An improved TLBO with elite strategy for parameters identification of PEM fuel cell and solar cell models

Clean and renewable energy generation and supply has drawn much attention worldwide in recent years, the proton exchange membrane (PEM) fuel cells and solar cells are among the most popular technologies. Accurately modeling the PEM fuel cells as well as solar cells is critical in their applications, and this involves the identification and optimization of model parameters. This is however challenging due to the highly nonlinear and complex nature of the models. In particular for PEM fuel cells, the model has to be optimized under different operation conditions, thus making the solution space extremely complex. In this paper, an improved and simplified teaching-learning based optimization algorithm (STLBO) is proposed to identify and optimize parameters for these two types of cell models. This is achieved by introducing an elite strategy to improve the quality of population and a local search is employed to further enhance the performance of the global best solution. To improve the diversity of the local search a chaotic map is also introduced. Compared with the basic TLBO, the structure of the proposed algorithm is much simplified and the searching ability is significantly enhanced. The performance of the proposed STLBO is firstly tested and verified on two low dimension decomposable problems and twelve large scale benchmark functions, then on the parameter identification of PEM fuel cell as well as solar cell models. Intensive experimental simulations show that the proposed STLBO exhibits excellent performance in terms of the accuracy and speed, in comparison with those reported in the literature.

Som da Maré: Um Projeto Participativo de Arte Sonora

In May 2014, the participative Project Som da Maré brings together the creative energy of a group of inhabitants from a cluster of favelas in Maré (Rio de Janeiro)* through the sonic arts. The work recalls everyday experiences, memories, stories and places. These memories elicit narratives that leave traces in space while contributing to the workings of local cultural.

The result of four months of workshops and fieldwork forms the basis of two cultural interventions: an exhibition in Museu da Maré** and guided soundwalks in the city of Rio de Janeiro. These interventions present realities, histories and ambitions of everyday life in the Maré favelas through immersive sound installation, documentary photography, text and objects.

Som da Maré brings together various groups of participants who together have developed themes, materials and strategies for the articulation of elements of everyday life in Maré. Participants include secondary level students under the Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ) “Young Talent” scholarships and their families, post-graduate students at the Universidade Federal do Rio de Janeiro (UFRJ), PhD students from the Sonic Arts Research Centre (Queen’s University Belfast) and members of the Cia Marginal, a theatre company based in Maré. The project also counts with the participation of academics from music, ethnomusicology, visual art and architecture at the UFRJ and a partnership with the Museu da Maré. Over thirty people have come together to make this project possible.