Performance analysis and availability optimization to improve maintenance schedule for the turbo-generator subsystem of a thermal power plant using particle swarm optimization

2020 ◽  
Vol 204 ◽  
pp. 107130
Author(s):  
Hanumant P. Jagtap ◽  
Anand K. Bewoor ◽  
Ravinder Kumar ◽  
Mohammad Hossein Ahmadi ◽  
Lingen Chen
Keyword(s):  
Particle Swarm Optimization ◽  
Power Plant ◽  
Performance Analysis ◽  
Thermal Power Plant ◽  
Thermal Power ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Maintenance Schedule ◽  
Turbo Generator

scholarly journals Optimal unit commitment of a power plant using particle swarm optimization approach

2020 ◽  
Vol 10 (2) ◽  
pp. 1135
Author(s):  
Boniface O. Anyaka ◽  
J. Felix Manirakiza ◽  
Kenneth C. Chike ◽  
Prince A. Okoro
Keyword(s):  
Particle Swarm Optimization ◽  
Power Plant ◽  
Unit Commitment ◽  
Thermal Power ◽  
Particle Swarm ◽  
Economic Load Dispatch ◽  
Optimization Approach ◽  
Swarm Optimization ◽  
Total Load ◽  
Generation Cost

Economic load dispatch among generating units is very important for any power plant. In this work, the economic load dispatch was made at Egbin Thermal Power plant supplying a total load of 600MW using six generating units. In carrying out this study, transmission losses were assumed to be included into the load supplied. Also three different combinations in the form of 6, 5 and 4 units commitment were considered. In each case, the total load was optimally dispatched between committed generating units using Particle Swarm Optimization (PSO). Similarly, the generation cost for each generating unit was determined. For case 1, the six generators were committed and the generation cost is 2,100,685.069$/h. For case 2, five generators were committed and the generation cost is 2,520,861.947$/h. For case 3, four generators were committed and the generation cost is 3,150,621.685$/h. From all considered cases, it was found that, the minimum generation cost was achieved when all six generating units were committed and a total of 420,178.878$/h was saved.

scholarly journals Nuclear Power Plant Construction Scheduling Problem with Time Restrictions: A Particle Swarm Optimization Approach

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Shang-Kuan Chen ◽  
Yen-Wu Ti ◽  
Kuo-Yu Tsai
Keyword(s):  
Particle Swarm Optimization ◽  
Power Plant ◽  
Nuclear Power Plant ◽  
Nuclear Power ◽  
Particle Swarm ◽  
Scheduling Problem ◽  
Swarm Optimization ◽  
Construction Scheduling ◽  
Plant Construction ◽  
Reactor Installation

In nuclear power plant construction scheduling, a project is generally defined by its dependent preparation time, the time required for construction, and its reactor installation time. The issues of multiple construction teams and multiple reactor installation teams are considered. In this paper, a hierarchical particle swarm optimization algorithm is proposed to solve the nuclear power plant construction scheduling problem and minimize the occurrence of projects failing to achieve deliverables within applicable due times and deadlines.

The Research and Comparison of some Methods which were Used to Account how to Distribute the Load in the same Plate

2013 ◽  
Vol 401-403 ◽  
pp. 2319-2322
Author(s):  
Xing Liu
Keyword(s):  
Genetic Algorithms ◽  
Power Plant ◽  
Thermal Power Plant ◽  
Load Distribution ◽  
Thermal Power ◽  
Unit Load ◽  
Coal Consumption ◽  
Swarm Optimization ◽  
Incremental Method ◽  
Nonlinear Programming Method

This paper discussed the advantages of genetic algorithm in the load distribution of the thermal power plant, and several other commonly used algorithms: equal incremental method, nonlinear programming method, particle swarm optimization for comparison and analysis. Compared with other methods, the results of use the genetic algorithms to calculate the load distribution between the thermal power plant units were both simple and accurate. So use the genetic algorithms to calculate the load distribution could optimizing the allocation of unit load, reduce coal consumption, improve the efficiency of the unit, responded to the call of the national energy saving.

scholarly journals Binary Particle Swarm Optimization for Scheduling MG Integrated Virtual Power Plant Toward Energy Saving

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 107937-107951 ◽  
Author(s):  
M. A. Hannan ◽  
M. G. M. Abdolrasol ◽  
M. Faisal ◽  
P. J. Ker ◽  
R. A. Begum ◽  
...  
Keyword(s):  
Particle Swarm Optimization ◽  
Power Plant ◽  
Energy Saving ◽  
Particle Swarm ◽  
Binary Particle Swarm Optimization ◽  
Virtual Power ◽  
Swarm Optimization ◽  
Virtual Power Plant
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