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Research on the Methods of Power Plant Load Dispatch

Author: WangYang
Tutor: HanZuo
School: North China Electric Power University
Course: Control Theory and Control Engineering
Keywords: Load distribution Multi-objective optimization Improved Non- dominated Sorting Genetic Algorithm Multi-objective particle swarm optimization
CLC: TM714
Type: Master's thesis
Year: 2011
Downloads: 137
Quote: 0
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Abstract


Power Plant Units optimal load distribution , has important implications for improving plant safety , reliability, and economy . The paper first analyzes the development of a thermal power plant load distribution on the basis of considering the actual operating characteristics of the thermal power plant units , find the main factors that affect the optimal load distribution between the Power Plant Units , coal consumption characteristic curves , establish the mathematical model of the distribution of the various loads . Discussion of standard coal consumption as the main goal of the load distribution in the analysis of the advantages and disadvantages of the various single- objective optimization approach based on highlights traditional single goal to represent a slight increase of the rate law and the dynamic programming method optimization algorithm . Details of the generation of these two methods , the development and the plant load allocation , load distribution scheme designed based on these two methods . The same time , with the development of the electricity market , the load distribution of thermal power plants not only need to meet the economic requirements of the load distribution , but also to meet the load adjustment time requirements , and pollutant emissions in electricity production requirements . The traditional methods only consider the cost of power generation can not meet the higher load distribution requirements , therefore , the use of multi-objective research has important significance on the load distribution of the thermal power plant . Relative to the traditional multi-objective algorithm , multi - target intelligent algorithm based on Pareto optimal solution has obvious advantages . In response to this issue , designed two types of multi- objective evolutionary algorithm to solve the multi-objective load distribution . Are improved Non- dominated Sorting Genetic Algorithm (NSGA-Ⅱ) and of Pareto sets based multi - objective particle swarm optimization algorithm ( PAMOPSO ) . Examples show , this method can be a good solution to multi-objective optimization problem, the same time, the simulation results of this paper, the design of multi-objective evolutionary method and the weighted method compared confirmed a the correctness of NSGA-Ⅱ and PAMOPSO and superior , demonstrated the multi-objective algorithm has the good sense and practical application value .

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CLC: > Industrial Technology > Electrotechnical > Transmission and distribution engineering, power network and power system > Theory and Analysis > Load analysis
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