Faculty Publications
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Item Distributed load flow analysis using graph theory(2011) Sharma, D.P.; Chaturvedi, A.; Purohit, G.; Shivarudraswamy, R.In today scenario, to meet enhanced demand imposed by domestic, commercial and industrial consumers, various operational & control activities of Radial Distribution Network (RDN) requires a focused attention. Irrespective of sub-domains research aspects of RDN like network reconfiguration, reactive power compensation and economic load scheduling etc, network performance parameters are usually estimated by an iterative process and is commonly known as load (power) flow algorithm. In this paper, a simple mechanism is presented to implement the load flow analysis (LFA) algorithm. The reported algorithm utilizes graph theory principles and is tested on a 69- bus RDN.Item Distributed load flow analysis using graph theory(2011) Sharma, D.P.; Chaturvedi, A.; Purohit, G.; Shivarudraswamy, R.In today scenario, to meet enhanced demand imposed by domestic, commercial and industrial consumers, various operational & control activities of Radial Distribution Network (RDN) requires a focused attention. Irrespective of sub-domains research aspects of RDN like network reconfiguration, reactive power compensation and economic load scheduling etc, network performance parameters are usually estimated by an iterative process and is commonly known as load (power) flow algorithm. In this paper, a simple mechanism is presented to implement the load flow analysis (LFA) algorithm. The reported algorithm utilizes graph theory principles and is tested on a 69- bus RDN.Item Faster load flow algorithm for radial distribution network using graph theory(John Wiley and Sons Ltd vgorayska@wiley.com Southern Gate Chichester, West Sussex PO19 8SQ, 2019) Sharma, D.P.; Chaturvedi, A.; Saxena, R.; Raguru, J.Since last 3 decades, load flow solutions have enjoyed success on different fronts. Primarily, the importance and utility of these algorithms is assessed using performance measures, which usually include issue like implementation complicacy, optimized execution time, and memory storage. In this work, a graph-theoretical approach is used to facilitate load flow solutions for a static network topology. Algorithm is tested for 2 different radial distribution topologies, and its deployment for both of these network finally results in phenomenal saving on 2 important algorithm performance measures, ie, time and space complexity. Obtained phenomenal saving for both of these 2 parameters is compared with earlier reported work on statistical basis. © 2018 John Wiley & Sons, Ltd.