Accommodating High Penetrations of Renewable Distributed Generation Mix in Smart Grids
A Master of Science thesis in Electrical Engineering by Mohammad Tarek Khayata entitled, "Accommodating High Penetrations of Renewable Distributed Generation Mix in Smart Grids," submitted in April 2017. Thesis advisor is Dr. Mostafa Shaaban. Soft and hard copy available.
محفوظ في:
| المؤلف الرئيسي: | |
|---|---|
| التنسيق: | doctoralThesis |
| منشور في: |
2017
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| الموضوعات: | |
| الوصول للمادة أونلاين: | http://hdl.handle.net/11073/8870 |
| الوسوم: |
إضافة وسم
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| _version_ | 1864513438469849088 |
|---|---|
| author | Khayata, Mohammad Tarek |
| author_facet | Khayata, Mohammad Tarek |
| author_role | author |
| dc.contributor.none.fl_str_mv | Shaaban, Mostafa |
| dc.creator.none.fl_str_mv | Khayata, Mohammad Tarek |
| dc.date.none.fl_str_mv | 2017-06-13T07:34:27Z 2017-06-13T07:34:27Z 2017-04 |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | 35.232-2017.17 http://hdl.handle.net/11073/8870 |
| dc.language.none.fl_str_mv | en_US |
| dc.subject.none.fl_str_mv | distributed generation genetic algorithms probability density function renewable resources smart grids Smart power grids Renewable energy sources |
| dc.title.none.fl_str_mv | Accommodating High Penetrations of Renewable Distributed Generation Mix in Smart Grids |
| dc.type.none.fl_str_mv | info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/doctoralThesis |
| description | A Master of Science thesis in Electrical Engineering by Mohammad Tarek Khayata entitled, "Accommodating High Penetrations of Renewable Distributed Generation Mix in Smart Grids," submitted in April 2017. Thesis advisor is Dr. Mostafa Shaaban. Soft and hard copy available. |
| format | doctoralThesis |
| id | aus_6603795afe4d1d13e707792e32cf9067 |
| identifier_str_mv | 35.232-2017.17 |
| language_invalid_str_mv | en_US |
| network_acronym_str | aus |
| network_name_str | aus |
| oai_identifier_str | oai:repository.aus.edu:11073/8870 |
| publishDate | 2017 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| spelling | Accommodating High Penetrations of Renewable Distributed Generation Mix in Smart GridsKhayata, Mohammad Tarekdistributed generationgenetic algorithmsprobability density functionrenewable resourcessmart gridsSmart power gridsRenewable energy sourcesA Master of Science thesis in Electrical Engineering by Mohammad Tarek Khayata entitled, "Accommodating High Penetrations of Renewable Distributed Generation Mix in Smart Grids," submitted in April 2017. Thesis advisor is Dr. Mostafa Shaaban. Soft and hard copy available.This work proposes a new method for renewable distributed generation (DG) allocation in smart grid. The main objective is to minimize the overall investment which includes the capital cost of DG units, the operation and maintenance costs of DG units, and the cost of purchasing energy from the grid. The proposed approach takes into consideration the uncertainty and variability associated with generation, demand, and energy cost in addition to the communication infrastructure which is the main contribution of this work. The communication infrastructure under the smart grid paradigm will allow real-time control of the system assets. Therefore, considering this property during the planning phase enhances the system performance and optimizes the overall investment. The proposed approach relies on developing probabilistic models for each generation technology, energy prices, and demand. Then, these models are combined into one multi-state gen-load-price probabilistic model that describes all possible conditions of the system. The number of states in the final model is a tradeoff between the accuracy of results and computational time. Genetic algorithm (GA) optimization technique is utilized in this study to solve the DG planning problem. Simulation results on a typical distribution system are provided to prove the effectiveness of the proposed approach in increasing the renewable DG penetration in smart grids while maximizing the profit of the investment. Moreover, the results obtained through the use of the proposed smart operation are compared with the conventional planning methodologies to demonstrate the targeted added value. A significant cost saving of 28.3% and 254% higher percentage of DG penetration are achieved with the proposed DGs curtailment technique to mitigate technical system violations, which proves the significant advantage of adopting smart grid operation in planning problems.College of EngineeringDepartment of Electrical EngineeringMaster of Science in Electrical Engineering (MSEE)Shaaban, Mostafa2017-06-13T07:34:27Z2017-06-13T07:34:27Z2017-04info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisapplication/pdf35.232-2017.17http://hdl.handle.net/11073/8870en_USoai:repository.aus.edu:11073/88702025-06-26T12:25:27Z |
| spellingShingle | Accommodating High Penetrations of Renewable Distributed Generation Mix in Smart Grids Khayata, Mohammad Tarek distributed generation genetic algorithms probability density function renewable resources smart grids Smart power grids Renewable energy sources |
| status_str | publishedVersion |
| title | Accommodating High Penetrations of Renewable Distributed Generation Mix in Smart Grids |
| title_full | Accommodating High Penetrations of Renewable Distributed Generation Mix in Smart Grids |
| title_fullStr | Accommodating High Penetrations of Renewable Distributed Generation Mix in Smart Grids |
| title_full_unstemmed | Accommodating High Penetrations of Renewable Distributed Generation Mix in Smart Grids |
| title_short | Accommodating High Penetrations of Renewable Distributed Generation Mix in Smart Grids |
| title_sort | Accommodating High Penetrations of Renewable Distributed Generation Mix in Smart Grids |
| topic | distributed generation genetic algorithms probability density function renewable resources smart grids Smart power grids Renewable energy sources |
| url | http://hdl.handle.net/11073/8870 |