TY - JOUR
T1 - Optimal design of a scaled-up PRO system using swarm intelligence approach
AU - Chen, Yingxue
AU - Shi, Zhongke
AU - Xu, Bin
AU - Shaheed, Mohammad Hasan
N1 - Publisher Copyright:
© 2021, Science China Press and Springer-Verlag GmbH Germany, part of Springer Nature.
PY - 2021/12
Y1 - 2021/12
N2 - In this study, the pressure-retarded osmosis (PRO) process is optimized using Harris hawks optimization (HHO)-based maximum power point tracking (MPPT) technology. To make the practical implementation of salinity-gradient-based energy harvesting using PRO feasible, MPPT is envisaged to play a substantial role. Therefore, this study focuses on the development of a novel MPPT controller using swarm intelligence. The HHO algorithm is the latest approach that mimics the unique chasing strategy of Harris hawks in nature. To test the cost effectiveness of the proposed method, two case studies with various operational scenarios are presented. Compared with the performance of selected well-known and recent approaches, such as perturb & observe, incremental mass resistance, and whale optimization algorithm techniques, that of the proposed metaheuristic-based MPPT technique is found to be highly competitive. Results also show that the proposed algorithm can overcome other methods’ limitations, such as low tracking efficiency; low robustness when encountered in various operational conditions, including temperature and salinity; and steady-state oscillations. Furthermore, the proposed MPPT strategy is suitable for use in other fields of renewable energy harvesting.
AB - In this study, the pressure-retarded osmosis (PRO) process is optimized using Harris hawks optimization (HHO)-based maximum power point tracking (MPPT) technology. To make the practical implementation of salinity-gradient-based energy harvesting using PRO feasible, MPPT is envisaged to play a substantial role. Therefore, this study focuses on the development of a novel MPPT controller using swarm intelligence. The HHO algorithm is the latest approach that mimics the unique chasing strategy of Harris hawks in nature. To test the cost effectiveness of the proposed method, two case studies with various operational scenarios are presented. Compared with the performance of selected well-known and recent approaches, such as perturb & observe, incremental mass resistance, and whale optimization algorithm techniques, that of the proposed metaheuristic-based MPPT technique is found to be highly competitive. Results also show that the proposed algorithm can overcome other methods’ limitations, such as low tracking efficiency; low robustness when encountered in various operational conditions, including temperature and salinity; and steady-state oscillations. Furthermore, the proposed MPPT strategy is suitable for use in other fields of renewable energy harvesting.
KW - Harris hawks optimization (HHO)
KW - maximum power point tracking (MPPT)
KW - metaheuristic algorithms
KW - pressure-retarded osmosis (PRO)
KW - swarm intelligence
UR - http://www.scopus.com/inward/record.url?scp=85120909811&partnerID=8YFLogxK
U2 - 10.1007/s11432-020-3110-x
DO - 10.1007/s11432-020-3110-x
M3 - 文章
AN - SCOPUS:85120909811
SN - 1674-733X
VL - 64
JO - Science China Information Sciences
JF - Science China Information Sciences
IS - 12
M1 - 222203
ER -