Siti Rafidah Abdul Rahim
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Preferred name
Siti Rafidah Abdul Rahim
Official Name
Siti Rafidah, Abdul Rahim
Alternative Name
Abdul Rahim, Siti Rafidah
Rahim, S. R.
Rahim, S.R.A
Abdul Rahim, S.R.
Rahim, S.R. Abd
Main Affiliation
Scopus Author ID
11639107900
Researcher ID
E-5412-2011

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  • Publication
    A hybrid multi-objective Evolutionary Programming-Firefly Algorithm for different type of Distributed Generation in distribution system
    ( 2022-12-01)
    Noor Najwa Husnaini Mohammad Husni
    ;
    Siti Rafidah Abdul Rahim
    ;
    Mohd Rafi Adzman
    ;
    Hussain M.H.
    ;
    Musirin I.
    ;
    Syahrul Ashikin Azmi
    With the rise in electricity demand, various additional sources of generation, known as Distributed Generation (DG), have been introduced to boost the performance of power systems. A hybrid multi-objective Evolutionary Programming-Firefly Algorithm (MOEPFA) technique is presented in this study for solving multi-objective power system problems which are minimizing total active and reactive power losses and improving voltage profile while considering the cost of energy losses. This MOEPFA is developed by embedding Firefly Algorithm (FA) features into the conventional EP method. The analysis in this study considered DG with 4 different scenarios. Scenario 1 is the base case or without DG, scenario 2 is for DG with injected active power, scenario 3 is for DG injected with reactive power only and scenario 4 is for DG injected with both active and reactive power. The IEEE 69-bus test system is applied to validate the suggested technique.
  • Publication
    Multiple DG planning considering distribution loss and penetration level using EMEFA-ANN method
    ( 2017-07-01)
    Siti Rafidah Abdul Rahim
    ;
    Musirin I.
    ;
    Othman M.
    ;
    Muhamad Hatta Hussain
    This paper presents the implementation of multiple distributed generations planning in distribution system using computational intelligence technique. A pre-developed computational intelligence optimization technique named as Embedded Meta EP-Firefly Algorithm (EMEFA) was utilized to determine distribution loss and penetration level for the purpose of distributed generation (DG) installation. In this study, the Artificial Neural Network (ANN) was used in order to solve the complexity of the multiple DG concepts. EMEFA-ANN was developed to optimize the weight of the ANN to minimize the mean squared error. The proposed method was validated on IEEE 69 Bus distribution system with several load variations scenario. The case study was conducted based on the multiple unit of DG in distribution system by considering the DGs are modeled as type I which is capable of injecting real power. Results obtained from the study could be utilized by the utility and energy commission for loss reduction scheme in distribution system.
  • Publication
    Effect of installation of distributed generation at different points in the distribution system on voltage drops and power losses
    ( 2021-05-03)
    Hasibuan A.
    ;
    Muzamir Isa
    ;
    Mohd Irwan Yusoff
    ;
    Siti Rafidah Abdul Rahim
    ;
    Nrartha I.M.A.
    The main purpose of this paper is to analyze the impact of different positions of different DG penetrations on bus voltage profiles and channel power losses. The main classification can be done by putting DG on the most critical bus, the closest bus to the most critical but critical bus too, the closest bus to the feeder but critical too, and the furthest from the feeder but critical too. Installing a distributed generation in a distribution network can significantly affect the power system. The effect depends on DG allocation of the distribution network. Implementation of this approach has been made with the IEEE 34 bus standard at different points. DG placement site selection method based on buses decreased voltage over the limit permitted. Simulation results from a case study on the IEEE 34 bus standard system show that the voltage profile on each bus and the loss of system power will be different when compared to the DG installation at different points.
  • Publication
    Integration of Multiple Distributed Generation Sources in Radial Distribution System Using a Hybrid Evolutionary Programming-Firefly Algorithm
    (Universiti Malaysia Perlis, 2024-02-29)
    Nik Hasmadi Nik Hassan
    ;
    Siti Rafidah Abdul Rahim
    ;
    Muhamad Hatta Hussain
    ;
    Syahrul Ashikin Azmi
    ;
    Azralmukmin Azmi
    ;
    Ismail Musirin
    ;
    Sazwan Ishak
    This paper presents an approach for the optimal integration of multiple distributed generation (DG) sources in a radial distribution system. The integration of DG sources poses various challenges such as can lead to higher power losses caused by reverse power flow, voltage exceeding secure limits, voltage stability, power quality, and economic operation. To address these challenges, a hybrid algorithm is proposed which combines the benefits of both Evolutionary Programming and Firefly Algorithm. The proposed hybrid Evolutionary - Firefly Algorithm is employed for the determination of the optimal size of the DG sources. The objective of the proposed algorithm is to minimize the total system power losses and improve the voltage profile. The algorithm considers various constraints including the DG capacity limits and voltage limits. A comprehensive case study is conducted on a radial distribution system to demonstrate the effectiveness of the proposed approach. The simulation results show that the hybrid algorithm can find the optimal size and location of DG sources while achieving the desired system performance. The integration of multiple DG sources leads to a significant reduction in power losses and improved voltage profile. Furthermore, the proposed approach provides a flexible framework for the optimal integration of DG sources in radial distribution systems, allowing for the accommodation of different types and capacities of DG sources. The proposed technique is tested on the IEEE Reliability Test systems, specifically the IEEE 69-bus. The combination of DG at bus 61 and bus 27 yields a loss reduction index of 94%.
