Selection criteria of dc-dc converter and control variable for MPPT of PV system utilized in heating and cooking applications
This paper deals with the selection of dc-dc converter and control variable required to track the maximum power of photovoltaic (PV) array, to optimize the utilization of solar power. To reduce the maintenance cost and to simplify the model, the battery has not been used in the proposed PV system ma...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2017-01-01
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| Series: | Cogent Engineering |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/23311916.2017.1363357 |
| _version_ | 1797716920229691392 |
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| author | Byamakesh Nayak Alivarani Mohapatra Kanungo Barada Mohanty |
| author_facet | Byamakesh Nayak Alivarani Mohapatra Kanungo Barada Mohanty |
| author_sort | Byamakesh Nayak |
| collection | DOAJ |
| description | This paper deals with the selection of dc-dc converter and control variable required to track the maximum power of photovoltaic (PV) array, to optimize the utilization of solar power. To reduce the maintenance cost and to simplify the model, the battery has not been used in the proposed PV system mainly used for cooking and heating applications. Since the battery has not been used, selection of dc-dc converter is an important consideration of the PV system in standalone applications. In the proposed system converter is selected based on maximum power transfer theorem which is dependent on load resistance. Different load resistance is considered for maximum power point tracking (MPPT) with different converter topologies, and it has been observed that buck-boost converter is suitable for any load resistance connected in the PV system. An effort has been taken to suitably choosing the control variable which is the output signal of the maximum power point (MPP) tracker. Control variable which is dependent on inputs of MPP tracker is decided based on the stability of the system. Two MPP trackers are designed based on neural-network (NN) controller and perturb and observe (P&O) algorithm. The tracking capabilities of both NN controller and the P&O algorithm is compared with the variation of irradiation and found that tracking capability of NN controller is better than P&O method. The system is simulated using MATLAB/Simulink environment, and the results show that NN controller tracks MPP at a faster rate with reduced oscillation. |
| first_indexed | 2024-03-12T08:28:37Z |
| format | Article |
| id | doaj.art-4734b99abf8f474b9b3c63abddc1388a |
| institution | Directory Open Access Journal |
| issn | 2331-1916 |
| language | English |
| last_indexed | 2024-03-12T08:28:37Z |
| publishDate | 2017-01-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Cogent Engineering |
| spelling | doaj.art-4734b99abf8f474b9b3c63abddc1388a2023-09-02T17:56:45ZengTaylor & Francis GroupCogent Engineering2331-19162017-01-014110.1080/23311916.2017.13633571363357Selection criteria of dc-dc converter and control variable for MPPT of PV system utilized in heating and cooking applicationsByamakesh Nayak0Alivarani Mohapatra1Kanungo Barada Mohanty2KIIT UniversityKIIT UniversityNIT, RourkelaThis paper deals with the selection of dc-dc converter and control variable required to track the maximum power of photovoltaic (PV) array, to optimize the utilization of solar power. To reduce the maintenance cost and to simplify the model, the battery has not been used in the proposed PV system mainly used for cooking and heating applications. Since the battery has not been used, selection of dc-dc converter is an important consideration of the PV system in standalone applications. In the proposed system converter is selected based on maximum power transfer theorem which is dependent on load resistance. Different load resistance is considered for maximum power point tracking (MPPT) with different converter topologies, and it has been observed that buck-boost converter is suitable for any load resistance connected in the PV system. An effort has been taken to suitably choosing the control variable which is the output signal of the maximum power point (MPP) tracker. Control variable which is dependent on inputs of MPP tracker is decided based on the stability of the system. Two MPP trackers are designed based on neural-network (NN) controller and perturb and observe (P&O) algorithm. The tracking capabilities of both NN controller and the P&O algorithm is compared with the variation of irradiation and found that tracking capability of NN controller is better than P&O method. The system is simulated using MATLAB/Simulink environment, and the results show that NN controller tracks MPP at a faster rate with reduced oscillation.http://dx.doi.org/10.1080/23311916.2017.1363357photovoltaic power systemdc-dc convertermaximum power point tracking (mppt)perturb and observe (p&o)neural network (nn) |
| spellingShingle | Byamakesh Nayak Alivarani Mohapatra Kanungo Barada Mohanty Selection criteria of dc-dc converter and control variable for MPPT of PV system utilized in heating and cooking applications Cogent Engineering photovoltaic power system dc-dc converter maximum power point tracking (mppt) perturb and observe (p&o) neural network (nn) |
| title | Selection criteria of dc-dc converter and control variable for MPPT of PV system utilized in heating and cooking applications |
| title_full | Selection criteria of dc-dc converter and control variable for MPPT of PV system utilized in heating and cooking applications |
| title_fullStr | Selection criteria of dc-dc converter and control variable for MPPT of PV system utilized in heating and cooking applications |
| title_full_unstemmed | Selection criteria of dc-dc converter and control variable for MPPT of PV system utilized in heating and cooking applications |
| title_short | Selection criteria of dc-dc converter and control variable for MPPT of PV system utilized in heating and cooking applications |
| title_sort | selection criteria of dc dc converter and control variable for mppt of pv system utilized in heating and cooking applications |
| topic | photovoltaic power system dc-dc converter maximum power point tracking (mppt) perturb and observe (p&o) neural network (nn) |
| url | http://dx.doi.org/10.1080/23311916.2017.1363357 |
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