Volume 22, Issue 2 (June 2026)                   IJEEE 2026, 22(2): 4180-4180 | Back to browse issues page

XML Print

Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Ajoudani M, Mosayyebi S R, Teimouri Yansari R. Active distribution system state estimation based on metaheuristic algorithms in the presence of distributed generations. IJEEE 2026; 22 (2) :4180-4180
URL: http://ijeee.iust.ac.ir/article-1-4180-en.html
Active distribution system state estimation based on metaheuristic algorithms in the presence of distributed generations
Mojtaba Ajoudani , Seyed Reza Mosayyebi , Ramazan Teimouri Yansari
Abstract:   (60 Views)
The increasing penetration of distributed generation (DG) significantly complicates Distribution System State Estimation (DSSE) by introducing stochasticity and uncertainty. This paper proposes a novel DSSE framework that unlike conventional methods simultaneously estimates the system state, load demands, and DGs output power through a unified constrained optimization model. The model is efficiently solved using the Whale Optimization Algorithm (WOA), whose unique balance of exploration and exploitation enables robust solution search in complex, active distribution networks. Simulation studies on standard IEEE 37-bus and 69-bus test systems reveal that the proposed WOA-based approach achieves outstanding accuracy. For the 37-bus system, WOA attains a Maximum Individual Relative Error (MIRE) of 1.15% and a Maximum Individual Absolute Error (MIAE) of 2.303 on load estimation. On the larger 69-bus system, the method further reduces these errors yielding a MIRE of 0.886% and a MIAE of 1.12 for load, and 0.73% and 1.058 for DG power estimation, respectively. Across all experiments, WOA consistently outperforms leading metaheuristics including ABC, PSO, and GA highlighting its superior accuracy, scalability, and robustness for real-world DSSE challenges.
Keywords: State estimation, Active distribution system, Distributed generation, Smart meter, Whale optimization algorithm
Full-Text [PDF 1178 kb]   (39 Downloads)    
Type of Study: Research Paper | Subject: Distribution Systems Automation
Received: 2025/10/19 | Revised: 2026/01/10 | Accepted: 2025/11/30
Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Creative Commons License
© 2022 by the authors. Licensee IUST, Tehran, Iran. This is an open access journal distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license.