Simulation on Improved Genetic Algorithm of the Ship's Superheated Steam Pressure

2014 ◽  
Vol 709 ◽  
pp. 335-338
Author(s):  
Peng Wang ◽  
Shuai Zeng ◽  
Ri Hui Dai ◽  
Hao Meng ◽  
Guo Lei Zhang
Keyword(s):  
Genetic Algorithm ◽  
Power Plant ◽  
Superheated Steam ◽  
Pressure Control ◽  
Steam Pressure ◽  
Improved Genetic Algorithm ◽  
Steam Power ◽  
Adjustment Time ◽  
Simulation Results ◽  
Main Steam

The traditional genetic algorithm was improved, and the marine steam power plant main steam pressure control was as an object, the improved genetic algorithm controller and the traditional genetic algorithm controller is studied by the simulation. The simulation results show that the improved genetic algorithm controller system can effectively reduce the overshoot and adjustment time of main steam pressure.

Study on Fuzzy Immune PID Controller for Main Steam Pressure Control System in Marine Steam Power Plant

2014 ◽  
Vol 686 ◽  
pp. 89-94
Author(s):  
Peng Wang ◽  
Meng Hao ◽  
Qing Zhou Ji
Keyword(s):  
Control System ◽  
Power Plant ◽  
Pid Controller ◽  
Fuzzy Controller ◽  
Pressure Control ◽  
Steam Pressure ◽  
Steam Power ◽  
Steam Power Plant ◽  
Pressure Control System ◽  
Main Steam

The main steam pressure control system in marine steam power plant has the characteristics of time-varying, nonlinear and strong coupling. In order to get satisfactory control effect, we propose a fuzzy immune PID controller with which we can make comprehensive utilization of advantages of artificial immune, PID and fuzzy controller. We build up mathematical model of main steam pressure control system, carry out simulation and comparison. The results prove that fuzzy immune PID controller can significantly reduce the overshoot and settling time of main steam pressure. It is more effective in main steam pressure control system than PID controller.

Study on the CFBB Main Steam Pressure Control System Based on ADRC Technology

2013 ◽  
Vol 291-294 ◽  
pp. 2470-2473 ◽  
Author(s):  
Jia Liang Zheng ◽  
Li Xiang Zhang ◽  
Pei Hua Zhang
Keyword(s):  
Control System ◽  
Pid Control ◽  
Combustion Process ◽  
Pressure Control ◽  
Steam Pressure ◽  
Operating Conditions ◽  
Excellent Performance ◽  
Adjustment Time ◽  
Pressure Control System ◽  
Main Steam

The combustion process of CFBB is a system with time-varying, nonlinear, large inertia and time delay. Therefore the control effects of traditional PID control system in the CFBB plant are not satisfactory , especially the overshoot of the main steam pressure control system is very big, and the adjustment time is too long. To improve the performance of the main steam pressure control system, ADRC technology was used . The disturbed signal was added in the different operating conditions, the testing results indicated that the ADRC main steam pressure control system had more excellent performance than the convention PID method.

A Study of Fixed Steam Pressure Control of Ultra-Supercritical Unit

2013 ◽  
Vol 291-294 ◽  
pp. 2178-2181
Author(s):  
Shi He Chen ◽  
Xi Zhang ◽  
Guo Liang Wang ◽  
Wei Wu Yan ◽  
Heng Feng Tian ◽  
...  
Keyword(s):  
Predictive Control ◽  
Tracking Control ◽  
Pressure Control ◽  
Steam Pressure ◽  
Steam Temperature ◽  
Load Demand ◽  
Valve Opening ◽  
Simulation Results ◽  
Coal Flow ◽  
Main Steam

Ultra-supercritical (USC) unit is more and more popular these years for its advantages. In this paper, a model predictive control (MPC) method is introduced for coordinated control of USC unit running in fixed pressure mode. Three inputs (i.e. valve opening, coal flow and feedwater flow) are employed to control three outputs (i.e. load, main steam temperature and main steam pressure). Piecewise models of the USC unit are obtained using the three inputs and the three outputs. In simulation, the output power follows load demand quickly and main steam temperature can be controlled around the setpoint closely in load tracking control. The simulation results show the effeteness of the proposed methods.

scholarly journals Simulation of 25 Mwe Steam Power Plants Using Gate Cycle

2019 ◽  
Vol 8 (6) ◽  
pp. 2326-2630
Keyword(s):  
Power Plant ◽  
Thermal Efficiency ◽  
Input Data ◽  
Power Plants ◽  
Electrical Power ◽  
Steam Pressure ◽  
Steam Temperature ◽  
Steam Power ◽  
Main Input ◽  
Main Steam

