Modified Taguchi-Based Approach for Optimal Distributed Generation Mix in Distribution Networks

Nand K. Meena, Anil Swarnkar, Jin Yang, Nikhil Gupta, K. R. Niazi

Research output: Contribution to journalArticle

Abstract

In this paper, a new two-stage optimization framework is proposed to determine the optimal-mix integration of dispatchable Distributed Generation (DG), in power distribution networks, in order to maximize various techno-economic and social benefits simultaneously. The proposed framework incorporates some of the newly introduced regulatory policies to facilitate low carbon networks. A modified Taguchi Method (TM), in combination with a node priority list, is proposed to solve the problem in a minimum number of experiments. Nevertheless, the standard TM is computationally fast but has some inherent tendencies of local trapping and usually converges to suboptimal solutions. Therefore, two modifications are suggested. A roulette wheel selection criterion is applied on priority list to select the most promising DG nodes and then modified TM determines the optimal DG sizes at these nodes. The proposed approach is implemented on two standard test distribution systems of 33 and 118 buses. To validate the suggested improvements, various algorithm performance parameters such as convergence characteristic, best and worst fitness values, and standard deviation are compared with existing variants of TM, and improved genetic algorithm. The comparison shows that the suggested corrections significantly improve the robustness and global searching ability of TM, even compared to meta-heuristic methods.
Original languageEnglish
JournalIEEE Access
Early online date18 Sep 2019
DOIs
Publication statusE-pub ahead of print - 18 Sep 2019

Fingerprint

Taguchi methods
Distributed power generation
Electric power distribution
Heuristic methods
Wheels
Carbon
Genetic algorithms
Economics
Experiments

Bibliographical note

This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/

Cite this

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title = "Modified Taguchi-Based Approach for Optimal Distributed Generation Mix in Distribution Networks",
abstract = "In this paper, a new two-stage optimization framework is proposed to determine the optimal-mix integration of dispatchable Distributed Generation (DG), in power distribution networks, in order to maximize various techno-economic and social benefits simultaneously. The proposed framework incorporates some of the newly introduced regulatory policies to facilitate low carbon networks. A modified Taguchi Method (TM), in combination with a node priority list, is proposed to solve the problem in a minimum number of experiments. Nevertheless, the standard TM is computationally fast but has some inherent tendencies of local trapping and usually converges to suboptimal solutions. Therefore, two modifications are suggested. A roulette wheel selection criterion is applied on priority list to select the most promising DG nodes and then modified TM determines the optimal DG sizes at these nodes. The proposed approach is implemented on two standard test distribution systems of 33 and 118 buses. To validate the suggested improvements, various algorithm performance parameters such as convergence characteristic, best and worst fitness values, and standard deviation are compared with existing variants of TM, and improved genetic algorithm. The comparison shows that the suggested corrections significantly improve the robustness and global searching ability of TM, even compared to meta-heuristic methods.",
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year = "2019",
month = "9",
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Modified Taguchi-Based Approach for Optimal Distributed Generation Mix in Distribution Networks. / Meena, Nand K.; Swarnkar, Anil; Yang, Jin; Gupta, Nikhil; Niazi, K. R.

In: IEEE Access, 18.09.2019.

Research output: Contribution to journalArticle

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AU - Yang, Jin

AU - Gupta, Nikhil

AU - Niazi, K. R.

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