Coordination between Demand Response Programming and Learning-Based FOPID Controller for Alleviation of Frequency Excursion of Hybrid Microgrid
In recent years, residential rate consumptions have increased due to modern appliances which require a high level of electricity demands. Although mentioned appliances can improve the quality of consumers’ lives to a certain extent, they suffer from various shortcomings including raising t...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-01-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/13/2/442 |
| _version_ | 1798024387151003648 |
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| author | Masoud Babaei Ahmadreza Abazari S. M. Muyeen |
| author_facet | Masoud Babaei Ahmadreza Abazari S. M. Muyeen |
| author_sort | Masoud Babaei |
| collection | DOAJ |
| description | In recent years, residential rate consumptions have increased due to modern appliances which require a high level of electricity demands. Although mentioned appliances can improve the quality of consumers’ lives to a certain extent, they suffer from various shortcomings including raising the electricity bill as well as serious technical issues such as lack of balance between electricity generation and load disturbances. This imbalance can generally lead to the frequency excursion which is a significant concern, especially for low-inertia microgrids with unpredictable parameters. This research proposes an intelligent combination of two approaches in order to alleviate challenges related to the frequency control mechanism. Firstly, a learning-based fractional-order proportional-integral-derivative (FOPID) controller is trained by recurrent adaptive neuro-fuzzy inference (RANFIS) in the generation side during various operational conditions and climatic changes. In the following, a decentralized demand response (DR) programming in the load side is introduced to minimize consumption rate through controllable appliances and energy storage systems (ESSs). Furthermore, parameters uncertainties and time delay, which are generally known as two main concerns of isolated microgrids, are regarded in the frequency plan of a low-inertia microgrid including renewable energy sources (RESs), and energy storage systems (ESSs). Simulation results are illustrated in three different case studies in order to compare the performance of the proposed two methods during various operational conditions. It is obvious that the frequency deviation of microgrid can be improved by taking advantage of intelligent combination of both DR program and modern control mechanism. |
| first_indexed | 2024-04-11T18:01:34Z |
| format | Article |
| id | doaj.art-1ad10b84fe8e4582b1c4f90260a4f46f |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-04-11T18:01:34Z |
| publishDate | 2020-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-1ad10b84fe8e4582b1c4f90260a4f46f2022-12-22T04:10:27ZengMDPI AGEnergies1996-10732020-01-0113244210.3390/en13020442en13020442Coordination between Demand Response Programming and Learning-Based FOPID Controller for Alleviation of Frequency Excursion of Hybrid MicrogridMasoud Babaei0Ahmadreza Abazari1S. M. Muyeen2Departmant of Electrical Engineering, Tarbiat Modares University, Tehran 1193653471, IranDepartmant of Electrical Engineering, University of Tehran, Tehran 1193653471, IranSchool of Electrical Engineering Computing and Mathematical Sciences, Curtin University, Perth, WA 6845, AustraliaIn recent years, residential rate consumptions have increased due to modern appliances which require a high level of electricity demands. Although mentioned appliances can improve the quality of consumers’ lives to a certain extent, they suffer from various shortcomings including raising the electricity bill as well as serious technical issues such as lack of balance between electricity generation and load disturbances. This imbalance can generally lead to the frequency excursion which is a significant concern, especially for low-inertia microgrids with unpredictable parameters. This research proposes an intelligent combination of two approaches in order to alleviate challenges related to the frequency control mechanism. Firstly, a learning-based fractional-order proportional-integral-derivative (FOPID) controller is trained by recurrent adaptive neuro-fuzzy inference (RANFIS) in the generation side during various operational conditions and climatic changes. In the following, a decentralized demand response (DR) programming in the load side is introduced to minimize consumption rate through controllable appliances and energy storage systems (ESSs). Furthermore, parameters uncertainties and time delay, which are generally known as two main concerns of isolated microgrids, are regarded in the frequency plan of a low-inertia microgrid including renewable energy sources (RESs), and energy storage systems (ESSs). Simulation results are illustrated in three different case studies in order to compare the performance of the proposed two methods during various operational conditions. It is obvious that the frequency deviation of microgrid can be improved by taking advantage of intelligent combination of both DR program and modern control mechanism.https://www.mdpi.com/1996-1073/13/2/442demand response (dr) programmingfopid controllerhybrid isolated microgridfrequency regulation |
| spellingShingle | Masoud Babaei Ahmadreza Abazari S. M. Muyeen Coordination between Demand Response Programming and Learning-Based FOPID Controller for Alleviation of Frequency Excursion of Hybrid Microgrid Energies demand response (dr) programming fopid controller hybrid isolated microgrid frequency regulation |
| title | Coordination between Demand Response Programming and Learning-Based FOPID Controller for Alleviation of Frequency Excursion of Hybrid Microgrid |
| title_full | Coordination between Demand Response Programming and Learning-Based FOPID Controller for Alleviation of Frequency Excursion of Hybrid Microgrid |
| title_fullStr | Coordination between Demand Response Programming and Learning-Based FOPID Controller for Alleviation of Frequency Excursion of Hybrid Microgrid |
| title_full_unstemmed | Coordination between Demand Response Programming and Learning-Based FOPID Controller for Alleviation of Frequency Excursion of Hybrid Microgrid |
| title_short | Coordination between Demand Response Programming and Learning-Based FOPID Controller for Alleviation of Frequency Excursion of Hybrid Microgrid |
| title_sort | coordination between demand response programming and learning based fopid controller for alleviation of frequency excursion of hybrid microgrid |
| topic | demand response (dr) programming fopid controller hybrid isolated microgrid frequency regulation |
| url | https://www.mdpi.com/1996-1073/13/2/442 |
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