Power plants using steam are a very popular system today. To develop a construction of power plant system requires an accurate analysis in determining operating parameters as expected. Designing with manual calculations certainly requires a very long time. One of faster method use a thermodynamic simulation system such as a Gate Cycle. The goal of this research was to simulate a steam power plant to produce 25 MW net electric power and to investigate the effect of an increasing of main steam temperature, main steam pressure and condenser pressure on electrical power and thermal efficiency. The simulation was done using the main input data of simulation were tempe rature of 535 0C, pressure of 89 bar, condenser pressure of 0.084 bar and heating value of low rank coal of 3800 kcal/kg. The main steam temperature was varied of 515; 535; 555 and 575 0C. The main steam pressure was varied of 79; 89; 99 and 120 bar, The condenser pressure was varied at 0.064; 0.074; 0.084 and 0.094 bar. The simulation results showed the net electric power produced of 25.8 MW on the main input data. An increasing of the main steam temperature and the main steam pressure would increase the net electrical power and the thermal efficiency but an increasing of condenser pressure would decrease the net electrical power and the thermal efficiency

Simulation on Improved Genetic Algorithm of the Ship's Superheated Steam Pressure

2014 ◽  
Vol 709 ◽  
pp. 323-326
Author(s):  
Peng Wang ◽  
Shuai Zeng ◽  
Ri Hui Dai ◽  
Hao Meng ◽  
Guo Lei Zhang
Keyword(s):  
Genetic Algorithm ◽  
Superheated Steam ◽  
Steam Pressure ◽  
Improved Genetic Algorithm ◽  
Self Adaptive

In this paper, we propose an improved self-adaptive GA PID and compare it with traditional GA PID in simulation. This research indicates that improved self-adaptive GA PID can reduce system’s overshoot and regulation time and perform effectively.

Task scheduling algorithm based on improved genetic algorithm in cloud computing environment

2020 ◽  
Vol 13 ◽  
Author(s):  
Ge Weiqing ◽  
Cui Yanru
Keyword(s):  
Genetic Algorithm ◽  
Cloud Computing ◽  
Task Scheduling ◽  
Scheduling Algorithm ◽  
Task Completion ◽  
Improved Genetic Algorithm ◽  
Fitness Functions ◽  
Task Scheduling Algorithm ◽  
Simulation Results

Background: In order to make up for the shortcomings of the traditional algorithm, Min-Min and Max-Min algorithm are combined on the basis of the traditional genetic algorithm. Methods: In this paper, a new cloud computing task scheduling algorithm is proposed, which introduces Min-Min and Max-Min algorithm to generate initialization population, and selects task completion time and load balancing as double fitness functions, which improves the quality of initialization population, algorithm search ability and convergence speed. Results: The simulation results show that the algorithm is superior to the traditional genetic algorithm and is an effective cloud computing task scheduling algorithm. Conclusion: Finally, this paper proposes the possibility of the fusion of the two quadratively improved algorithms and completes the preliminary fusion of the algorithm, but the simulation results of the new algorithm are not ideal and need to be further studied.

scholarly journals Economic Environmental Dispatch of Wind Integrated Thermal Power System

2020 ◽  
Vol 8 (6) ◽  
pp. 5186-5192
Keyword(s):  
Genetic Algorithm ◽  
Power Plant ◽  
Thermal Power ◽  
Nsga Ii ◽  
Strength Pareto Evolutionary Algorithm ◽  
Experimental Constraint ◽  
Thermal Power System ◽  
Power Plant Operation ◽  
Simulation Results ◽  
The Given

In electric power plant operation, Economic Environmental Dispatch (EED) of a thermal-wind is a significant chore to involve allocation of production amongst the running units so the price, NOx extraction status and SO2 extraction status are enhanced concurrently whilst gratifying each and every experimental constraint. This is an exceedingly controlled multiobjective optimizing issue concerning contradictory objectives having Primary and Secondary constraints. For the given work, a Non-dominated Sorting Genetic Algorithm-II (NSGA-II) is recommended for taking care of EED issue. In simulation results that are obtained by applying the two test systems on the proposed scheme have been evaluated against Strength Pareto Evolutionary Algorithm 2 (SPEA 2).

Sign in / Sign up

Export Citation Format

Share Document