Lilis Widayanti, Arif Nur Afandi, Heru Wahyu Herwanto
The goal of this study is to create a new algorithm based on the Navigation Orca Algorithm (NOA), which was inspired by orca whale hunting strategies and incorporates echolocation processes and Doppler effects to improve the performance of power plant schedule optimization. Scheduling a generator that incorporates economic efficiency and exhaust emission reduction remains a complex task, particularly when optimizing multiple generating units with varying operational constraints. NOA is an extension of the Orca Algorithm (OA) that incorporates echolocation and Doppler effect methods to improve the accuracy of finding optimal solutions to the Integrated Economic Emission Dispatch problem. The NOA algorithm is intended to provide economically efficient and environmentally beneficial power plant scheduling by mimicking orca whale hunting behavior. In this research, a novel NOA algorithm is designed, and its efficacy is evaluated through a series of parameter-setting tests conducted for the first time in the test scenario to identify the optimal configuration that ensures stable and optimal convergence. Then, NOA is applied to solve scheduling problems involving 6 generator units using IEEE 30-bus, and 10 and 19 generator units using IEEE 62-bus data, and its performance is compared with Particle Swarm Optimization, Grey Wolf Optimization, and OA. The results show that NOA optimally addresses the IEED issue and exhibits excellent solution stability in 10-and 19-generator scheduling problems, although it incurs higher computational time than other techniques. NOA has the lowest Best Cost and Mean Total Cost, outperforming PSO, GWO, and OA in efficiency of operational cost and emission dispatch. © 2026, Politeknik Negeri Padang. All rights reserved.
Department of Electrical and Informatics Engineering, Universitas Negeri Malang, East Java, Malang, Indonesia; Department of Computer System, Institut Teknologi dan Bisnis Asia Malang, East Java, Malang, Indonesia
