M H Refan, A Dameshghi, M Kamarzarrin,
Volume 9, Issue 4 (12-2013)
Abstract
Differential base station sometimes is not capable of sending correction information for minutes, due to radio interference or loss of signals. To overcome the degradation caused by the loss of Differential Global Positioning System (DGPS) Pseudo-Range Correction (PRC), predictions of PRC is possible. In this paper, the Support Vector Machine (SVM) and Genetic Algorithms (GAs) will be incorporated for predicting DGPS PRC information. The Genetic Algorithm is employed to feature subset selection. Online training for real-time prediction of the PRC enhances the continuity of service on the differential correction signals and therefore improves the positioning accuracy in Real Time DGPS. Given a set of data received from low cost GPS module, the GASVM can predict the PRC precisely when the PRC signal is lost for a short period of time. This method which is introduced for the first time for prediction of PRC is compared to other recently published methods. The experiments show that the total RMS prediction error of GASVM is less than 0.06m for on step and 0.16m for 10 second ahead cases
A. Boukaroura, L. Slimani, T. Bouktir,
Volume 16, Issue 3 (9-2020)
Abstract
The progression towards smart grids, integrating renewable energy resources, has increased the integration of distributed generators (DGs) into power distribution networks. However, several economic and technical challenges can result from the unsuitable incorporation of DGs in existing distribution networks. Therefore, optimal placement and sizing of DGs are of paramount importance to improve the performance of distribution systems in terms of power loss reduction, voltage profile, and voltage stability enhancement. This paper proposes a methodology based on Dragonfly Optimization Algorithm (DA) for optimal allocation and sizing of DG units in distribution networks to minimize power losses considering variations of load demand profile. Load variations are represented as lower and upper bounds around base levels. Efficiency of the proposed method is demonstrated on IEEE 33-bus and IEEE 69-bus radial distribution test networks. The results show the performance of this method over other existing methods in the literature.
P. Paliwal,
Volume 18, Issue 1 (3-2022)
Abstract
The determination of a suitable technology combination for an isolated micro-grid (IMG) based on hybrid renewable energy resources (HRES) is a challenging task. The intermittent behavior of RES leads to an adverse impact on system reliability and thus complicates the planning process. This paper proposes a two-fold approach to provide a suitably designed HRES-IMG. Firstly, a reliability-constrained formulation based on load index of reliability (LIR) is developed with an objective to achieve a minimum levelized cost of energy (LCOE). Multi-state modeling of HRES-IMG is carried out based on hardware availability of generating units and uncertainties due to meteorological conditions. Modeling of battery storage units is realized using a multi-state probabilistic battery storage model. Secondly, an efficient optimization technique using a decentralized multi-agent-based approach is applied for obtaining high-quality solutions. The butterfly-PSO is embodied in a multi-agent (MA) framework. The enhanced version, MA-BFPSO is used to determine optimum sizing and technology combinations. Three different technology combinations have been investigated. The combination complying with LIR criterion and least LCOE is chosen as the optimal technology mix. The optimization is carried out using classic PSO, BF-PSO, and, MA-BFPSO and obtained results are compared. Further, in order to add a dimension in system planning, the effect of uncertainty in load demand has also been analyzed. The study is conducted for an HRES-IMG situated in Jaisalmer, India. The technology combination comprising of solar, wind, and battery storage yields the least LCOE of 0.2051 $/kWh with a very low value of LIR (0.08%). A reduction in generator size by 53.8% and LCOE by 16.5% is obtained with MABFPSO in comparison with classic PSO. The results evidently demonstrate that MA-BFPSO offers better solutions as compared to PSO and BF-PSO.
Mohamad Almas Prakasa, Mohamad Idam Fuadi, Muhammad Ruswandi Djalal, Imam Robandi, Dimas Fajar Uman Putra,
Volume 20, Issue 3 (9-2024)
Abstract
The unbalanced load distribution in the electrical distribution network caused crucial power losses. This condition occurs in one of the electrical distribution networks, 20 kV Tarahan Substation, Province of Bandar Lampung, Indonesia. This condition can be maintained using optimal reconfiguration with the integration of Distributed Generation (DG) based on Renewable Energy (RE). This study demonstrates the optimal reconfiguration of the 20 kV Tarahan Substation with the integration of the Photovoltaic (PV) and Battery Energy Storage System (BESS). The reconfiguration process is optimized by using the Firefly Algorithm (FA). This process is conducted in the 24-hour simulation with various load profiles. The optimal reconfiguration is investigated in two scenarios based on without and with DG integration. The optimal configuration with more balanced load distribution conducted by FA reduces the power losses by up to 31.39% and 32.38% in without and with DG integration, respectively. Besides that, the DG integration improves the lowest voltage bus in the electrical distribution network from 0.95 p.u to 0.97 p.u.
Trung Kien Do, Thanh Long Duong,
Volume 21, Issue 1 (3-2025)
Abstract
Frequency instability is one of the causes of severe disturbances in the power system, including load shedding and widespread blackouts. Especially in modern power systems, frequency instability has even more serious consequences due to the propagation occurring in interconnected regions. Load frequency control (LFC) is a powerful tool in power system operation to ensure that the frequency is always within the allowable limits. The control parameters of LFC must be optimally adjusted for stable system operation. However, researchers are currently unable to find a suitable and robust method for optimal tuning of LFC control parameters. The paper proposes the Puma Optimizer (PO) algorithm to optimize the parameters of PID, FOPID, and FOPTID+1 controllers for solving the LFC problem. The proposed PO algorithm is evaluated through two models of single-area and two-area power systems with different power sources, including thermal power, hydropower, and gas power. The simulation results show that the integral time absolute error (ITAE) value of the proposed PO method is smaller by 5.25%, 18.16%, 28.35%, and 59.92% compared to Particle Swarm Optimization (PSO), Crested Porcupine Optimization (CPO), Newton-Raphson-based optimization (NRBO), and Global Neighborhood Algorithm (GNA), respectively. The results obtained demonstrate that the PO algorithm is a reliable and efficient tool for finding solutions to the LFC problem.
