Lists
Lists
Gupta, Rahul, Khanna, Ashish and Virdee, Bal Singh (2024) AOBL‑IPACO: a novel and optimized algorithm to mitigate losses in electrical grid systems. International Journal of Information Technology. pp. 1-9. ISSN 2511-2112
This paper shows the framework for solving the economic optimization problem in electrical grid system using Advanced Oppositional Based Learning (AOBL) technique with Invasive Plant Ant Colony Optimization (IPACO) algorithm. The work focuses on application of newly developed algorithm called Advance Oppositional Invasive Plant Ant Colony Optimization (AOIPACO) to solve the various constraints of single objective problem. The artificial algorithm leads to direction of exploration for new space of ant colonies with process of threats elimination from native candidates in energy management. During simulation process, the proposed algorithm reduces the power loss along with improvement of cost factor and computational time. The proposed AOIPACO approach is implemented on standard IEEE-5, 13 and 40 bus systems and generates optimal results as compared to other conventional techniques while solving the complex problem of optimization. Further, this meta heuristic technique help to improve the quality of power market system with minimum computation error at fast convergence rate.
![[thumbnail of BJIT ROIPACO accepted 10-09-2024.pdf]](https://repository.londonmet.ac.uk/style/images/fileicons/text.png "BJIT ROIPACO accepted 10-09-2024.pdf")
Restricted to Repository staff only until 24 September 2025.
Download (568kB) | Request a copy
 |
View Item |