Using Improved DDAO Algorithm to Solve Economic Emission Load Dispatch Problem in the Presence of Wind Farms
In power systems planning, economic load dispatch considering the uncertainty of renewable energy sources is one of the most important challenges that researchers have been concerned about. Complex operational constraints, non-convex cost functions of power generation, and some uncertainties make it...
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| Format: | Article |
| Language: | English |
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University of Sistan and Baluchestan
2023-09-01
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| Series: | International Journal of Industrial Electronics, Control and Optimization |
| Subjects: | |
| Online Access: | https://ieco.usb.ac.ir/article_7781_9c7b6857737ef05f88eb39b0ea4225f3.pdf |
| _version_ | 1797670299684044800 |
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| author | Mehdi Shafiee Abbas-Ali Zamani Mehdi Sajadinia |
| author_facet | Mehdi Shafiee Abbas-Ali Zamani Mehdi Sajadinia |
| author_sort | Mehdi Shafiee |
| collection | DOAJ |
| description | In power systems planning, economic load dispatch considering the uncertainty of renewable energy sources is one of the most important challenges that researchers have been concerned about. Complex operational constraints, non-convex cost functions of power generation, and some uncertainties make it difficult to solve this problem through conventional optimization techniques. In this article, an improved dynamic differential annealed optimization (IDDAO) meta-heuristic algorithm, which is an improved version of the dynamic differential annealed optimization (DDAO) algorithm has been introduced. This algorithm has been used to solve the economic emission load dispatch (EELD) problem in power systems that include wind farms, and the performance of the proposed technique was evaluated in the IEEE 40-unit and 6-unit standard test systems. The results obtained from numerical simulations demonstrate the profound accuracy and convergence speed of the proposed IDDAO algorithm compared to conventional optimization algorithms including, PSO, GSA, and DDAO, while independent runs indicate the robustness and stability of the proposed algorithm. |
| first_indexed | 2024-03-11T20:57:42Z |
| format | Article |
| id | doaj.art-637cbeeee3a34e75bb1da3d649d7cf17 |
| institution | Directory Open Access Journal |
| issn | 2645-3517 2645-3568 |
| language | English |
| last_indexed | 2024-03-11T20:57:42Z |
| publishDate | 2023-09-01 |
| publisher | University of Sistan and Baluchestan |
| record_format | Article |
| series | International Journal of Industrial Electronics, Control and Optimization |
| spelling | doaj.art-637cbeeee3a34e75bb1da3d649d7cf172023-09-30T03:40:51ZengUniversity of Sistan and BaluchestanInternational Journal of Industrial Electronics, Control and Optimization2645-35172645-35682023-09-016316116910.22111/ieco.2023.45189.14707781Using Improved DDAO Algorithm to Solve Economic Emission Load Dispatch Problem in the Presence of Wind FarmsMehdi Shafiee0Abbas-Ali Zamani1Mehdi Sajadinia2Department of Electrical Engineering, Technical and Vocational University(TVU), Tehran,Iran.Department of Electrical Engineering, Technical and Vocational University(TVU), Tehran, Iran.Department of Electrical Engineering, Technical and Vocational University(TVU), Tehran, Iran.In power systems planning, economic load dispatch considering the uncertainty of renewable energy sources is one of the most important challenges that researchers have been concerned about. Complex operational constraints, non-convex cost functions of power generation, and some uncertainties make it difficult to solve this problem through conventional optimization techniques. In this article, an improved dynamic differential annealed optimization (IDDAO) meta-heuristic algorithm, which is an improved version of the dynamic differential annealed optimization (DDAO) algorithm has been introduced. This algorithm has been used to solve the economic emission load dispatch (EELD) problem in power systems that include wind farms, and the performance of the proposed technique was evaluated in the IEEE 40-unit and 6-unit standard test systems. The results obtained from numerical simulations demonstrate the profound accuracy and convergence speed of the proposed IDDAO algorithm compared to conventional optimization algorithms including, PSO, GSA, and DDAO, while independent runs indicate the robustness and stability of the proposed algorithm.https://ieco.usb.ac.ir/article_7781_9c7b6857737ef05f88eb39b0ea4225f3.pdfeconomic emission load dispatchwind farmimproved dynamic differential annealed optimization algorithm |
| spellingShingle | Mehdi Shafiee Abbas-Ali Zamani Mehdi Sajadinia Using Improved DDAO Algorithm to Solve Economic Emission Load Dispatch Problem in the Presence of Wind Farms International Journal of Industrial Electronics, Control and Optimization economic emission load dispatch wind farm improved dynamic differential annealed optimization algorithm |
| title | Using Improved DDAO Algorithm to Solve Economic Emission Load Dispatch Problem in the Presence of Wind Farms |
| title_full | Using Improved DDAO Algorithm to Solve Economic Emission Load Dispatch Problem in the Presence of Wind Farms |
| title_fullStr | Using Improved DDAO Algorithm to Solve Economic Emission Load Dispatch Problem in the Presence of Wind Farms |
| title_full_unstemmed | Using Improved DDAO Algorithm to Solve Economic Emission Load Dispatch Problem in the Presence of Wind Farms |
| title_short | Using Improved DDAO Algorithm to Solve Economic Emission Load Dispatch Problem in the Presence of Wind Farms |
| title_sort | using improved ddao algorithm to solve economic emission load dispatch problem in the presence of wind farms |
| topic | economic emission load dispatch wind farm improved dynamic differential annealed optimization algorithm |
| url | https://ieco.usb.ac.ir/article_7781_9c7b6857737ef05f88eb39b0ea4225f3.pdf |
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