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International Journal of Artificial Intelligence and Robotics (IJAIR)
Published by Universitas Dr. Soetomo Surabaya
ISSN : -     EISSN : 26866269     DOI : 10.25139
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering
International Journal of Artificial Intelligence & Robotics (IJAIR) is One of the journals published by Informatics Department, Universitas Dr Soetomo, was established in November 2019. IJAIR a double-blind peer-reviewed journal, the aim of this journal is to publish high-quality articles dedicated to the field of information and communication technology, Published 2 times a year in November and May. Focus and Scope: Machine Learning & Soft Computing, Data Mining & Big Data, Computer Vision & Pattern Recognition dan Robotics.
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 1 Documents
 1 
Search results for , issue "Vol. 7 No. 2 (2025): November 2025" : 1 Documents clear
Optimization of Unit Commitment Problems Integrated PV Generation Plants Based on Particle Swarm Optimization Algorithm Hendrayant, Arya; Wirateruna, Efendi S; Melfazen, Oktriza; Utomo, Wahyu Mulyo
International Journal of Artificial Intelligence & Robotics (IJAIR) Vol. 7 No. 2 (2025): November 2025
Publisher : Informatics Department-Universitas Dr. Soetomo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25139/ijair.v7i2.10510

Abstract

The increasing integration of renewable energy sources, particularly photovoltaic (PV) systems, poses significant challenges in the Unit Commitment (UC) problem due to their intermittent and inertial nature. This condition can cause frequency instability during system disturbances, necessitating the development of new strategies to maintain reliable power system operation. This study proposes an enhanced UC optimization framework by integrating conventional thermal generating units, PV plants, and energy storage systems (ESS) that act as virtual inertia providers. To solve the optimization problem while considering various technical constraints—such as ramping limits, minimum on/off times, rotating reserve requirements, and nadir frequency thresholds—a modified Particle Swarm Optimization (PSO) algorithm is employed. The model is tested on a generating system consisting of nine thermal units, one PV plant, and one ESS. Simulation results show that the proposed method is capable of maintaining the system frequency above the nadir threshold of 49.5 Hz during disturbances while minimizing the total operating cost. Specifically, the optimal configurations without nadir constraints and with ESS integration achieve convergence in only four iterations with a computational time of 1.9 seconds. These findings demonstrate the effectiveness of integrating ESS as virtual inertia and the efficiency of a modified PSO algorithm in handling UC in systems with high renewable energy penetration. This framework offers a promising approach to improving cost efficiency and frequency stability in future renewable energy-based power systems.

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