A Genetic–Based Tabu Search Algorithm for Optimal DG Allocation in Distribution Networks

Gandomkar, Majid; Vakilian, Mehdi; Ehsan, M.

doi:10.1080/15325000590964254

Cited by 164 publications

(79 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Experiments on both SVM and WSVM were conducted with Libsvm, which was developed by professor Lin [3]. For each classification problem, we generate a total of 1000 data points and for cross validation purposes, 90% of the data was used for training and the rest 10% was used for testing.…”

Section: Resultsmentioning

confidence: 99%

An Effective and Novel Weighted Support Vector Machine Method for Control Chart Pattern Recognition

Chen¹,

Xia²,

Chen³

2016

Proceedings of the 2016 International Conference on Artificial Intelligence and Engineering Applications

View full text Add to dashboard Cite

Abstract. Control chart pattern recognition is the method to realize quality online monitoring and diagnosis of production process. For the conditions that the number of existing normal mode products is much higher than the abnormal ones during the actual manufacturing process, we proposed a method about WSVM (Weighted Support Vector Machines) for dynamic process of abnormal pattern recognition based on PCA (Principal Component Analysis). We put the proposed method into our experiment, the experimental simulation results show that this method proposed in this paper has a big advantage over the existing SVM (Support Vector Machine) on highly imbalanced classification problem, which suitable for quality monitoring and diagnosis of dynamic production process.

show abstract

Section: Resultsmentioning

confidence: 99%

An Effective and Novel Weighted Support Vector Machine Method for Control Chart Pattern Recognition

Chen¹,

Xia²,

Chen³

2016

Proceedings of the 2016 International Conference on Artificial Intelligence and Engineering Applications

View full text Add to dashboard Cite

show abstract

“…However, meta heusutic algorithms such as GA, PSO, EP, Tabu search (TS), simulated annealing (SA) seems to have shared the same dominance as deterministic methods [3]. This is due to the fact that meta heuristic are derivative free problems unlike the deterministic methods and can be solved without need for convexcity.…”

Section: Introductionmentioning

confidence: 99%

A Review of Particle Swarm Optimization (PSO) Algorithms for Optimal Distributed Generation Placement

Musa¹

2015

IJEPE

View full text Add to dashboard Cite

Abstract:Particle Swarm Optimization (PSO) has became one of the most popular optimization methods in the domain of Swarm Intelligence. Many PSO algorithms have been proposed for distributed generations (DGs) deployed into grids for quality power delivery and reliability to consumers. These can only be achieved by placing the DG units at optimal locations. This made DG planning problem solution to be of two steps namely, finding the optimal placement bus in the distribution system as well as optimal sizing of the DG. This paper reviews some of the PSO and hybrids of PSO Algorithms formulated for DG placement being one of the meta-heuristic optimization methods that fits stochastic optimization problems. The review has shown that PSO Algorithms are very efficient in handling the DG placement and sizing problems.

show abstract

“…In paper [32] a new optimization technique is presented based on the combination of genetic algorithms and tabu search method for the optimal allocation of dispersed generation resources in distribution networks. It investigates the reduction of losses with the optimal placement of the DG on the demand side of the power system.…”

Section: Literature On Tabu Searchmentioning

confidence: 99%

Impact of distributed generation on distribution contingency analysis

Kotamarty

Khushalani

Schulz

2008

Electric Power Systems Research

View full text Add to dashboard Cite

It is expected that increasing amounts of distributed generation (DG) will be connected to the power system in the future. Advances in technology, deregulation in the market to end the monopoly of the vertically integrated power utilities, alternative energy sources that are becoming more cost effective are encouraging the growth of this new technology. Although there are many advantages, there are many issues to be considered for the interconnection of DG's, like the sizing and siting of the DG. Since it is necessary that the voltages be within a specified limit, this problem of the siting and sizing of the DG has taken top priority as they affect the voltages and operations of the distribution power system. This thesis discusses a procedure for evaluating the impact of the site, size of the DG and also a change in the loading conditions of the system before and after the reconfiguration of the system due to the fault. Many feasible combinations of the size and site of a DG on the IEEE 13 and IEEE 37 node distribution feeder are analyzed, which resulted in large number of data from the load flow. The results and trends are presented. DEDICATION

show abstract

A Genetic–Based Tabu Search Algorithm for Optimal DG Allocation in Distribution Networks

Cited by 164 publications

References 10 publications

An Effective and Novel Weighted Support Vector Machine Method for Control Chart Pattern Recognition

An Effective and Novel Weighted Support Vector Machine Method for Control Chart Pattern Recognition

A Review of Particle Swarm Optimization (PSO) Algorithms for Optimal Distributed Generation Placement

Impact of distributed generation on distribution contingency analysis

Contact Info

Product

Resources

About