Articles
<![CDATA[Determining optimal location and size of capacitors in radial distribution networks using moth swarm algorithm ]]>
<![CDATA[Thanh Long Duong]]>;
<![CDATA[Thuan Thanh Nguyen]]>;
<![CDATA[Van-Duc Phan]]>;
<![CDATA[Thang Trung Nguyen]]>
<![CDATA[ International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 5: October 2020 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
Full PDF (607.031 KB)
|
DOI: 10.11591/ijece.v10i5.pp4514-4521
<![CDATA[In this study, the problem of optimal capacitor location and size determination (OCLSD) in radial distribution networks for reducing losses is unraveled by moth swarm algorithm (MSA). MSA is one of the most powerful meta-heuristic algorithm that is taken from the inspiration of the food source finding behavior of moths. Four study cases of installing different numbers of capacitors in the 15-bus radial distribution test system including two, three, four and five capacitors areemployed to run the applied MSA for an investigation of behavior and assessment of performances. Power loss and the improvement of voltage profile obtained by MSA are compared with those fromother methods. As a result, it can be concluded that MSA can give a good truthful and effective solution method for OCLSD problem.]]>
<![CDATA[Optimal power generation for wind-hydro-thermal system using meta-heuristic algorithms ]]>
<![CDATA[Thuan Thanh Nguyen]]>;
<![CDATA[Van-Duc Phan]]>;
<![CDATA[Bach Hoang Dinh]]>;
<![CDATA[Tan Minh Phan]]>;
<![CDATA[Thang Trung Nguyen]]>
<![CDATA[ International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 5: October 2020 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
Full PDF (1068.584 KB)
|
DOI: 10.11591/ijece.v10i5.pp5123-5130
<![CDATA[In this paper, Cuckoo search algorithm (CSA) is suggested for determining optimal operation parameters of the combined wind turbine and hydrothermal system (CWHTS) in order to minimize total fuel cost of all operating thermal power plants while all constraints of plants and system are exactly satisfied. In addition to CSA, Particle swarm optimization (PSO), PSO with constriction factor and inertia weight factor (FCIWPSO) and Social Ski-Driver (SSD) are also implemented for comparisons. The CWHTS is optimally scheduled over twenty-four one-hour interval and total cost of producing power energy is employed for comparison. Via numerical results and graphical results, it indicates CSA can reach much better results than other ones in terms of lower total cost, higher success rate and faster search process. Consequently, the conclusion is confirmed that CSA is a very efficient method for the problem of determining optimal operation parameters of CWHTS.]]>
<![CDATA[Electric distribution network reconfiguration for power loss reduction based on runner root algorithm ]]>
<![CDATA[Thuan Thanh nguyen]]>
<![CDATA[ International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 5: October 2020 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
Full PDF (796.265 KB)
|
DOI: 10.11591/ijece.v10i5.pp5016-5024
<![CDATA[This paper proposes a method for solving the distribution network reconfiguration (NR) problem based on runner root algorithm (RRA) for reducing active power loss. The RRA is a recent developed metaheuristic algorithm inspired from runners and roots of plants to search water and minerals. RRA is equipped with four tools for searching the optimal solution. In which, the random jumps and the restart of population are used for exploring and the elite selection and random jumps around the current best solution are used for exploiting. The effectiveness of the RRA is evaluated on the 16 and 69-node system. The obtained results are compared with particle swarm optimization and other methods. The numerical results show that the RRA is the potential method for the NR problem.]]>
<![CDATA[Enhanced sunflower optimization for placement distributed generation in distribution system ]]>
<![CDATA[Thuan Thanh Nguyen]]>
<![CDATA[ International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 1: February 2021 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.11591/ijece.v11i1.pp107-113
<![CDATA[Installation of distribution generation (DG) in the distribution system gains many technical benefits. To obtain more benefits, the location and size of DG must be selected with the appropriate values. This paper presents a method for optimizing location and size of DG in the distribution system based on enhanced sunflower optimization (ESFO) to minimize power loss of the system. In which, based on the operational mechanisms of the original sunflower optimization (SFO), a mutation technique is added for updating the best plant. The calculated results on the 33 nodes test system have shown that ESFO has proficiency for determining the best location and size of DG with higher quality than SFO. The compared results with the previous methods have also shown that ESFO outperforms to other methods in term of power loss reduction. As a result, ESFO is a reliable approach for the DG optimization problem.]]>
<![CDATA[Optimizing location and size of capacitors for power loss reduction in radial distribution networks ]]>
<![CDATA[Thuan Thanh Nguyen]]>;
<![CDATA[Phan Nguyen Vinh]]>;
<![CDATA[Hung Duc Nguyen]]>;
<![CDATA[Ly Huu Pham]]>;
<![CDATA[Thang Trung Nguyen]]>
<![CDATA[ TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 1: February 2021 ]]>
Publisher : <![CDATA[Universitas Ahmad Dahlan ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.12928/telkomnika.v19i1.16491
<![CDATA[Power radial distribution systems are increasingly more and more important in transmitting the electric energy from power plants to customers. However, total loss in lines are very high. This issue can be solved by allocating capacitor banks. Determining the suitable allocation and optimal sizing of capacitor banks needs an efficient approach. In this study, the diffusion and update techniques-based algorithm (DUTA) is proposed for such reason. The efficiency of DUTA is inspected on two distribution systems consisting of 15-bus and 33-bus systems with different study cases. The solutions attained by DUTA are competed with recently published methods. As a consequence, the method is more effective than the other methods in terms of the quality of solution.]]>
<![CDATA[Modified moth swarm algorithm for optimal economic load dispatch problem ]]>
<![CDATA[Phu Trieu Ha]]>;
<![CDATA[Hanh Minh Hoang]]>;
<![CDATA[Thuan Thanh Nguyen]]>;
<![CDATA[Thang Trung Nguyen]]>
<![CDATA[ TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 4: August 2020 ]]>
Publisher : <![CDATA[Universitas Ahmad Dahlan ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.12928/telkomnika.v18i4.15032
<![CDATA[In this study, optimal economic load dispatch problem (OELD) is resolved by a novel improved algorithm. The proposed modified moth swarm algorithm (MMSA), is developed by proposing two modifications on the classical moth swarm algorithm (MSA). The first modification applies an effective formula to replace an ineffective formula of the mutation technique. The second modification is to cancel the crossover technique. For proving the efficient improvements of the proposed method, different systems with discontinuous objective functions as well as complicated constraints are used. Experiment results on the investigated cases show that the proposed method can get less cost and achieve stable search ability than MSA. As compared to other previous methods, MMSA can archive equal or better results. From this view, it can give a conclusion that MMSA method can be valued as a useful method for OELD problem.]]>
<![CDATA[Optimal distribution network configuration using improved backtracking search algorithm ]]>
<![CDATA[Thuan Thanh Nguyen]]>
<![CDATA[ TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 1: February 2021 ]]>
Publisher : <![CDATA[Universitas Ahmad Dahlan ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.12928/telkomnika.v19i1.16773
<![CDATA[Optimal network configuration is one of the effective approaches for power loss reduction of the distribution network. This paper shows a network reconfiguration method using improved backtracking search algorithm (IBSA). Wherein, IBSA is improved in the process of generating randomly the initialization population. The network reconfiguration method based on IBSA is used to find the optimal network configuration for the 33-node and 69-node systems. The results are compared to the original backtracking search algorithm (BSA), particle swarm optimization (PSO), firefly algorithm (FA) and previous approaches. From the compared results, IBSA can determine the optimal network configuration with higher success rate than BSA, PSO, FA and lower power loss than other previous approaches. As a result, IBSA is an effective approach for finding the optimal network configuration.]]>
<![CDATA[Optimization of distribution network configuration with multi objective function based on improved cuckoo search algorithm ]]>
<![CDATA[Thuan Thanh Nguyen]]>
<![CDATA[ Bulletin of Electrical Engineering and Informatics Vol 9, No 4: August 2020 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
Full PDF (591.535 KB)
|
DOI: 10.11591/eei.v9i4.1886
<![CDATA[This paper proposes an improved cuckoo search (ICSA) for solving the distribution network reconfiguration (NR) problem with multi-objective function. The membership functions are considered consisting of minimizing of power loss, load balancing among branches and among the feeders, node voltage deviation and switching operation numbers. ICSA is developed from the original CSA with adding the local search mechanism for exploiting around the current best solution. The effectiveness of the ICSA has validated on the 70-node and the 83-node practical systems. The obtained results have been compared to those from runner root algorithm (RRA) and other methods in the literature. The obtained results demonstrate that ICSA has high ability for searching the optimal solution with higher successful rate and better quality of obtained solution as well as smaller iterations compared to RRA and other methods. Therefore, ICSA is a reliable method for the multi-objective NR problems.]]>
<![CDATA[Optimal electric distribution network configuration using adaptive sunflower optimization ]]>
<![CDATA[Thuan Thanh Nguyen]]>;
<![CDATA[Ngoc Thiem Nguyen]]>;
<![CDATA[Trung Dung Nguyen]]>
<![CDATA[ Bulletin of Electrical Engineering and Informatics Vol 10, No 4: August 2021 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.11591/eei.v10i4.2588
<![CDATA[Network reconfiguration (NR) is a powerful approach for power loss reduction in the distribution system. This paper presents a method of network reconfiguration using adaptive sunflower optimization (ASFO) to minimize power loss of the distribution system. ASFO is developed based on the original sunflower optimization (SFO) that is inspired from moving of sunflower to the sun. In ASFO, the mechanisms including pollination, survival and mortality mechanisms have been adjusted compared to the original SFO to fit with the network reconfiguration problem. The numerical results on the 14-node and 33-node systems have shown that ASFO outperforms to SFO for finding the optimal network configuration with greater success rate and better obtained solution quality. The comparison results with other previous approaches also indicate that ASFO has better performance than other methods in term of optimal network configuration. Thus, ASFO is a powerful method for the NR.]]>
<![CDATA[Optimization of location and size of distributed generations for maximizing their capacity and minimizing power loss of distribution system based on cuckoo search algorithm ]]>
<![CDATA[Thuan Thanh Nguyen]]>;
<![CDATA[Trieu Ton Ngoc]]>;
<![CDATA[Thang Trung Nguyen]]>;
<![CDATA[Thanh-Phuc Nguyen]]>;
<![CDATA[Ngoc Au Nguyen]]>
<![CDATA[ Bulletin of Electrical Engineering and Informatics Vol 10, No 4: August 2021 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.11591/eei.v10i4.2278
<![CDATA[Maximizing capacity of distributed generations (DGs) embed into distribution network is a solution to attract investment for DGs installation on the distribution system. This paper introduces a approach of optimizing location and capacity of DGs for maximizing DGs capacity and minimizing the system’s power loss based on cuckoo search algorithm (CSA). The proposed problem and method are simulated on two test systems including the 33-node and 69-node networks. The numerical results have demonstrated that the proposed method not only reduces power losses but also maximizes the power of DGs embed into the distribution network. The results also introduce that the proposed CSA method is better performance that some previous methods in terms of power loss and DGs capacity. The results obtained in many independent runs for two test systems indicate that CSA in one of the reliable methods for the DGs placement problems.]]>
