An improved golden jackal optimization algorithm for combined economic emission dispatch problems Ramamoorthi Ragunathan, Balamurugan Ramadoss International Journal of Advances in Applied Sciences, 2024 In this research paper, a new improved golden jackal optimization (IGJO) algorithm is applied to address the combined economic emission dispatch (CEED) problem, along with various thermal generator constraints such as valve point loading (VPL) effect, generator limits (GL) in power system. The hunting behavior of the golden jackals is mimicked in the golden jackal optimization (GJO) algorithm. The main aim of the CEED problem is to find the best optimal generation scheduling while minimizing both fuel cost and emission besides meeting the different power system constraints. The original GJO algorithm faces challenges when dealing with high-dimensional optimization problems, as it tends to get trapped in local optima. To address this issue the opposition-based learning (OBL) method was adopted in this GJO algorithm to obtain the global optimal solution and ensure enhanced performance in finding the solution for the CEED problems. To assess the competitiveness of the IGJO algorithm, it is used for various CEED test problems available in the literature, and results are contrasted with other recent heuristic optimization algorithms. Simulation results show that the proposed IGJO performs more effectively than the other compared algorithms in terms of solution quality, and robustness.
Golden jackal optimization for economic load dispatch problems with complex constraints Ramamoorthi Ragunathan, Balamurugan Ramadoss Bulletin of Electrical Engineering and Informatics, 2024 This research paper uses the golden jackal optimization (GJO), a novel meta-heuristic algorithm, to address power system economic load dispatch (ELD) problems. The GJO emulates the hunting behavior of golden jackals. GJO algorithm uses the cooperative attacking behavior of golden jackals to tackle complicated optimization problems efficaciously. The objective of ELD problem is to distribute power system load requirement to the different generators with a minimum total fuel cost of generation. ELD problems are highly complex, non-linear, and non-convex optimization problems while considering constraints namely valve point loading effect (VPL) and prohibited operating zones (POZs). The proposed GJO algorithm is applied to solve complex, non-linear, and non-convex ELD problems. Six different test systems having 6, 10, 13, 40, and 140 generators with various constraints are used to validate the usefulness of the suggested GJO method. Simulation outcomes of the test system are compared with various algorithms reported in the algorithms such as particle swarm optimization (PSO), ant colony optimization (ACO), and backtracking search algorithm (BSA). Results show that the proposed GJO algorithm produces minimal fuel cost and has good convergence in solving ELD problems of power system engineering.
A hybrid approach based energy management of hybrid energy systems with efficient economic model Ramamoorthi Ragunathan, P. Rajesh, Francis H Shajin, R. Sakthivel Smart Science, 2024 This paper proposes a hybrid AHO-SNN-based energy management (EM) of hybrid energy systems (HES) with an efficient economic model. The proposed hybrid method is combined with the Archerfish Hunting Optimizer (AHO) and Spiking Neural Network (SNN). Commonly, it is named as AHO-SNN technique. The major aim of the AHO-SNN method is the efficient economical modeling of HES and the study of sizing and EM. The comprehensive approach for describing the ideal size EM system (EMS) combination for HES is presented in this paper. The HESs, like fuel cell (FC), electrolyzer (EL), PV, battery energy system (BES), diesel generator (DSL), and hydrogen tank (HT). To determine the ideal size-EMS combination, this new EMS is employed to re-use the analytical as well as economic sizing. The AHO-SNN technique is implemented in the MATLAB software and is compared to various existing techniques. The AHO-SNN method provides an optimum outcome than the existing Particle Swarm optimization (PSO), Heap based optimizer (HBO), and Wild horse optimizer (WHO) methods. The power comparison of the existing technique HBO achieved power is 30 W, WHO is 20 W, WHO is around 10 W. In the proposed technique, the power generated is 40 W, which is way higher than the existing techniques. After implementing the integrated framework, the size of PV is cut in half, from 140 to 60 kW, which reduces the electrolyzer and the size of the hydrogen tank in also cut in half. In addition to a 35% decrease in diesel generator working hours and a 40% reduction in the leveled energy cost, PV degrades at a rate of 0.5%.
