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All Journal International Journal of Electrical and Computer Engineering Perfecting a Video Game with Game Metrics Bulletin of Electrical Engineering and Informatics
Phu Trieu Ha
Saigon University
Computer Science & IT Electrical & Electronics Engineering

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Improved particle swarm optimization algorithms for economic load dispatch considering electric market Tan Minh Phan; Phu Trieu Ha; Thanh Long Duong; Thang Trung  Nguyen
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (446.44 KB) | DOI: 10.11591/ijece.v10i4.pp3918-3926

Abstract

Economic load dispatch problem under the competitive electric market (ELDCEM) is becoming a hot problem that receives a big interest from researchers. A lot of measures are proposed to deal with the problem. In this paper, three versions of PSO method such as conventional particle swarm optimization (PSO), PSO with inertia weight (IWPSO) and PSO with constriction factor (CFPSO) are applied for handling ELDCEM problem. The core duty of the PSO methods is to determine the most optimal power output of generators to obtain total profit as much as possible for generation companies without violation of constraints. These methods are tested on three and ten-unit systems considering payment model for power delivered and different constraints. Results obtained from the PSO methods are compared with each other to evaluate the effectiveness and robustness. As results, IWPSO method is superior to other methods. Besides, comparing the PSO methods with other reported methods also gives a conclusion that IWPSO method is a very strong tool for solving ELDCEM problem because it can obtain the highest profit, fast converge speed and simulation time.
Modified moth swarm algorithm for optimal economic load dispatch problem Phu Trieu Ha; Hanh Minh Hoang; Thuan Thanh Nguyen; Thang Trung Nguyen
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 4: August 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i4.15032

Abstract

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.
Apply three metaheuristic algorithms for energy storage-based integrated power system to reduce generation cost Dao Trong Tran; Phu Trieu Ha; Hung Duc Nguyen; Thang Trung Nguyen
Bulletin of Electrical Engineering and Informatics Vol 12, No 2: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i2.4544

Abstract

This research applies new computing methods to optimize the operation of a typical hydrothermal system for one day. The system consists of one thermal power plant (TPP) and one pumped storage hydropower plant (PSHP). The main target of the research is to determine the amount of water that must be discharged or pumped back to the reservoir to reduce the total electricity production cost (TEPC) of TTP. The volumes of water storage in the reservoir at the beginning and end points of the schedule must be the same. Three meta-heuristic algorithms are applied, including Coot optimizer (COOT), aquila optimizer (AO), and particle swarm optimizations (PSO) in which COOT and AO were proposed at early 2021. The results show that the effectiveness of COOT is better than AO, PSO and several methods in previous studies. Hence, COOT is considered a powerful computing tool for the problem.
Co-Authors Dao Trong Tran Hanh Minh Hoang Hung Duc Nguyen Tan Minh Phan Thang Trung Nguyen Thang Trung  Nguyen Thanh Long Duong Thuan Thanh Nguyen