Author
Satish Kansal
Bio: Satish Kansal is an academic researcher from Indian Institute of Technology Roorkee. The author has contributed to research in topics: AC power & Distributed generation. The author has an hindex of 8, co-authored 12 publications receiving 618 citations.
Papers
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TL;DR: The particle swarm optimization (PSO) technique has been used to solve the optimal placement of DGs and the optimal power factor for DG supplying, both real and reactive power, has been obtained.
322 citations
TL;DR: In this paper, a hybrid approach has been proposed for optimal placement of multiple DGs of multiple types in power distribution network for reduction of power loss, where the sizes of DGs are evaluated at each bus by analytical method while the locations are determined by PSO based technique.
214 citations
TL;DR: In this article, the particle swarm optimization (PSO) technique was used to find the optimal size and optimum location for the placement of DG in the radial distribution networks for active power compensation by reduction in real power losses and enhancement in voltage profile.
Abstract: This paper proposes the application of Particle Swarm Optimization (PSO) technique to find the optimal size and optimum location for the placement of DG in the radial distribution networks for active power compensation by reduction in real power losses and enhancement in voltage profile. In the first segment, the optimal size of DG is calculated at each bus using the exact loss formula and in the second segment the optimal location of DG is found by using the loss sensitivity factor. The analytical expression is based on exact loss formula. The optimal size of DG is calculated at each bus using the exact loss formula and the optimal location of DG is found by using the loss sensitivity factor. The proposed technique is tested on standard 33-bus test system and the obtained results are compared with the exhaustive load flows.
68 citations
TL;DR: In this article, an optimisation method to determine optimal allocations of distributed generation (DGs) and capacitors based on maximisation of a profit/worth analysis approach is presented.
Abstract: This paper presents an optimisation method to determine optimal allocations of distributed generation (DGs) and capacitors based on maximisation of a profit/worth analysis approach. The optimal loc...
41 citations
01 Jan 2011
TL;DR: In this article, the Particle Swarm Optimization (PSO) technique was used to find the optimal placement of wind turbine DG in the primary distribution system to reduce the real power losses and improvement in voltage profile.
Abstract: Proper allocation of wind turbine DG unit is essential, as inappropriate allocation of the DG unit may adverse the system performance. The wind turbine DG supplies real power and in turn absorbs the reactive power. This paper proposes the application of Particle Swarm Optimization (PSO) technique to find the optimal placement of wind turbine DG in the primary distribution system to reduce the real power losses and improvement in voltage profile. The results are verified with analytical approach which uses analytical expressions of wind turbine characteristics for proper deployment of the DG unit and the effects on system performance are investigated. In the first segment, the optimal size of wind-based DG is calculated at each bus using the exact loss formula and in the second segment the optimal location of DG is found by using the least loss method. The proposed technique is tested on standard 33-bus and 69-bus test systems. (6 pages)
38 citations
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TL;DR: In this article, the authors present a review of recent optimization methods applied to solve the problem of placement and sizing of distributed generation units from renewable energy sources based on a classification of the most recent and highly cited papers.
345 citations
TL;DR: In this article, a comprehensive review and critical discussion of state-of-the-art analytical techniques for optimal planning of renewable distributed generation is conducted, and a comparative analysis of analytical techniques is presented to show their suitability for distributed generation planning in terms of various optimization criteria.
327 citations
TL;DR: The particle swarm optimization (PSO) technique has been used to solve the optimal placement of DGs and the optimal power factor for DG supplying, both real and reactive power, has been obtained.
322 citations
TL;DR: Fireworks Algorithm is used to simultaneously reconfigure and allocate optimal DG units in a distribution network using a new swarm intelligence based optimization algorithm conceptualized using the fireworks explosion process of searching for a best location of sparks.
281 citations
TL;DR: In this paper, a review of the classical and heuristic approaches for optimal sizing and placement of DG units in distribution networks and study their impacts on utilities and customers is presented, and an attempt has also been made to compare the analytical (classical) and meta-heuristic techniques for optimal size and siting of DG in distribution network.
Abstract: To extract the maximum potential advantages in light of environmental, economical and technical aspects, the optimum installation and sizing of Distributed Generation (DG) in distribution network has always been challenging for utilities as well as customers. The installation of DG would be of maximum benefit where setting up of central power generating units are not practical, or in remote and small areas where the installation of transmission lines or availability of unused land is out of question. The objective of optimal installation of DG in distribution system is to achieve proper operation of distribution networks with minimization of the system losses, improvement of the voltage profile, enhanced system reliability, stability and loadability etc. In this respect analytical (classical) methods, although well-matched for small systems, perform adversely for large and complex objective functions. Unlike the analytical (classical) methods, the intelligent techniques for optimal sizing and siting of DGs are speedy, possess good convergence characteristics, and are well suited for large and complex systems. However, to find a global optimal solution of complex multi-objective problems, a hybrid of two or more meta-heuristic optimization techniques give more effective and reliable solution. This paper presents the fundamentals of DG and DG technologies review the classical and heuristic approaches for optimal sizing and placement of DG units in distribution networks and study their impacts on utilities and customers. An attempt has also been made to compare the analytical (classical) and meta-heuristic techniques for optimal sizing and siting of DG in distribution networks. The present study can contribute meaningful knowledge and assist as a reference for investigators and utility engineers on issues to be considered for optimal sizing and siting of DG units in distribution systems.
266 citations