Stochastic Algorithms for Controller Optimization of Grid Tied Hybrid AC/DC Microgrid with Multiple Renewable Sources
The hybrid AC/DC microgrid (MG) configuration is efficient as it reduces the need for multiple power conversions and hence losses. Therefore, this paper focuses on the study of grid assisted hybrid AC/DC MG comprising of solar PV and fuel cell (FC) systems on DC subgrid with supercapacitor (SC) as...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Stefan cel Mare University of Suceava
2019-05-01
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| Series: | Advances in Electrical and Computer Engineering |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.4316/AECE.2019.02007 |
| _version_ | 1819023232538247168 |
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| author | NEMPU, P. B. SABHAHIT, J. N. |
| author_facet | NEMPU, P. B. SABHAHIT, J. N. |
| author_sort | NEMPU, P. B. |
| collection | DOAJ |
| description | The hybrid AC/DC microgrid (MG) configuration is efficient as it reduces the need for multiple power conversions
and hence losses. Therefore, this paper focuses on the study of grid assisted hybrid AC/DC MG comprising of solar
PV and fuel cell (FC) systems on DC subgrid with supercapacitor (SC) as the short term storage device and wind energy
conversion system (WECS) on the AC subgrid. A comprehensive study of the operation of MG is performed under varying
system conditions in MATLAB/Simulink software. The real and reactive power (PQ) control scheme is used to regulate
the DC bus voltage and power flow between the subgrids. Genetic algorithm (GA), artificial bee colony (ABC) optimization,
particle swarm optimization (PSO) and the PSO with new update mechanism (PSOd) are used to compute the optimum gain values
of proportional-integral (PI) controller in the PQ control scheme. The SC bank effectively reduces the power stress on
the subgrids of the proposed hybrid MG system during intermittent conditions of load and generation. In addition, a
comparative study of the heuristic optimization techniques is presented in detail. The ABC algorithm is found to arrive
at the best results in determining the optimal gains of PI controller. |
| first_indexed | 2024-12-21T04:35:37Z |
| format | Article |
| id | doaj.art-e754b0e874834815b5b3859e339270ee |
| institution | Directory Open Access Journal |
| issn | 1582-7445 1844-7600 |
| language | English |
| last_indexed | 2024-12-21T04:35:37Z |
| publishDate | 2019-05-01 |
| publisher | Stefan cel Mare University of Suceava |
| record_format | Article |
| series | Advances in Electrical and Computer Engineering |
| spelling | doaj.art-e754b0e874834815b5b3859e339270ee2022-12-21T19:15:51ZengStefan cel Mare University of SuceavaAdvances in Electrical and Computer Engineering1582-74451844-76002019-05-01192536010.4316/AECE.2019.02007Stochastic Algorithms for Controller Optimization of Grid Tied Hybrid AC/DC Microgrid with Multiple Renewable SourcesNEMPU, P. B.SABHAHIT, J. N.The hybrid AC/DC microgrid (MG) configuration is efficient as it reduces the need for multiple power conversions and hence losses. Therefore, this paper focuses on the study of grid assisted hybrid AC/DC MG comprising of solar PV and fuel cell (FC) systems on DC subgrid with supercapacitor (SC) as the short term storage device and wind energy conversion system (WECS) on the AC subgrid. A comprehensive study of the operation of MG is performed under varying system conditions in MATLAB/Simulink software. The real and reactive power (PQ) control scheme is used to regulate the DC bus voltage and power flow between the subgrids. Genetic algorithm (GA), artificial bee colony (ABC) optimization, particle swarm optimization (PSO) and the PSO with new update mechanism (PSOd) are used to compute the optimum gain values of proportional-integral (PI) controller in the PQ control scheme. The SC bank effectively reduces the power stress on the subgrids of the proposed hybrid MG system during intermittent conditions of load and generation. In addition, a comparative study of the heuristic optimization techniques is presented in detail. The ABC algorithm is found to arrive at the best results in determining the optimal gains of PI controller.http://dx.doi.org/10.4316/AECE.2019.02007fuel cellsheuristic algorithmsmicrogridrenewable energy sourcessupercapacitors |
| spellingShingle | NEMPU, P. B. SABHAHIT, J. N. Stochastic Algorithms for Controller Optimization of Grid Tied Hybrid AC/DC Microgrid with Multiple Renewable Sources Advances in Electrical and Computer Engineering fuel cells heuristic algorithms microgrid renewable energy sources supercapacitors |
| title | Stochastic Algorithms for Controller Optimization of Grid Tied Hybrid AC/DC Microgrid with Multiple Renewable Sources |
| title_full | Stochastic Algorithms for Controller Optimization of Grid Tied Hybrid AC/DC Microgrid with Multiple Renewable Sources |
| title_fullStr | Stochastic Algorithms for Controller Optimization of Grid Tied Hybrid AC/DC Microgrid with Multiple Renewable Sources |
| title_full_unstemmed | Stochastic Algorithms for Controller Optimization of Grid Tied Hybrid AC/DC Microgrid with Multiple Renewable Sources |
| title_short | Stochastic Algorithms for Controller Optimization of Grid Tied Hybrid AC/DC Microgrid with Multiple Renewable Sources |
| title_sort | stochastic algorithms for controller optimization of grid tied hybrid ac dc microgrid with multiple renewable sources |
| topic | fuel cells heuristic algorithms microgrid renewable energy sources supercapacitors |
| url | http://dx.doi.org/10.4316/AECE.2019.02007 |
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