Energy management system for grid-connected solar photovoltaic with battery using MATLAB simulation tool
Fuzzy logic controller system is one of the intelligent methods of energy management system that aims at conserving energy. The effectiveness of fuzzy logic controller is depending on set of restrictions, linguistic variables, values, and number of probabilistic combinations of resources to formulat...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2020-01-01
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| Series: | Cogent Engineering |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/23311916.2020.1827702 |
| _version_ | 1797762893733691392 |
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| author | Abraham Hizkiel Nebey |
| author_facet | Abraham Hizkiel Nebey |
| author_sort | Abraham Hizkiel Nebey |
| collection | DOAJ |
| description | Fuzzy logic controller system is one of the intelligent methods of energy management system that aims at conserving energy. The effectiveness of fuzzy logic controller is depending on set of restrictions, linguistic variables, values, and number of probabilistic combinations of resources to formulate the rules. These should be considered to obtain optimal results in terms of energy conservation. Therefore, the objective of this study was to maximize power supply from solar and battery for energy saving. The evaluated performances in this study were the demand and supply. Optimization was conducted with the rule-based fuzzy logic control system in MAT LAB software. A total of thirty-three (33) number of combinations/rules were performed. Using rule viewer tool in Mat lab as performance analysis, it was observed that the demand was the main set of restriction for all three resources to supply (35.3 contribution of grid,17.5 contribution of battery, and 17.5 contribution of solar, respectively), while the grid had the highest contribution to supply 35.3 kW of demand. Rule based fuzzy shown that the results obtained are in total conformance to that of the traditional energy management method, with intelligently switch the load to the available resources at a time. Thus, 80% of the national grid energy was saved during day time and 35% during night time. The majority of the loads were shared by solar in day time and battery and grid in night time. |
| first_indexed | 2024-03-12T19:33:49Z |
| format | Article |
| id | doaj.art-ca4c957e640641da90677e475529c3d3 |
| institution | Directory Open Access Journal |
| issn | 2331-1916 |
| language | English |
| last_indexed | 2024-03-12T19:33:49Z |
| publishDate | 2020-01-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Cogent Engineering |
| spelling | doaj.art-ca4c957e640641da90677e475529c3d32023-08-02T04:19:50ZengTaylor & Francis GroupCogent Engineering2331-19162020-01-017110.1080/23311916.2020.18277021827702Energy management system for grid-connected solar photovoltaic with battery using MATLAB simulation toolAbraham Hizkiel Nebey0Bahir Dar University Institute of TechnologyFuzzy logic controller system is one of the intelligent methods of energy management system that aims at conserving energy. The effectiveness of fuzzy logic controller is depending on set of restrictions, linguistic variables, values, and number of probabilistic combinations of resources to formulate the rules. These should be considered to obtain optimal results in terms of energy conservation. Therefore, the objective of this study was to maximize power supply from solar and battery for energy saving. The evaluated performances in this study were the demand and supply. Optimization was conducted with the rule-based fuzzy logic control system in MAT LAB software. A total of thirty-three (33) number of combinations/rules were performed. Using rule viewer tool in Mat lab as performance analysis, it was observed that the demand was the main set of restriction for all three resources to supply (35.3 contribution of grid,17.5 contribution of battery, and 17.5 contribution of solar, respectively), while the grid had the highest contribution to supply 35.3 kW of demand. Rule based fuzzy shown that the results obtained are in total conformance to that of the traditional energy management method, with intelligently switch the load to the available resources at a time. Thus, 80% of the national grid energy was saved during day time and 35% during night time. The majority of the loads were shared by solar in day time and battery and grid in night time.http://dx.doi.org/10.1080/23311916.2020.1827702energy conservationenergy management systemfuzzy logic controllerethiopiamatlab/simulink |
| spellingShingle | Abraham Hizkiel Nebey Energy management system for grid-connected solar photovoltaic with battery using MATLAB simulation tool Cogent Engineering energy conservation energy management system fuzzy logic controller ethiopia matlab/simulink |
| title | Energy management system for grid-connected solar photovoltaic with battery using MATLAB simulation tool |
| title_full | Energy management system for grid-connected solar photovoltaic with battery using MATLAB simulation tool |
| title_fullStr | Energy management system for grid-connected solar photovoltaic with battery using MATLAB simulation tool |
| title_full_unstemmed | Energy management system for grid-connected solar photovoltaic with battery using MATLAB simulation tool |
| title_short | Energy management system for grid-connected solar photovoltaic with battery using MATLAB simulation tool |
| title_sort | energy management system for grid connected solar photovoltaic with battery using matlab simulation tool |
| topic | energy conservation energy management system fuzzy logic controller ethiopia matlab/simulink |
| url | http://dx.doi.org/10.1080/23311916.2020.1827702 |
| work_keys_str_mv | AT abrahamhizkielnebey energymanagementsystemforgridconnectedsolarphotovoltaicwithbatteryusingmatlabsimulationtool |