Comparison between Kalman filter and incremental conductance algorithm for optimizing photovoltaic energy
Abstract The purpose of this paper is to present a performance comparison between two maximum power point tracking algorithms. These two algorithms are incremental conductance (INC) which is an improved version of the perturb and observe algorithm, and the second algorithm is the Kalman filter appli...
Main Authors: | , , , , |
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Format: | Article |
Language: | English |
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SpringerOpen
2017-12-01
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Series: | Renewables: Wind, Water, and Solar |
Subjects: | |
Online Access: | http://link.springer.com/article/10.1186/s40807-017-0046-8 |
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author | Saad Motahhir Ayoub Aoune Abdelaziz El Ghzizal Souad Sebti Aziz Derouich |
author_facet | Saad Motahhir Ayoub Aoune Abdelaziz El Ghzizal Souad Sebti Aziz Derouich |
author_sort | Saad Motahhir |
collection | DOAJ |
description | Abstract The purpose of this paper is to present a performance comparison between two maximum power point tracking algorithms. These two algorithms are incremental conductance (INC) which is an improved version of the perturb and observe algorithm, and the second algorithm is the Kalman filter applied to a photovoltaic system. In this work, a photovoltaic panel is modeled in PSIM tool; a Boost converter controlled by the maximum power point tracker is put between the PV panel and the load. Then the two algorithms are implemented by using C language and C block provided by PSIM tool. Next, several tests under stable and variable environmental conditions are made for the two algorithms, and results show a better performance of the Kalman filter compared to the INC in terms of response time, efficiency and steady-state oscillations. |
first_indexed | 2024-03-12T08:41:35Z |
format | Article |
id | doaj.art-23a2fdfa17ed4d4ca4f4642319139489 |
institution | Directory Open Access Journal |
issn | 2198-994X |
language | English |
last_indexed | 2024-03-12T08:41:35Z |
publishDate | 2017-12-01 |
publisher | SpringerOpen |
record_format | Article |
series | Renewables: Wind, Water, and Solar |
spelling | doaj.art-23a2fdfa17ed4d4ca4f46423191394892023-09-02T16:45:17ZengSpringerOpenRenewables: Wind, Water, and Solar2198-994X2017-12-014111010.1186/s40807-017-0046-8Comparison between Kalman filter and incremental conductance algorithm for optimizing photovoltaic energySaad Motahhir0Ayoub Aoune1Abdelaziz El Ghzizal2Souad Sebti3Aziz Derouich4Laboratory of Production Engineering, Energy and Sustainable Development, Higher School of Technology, SMBA UniversityLaboratory of Production Engineering, Energy and Sustainable Development, Higher School of Technology, SMBA UniversityLaboratory of Production Engineering, Energy and Sustainable Development, Higher School of Technology, SMBA UniversityLaboratory of Production Engineering, Energy and Sustainable Development, Higher School of Technology, SMBA UniversityLaboratory of Production Engineering, Energy and Sustainable Development, Higher School of Technology, SMBA UniversityAbstract The purpose of this paper is to present a performance comparison between two maximum power point tracking algorithms. These two algorithms are incremental conductance (INC) which is an improved version of the perturb and observe algorithm, and the second algorithm is the Kalman filter applied to a photovoltaic system. In this work, a photovoltaic panel is modeled in PSIM tool; a Boost converter controlled by the maximum power point tracker is put between the PV panel and the load. Then the two algorithms are implemented by using C language and C block provided by PSIM tool. Next, several tests under stable and variable environmental conditions are made for the two algorithms, and results show a better performance of the Kalman filter compared to the INC in terms of response time, efficiency and steady-state oscillations.http://link.springer.com/article/10.1186/s40807-017-0046-8Photovoltaic panelMPPTIncremental conductance algorithmKalman filterBoost converterPSIM |
spellingShingle | Saad Motahhir Ayoub Aoune Abdelaziz El Ghzizal Souad Sebti Aziz Derouich Comparison between Kalman filter and incremental conductance algorithm for optimizing photovoltaic energy Renewables: Wind, Water, and Solar Photovoltaic panel MPPT Incremental conductance algorithm Kalman filter Boost converter PSIM |
title | Comparison between Kalman filter and incremental conductance algorithm for optimizing photovoltaic energy |
title_full | Comparison between Kalman filter and incremental conductance algorithm for optimizing photovoltaic energy |
title_fullStr | Comparison between Kalman filter and incremental conductance algorithm for optimizing photovoltaic energy |
title_full_unstemmed | Comparison between Kalman filter and incremental conductance algorithm for optimizing photovoltaic energy |
title_short | Comparison between Kalman filter and incremental conductance algorithm for optimizing photovoltaic energy |
title_sort | comparison between kalman filter and incremental conductance algorithm for optimizing photovoltaic energy |
topic | Photovoltaic panel MPPT Incremental conductance algorithm Kalman filter Boost converter PSIM |
url | http://link.springer.com/article/10.1186/s40807-017-0046-8 |
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