RECENT SCHOLAR PUBLICATIONS
Telemedicine system for healthcare monitoring: heart rate and body temperature vital signs A Vajravelu, S Vijay, R Ramamoorthi, S Ramesh International Journal of Medical Engineering and Informatics 18 (3), 291-302 , 2026 2026.0
Optimal interval based tuning of 3DOF-PID controllers for power system stabilizers and dynamic performance in multi machine power systems R Ramamoorthi, MS Veerraju, MVR Rao, T Himaja Renewable Energy Focus 55, 100727 , 2025 2025.0 Citations: 3
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An improved golden jackal optimization algorithm for combined economic emission dispatch problems BR Ramamoorthi Ragunathan International Journal of Advances in Applied Sciences 13 (2), 249-259 , 2024 2024.0
Golden jackal optimization for economic load dispatch problems with complex constraints R Ragunathan, B Ramadoss Bulletin of Electrical Engineering and Informatics 13 (2), 781-793 , 2024 2024.0 Citations: 13
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SOLVING ECONOMIC EMISSION DISPATCH PROBLEM OF THERMAL GENERATORS USING GREY WOLF ALGORITHM R Ramamoorthi, R Balamurugan International Research Journal of Modernization in Engineering Technology … , 2023 2023.0
Solving Economic Load Dispatch Problem Using Grey Wolf Optimization Algorithm R Ramamoorthi, R Balamurugan International Journal for Research in Applied Science & Engineering … , 2023 2023.0
Power Quality Study in an Educational Institution-A Case Study R Ramamoorthi, S Nirmalkumar 2022.0
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MOST CITED SCHOLAR PUBLICATIONS
Golden jackal optimization for economic load dispatch problems with complex constraints R Ragunathan, B Ramadoss Bulletin of Electrical Engineering and Informatics 13 (2), 781-793 , 2024 2024.0 Citations: 13
Optimal interval based tuning of 3DOF-PID controllers for power system stabilizers and dynamic performance in multi machine power systems R Ramamoorthi, MS Veerraju, MVR Rao, T Himaja Renewable Energy Focus 55, 100727 , 2025 2025.0 Citations: 3
A hybrid approach based energy management of hybrid energy systems with efficient economic model R Ragunathan, P Rajesh, F H Shajin, R Sakthivel Smart Science 12 (4), 535-554 , 2024 2024.0 Citations: 3
Quasi-Oppositional Golden Jackal Optimization algorithm for the Multi Area Economic Load Dispatch Problem with Real Time Constraints in Power Systems R Ragunathan, B Ramadoss Iranian Journal of Science and Technology, Transactions of Electrical … , 2025 2025.0 Citations: 2
Telemedicine system for healthcare monitoring: heart rate and body temperature vital signs A Vajravelu, S Vijay, R Ramamoorthi, S Ramesh International Journal of Medical Engineering and Informatics 18 (3), 291-302 , 2026 2026.0
A novel method to increase the security in 5G networks using deep learning A Rajasekar, R Ramamoorthi, M Ramya, V Arunachalam International Journal of Electronic Security and Digital Forensics 17 (3 … , 2025 2025.0
An improved golden jackal optimization algorithm for combined economic emission dispatch problems BR Ramamoorthi Ragunathan International Journal of Advances in Applied Sciences 13 (2), 249-259 , 2024 2024.0
Implementations of Golden Jackal Algorithm for Solving CCFELD Problems R Ramamoorthi, R Balamurugan Journal of Soft Computing Paradigm 5 (2), 164-180 , 2023 2023.0
SOLVING ECONOMIC EMISSION DISPATCH PROBLEM OF THERMAL GENERATORS USING GREY WOLF ALGORITHM R Ramamoorthi, R Balamurugan International Research Journal of Modernization in Engineering Technology … , 2023 2023.0
Solving Economic Load Dispatch Problem Using Grey Wolf Optimization Algorithm R Ramamoorthi, R Balamurugan International Journal for Research in Applied Science & Engineering … , 2023 2023.0
Power Quality Study in an Educational Institution-A Case Study R Ramamoorthi, S Nirmalkumar 2022.0
ARTIFICIAL NEURAL NETWORK-BASED TRANSIENT STABILITY ASSESSMENT OF WSCC 9 BUS AND NEW ENGLAND 39 BUS SYSTEMS S Nirmalkumar, R Ramamoorthi
