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All Journal International Journal of Electrical and Computer Engineering TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Indonesian Journal of Electrical Engineering and Informatics (IJEEI)
Thuan Thanh Nguyen
Industrial University of Ho Chi Minh City
Computer Science & IT Electrical & Electronics Engineering

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Application of a new constraint handling method for economic dispatch considering electric market Thanh Long Duong; Ly Huu Pham; Thuan Thanh Nguyen; Thang Trung Nguyen
Bulletin of Electrical Engineering and Informatics Vol 9, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (709.18 KB) | DOI: 10.11591/eei.v9i4.2351

Abstract

In this paper, optimal load dispatch problem under competitive electric market (OLDCEM) is solved by the combination of cuckoo search algorithm (CSA) and a new constraint handling approach, called modified cuckoo search algorithm (MCSA). In addition, we also employ the constraint handling method for salp swarm algorithm (SSA) and particle swarm optimization algorithm (PSO) to form modified SSA (MSSA) and modified PSO (MPSO). The three methods have been tested on 3-unit system and 10-unit system under the consideration of payment model for power reserve allocated, and constraints of system and generators. Result comparisons among MCSA and CSA indicate that the proposed constraint handling method is very useful for metaheuristic algorithms when solving OLDCEM problem. As compared to MSSA, MPSO as well as other previous methods, MCSA is more effective by finding higher total benefit for the two systems with faster manner and lower oscillations. Consequently, MCSA method is a very effective technique for OLDCEM problem in power systems.
Modified sunflower optimization for network reconfiguration and distributed generation placement Thuan Thanh Nguyen; Ngoc Anh Nguyen; Thanh Long Duong; Thanh Quyen Ngo; Thanhquy Bach
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 6: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i6.pp5765-5774

Abstract

This paper proposed modified sunflower optimization (MSFO) for the combination of network reconfiguration and distributed generation placement problem (NR-DGP) to minimize power loss of the electric distribution system (EDS). Sunflower optimization (SFO) is inspired form the ideal of sunflower plant motion to get the sunlight and its reproduction. To enhance the performance of SFO, it is modified to MSFO wherein, the pollination and mortality techniques have been modified by using Levy distribution and mutation of the best solutions. The results are evaluated on two test systems. The efficiency of MSFO is compared with that of the original SFO and other algorithms in literature. The comparisons show that MSFO outperforms to SFO and other methods in obtained optimal solution. Furthermore, MSFO demonstrates the better statistical results than SFO. So, MSFO can be a powerful approach for the NR-DGP problem.
Minimizing electricity cost by optimal location and power of battery energy storage system using wild geese algorithm Thuan Thanh Nguyen; Thang Trung Nguyen; Trung Dung Nguyen
Bulletin of Electrical Engineering and Informatics Vol 12, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i3.4779

Abstract

The mismatch between load demand and supply power may increase when distributed generation based on renewable energy sources is connected to the distribution system (DS). This paper shows the optimal battery energy storage system (BESS) placement problem on the DS to minimize the electricity cost. Diverse electricity prices are considered for normal, off-peak and peak hours in a day. Wild geese algorithm (WGA) is applied to optimize the location and power of the BESS. The problem and the efficiency of WGA is validated on the 18-bus DS four scenarios consisting of the DS without BESS placement, the DS with BESS placement, the DS existing photovoltaic system (PVS) without BESS placement and the DS existing PVS with BESS placement. The numerical results show that optimal BESS placement is an effective solution for minimizing electricity cost on the DS with and without PVS. In addition, the results have also shown that WGA is a potential method for the BESS placement problem.
Optimal placement of distributed generations on distribution network for reducing power loss and improving feeder balance Huu Truong Trinh; Thuan Thanh Nguyen
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 22, No 2: April 2024
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v22i2.25683

Abstract

The suitable placement and power of distributed generation (DG) can bring technical benefits to the distribution network. This paper applies the Coot optimization algorithm to the DG placement problem with the goal of minimizing power loss and feeder balancing load (LBF). The weight method is used to combine the membership objectives. The evaluation results on the network of 70 nodes for different weight values of the objective function show that the optimal power and installation location of DGs significantly reduces power loss and improves LBF index. In this study, eleven cases were considered. As the weight of power loss part ?1 increases from 0 to 1, the power loss gradually decreases, the LBF index gradually increases, the maximum current gradually decreases, and the minimum voltage amplitude gradually improves. Comparing the results of Coot with particle swarm optimization (PSO) shows that the indicators are improved. In the three cases where ?1 is 0, 0.5, and 1, power loss gained by Coot compared to PSO is less than 47.2663 kW, 73.2725 kW, 30.8708 kW, respectively. LBF index of Coot compared to PSO is less than 98.2%, 88.2%, 81.9%, respectively. The maximum, minimum, average, standard deviation, and CPU time of Coot are smaller than those of PSO. So, Coot is one of the promising methods for this problem.
Co-Authors Bach Hoang Dinh Hanh Minh Hoang Hung Duc Nguyen Huu Truong Trinh Ly Huu Pham Ly Huu Pham Ngoc Anh Nguyen Ngoc Au Nguyen Ngoc Thiem Nguyen Phan Nguyen Vinh Phu Trieu Ha Tan Minh Phan Thang Trung Nguyen Thang Trung Nguyen Thang Trung  Nguyen Thanh Long Duong Thanh Quyen Ngo Thanh-Phuc Nguyen Thanhquy Bach Trieu Ton Ngoc Trung Dung Nguyen Van-Duc Phan