A multi-objective optimization model for active power steady-state security region analysis incorporating wind power

Author(s):  
Jinqing Luo ◽  
Libao Shi ◽  
Liangzhong Yao
2017 ◽  
Vol 2017 (13) ◽  
pp. 2378-2383
Author(s):  
Baoping Chen ◽  
Tao Lin ◽  
Rusi Chen ◽  
Yong Li ◽  
Xialing Xu

2013 ◽  
Vol 860-863 ◽  
pp. 414-418
Author(s):  
Yan Qing Li ◽  
Hao Shan Li ◽  
Chi Dong ◽  
Jian Wang

Large-scale wind power integration constituted great challenges for the power system operation and dispatching, due to the volatile and peak-reversal nature of wind power.The multi-objective optimization model of the wind farm combined with pumped-storage was studied to solve the problem.An optimization model for wind-storage combined operation was established, aiming at tracking load changes ,improving wind power economic benefits and peak shaving benefits, using improved multi-objective particle swarm optimization.The optimization calculation attempted to reduce volatility of the remaining load after removal of wind-storage joint output and increase economic benefits of wind farrms. Through the optimization calculation the wind farm and storage plant scheduling values of each time are available. The calculation example shows that the model and method are conducive to large-scale wind power integration and have a certain practicality and effectiveness.


2014 ◽  
Vol 602-605 ◽  
pp. 2897-2900
Author(s):  
Si Qing Sheng ◽  
Xiao Xia Sun

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.


2021 ◽  
Vol 13 (4) ◽  
pp. 1929
Author(s):  
Yongmao Xiao ◽  
Wei Yan ◽  
Ruping Wang ◽  
Zhigang Jiang ◽  
Ying Liu

The optimization of blank design is the key to the implementation of a green innovation strategy. The process of blank design determines more than 80% of resource consumption and environmental emissions during the blank processing. Unfortunately, the traditional blank design method based on function and quality is not suitable for today’s sustainable development concept. In order to solve this problem, a research method of blank design optimization based on a low-carbon and low-cost process route optimization is proposed. Aiming at the processing characteristics of complex box type blank parts, the concept of the workstep element is proposed to represent the characteristics of machining parts, a low-carbon and low-cost multi-objective optimization model is established, and relevant constraints are set up. In addition, an intelligent generation algorithm of a working step chain is proposed, and combined with a particle swarm optimization algorithm to solve the optimization model. Finally, the feasibility and practicability of the method are verified by taking the processing of the blank of an emulsion box as an example. The data comparison shows that the comprehensive performance of the low-carbon and low-cost multi-objective optimization is the best, which meets the requirements of low-carbon processing, low-cost, and sustainable production.


Sign in / Sign up

Export Citation Format

Share Document