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RISS 인기검색어
- 검색키워드
- 저자 : Salomé Ndjakomo Essiane (검색결과 2 건)
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Patrick Juvet Gnetchejo,Salomé Ndjakomo Essiane,Abdouramani Dadjé,Pierre Ele,Daniel Eutyche Mbadjoun Wapet,Steve Perabi Ngoffe,ZhiCong Chen 한국전기전자재료학회 2021 Transactions on Electrical and Electronic Material Vol.22 No.6
The word’s demand for renewable energy has be rinsing incrementally. One of the solutions for the energy crisis is photovoltaic. However, the design and development of better performing photovoltaic cells and modules requires accurate extraction of their intrinsic parameters. Metaheuristic algorithms have been reported to be the best methods for obtaining accurate values of these intrinsic parameters. However, local convergence goes against the recently devised heuristic methods and inhibits them from producing optimal result. This paper proposes a hybrid method that is based on the Newton Raphson method and a self-adaptive algorithm called the Drone Squadron Optimisation. The latter is an artifact technique inspired by the simulation of a drone squadron from a command centre. It is proposed that this hybrid method can help extract the best intrinsic parameters of photovoltaic cell and module. This study also provides insights and clarifi cation on the reported approaches that have been recently proposed to formulate the objective function. Further, this study also computes and compares the ten best recently published heuristics algorithms in the domain of photovoltaic estimation. The study’s results obtain point to the diff erence between the two formulations and the accuracy of the best formulation. The results obtained from the six case studies covered in this study present the combined performance of the Newton Raphson method and Drone Squadron Optimisation to extract the accurate parameters of a photovoltaic module.
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Dynamic Optimization of Switching States of an Hybrid Power Network
Aristide Tolok Nelem,Pierre Ele,Papa Alioune Ndiaye,Salomé Ndjakomo Essiane,Mathieu Jean Pierre Pesdjock 제어·로봇·시스템학회 2021 International Journal of Control, Automation, and Vol.19 No.7
This paper presents the quality improvement of electric power and the optimization of the switching transient states. We have used a hybrid power generating network by combining the AHP (Hierarchical Process Analysis) and SASV (Automated Variable Structured Automation Systems) methods. This combination revisits the interest of the use of decision support methods in the management of the problem of source switching instants in a hybrid network. The results ensure not only optimal control, supervision, but also a considerable reduction in the repetitive switching that exists in such network and which is detrimental to sensitive loads; because it is perceived as power micro-interruptions. All data collected from different sources (photovoltaic field, battery, generator set and public electricity network), the models of this network and interconexion of different buses are presented.
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