Multi-objective Taguchi Approach
What is it about?
This paper presents a new multi-objective Taguchi approach for optimal integration of Distributed Generations (DGs) in small and large-scale distribution networks. The Taguchi method is a statistical method and employs Orthogonal Arrays (OAs) to estimate the output response in less number of computations. In every cycle, OA is updated according to mean response of each parameter at its respective levels in previous cycle. A new node priority list is proposed to guide TM to select promising nodes. For multi-objective problems, a trade-off is developed between various objectives using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) that reduces Euclidean distances of various objectives from their best solutions and increases Euclidean distances from their worst solutions. A multi-objective DG integration problem is formulated to demonstrate the applicability of proposed approach and tested on IEEE 33-bus, 118-bus and a practical 201-bus radial distribution systems. The simulation results are compared with existing multi-objective optimization techniques used for optimal DG integration problems in literature and found to be promising.
Why is it important?
Taguchi Method (TM) is an optimization technique which is capable of providing near optimal solution in less number of experiments . It is successfully employed in manufacturing process to save millions of dollar by avoiding the revenue loss due to manufacturing defect in products at early stage of the process. It is proved to be an efficient optimization technique when number of input parameters is small but too large to allow for exhaustive search of every possible input value.
The following have contributed to this page: Prof. Khaleeq Niazi and Dr. Nand Kishor Meena
In partnership with: