Dynamic Multi-Objective Power Dispatch Considering Load and Wind Power Variations in Wind Power Integrated System

2014 ◽  
Vol 672-674 ◽  
pp. 316-319
Author(s):  
Chen Li ◽  
Zhi Jian Hu
Keyword(s):  
Wind Power ◽  
Wind Farm ◽  
Integrated System ◽  
Multi Objective ◽  
Operational Space ◽  
Power Dispatch ◽  
Proposed Model ◽  
Teaching Learning Based Optimization ◽  
Simulation Results ◽  
Teaching Learning

A modeling for dynamic multi-objective power dispatch considering load and wind power variations in wind power integrated system is presented. To deal with the random variables, probabilistic sequence theory is introduced and the operational space is extended. To solve the problem, an improved multi-objective teaching-learning-based optimization algorithm is proposed. Finally, the proposed model and algorithm are tested on a 10-units system including wind farm and the simulation results demonstrate that the proposed model and algorithm are feasible and effective.

Multi-Objective Optimization Model of Wind Farm and Pumped Storage Power Station

2014 ◽  
Vol 602-605 ◽  
pp. 2897-2900
Author(s):  
Si Qing Sheng ◽  
Xiao Xia Sun
Keyword(s):  
Wind Power ◽  
Optimization Model ◽  
Wind Farm ◽  
Multi Objective Optimization ◽  
Power Station ◽  
Joint System ◽  
Multi Objective ◽  
Proposed Model ◽  
Wind Rate ◽  
Pumped Storage

This paper presents a multi-objective optimization model to solve the volatility and anti load characteristic of wind power. The pumped storage power station is introduced in this paper. Though pumping and watering, the pumped storage power station can cut peak down to smooth the wind power. Given to the economical efficiency of wind farm, operation efficiency of the wind storage joint system is investigated. In order to improve the wind rate, minimize abandon wind is employed in objective function. To demonstrate the effectiveness of the proposed model, a practical example is tested. The result shows that this model is feasible and effective.

scholarly journals Enhanced Multi-Objective Teaching-Learning-Based Optimization for Machining of Delrin

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 51528-51546 ◽  
Author(s):  
Elango Natarajan ◽  
Varadaraju Kaviarasan ◽  
Wei Hong Lim ◽  
Sew Sun Tiang ◽  
Teng Hwang Tan
Keyword(s):  
Multi Objective ◽  
Teaching Learning Based Optimization ◽  
Teaching Learning

Multi-Objective Optimal Dispatch of Power System with Wind Power Based on Improved Particle Swarm Algorithm

2013 ◽  
Vol 860-863 ◽  
pp. 353-360
Author(s):  
Yi Hui Zhang ◽  
Zhi Jian Hu ◽  
Xiao Lu Gong ◽  
Meng Lin Zhang ◽  
He Wang ◽  
...  
Keyword(s):  
Power System ◽  
Wind Power ◽  
Particle Swarm ◽  
Environmental Benefits ◽  
Particle Swarm Algorithm ◽  
Security Risks ◽  
Swarm Optimization ◽  
Optimal Dispatch ◽  
Multi Objective ◽  
Simulation Results

With the increase of its proportion in power system, wind power not only brings economic and environmental benefits but also the potential security risks due to its fluctuation and uncertainty. In order to take the potential security risks into account, an environmental/economic/safe static dispatch (EESD) model of power system with wind power is built. A new multi-objective particle swarm optimization (MOPSO) algorithm with standby selection and micro variation is proposed to solve the model. Two cases with and without wind power are simulated with the standard IEEE-30 system. The simulation results validate the effectiveness of the proposed algorithm.

Sign in / Sign up

Export Citation Format

Share Document