Enhancement of AC System Stability using Artificial Neural Network Based HVDC Controls

In this paper, investigation is carried out for the improvement of power system stability by utilizing auxiliary controls for controlling HVDC power flow. The current controller model and the line dynamics are considered in the stability analysis. Transient stability analysis is done on a multi-machine system, where, a neural network controller is developed to improve the stability of the power system and to improve the response time of the controller to the changing conditions in power system. The results show the application of the neural network controller in AC-DC power systems and case studied at different fault locations.DOI:http://dx.doi.org/10.11591/ijece.v3i4.259

From QTL to variety- Harnessing the benefits of QTLs for drought, flood and salt tolerance in mega rice varieties of India through a multi-institutional network.

Rice is a staple cereal of India cultivated in about 43.5 Mha area but with relatively low average productivity. Abiotic factors like drought, flood and salinity affect rice production adversely in more than 50% of this area. Breeding rice varieties with inbuilt tolerance to these stresses offers an economically viable and sustainable option to improve rice productivity. Availability of high quality reference genome sequence of rice, knowledge of exact position of genes/QTLs governing tolerance to abiotic stresses andavailability of DNA markers linked to these traits has opened up opportunities for breeders to transfer the favorable alleles into widely grown rice varieties through marker-assisted back cross breeding (MABB). Alarge multi-institutional project, “From QTL to variety: marker-assisted breeding of abiotic stress tolerant rice varieties with major QTLs for drought, submergence and salt tolerance” was initiated in 2010 with funding support from Department of Biotechnology, Government of India, in collaboration with Interna-tional Rice Research Institute, Philippines. The main focus of this project is to improve rice productivity inthe fragile ecosystems of eastern, northeastern and southern part of the country, which bear the brunt ofone or the other abiotic stresses frequently. Seven consistent QTLs for grain yield under drought, namely,qDTY1.1, qDTY2.1, qDTY2.2, qDTY3.1, qDTY3.2, qDTY9.1and qDTY12.1are being transferred into submergence IR64-Sub1. To address the problem of complete submergence due to flash floods in the major river basins,the Sub1 gene is being transferred into ten highly popular locally adapted rice varieties namely, ADT 39,ADT 46, Bahadur, HUR 105, MTU 1075, Pooja, Pratikshya, Rajendra Mahsuri, Ranjit, and Sarjoo 52. Further,to address the problem of soil salinity, Saltol, a major QTL for salt tolerance is being transferred into sevenpopular locally adapted rice varieties, namely, ADT 45, CR 1009, Gayatri, MTU 1010, PR 114, Pusa 44 andSarjoo 52. Genotypic background selection is being done after BC2F2stage using an in-house designed50K SNP chip on a set of twenty lines for each combination, identified with phenotypic similarity in the field to the recipient parent. Near-isogenic lines with more than 90% similarity to the recipient parentare now in advanced generation field trials. These climate smart varieties are expected to improve rice productivity in the adverse ecologies and contribute to the farmer’s livelihood