M
Mohan Kashyap
Researcher at Punjab Technical University
Publications - 10
Citations - 82
Mohan Kashyap is an academic researcher from Punjab Technical University. The author has contributed to research in topics: AC power & Automatic Generation Control. The author has an hindex of 4, co-authored 9 publications receiving 56 citations.
Papers
More filters
Book ChapterDOI
Optimal Placement of Distributed Generation Using Genetic Algorithm Approach
TL;DR: An optimization approach using Genetic Algorithm (GA) to find optimal location and size of DG in radial distribution system to minimize the active power loss keeping the voltage profile in distribution system within defined limits is presented.
Journal ArticleDOI
Hybrid approach for congestion management using optimal placement of distributed generator
Mohan Kashyap,Satish Kansal +1 more
TL;DR: The proposed hybrid approach of firefly technique and differential evolution optimisation search is an efficient tool in handling CM resulting in a secure operation to reduce flows in the heavily loaded lines with low system loss and increasing power capability with improved stability of network.
Journal ArticleDOI
Sizing and Allocation of DGs in A Passive Distribution Network Under Various Loading Scenarios
TL;DR: In this paper , an analytical approach to find the optimal location and capacity of different characteristic DGs in a passive distribution network (PDN) is proposed, where real-life scenario of power consumption is considered by using different load scenarios.
Journal ArticleDOI
Optimal installation of multiple type DGs considering constant, ZIP load and load growth
TL;DR: This paper proposes an analytical approach for optimal installation of multiple type DGs in a radial distribution network with consideration of constant, ZIP load model (combination of constant impedance, current, power load models) and load growth.
Congestion Management in Deregulated Power Market – a Review
TL;DR: In this paper, the authors reviewed some congestion management (CM) methods including the nodal pricing method, differential evolution (DE), addition of renewable energy sources, extended quadratic interior point (EQIP) based OPF, mixed integer nonlinear programming, particle swarm optimization (PSO), cost free methods and genetic algorithm (GA).