPY dateStart: 20110101 isFulltext: true titleUrlDefault: http://search.proquest.com/publiccontent providerName: ProQuest |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV3BbtQwEB3BlgMcgBZQF0plCQ70YLGOk9g-oRZaQCrLqgJRTpEztlHVsrtsFiT-vh7Hu60E4sIxjhUlGXvmjT1-D-B57YXXvtRcRjjNSxEq3obacWeCI3IZG2xi1z9W47E-PTWTvODW5bLKlU9MjtrNkNbIX8bILyIajGj51fwHJ9Uo2l3NEho3YYOYysoBbBwcjicn61UWYr3UYtTzksqY39O-sImthrSxr0WiRNj_hz9OQebo3v--3n24m-El2-_Hwybc8NMtuHONdHALNvN07tiLzDm99wC-nJx155zUO5NmhHfsY_Ql3-OjiPv4wi_Y8SxV27NMZ_ubpWIDlo8zkXnZWztnb7JmD-sP_T-Ez0eHn16_41lzgaOsxZLbmA4VdYxqthXCKldLFdCpICuHQkltI8wVJVrtVd2GAvVIYtEWdiQVFqisfASD6Wzqt4GhMZV1odKmijmn1Vb6SpnKm7LA2lRhCHur_99gJiSnb7xoYmJCtmqubDWEZ-u-856G46-9DsiM6x5EnZ0aZotvTZ6JjcMIipEyuVaWMoZj1KhFcJq4ylpthrCzsnCT53PXXJn38b9vP4HbEVKZviRyBwbLxU__FG7hr-VZt9jNw3M3Zf7xavL-w-TrJdHQ8iI |
| linkProvider | ProQuest |
| linkToHtml | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1dTxQxFL1BMBEfVFDjKmoTNZGHxm07M20fjBEBIawrIRh4Gzv9IETcXXdWDX_K3-jtTGch0fjGg6-dpkmnp7fn9uMcgOeFZ175TFGBdJpmLOS0CoWjTgcXxWVMMI26_kAOh-r4WO8vwK_uLUy8VtnFxCZQu7GNe-SvcOVnyAaRLb-ZfKPRNSqernYWGi0s9vz5T0zZ6te7mzi-Lzjf3jp8t0OTqwC1omAzapDw8wLjtqkYM9IVQgbrZBC5s0wKZZDIscwa5WVRBW5VX1hecdMX0nIrjcB2r8FSJjKJ82ppY2u4fzDf1Ykqm4r1Wx1UIXQ_nkNrLNXRi_vSytcYBPwR_5tFbfv2__Y77sCtRJ_J2xbvK7DgR6tw85Ko4iqspHBVk5dJU3v9LhwdnNZfaHQnbTwxvCMfMVZ-xaaitvOZn5LBuHlNQJJc7zlpLlOQ9Fwrwpe8NxOymTyJSCtqcA8-XUl378PiaDzyD4BYrXPjQq50jjm1UUb4XOrc64zbQuehB-vdeJc2Ca7HPp6VmHhFbJQX2OjBs3ndSSsz8tdaGxE28xpRGrwpGE9PyhRpSmeR9NuYqVYCQcq1VVax4FTUYquU7sFah6gyxau6vIDTw39_fgo3dg4_DMrB7nDvESwjfdTt9c81WJxNv_vHcN3-mJ3W0ydpahD4fNXw-w0NmUxm |
| linkToPdf | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1NbxMxEB2VFiE4AC2gphSwBEj0YDVe767tA0JACEQNIUIgymnx-qOqKEnIpq361_h1jHe9aSUQtx64ei1LXj_PvLHHbwCe5I456VJJOdJpmjKf0dLnllrlbRCX0V7X6vpDMRrJ_X01XoFf7VuYkFbZ2sTaUNupCWfku-j5GbJBZMu7PqZFjHv9F7OfNFSQCjetbTmNBiJ77uwUw7fq-aCHa_00SfpvPr1-R2OFAWp4zhZUI_lPcrThumRMC5tz4Y0VnmfWMMGlRlLHUqOlE3npEyO73CRlortcmMQIzXHcK7CGlDzFPbY2Hrwff12e8ATFTcm6jSYq56ob7qQVtqpQl_uCF6yLBfzhC2oH17_1P_-a23Az0mrystkH67DiJhtw44LY4gasRzNWkWdRa3vnDnz5eFh9p6FqaV0rw1nyAW3oDxwqaD4fuTkZTutXBiTK-J6ROsmCxGdcAdbkrZ6RXqxVRBqxg7vw-VKmew9WJ9OJ2wRilMq09ZlUGcbaWmruMqEyp9LE5CrzHdhp174wUYg9zPGowIAs4KQ4x0kHHi_7zhr5kb_2ehUgtOwRJMPrhun8oIgWqLAGgwETItiSpxxpiJFGMm9l0GgrperAdouuItqxqjiH1ta_Pz-Ca4i5YjgY7d2H68gqVZMVug2ri_mxewBXzcnisJo_jLuEwLfLRt9v4htVWA |
| 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=Risk-Constrained+Optimal+Chiller+Loading+Strategy+Using+Information+Gap+Decision+Theory&rft.jtitle=Applied+sciences&rft.au=Er+Shi&rft.au=Jabari%2C+Farkhondeh&rft.au=Anvari-Moghaddam%2C+Amjad&rft.au=Mousa+Mohammadpourfard&rft.date=2019-05-01&rft.pub=MDPI+AG&rft.eissn=2076-3417&rft.volume=9&rft.issue=9&rft_id=info:doi/10.3390%2Fapp9091925&rft.externalDBID=HAS_PDF_LINK |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=2076-3417&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=2076-3417&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=2076-3417&client=summon |