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Study On Evaluation System Of Energy Saving And Emission Reduction Of Coal-fired Generation

Posted on:2013-10-24Degree:MasterType:Thesis
Country:ChinaCandidate:T T HuFull Text:PDF
GTID:2232330395976394Subject:Power engineering
Abstract/Summary:PDF Full Text Request
At present, thermal power generation has taken important place in electricity supply of China. With the development of power industry and the national economy, energy consumption has increased sharply. The traditional power dispatching mode gradually reveals its defecsts, such as low efficiency, being seriously polluted and so on. Energy-saving power dispatching has become the development direction of power dispatching. Under the reliable operation of the generating units, to establish a unified evaluating system as well as to make analysis of energy saving and emission reduction is crucial. Therefore, this paper puts forward to building coal-fired generating evaluation system of energy saving and emission reduction. With the establishment of the model, energy-saving and emission reduction indexes can be calculated, and the units can be sorted.This paper firstly determines the energy saving and emission reduction indexes of coal-fired power plants with rational analysis. Secondly, entropy method is used to make the indexes standardized and normalized, and is used to calculate the entropy weight of each index. Thirdly, this paper is based on MATLAB and uses Particle Swarm Optimization and Immune Particle Swarm Optimization to analyze. Through the operation, the energy saving and emission reduction indexes can be got and the order of the units can be got. Finally, this paper compares the results of the two algorithms and verifies the superiority of the improved algorithm. Through the operation and analysis, Immune Particle Swarm Optimization combines the advantages of Particle Swarm Optimization and Immune Algorithm, and greatly improves the efficiency. It overcomes the "premature" phenomenon in optimizing process and improves the algorithm’s ability to step out of the local extreme point. The algorithm has stronger global searching ability and faster convergence speed.This paper establishes the optimization evaluation model of energy saving and emission reduction of coal-fired power generation and according to which the order of the units can be got. It provides an important theoretical foundation for further study.
Keywords/Search Tags:energy saving and emission reduction, entropy method, PSO, IPSO
PDF Full Text Request
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