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Optimal Scheduling Of Hydro-thermal Combined Power System Based On Improved Particlc Swarm Optimization Algorithm

Posted on:2016-08-31Degree:MasterType:Thesis
Country:ChinaCandidate:H B XiaoFull Text:PDF
GTID:2272330470972244Subject:Control engineering
Abstract/Summary:PDF Full Text Request
With the rapid development of new energy power, the effect of large-scale new energy power on the grid will happen because of instability and volatility. In order to reduce the effect of large-scale new energy power on the grid, it is important to improve the quick adjustment ability of power supply. It is necessary to improve the ability of thermal power plant and hydropower plant with the reason of gas power generation and fuel power generation with quick response ability occupying a small proportion in the energy structure of China. Therefore, to achieve the maximum benefit based on process of hydrothermal power dispatching, the following works have been carried out in this thesis.1. On the basis of analyzing the step hydropower system and characteristics of thermal power system, the output characteristics, correlation characteristic and restrict with each other of step hydropower system is studied. The coal consumption of thermal power plant and its pollution on environment is studied which makes a basis on optimal dispatch of hydrothermal power system.2. The problem of hydrothermal power optimal dispatch can be solved as the problem of multi-objective and multi-constraint.Based on the analysis of multi objective optimization and multi objective PSO algorithm, the PSO on the basis of multi-agent algorithm is studied.3. The hydrothermal optimal dispatch model is proposed for multi-objective and multi-constraint on the hydrothermal dispatch. The simulation and verification on the hydrothermal dispatch system including 4 hydropower plants and 3 thermal power plants are conducted with the improved PSO algorithm and optimal dispatch control method at different generation time is achieved.
Keywords/Search Tags:cascade hydropower station, coal-fired power plant, particle swarm optimization algorithm, optimal scheduling
PDF Full Text Request
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