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Optimized Design of Mini-grid System for Hilly Region.

Authors :
Kumar, Jaynendra
Agarwal, Anshul
Agarwal, Vineeta
Source :
IETE Journal of Research; Jan/Feb2022, Vol. 68 Issue 1, p678-689, 12p
Publication Year :
2022

Abstract

In the hilly regions of India, hydro power potential is available, but it is not completely utilized for power generation till date due to the unavailability of proper electrical structure. Nine micro/mini hydro power plants have been developed in the bageswar district in Uttarakhand. The development of the optimized Mini-grid structure is an effective and reliable solution for the full utilization of these MHPs potentials. Although Ajit Singh et al. proposed some Mini-grid structures for this area, their work is not appropriate due to their calculation method of reliability. For the determination of reliability (failure and repair time), they have considered only the line length. However, its demographic situations such as elevation level of MHPs, availability of roads, the presence of obstacles like streams will also affect the failure and repair time. This paper proposes an optimized Mini-grid structure for interconnection of these nine MHPs and load substations. All the MHPs are spreads in two blocks, namely Kapkote and Bagheswar, so two substations (load canters) are considered. These MHPs and substations are mapped through the Google Earth software and the optimization data such as distances between MHPs and substations, their elevation levels, the highest and lowest elevation in the connecting path and the path profile are collected through it. The Mini-grid structure is optimized through the Genetic Algorithm using the MATLAB tool. The optimization is performed by making the cost function as an objective function considering the line lengths and reliability of the path for its parameters. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
03772063
Volume :
68
Issue :
1
Database :
Complementary Index
Journal :
IETE Journal of Research
Publication Type :
Academic Journal
Accession number :
156785108
Full Text :
https://doi.org/10.1080/03772063.2019.1620642