S
Sandip Chanda
Researcher at Narula Institute of Technology
Publications - 23
Citations - 108
Sandip Chanda is an academic researcher from Narula Institute of Technology. The author has contributed to research in topics: Electric power system & Smart grid. The author has an hindex of 5, co-authored 22 publications receiving 93 citations. Previous affiliations of Sandip Chanda include Techno India & Budge Budge Institute of Technology.
Papers
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Journal ArticleDOI
Congestion Relief of Contingent Power Network with Evolutionary Optimization Algorithm
Sandip Chanda,Abhinandan De +1 more
TL;DR: The algorithm proposed can be adopted for selecting the congested lines in a power networks and then to search for a congestion constrained optimal generation schedule at the cost of a minimum ‘congestion management charge’ without any load curtailment and installation of FACTS devices.
Journal ArticleDOI
A multi-objective solution algorithm for optimum utilization of Smart Grid infrastructure towards social welfare
Sandip Chanda,Abhinandan De +1 more
TL;DR: An optimization model to maximize social welfare by standardizing the operating conditions with an overall improvement of dynamic stability of power markets endowed with Smart Grid communication technology is proposed.
Journal ArticleDOI
Demand response governed swarm intelligent grid scheduling framework for social welfare
TL;DR: An on-going effort to develop Demand Response governed swarm intelligence based stochastic peak load modeling methodology capable of restoring the market equilibrium during price and demand oscillations of the real-time smart power networks is presented.
Proceedings ArticleDOI
Application of particle swarm optimisation for relieving congestion in deregulated power system
Sandip Chanda,Abhinandan De +1 more
TL;DR: A Swarm intelligence based Optimization technique to manage congestion in power system networks with transmission line overload using a standard congestion sensitivity Index to identify the congested lines and optimizes ‘congestion management charge’ without any load curtailment and installation of FACTS devices is presented.
Proceedings ArticleDOI
Alleviation of line congestion using Multiobjective Particle Swarm Optimization
TL;DR: It has been demonstrated that the proposed method can reduce congestion even below the minimum level obtained from the conventional cost optimization results, and it has been depicted that the methodology on application can provide better operating conditions in respect of improvement of bus voltage profile.