A Hybrid Modified Artificial Bee Colony (ABC)-Based Artificial Neural Network Model for Power Management Controller and Hybrid Energy System for Energy Source Integration
Small MGS (microgrid systems) are capable of decreasing energy losses. Long-distance power transmission lines are constructed by integrating distributed power sources with energy storage subsystems, which is the current trend in the development of RES (renewable energy sources). Although energies pr...
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MDPI AG
2023-12-01
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| author | Udayakumar Ramanathan Sugumar Rajendran Devi Thiyagarajan Elankavi Rajendran |
| author_facet | Udayakumar Ramanathan Sugumar Rajendran Devi Thiyagarajan Elankavi Rajendran |
| author_sort | Udayakumar Ramanathan |
| collection | DOAJ |
| description | Small MGS (microgrid systems) are capable of decreasing energy losses. Long-distance power transmission lines are constructed by integrating distributed power sources with energy storage subsystems, which is the current trend in the development of RES (renewable energy sources). Although energies produced by RES do not cause pollution, they are stochastic and hence challenging to manage. This disadvantage makes high penetration of RES risky for the stability, dependability, and power quality of main electrical grids. The energies obtained from RES must thus be integrated in the best possible way. To provide maximum energy sustainability and best energy usage, hybrid energy systems must manage energy efficiently. In order to improve power management and make better use of RES, this study offers a hybrid energy power management controller based on hybrid MABC (modified artificial bee colony) and ANN (artificial neural network) for MGS, PVS (photovoltaic system), and WT (wind turbine). Controlling power flows between grids and energy sources is the suggested approach for power control. D/R (demands/responses), customer reactions, offering priorities, D/R properties like COE (cost of energies), and sizes (lengths) are considered in this work. Along with current techniques, a suggested model is implemented in the MATLAB/Simulink platform. |
| format | Article |
| id | doaj-art-7abdaf11c1cf4f0aa9a01b622e3ca82c |
| institution | Kabale University |
| issn | 2673-4591 |
| language | English |
| publishDate | 2023-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Engineering Proceedings |
| spelling | doaj-art-7abdaf11c1cf4f0aa9a01b622e3ca82c2025-08-20T03:43:02ZengMDPI AGEngineering Proceedings2673-45912023-12-015913510.3390/engproc2023059035A Hybrid Modified Artificial Bee Colony (ABC)-Based Artificial Neural Network Model for Power Management Controller and Hybrid Energy System for Energy Source IntegrationUdayakumar Ramanathan0Sugumar Rajendran1Devi Thiyagarajan2Elankavi Rajendran3Department of CS & IT, Kalinga University, Naya Raipur 492101, Chhattisgarh, IndiaInstitute of CSE, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai 600077, Tamilnadu, IndiaDepartment of Computer Science & Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai 600077, Tamilnadu, IndiaDepartment of Computer Science and Engineering, Siddharth Institute of Engineering & Technology, Tirupati District, Puttur 517583, Andhra Pradesh, IndiaSmall MGS (microgrid systems) are capable of decreasing energy losses. Long-distance power transmission lines are constructed by integrating distributed power sources with energy storage subsystems, which is the current trend in the development of RES (renewable energy sources). Although energies produced by RES do not cause pollution, they are stochastic and hence challenging to manage. This disadvantage makes high penetration of RES risky for the stability, dependability, and power quality of main electrical grids. The energies obtained from RES must thus be integrated in the best possible way. To provide maximum energy sustainability and best energy usage, hybrid energy systems must manage energy efficiently. In order to improve power management and make better use of RES, this study offers a hybrid energy power management controller based on hybrid MABC (modified artificial bee colony) and ANN (artificial neural network) for MGS, PVS (photovoltaic system), and WT (wind turbine). Controlling power flows between grids and energy sources is the suggested approach for power control. D/R (demands/responses), customer reactions, offering priorities, D/R properties like COE (cost of energies), and sizes (lengths) are considered in this work. Along with current techniques, a suggested model is implemented in the MATLAB/Simulink platform.https://www.mdpi.com/2673-4591/59/1/35microgrid (MG)photovoltaic (PV)wind turbine (WT)modified artificial bee colony (MABC)artificial neural network (ANN) |
| spellingShingle | Udayakumar Ramanathan Sugumar Rajendran Devi Thiyagarajan Elankavi Rajendran A Hybrid Modified Artificial Bee Colony (ABC)-Based Artificial Neural Network Model for Power Management Controller and Hybrid Energy System for Energy Source Integration Engineering Proceedings microgrid (MG) photovoltaic (PV) wind turbine (WT) modified artificial bee colony (MABC) artificial neural network (ANN) |
| title | A Hybrid Modified Artificial Bee Colony (ABC)-Based Artificial Neural Network Model for Power Management Controller and Hybrid Energy System for Energy Source Integration |
| title_full | A Hybrid Modified Artificial Bee Colony (ABC)-Based Artificial Neural Network Model for Power Management Controller and Hybrid Energy System for Energy Source Integration |
| title_fullStr | A Hybrid Modified Artificial Bee Colony (ABC)-Based Artificial Neural Network Model for Power Management Controller and Hybrid Energy System for Energy Source Integration |
| title_full_unstemmed | A Hybrid Modified Artificial Bee Colony (ABC)-Based Artificial Neural Network Model for Power Management Controller and Hybrid Energy System for Energy Source Integration |
| title_short | A Hybrid Modified Artificial Bee Colony (ABC)-Based Artificial Neural Network Model for Power Management Controller and Hybrid Energy System for Energy Source Integration |
| title_sort | hybrid modified artificial bee colony abc based artificial neural network model for power management controller and hybrid energy system for energy source integration |
| topic | microgrid (MG) photovoltaic (PV) wind turbine (WT) modified artificial bee colony (MABC) artificial neural network (ANN) |
| url | https://www.mdpi.com/2673-4591/59/1/35 |
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