Enhanced parallel salp swarm algorithm based on Taguchi method for application in the heatless combined cooling‐power system. Issue 6 (28th December 2022)
- Record Type:
- Journal Article
- Title:
- Enhanced parallel salp swarm algorithm based on Taguchi method for application in the heatless combined cooling‐power system. Issue 6 (28th December 2022)
- Main Title:
- Enhanced parallel salp swarm algorithm based on Taguchi method for application in the heatless combined cooling‐power system
- Authors:
- Shan, Jie
Xie, Bo‐Lin
Zhang, Yong‐Jun
Pan, Jeng‐Shyang
Xie, Yu‐Hong
Fu, Yang - Abstract:
- Abstract: Salp swarm algorithm (SSA) is an excellent meta‐heuristic algorithm, which has been widely used in the engineering field. However, there is still room for improvement in terms of convergence rate and solution accuracy. Therefore, this paper proposes an enhanced parallel salp swarm algorithm based on the Taguchi method (PTSSA). The parallel trick is to split the initial population uniformly into several subgroups and then exchange information among the subgroups after a fixed number of iterations, which speeds up the convergence. Communication strategies are an important component of parallelism techniques. The Taguchi method is widely used in the industry for optimizing product and process conditions. In this paper, the Taguchi method is adopted into the parallelization technique as a novel communication strategy, which improves the robustness and accuracy of the solution. The proposed algorithm was also tested under the CEC2013 test suite. Experimental results show that PTSSA is more competitive than some common algorithms. In addition, PTSSA is applied to optimize the operation of a heatless combined cooling‐power system. Simulation results show that the optimized operation provided by PTSSA is more stable and efficient in terms of operating cost reduction. Abstract : In this paper, enhanced parallel salp swarm algorithm is proposed based on Taguchi method (PTSSA). Experimental results show that PTSSA is competitive than other algorithms. The results of theAbstract: Salp swarm algorithm (SSA) is an excellent meta‐heuristic algorithm, which has been widely used in the engineering field. However, there is still room for improvement in terms of convergence rate and solution accuracy. Therefore, this paper proposes an enhanced parallel salp swarm algorithm based on the Taguchi method (PTSSA). The parallel trick is to split the initial population uniformly into several subgroups and then exchange information among the subgroups after a fixed number of iterations, which speeds up the convergence. Communication strategies are an important component of parallelism techniques. The Taguchi method is widely used in the industry for optimizing product and process conditions. In this paper, the Taguchi method is adopted into the parallelization technique as a novel communication strategy, which improves the robustness and accuracy of the solution. The proposed algorithm was also tested under the CEC2013 test suite. Experimental results show that PTSSA is more competitive than some common algorithms. In addition, PTSSA is applied to optimize the operation of a heatless combined cooling‐power system. Simulation results show that the optimized operation provided by PTSSA is more stable and efficient in terms of operating cost reduction. Abstract : In this paper, enhanced parallel salp swarm algorithm is proposed based on Taguchi method (PTSSA). Experimental results show that PTSSA is competitive than other algorithms. The results of the simulation experiments on the heatless combined cooling‐power system show that the optimized operation provided by PTSSA is more stable and efficient in terms of reducing operating costs. … (more)
- Is Part Of:
- IET generation, transmission & distribution. Volume 17:Issue 6(2023)
- Journal:
- IET generation, transmission & distribution
- Issue:
- Volume 17:Issue 6(2023)
- Issue Display:
- Volume 17, Issue 6 (2023)
- Year:
- 2023
- Volume:
- 17
- Issue:
- 6
- Issue Sort Value:
- 2023-0017-0006-0000
- Page Start:
- 1256
- Page End:
- 1271
- Publication Date:
- 2022-12-28
- Subjects:
- artificial bee colony algorithm -- hybrid power systems -- optimal control -- parallel architectures -- particle swarm optimisation -- Taguchi methods
Electric power production -- Periodicals
Electric power transmission -- Periodicals
Electric power distribution -- Periodicals
621.3105 - Journal URLs:
- http://digital-library.theiet.org/content/journals/iet-gtd ↗
http://ieeexplore.ieee.org/servlet/opac?punumber=4082359 ↗
http://www.ietdl.org/IET-GTD ↗
https://ietresearch.onlinelibrary.wiley.com/journal/17518695 ↗
http://www.theiet.org/ ↗ - DOI:
- 10.1049/gtd2.12731 ↗
- Languages:
- English
- ISSNs:
- 1751-8687
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4363.252540
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