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Journal : International Journal of Electrical and Computer Engineering

Optimal generation for wind-thermal power plant systems with multiple fuel sources Phan Nguyen Vinh; Bach Hoang Dinh; Van-Duc Phan; Hung Duc Nguyen; Thang Trung Nguyen
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 2: April 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i2.pp1022-1028

Abstract

In this paper, the combined wind and thermal power plant systems are operated optimally to reduce the total fossil fuel cost (TFFC) of all thermal power plants and supply enough power energy to loads. The objective of reducing TFFC is implemented by using antlion algorithm (ALA), particle swarm optimization (PSO) and Cuckoo search algorithm (CSA). The best method is then determined based on the obtained TFFC from the three methods as dealing with two study cases. Two systems with eleven units including one wind power plant (WPP) and ten thermal power plants are optimally operated. The two systems have the same characteristic of MFSs but the valve loading effects (VLEs) on thermal power plants are only considered in the second system. The comparisons of TFFC from the two systems indicate that CSA is more powerful than ALA and PSO. Furthermore, CSA is also superior to the two methods in terms of faster search process. Consequently, CSA is a powerful method for the problem of optimal generation for wind-thermal power plant systems with consideration of MFSs from thermal power plants.
Optimal power generation for wind-hydro-thermal system using meta-heuristic algorithms Thuan Thanh Nguyen; Van-Duc Phan; Bach Hoang Dinh; Tan Minh Phan; Thang Trung Nguyen
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 5: October 2020
Publisher : 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

Abstract

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.
A robust diagnosis method for speed sensor fault based on stator currents in the RFOC induction motor drive Cuong Dinh Tran; Pavel Brandstetter; Minh Chau Huu Nguyen; Sang Dang Ho; Bach Hoang Dinh; Phuong Nhat Pham
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (777.425 KB) | DOI: 10.11591/ijece.v10i3.pp3035-3046

Abstract

A valid diagnosis method for the speed sensor failure (SSF) is an essential requirement to ensure the reliability of Fault-Tolerant Control (FTC) models in induction motor drive (IMD) systems. Most recent researches have focused on directly comparing the measured and estimated rotor speed signal to detect the speed sensor fault. However, using that such estimated value in both the fault diagnosis and the controller reconfiguration phases leads to the insufficient performance of FTC modes. In this paper, a novel diagnosis-technique based on the stator current model combined with a confusion prevention condition is proposed to detect the failure states of the speed sensor in the IMD systems. It helps the FTC mode to separate between the diagnosis and reconfiguration phases against a speed sensor fault. This proposed SSF diagnosis method can also effectively apply for IMs’ applications at the low-speed range where the speed sensor signal often suffers from noise. MATLAB/Simulink software has been used to implement the simulations in various speed ranges. The achieved results have demonstrated the capability and effectiveness of the proposed SSF method against speed sensor faults.
Minimize electricity generation cost for large scale wind- thermal systems considering prohibited operating zone and power reserve constraints Phan Nguyen Vinh; Bach Hoang Dinh; Van-Duc Phan; Hung Duc Nguyen; Thang Trung Nguyen
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i3.pp1905-1911

Abstract

Wind power plants (WPs) play a very important role in the power systems because thermal power plants (TPs) suffers from shortcomings of expensive cost and limited fossil fuels. As compared to other renewable energies, WPs are more effective because it can produce electricity all a day from the morning to the evening. Consequently, this paper integrates the optimal power generation of TPs and WPs to absolutely exploit the energy from WPs and reduce the total electricity generation cost of TPs. The target can be reached by employing a proposed method, called one evaluation-based cuckoo search algorithm (OEB-CSA), which is developed from cuckoo search algorithm (CSA). In addition, conventional particle swarm optimization (PSO) is also implemented for comparison. Two test systems with thirty TPs considering prohibited working zone and power reserve constraints are employed. The first system has one wind power plant (WP) while the second one has two WPs. The result comparisons indicate that OEB-CSA can be the best method for the combined systems with WPs and TPs.