Sajal Debbarma, Dipu Sarkar,
Volume 21, Issue 1 (3-2025)
Abstract
Transmission line congestion is more severe and persistent in deregulated power systems than it is in traditionally controlled power systems. In a deregulated power market (DPM) scenario, transmission line congestion is one of the most critical problems. To guarantee the electricity system framework runs consistently and securely, the independent system operator (ISO) controls congestion. Congestion management (CM), which takes into account the inherent uncertainties of the restructured power system, is essential to the functioning and security of DPM. This article demonstrates how to control congestion with generation rescheduling. The system is designed in such a way that it helps the traders to compete and trade using the bid prices. Network security is maintained by keeping all constraints within the allowed limits via the Newton-Raphson load flow. An innovative Cheetah Optimizer is employed to handle the congestion management challenge. The weighted sum approach is used instead of multiobjective optimization to simplify the problem as a single-objective optimization, solve the issue for multiple instances of congestion, and be tested in an IEEE 30 bus system. The MATLAB software serves as a tool for modeling the full process, and the results acquired with the Cheetah optimizer give better results than the conventional optimization technique.
Wan Ismail Ibrahim, Nasiruddin Sadan, Noorlina Ramli , Mohd Riduwan Ghazali Riduwan Ghazali , Ilham Fuad,
Volume 21, Issue 2 (6-2025)
Abstract
Hydrokinetic energy harnessing has emerged as a promising renewable energy that utilizes the kinetic energy of moving water to generate electricity. Nevertheless, the variation and fluctuation of water velocity and turbulence flow in a river is a challenging issue, especially in designing a control system that can harness the maximum output power with high efficiency. Besides, the conventional Hill-climbing Search (HCS) MPPT algorithm has weaknesses, such as slow tracking time and producing high steady-state oscillation, which reduces efficiency. In this paper, the Variable-Step Hill Climbing Search (VS-HCS) MPPT algorithm is proposed to solve the limitation of the conventional HCS MPPT. The model of hydrokinetic energy harnessing is developed using MATLAB/Simulink. The system consists of a water turbine, permanent magnet synchronous generator (PMSG), passive rectifier, and DC-DC boost converter. The results show that the power output achieves a 28 % increase over the system without MPPT and exhibits the lowest energy losses with a loss percentage of 0.9 %.
Ying Foo Leong, Nizaruddin M. Nasir, Suliana Ab-Ghani, Norazila Jaalam, Nur Huda Ramlan,
Volume 21, Issue 2 (6-2025)
Abstract
This paper focuses on the application of a cascaded multilevel inverter, specifically the 5-level multilevel inverter, utilizing a proposed controller known as the FLC-PSO-PI controller. The primary challenge addressed in this research is the precise regulation of output voltage in the multilevel inverter during load variations while meeting voltage harmonic and transition requirements as per industry standards, which are the 10 % voltage limit recommended by IEC and 8 % of total harmonic distortion (THD) by IEEE. An innovative solution is proposed by integrating PSO and FLC to dynamically adapt the controller in real-time, ensuring stable and accurate output voltage regulation. The proposed controller is designed and simulated using MATLAB/Simulink, and its performance is compared with PSO-PI and no controller under various load conditions. The results demonstrate that the FLC-PSO-PI controller significantly enhances output voltage regulation were achieving the desired peak voltage and low THD across different load scenarios, including half load to full load (0.8 %) and no load to full load (0.89 %). Furthermore, the FLC-PSO-PI controller exhibits superior transient response characteristics, such as reduced overshooting (2.89 %), faster rise time at 36.946 µs, and satisfactory settling time at 151.014 µs. This research contributes to the advancement of multilevel inverter technology and its potential applications in renewable energy systems, motor drives, and grid-connected devices. The proposed FLC-PSO-PI controller offers a promising solution for precise voltage regulation in multilevel inverters, enhancing their performance and enabling widespread adoption in various industrial sectors.
Murni Nabila Mohd Zawawi, Zainuddin Mat Isa, Baharuddin Ismail, Mohd Hafiz Arshad, Ernie Che Mid, Md Hairul Nizam Talib, Muhammad Fitra Zambak,
Volume 21, Issue 2 (6-2025)
Abstract
This study introduces a pioneering method to enhance the efficiency and effectiveness of three-phase five-level reduced switch cascaded H-bridge multilevel inverters (CHB MLI) by employing the Henry Gas Solubility Optimization (HGSO) algorithm. Targeting the selective harmonic elimination (SHE) technique, the research emphasizes the optimization of switching angles to significantly reduce total harmonic distortion (THD) and align the fundamental output voltage closely with the reference voltage. Central to this exploration are three distinct objective functions (OFs), meticulously designed to assess the HGSO algorithm’s performance across various modulation indices. Simulation results, facilitated by PSIM software, illustrate the impactful role these objective functions play in the optimization process. OF1 demonstrated a superior ability in generating low OF values and maintaining a consistent match between reference and fundamental voltages across the modulation index spectrum. Regarding the reduction of THD, it is crucial to emphasize that all OFs can identify the most effective switching angle to minimize THD and eliminate the fifth harmonic to a level below 0.1%. The findings highlight the potential of HGSO in solving complex optimization challenges within power electronics, offering a novel pathway for advancing modulation strategies in CHB MLIs and contributing to the development of more efficient, reliable, and compact power conversion systems.
