Abstract
The analytical solutions of complex dynamic PRO systems pose challenges to ensuring that maximum power can be harvested in stable, rapid, and efficient ways in response to varying operational environments. In this paper, a boosted particle swarm optimization (BPSO) method with enhanced essential coefficients is proposed to enhance the exploration and exploitation stages in the optimization process. Moreover, several state-of-the-art techniques are utilized to evaluate the proposed BPSO of scaled-up PRO systems. The competitive results revealed that the proposed method improves power density by up to 88.9% in comparison with other algorithms, proving its ability to provide superior performance with complex and computationally intensive derivative problems. The analysis and comparison of the popular and recent metaheuristic methods in this study could provide a reference for the targeted selection method for different applications.
Highlights
The hydrological cycle of nature provides significant renewable energy sources (RES)through the salinity gradient
The research of the MPPT control methods is of great significance for improving the performance of the Pressure retarded osmosis (PRO) system under varying operational conditions
Where k is the current iteration and vi and ∆Pi denote the velocity and position of the ith particle, where the position indicates the best-obtained solution in the problem. w is an inertia weight parameter equal to 1, and c1 and c2 are constants equal to 1.5 and 2, respectively. r1 and r2 represent the normalized random values in the interval (0, 1), pbest donates the best position found in the ith iteration, and gbest depicts the best acquired global position
Summary
The hydrological cycle of nature provides significant renewable energy sources (RES). The first MPPT research for PRO systems was conducted in 2015, considering dynamic changes, including incremental mass resistance (IMR) as well as perturbation and observation (P&O) methods [8] Both algorithms have to find a balance between oscillations and the response time, resulting in greater power loss [9]. The research of the MPPT control methods is of great significance for improving the performance of the PRO system under varying operational conditions It can be implemented on the stand-alone PRO system, and on the hybrid PRO system and other RES systems. The proposed method can be applied to other systems, especially renewable energy systems, such as photovoltaic systems, wind turbine systems, and hybrid renewable systems This has, motivated the research and application of metaheuristic-based maximum energy extraction methods in PRO design optimization
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