• CN: 11-2187/TH
  • ISSN: 0577-6686

Journal of Mechanical Engineering ›› 2017, Vol. 53 ›› Issue (10): 145-150.doi: 10.3901/JME.2017.10.145

Previous Articles     Next Articles

Operation Optimization Study on Steam Power System Based on Adjustment Rules and Particle Swarm Optimization Algorithm With Inertia Weight Logarithmic Decrement

DAI Wenzhi1,2, CHEN Yuehan3, YANG Xinle1   

  1. 1. School of Mechanical Engineering, Liaoning Technical University, Fuxin 123000;
    2. School of Geomatics, Liaoning Technical University, Fuxin 123000;
    3. School of Mines, Liaoning Technical University, Fuxin 123000
  • Online:2017-05-15 Published:2017-05-15

Abstract:

The fuel consumption calculation method in multi-period steam power system can be established the relationship model between evaporation and efficiency then calculated with energy balance equation. In order to simplify the calculation, a mathematical model of dual fuel boiler is put forward based on relationship between evaporation and fuel quantity. The adjustment rules of back pressure turbine and back pressure extraction turbine are put forward. If you need to run two more than the same type of turbine at the same time, the maximum load operation and the slope of the mathematical model of the turbine should be a priority. Slope equality then arbitrary allocation load. Steam turbine tuning rule extension to the single fuel boiler load distribution. And fuel quantity and the evaporation capacity of single fuel boiler is a linear relationship. If one-order term coefficient is equal, evaporation arbitrary distribution. Otherwise, the maximum load running small slope of boiler. An improved particle swarm optimization(PSO) with Inertia weigh and logarithmic decrement are put up because of slower convergence rate and premature in PSO. The operation cost could be saved, the validity and practicability of algorithm and the correctness of the optimization rules are verified by using the improved PSO for solving mixed integer nonlinear programming model of steam power system optimal scheduling.

Key words: adjustment rules, boiler, mathematical modeling, particle swarm optimization based on logarithmic decrement, steam power system, turbine, thermoelectric power plant