  • Publication
    Grid integration of multiple PV inverters with reduced number of interfacing transformers— A dedicated controller for elimination of DC current injection
    ( 2023-03-01)
    Syahrul Ashikin Azmi
    ;
    Adam G.P.
    ;
    Williams B.W.
    ;
    Rahim N.A.
    ;
    Siti Rafidah Abdul Rahim
    The injection of dc current offset into ac networks may impacted the lifespan of the distribution system equipment including isolation transformers and measurement devices and in serious event may cause equipment's malfunction. This paper intents to eliminate dc current offsets in the output currents using a combinational of proportional-integral (PI) and proportional resonance (PR) controls embedded in one inverter unit. Resultant output currents of this method are sinusoidal and clean from dc offset before entering the point of common coupling. This method gives advantages for transformerless option for group of interfacing inverters in the medium-scale solar farm or in arrangement of inverters restricted in a small locale. Moreover, the use of expensive and high-accuracy measurement sensor nor complex transformer can be omitted, whilst indirectly give positive impact to the operational cost of the farm. The simulation verifications proved the usefulness of the proposed method by introducing varying unknown dc offset levels in the phase currents, and a dedicated dc offset suppressor inverter able to successfully eliminate the dc offset to zero. The validity of the proposed method is demonstrated in simulation using MATLAB/Simulink.
      27  1
  • Publication
    Optimal Integration of Active and Reactive Power DGs in Distribution Network via a Novel Multi-Objective Intelligent Technique
    ( 2024-01-01)
    Azlina Abdullah
    ;
    Ismail Musirin
    ;
    Muhammad Murthada Othman
    ;
    Siti Rafidah Abdul Rahim
    ;
    Sharifah Azwa Shaaya
    ;
    Senthil Kumar A.V.
    This work introduces a novel approach called the Multi-Objective Integrated Immune Moth Flame Evolutionary Programming (MO-IIMFEP) algorithm. This algorithm aims to determine the optimal sizes and positions for Type III distributed generators (DGs) that generate both active and reactive power. The objectives involve reducing overall losses in the distribution system while adhering to voltage restrictions and taking into account the cost limitations connected with the installation of DG. MO-IIMFEP overcomes the constraints of traditional Evolutionary Programming (EP) and Moth Flame Optimization (MFO), particularly in effectively handling local optima. Fuzzy logic is employed in MO-IIMFEP to determine the best solution to compromise conflicting goals, as obtained from the non-dominated Pareto solutions. The efficacy of MOIIMFEP in identifying optimal solutions for multi-objective problems is demonstrated through comprehensive assessments conducted on the 118-Bus Radial Distribution Systems (RDS), comparing it against MO-EP and MO-MFO. The results underscore the strategic benefits of DG installation in sustaining voltage levels, reducing power losses, and minimizing total operating costs for power suppliers.
      9  14
  • Publication
    Optimal sizing of a fixed-tilt ground-mounted grid-connected photovoltaic system with bifacial modules using Harris Hawks Optimization
    ( 2024-08-15)
    Nor Syafiqah Syahirah Mohamed
    ;
    Shahril Irwan Sulaiman
    ;
    Siti Rafidah Abdul Rahim
    ;
    Azralmukmin Azmi
    This paper presents an optimal design for ground-mounted grid-connected bifacial PV power plants using a Computational Intelligence (CI)- based Harris Hawks Optimization (HHO) algorithm. This HHO algorithm identifies the best configuration of components and installation parameters for the bifacial PV power plant, aiming to maximize the final yield, minimize the Levelized Cost of Electricity, and boost the Net Present Value. Four variables were optimized: the bifacial PV module model, inverter model, tilt angle, and module elevation. Furthermore, the paper introduces a Harris Hawks Optimization Sizing Algorithm (HHOSA) to address the sizing challenges. The presented HHOSA was purely developed in Matlab R2017b. The usage of PVsyst was only limited to the derivation of irradiation data at different tilt angle of PV array. These data were later used in HHOSA. To verify its effectiveness, HHOSA was benchmarked against other CI algorithms, including the Slime Mould Algorithm (SMA), Firefly Algorithm (FA), Manta Ray Foraging Optimization (MRFO), and Cuckoo Search Algorithm (COA). The evaluation considered the algorithm's stability, local search capability, convergence rate, computation time, and required population size. Findings suggest that the HHOSA outperforms its peers, marking it as a potential leader for designing bifacial PV power plants. The results indicate that the HHOSA algorithm exhibits superior performance in these aspects, making it a promising approach for optimizing the design of bifacial PV power plants. Moreover, this study provides insights into the economic and technical viability of bifacial PV systems under various environmental and system conditions. A sensitivity analysis, focusing on the interplay of three decision variables − albedo values (25 %, 50 %, and 75 %), tilt angles (10°, 25°, and 35°), and module elevations (0.5 m, 1.5 m, and 2 m) − was conducted. It assessed their influence on final yield, additional bifacial PV module yield, Levelized Cost of Electricity, and the system's Net Present Value. The results emphasize the importance of carefully considering the impacts of albedo, module elevation, and tilt angle on the financial performance of bifacial PV installations.
