Design of a Fractional Order Frequency PID Controller for an Islanded Microgrid: A Multi-Objective Extremal Optimization Method
Fractional order proportional-integral-derivative(FOPID) controllers have attracted increasing attentions recently due to their better control performance than the traditional integer-order proportional-integral-derivative (PID) controllers. However, there are only few studies concerning the fractio...
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| Format: | Article |
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MDPI AG
2017-10-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/10/10/1502 |
| _version_ | 1828113993775972352 |
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| author | Huan Wang Guoqiang Zeng Yuxing Dai Daqiang Bi Jingliao Sun Xiaoqing Xie |
| author_facet | Huan Wang Guoqiang Zeng Yuxing Dai Daqiang Bi Jingliao Sun Xiaoqing Xie |
| author_sort | Huan Wang |
| collection | DOAJ |
| description | Fractional order proportional-integral-derivative(FOPID) controllers have attracted increasing attentions recently due to their better control performance than the traditional integer-order proportional-integral-derivative (PID) controllers. However, there are only few studies concerning the fractional order control of microgrids based on evolutionary algorithms. From the perspective of multi-objective optimization, this paper presents an effective FOPID based frequency controller design method called MOEO-FOPID for an islanded microgrid by using a Multi-objective extremal optimization (MOEO) algorithm to minimize frequency deviation and controller output signal simultaneously in order to improve finally the efficient operation of distributed generations and energy storage devices. Its superiority to nondominated sorting genetic algorithm-II (NSGA-II) based FOPID/PID controllers and other recently reported single-objective evolutionary algorithms such as Kriging-based surrogate modeling and real-coded population extremal optimization-based FOPID controllers is demonstrated by the simulation studies on a typical islanded microgrid in terms of the control performance including frequency deviation, deficit grid power, controller output signal and robustness. |
| first_indexed | 2024-04-11T12:17:35Z |
| format | Article |
| id | doaj.art-d77ea83125134fe8b647ba06d1d584fe |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-04-11T12:17:35Z |
| publishDate | 2017-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-d77ea83125134fe8b647ba06d1d584fe2022-12-22T04:24:12ZengMDPI AGEnergies1996-10732017-10-011010150210.3390/en10101502en10101502Design of a Fractional Order Frequency PID Controller for an Islanded Microgrid: A Multi-Objective Extremal Optimization MethodHuan Wang0Guoqiang Zeng1Yuxing Dai2Daqiang Bi3Jingliao Sun4Xiaoqing Xie5College of Electrical and Information Engineering, Hunan University, Changsha 410082, ChinaNational-Local Joint Engineering Laboratory of Digitalize Electrical Design Technology, Wenzhou University, Wenzhou 325035, ChinaCollege of Electrical and Information Engineering, Hunan University, Changsha 410082, ChinaState Key Laboratory of Power Systems and Department of Electrical Engineering, Tsinghua University, Beijing 100084, ChinaState Grid Wenzhou Electric Power Supply Company, Wenzhou 325000, ChinaNational-Local Joint Engineering Laboratory of Digitalize Electrical Design Technology, Wenzhou University, Wenzhou 325035, ChinaFractional order proportional-integral-derivative(FOPID) controllers have attracted increasing attentions recently due to their better control performance than the traditional integer-order proportional-integral-derivative (PID) controllers. However, there are only few studies concerning the fractional order control of microgrids based on evolutionary algorithms. From the perspective of multi-objective optimization, this paper presents an effective FOPID based frequency controller design method called MOEO-FOPID for an islanded microgrid by using a Multi-objective extremal optimization (MOEO) algorithm to minimize frequency deviation and controller output signal simultaneously in order to improve finally the efficient operation of distributed generations and energy storage devices. Its superiority to nondominated sorting genetic algorithm-II (NSGA-II) based FOPID/PID controllers and other recently reported single-objective evolutionary algorithms such as Kriging-based surrogate modeling and real-coded population extremal optimization-based FOPID controllers is demonstrated by the simulation studies on a typical islanded microgrid in terms of the control performance including frequency deviation, deficit grid power, controller output signal and robustness.https://www.mdpi.com/1996-1073/10/10/1502microgridfractional order controllerfrequency controlmulti-objective optimizationextremal optimization |
| spellingShingle | Huan Wang Guoqiang Zeng Yuxing Dai Daqiang Bi Jingliao Sun Xiaoqing Xie Design of a Fractional Order Frequency PID Controller for an Islanded Microgrid: A Multi-Objective Extremal Optimization Method Energies microgrid fractional order controller frequency control multi-objective optimization extremal optimization |
| title | Design of a Fractional Order Frequency PID Controller for an Islanded Microgrid: A Multi-Objective Extremal Optimization Method |
| title_full | Design of a Fractional Order Frequency PID Controller for an Islanded Microgrid: A Multi-Objective Extremal Optimization Method |
| title_fullStr | Design of a Fractional Order Frequency PID Controller for an Islanded Microgrid: A Multi-Objective Extremal Optimization Method |
| title_full_unstemmed | Design of a Fractional Order Frequency PID Controller for an Islanded Microgrid: A Multi-Objective Extremal Optimization Method |
| title_short | Design of a Fractional Order Frequency PID Controller for an Islanded Microgrid: A Multi-Objective Extremal Optimization Method |
| title_sort | design of a fractional order frequency pid controller for an islanded microgrid a multi objective extremal optimization method |
| topic | microgrid fractional order controller frequency control multi-objective optimization extremal optimization |
| url | https://www.mdpi.com/1996-1073/10/10/1502 |
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