Modified invasive weed optimization MPPT approach for PV system interfaced with BLDC motor for water pumping system
Abstract Water pumping systems (WPSs) are vital to many elements of human life, including drinking, agriculture, and industrial use. In many areas, photovoltaic system (PVS)-powered WPSs are regarded as the most efficient means of water supply. Multiple WPSs may be required to accommodate demand. To...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2025-06-01
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| Series: | Journal of Engineering and Applied Science |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s44147-025-00651-7 |
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| Summary: | Abstract Water pumping systems (WPSs) are vital to many elements of human life, including drinking, agriculture, and industrial use. In many areas, photovoltaic system (PVS)-powered WPSs are regarded as the most efficient means of water supply. Multiple WPSs may be required to accommodate demand. To pump out the water from underground, electric motors—specifically, brushless DC (BLDC) motors—are needed. In the proposed research, two separate WPSs that will interface with the single PVS to supply water to different locations with the two BLDC motors each. In order to reduce maintenance costs, this study examines a PVS interfaced with BLDC motor-driven WPS that does not require batteries leads to reduced maintenance. Furthermore, the sensor-less speed control by sliding mode controller (SMC) is employed instead of sensors to maintain the motor speed. Partial shading is a major issue in PVS, affecting power generation. With partial shading conditions (PSC), the perturbed and observe (P&O) method might not be enough to produce a voltage signal that corresponds to the maximum power point (MPP). Therefore, the modified invasive weed optimization (MIWO) approach integrated with P&O approach to improve performance under PSC. Results of proposed MIWO with P&O approach has been compared with other MPP approaches i.e., grey wolf optimization (GWO) approach, particle swarm optimization (PSO) approach, and genetic algorithm (GA) approaches for MPP tracking under different PSCs. By combining SMC with the suggested MPP, converter has the ability to serve as an MPP tracker. The suggested inverter control uses long short-term memory (LSTM) with artificial neural network (ANN) controller to obtain more accurate responses with various operational circumstances. The suggested single PVS with MIWO with P&O-based MPP approach for WPSs interfaced by two BLDC motors has been tested and validated on the Hardware in Loop (HIL) platform, which driven by OPAL-RT technology. |
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| ISSN: | 1110-1903 2536-9512 |