      1  27
  • Publication
    Comparative Evaluation of Three-Phase Inverter Topologies Based on Voltage Boosting Features
    ( 2023-01-01)
    Yee C.S.
    ;
    Syahrul Ashikin Azmi
    ;
    Hwai L.J.
    ;
    Mohammad Faridun Naim Tajuddin
    ;
    Zahari M.Z.A.
    ;
    Siti Rafidah Abdul Rahim
    Voltage source inverter (VSI) is commonly used in industrial due to its stable operation and low cost. However, VSI needs to operate with an extra converter stage which is a DC-DC converter for voltage boosting purposes. In contrast, current source inverter (CSI) inherits voltage boosting features may become an alternative option to VSI. Yet, there were minimal research on CSI that dedicates to the voltage boosting features. This research focuses on comparing the voltage boosting features of CSI and VSI in both open-loop and closed-loop conditions. The performance of VSI and CSI are simulated using MATLAB/Simulink. Under open-loop operation, CSI produces a voltage boosting capability at approximately 55% higher than VSI. Yet, CSI suffers high THD percentage as compared to VSI for the same switching frequency. This high THD shortcoming can be easily resolved by using a simple CL filter. For closed-loop operation, VSI and CSI with voltage-controlled synchronous frame PI control systems are proven to have good reference tracking and harmonic rejection and are suitable to be implemented for household applications or for a standalone system. Interestingly, CSI closed-loop system can achieve a wider range of output due to the voltage boosting capability and provide a better quality of output waveform as compared to VSI.
      1  23
  • Publication
    A Hybrid Optimization Approach for Power Loss Reduction and Voltage Profile Improvement in Distribution System
    ( 2022-01-01)
    Noor Najwa Husnaini Mohammad Husni
    ;
    Siti Rafidah Abdul Rahim
    ;
    Mohd Rafi Adzman
    In the past decades, the electrical power system is designed and developed to satisfy the owner demand that continuously appears in many variations. Hence, engineers have put their full effort to solve the problem associated with electrical power systems that come and might arise in the future. Therefore, distributed generation (DG) has been introduced to solve multiple electrical power system problems. The proposed methodology presented in this study focuses on minimizing network power losses, improving the voltage profile of system operation, and security constraints in a distribution. It is known that the location and capacity of DG play significant roles in the system losses in a distribution system. A hybrid metaheuristic nature-inspired algorithm is presented in this study for optimal location and sizing of multiple DG units. The best location and optimal sizing of DGs will be determined through Hybrid metaheuristic of Artificial Immune System Firefly Algorithm (AISFA). The designated technique will be tested into IEEE-69 test system using MATLAB software. For reducing the power losses, the simulation results have shown that bus 61 is the best location for reducing power losses and improving voltage profile in IEEE-69 test system in the preliminary result. By installing DG at bus 61, the real power losses improve about 89%, with a voltage profile improvement index up to 1.249099.
      25  2
  • Publication
    Modified firefly algorithm-artificial neural network based technique for the prediction of time-current characteristic in directional overcurrent relay
    ( 2020-01-01)
    Muhamad Hatta Hussain
    ;
    Musirin I.
    ;
    Siti Rafidah Abdul Rahim
    ;
    Abidin A.F.
    This paper presents an integrated optimal predictor optimization technique termed as Modified Firefly Algorithm-Artificial Neural Network (MFA-ANN) for accurate prediction of Relay Operating Time (ROT). Directional Overcurrent Relays (DOCRs) coordination problem is formulated as Mixed Integer Linear Programming (MILP) problem. The developed techniques have been validated on the IEEE 8-bus systems using MATLAB. The simulation results obtained revealed that the proposed MFA-ANN model has shown the reduction in Root Mean Square Error (RMSE) values as compared with Particle Swarm Optimization-Artificial Neural Network (PSO-ANN) which improved the correlation coefficient of the relay operating time. The proposed MFA-ANN model managed to achieve 0% RMSE value.
      2  25