Microgrid optimal scheduling considering normal and emergency operation
This paper deals with the optimal scheduling of a microgrid (MG) equipped with dispatchable distributed generators (DGs), renewable generators and electrical storages (batteries). A chance-constrained model is developed to handle normal operation and emergency conditions of MG including DG outage an...
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| Format: | Article |
| Language: | English |
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University of Sistan and Baluchestan
2019-10-01
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| Series: | International Journal of Industrial Electronics, Control and Optimization |
| Subjects: | |
| Online Access: | https://ieco.usb.ac.ir/article_4665_eff76511ff7afa8373d22489dd620aa4.pdf |
| _version_ | 1818250497007550464 |
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| author | Ali Sefidgar-dezfouli Mahmood Joorabian Elaheh Mashhour |
| author_facet | Ali Sefidgar-dezfouli Mahmood Joorabian Elaheh Mashhour |
| author_sort | Ali Sefidgar-dezfouli |
| collection | DOAJ |
| description | This paper deals with the optimal scheduling of a microgrid (MG) equipped with dispatchable distributed generators (DGs), renewable generators and electrical storages (batteries). A chance-constrained model is developed to handle normal operation and emergency conditions of MG including DG outage and unwanted islanding. Purchasing reserve from the upstream grid is also considered. Moreover, the uncertainties of loads and renewable resources are incorporated into the model. Furthermore, a novel probabilistic formulation is presented to determine the amount of required reserve in different conditions of MG by introducing separate probability distribution functions (PDFs) for each condition. Accordingly, an index named as the probability of reserve sufficiency (PRS) is introduced. The presented model keeps a given value of PRS in normal and emergency conditions of MG operation. In addition, some controllable variables are added to the chance constraints as an innovative technique to reduce the complexity of the model. Finally, a test microgrid is studied in different case studies and the results are evaluated. |
| first_indexed | 2024-12-12T15:53:19Z |
| format | Article |
| id | doaj.art-5f81cb818ee04265a09ebe528d9b8f74 |
| institution | Directory Open Access Journal |
| issn | 2645-3517 2645-3568 |
| language | English |
| last_indexed | 2024-12-12T15:53:19Z |
| publishDate | 2019-10-01 |
| publisher | University of Sistan and Baluchestan |
| record_format | Article |
| series | International Journal of Industrial Electronics, Control and Optimization |
| spelling | doaj.art-5f81cb818ee04265a09ebe528d9b8f742022-12-22T00:19:32ZengUniversity of Sistan and BaluchestanInternational Journal of Industrial Electronics, Control and Optimization2645-35172645-35682019-10-012427928810.22111/ieco.2019.27484.11004665Microgrid optimal scheduling considering normal and emergency operationAli Sefidgar-dezfouli0Mahmood Joorabian1Elaheh Mashhour2Department of Electrical Engineering, Faculty of Engineering, Shahid Chamran University of Ahvaz, Ahvaz, IranDepartment of Electrical Engineering, Faculty of Engineering, Shahid Chamran University of Ahvaz, Ahvaz, IranDepartment of Electrical Engineering, Faculty of Engineering, Shahid Chamran University of Ahvaz, Ahvaz, IranThis paper deals with the optimal scheduling of a microgrid (MG) equipped with dispatchable distributed generators (DGs), renewable generators and electrical storages (batteries). A chance-constrained model is developed to handle normal operation and emergency conditions of MG including DG outage and unwanted islanding. Purchasing reserve from the upstream grid is also considered. Moreover, the uncertainties of loads and renewable resources are incorporated into the model. Furthermore, a novel probabilistic formulation is presented to determine the amount of required reserve in different conditions of MG by introducing separate probability distribution functions (PDFs) for each condition. Accordingly, an index named as the probability of reserve sufficiency (PRS) is introduced. The presented model keeps a given value of PRS in normal and emergency conditions of MG operation. In addition, some controllable variables are added to the chance constraints as an innovative technique to reduce the complexity of the model. Finally, a test microgrid is studied in different case studies and the results are evaluated.https://ieco.usb.ac.ir/article_4665_eff76511ff7afa8373d22489dd620aa4.pdfmicrogridrenewable generationprobability distribution function (pdf)unwanted islandingdg outage |
| spellingShingle | Ali Sefidgar-dezfouli Mahmood Joorabian Elaheh Mashhour Microgrid optimal scheduling considering normal and emergency operation International Journal of Industrial Electronics, Control and Optimization microgrid renewable generation probability distribution function (pdf) unwanted islanding dg outage |
| title | Microgrid optimal scheduling considering normal and emergency operation |
| title_full | Microgrid optimal scheduling considering normal and emergency operation |
| title_fullStr | Microgrid optimal scheduling considering normal and emergency operation |
| title_full_unstemmed | Microgrid optimal scheduling considering normal and emergency operation |
| title_short | Microgrid optimal scheduling considering normal and emergency operation |
| title_sort | microgrid optimal scheduling considering normal and emergency operation |
| topic | microgrid renewable generation probability distribution function (pdf) unwanted islanding dg outage |
| url | https://ieco.usb.ac.ir/article_4665_eff76511ff7afa8373d22489dd620aa4.pdf |
| work_keys_str_mv | AT alisefidgardezfouli microgridoptimalschedulingconsideringnormalandemergencyoperation AT mahmoodjoorabian microgridoptimalschedulingconsideringnormalandemergencyoperation AT elahehmashhour microgridoptimalschedulingconsideringnormalandemergencyoperation |