TY - JOUR
T1 - Optimizing MPPT Control for Enhanced Efficiency in Sustainable Photovoltaic Microgrids
T2 - A DSO-Based Approach
AU - Mazumdar, Debabrata
AU - Biswas, Pabitra Kumar
AU - Sain, Chiranjit
AU - Ahmad, Furkan
AU - Sarker, Rishiraj
AU - Ustun, Taha Selim
N1 - Publisher Copyright:
© 2024 Debabrata Mazumdar et al.
PY - 2024/4/17
Y1 - 2024/4/17
N2 - The output of photovoltaic (PV) systems is significantly impacted by the vagaries of ambient temperature, solar irradiance, and environmental fluctuations. To achieve the utmost attainable power from PV systems, it is desired to be efficient at the maximum power point in diverse weather climates. Maximum power point tracking (MPPT) is used to schedule a designated location from where the highest power can be harvested. In the context of solar photovoltaic systems connected with DC microgrid platforms, this study introduces a recently developed drone squadron optimization (DSO) scheme that tracks the global maximum power point under PSCS difficulties. Furthermore, an exhaustive comparative analysis has been presented among particle swarm optimization (PSO), cuckoo search algorithm (CUSA), and grey wolf optimization (GWO) under different operating environments to endorse the supremacy of the nominated technique. The suggested method performs noticeably faster than many other methods currently in use, and in addition to offering the highest power, it can also use bidirectional power flow regulation in both constant and variable air conditions. Lastly, an MPPT system interfaced with the DC microgrid based on DSO ensures a sustainable and reliable architecture to provide at load in low power generating situations.
AB - The output of photovoltaic (PV) systems is significantly impacted by the vagaries of ambient temperature, solar irradiance, and environmental fluctuations. To achieve the utmost attainable power from PV systems, it is desired to be efficient at the maximum power point in diverse weather climates. Maximum power point tracking (MPPT) is used to schedule a designated location from where the highest power can be harvested. In the context of solar photovoltaic systems connected with DC microgrid platforms, this study introduces a recently developed drone squadron optimization (DSO) scheme that tracks the global maximum power point under PSCS difficulties. Furthermore, an exhaustive comparative analysis has been presented among particle swarm optimization (PSO), cuckoo search algorithm (CUSA), and grey wolf optimization (GWO) under different operating environments to endorse the supremacy of the nominated technique. The suggested method performs noticeably faster than many other methods currently in use, and in addition to offering the highest power, it can also use bidirectional power flow regulation in both constant and variable air conditions. Lastly, an MPPT system interfaced with the DC microgrid based on DSO ensures a sustainable and reliable architecture to provide at load in low power generating situations.
KW - Algorithm
KW - Control strategies
KW - Implementation
KW - P-and-o
KW - Perturb
KW - Power point tracking
KW - Systems
UR - http://www.scopus.com/inward/record.url?scp=85191901003&partnerID=8YFLogxK
U2 - 10.1155/2024/5525066
DO - 10.1155/2024/5525066
M3 - Article
AN - SCOPUS:85191901003
SN - 1430-144X
VL - 2024
JO - International Transactions on Electrical Energy Systems
JF - International Transactions on Electrical Energy Systems
M1 - 5525066
ER -