scholarly journals Optimization of multi-objective micro-grid based on improved particle swarm optimization algorithm

2018 ◽  
Author(s):  
Jian Zhang ◽  
Yang Gan
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Algorithm ◽  
Particle Swarm Optimization Algorithm ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Improved Particle Swarm Optimization ◽  
Multi Objective ◽  
Micro Grid ◽  
Grid Based

A Study of Multi-Objective Load Optimal Dispatch in Thermal Power Unit Based on Improved Particle Swarm Optimization Algorithm

2013 ◽  
Vol 860-863 ◽  
pp. 1425-1430
Author(s):  
Ai Chen Wang ◽  
Wei Guo Pan ◽  
Wen Huan Wang
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Algorithm ◽  
Particle Swarm Optimization Algorithm ◽  
Particle Swarm ◽  
Solution Set ◽  
Pollutant Emissions ◽  
Good Effect ◽  
Swarm Optimization ◽  
Improved Particle Swarm Optimization ◽  
Multi Objective

In order to fit in with the demands of the development of electricity market in China, a multi-objective optimization mathematical model is presented to dispatch load within the units, taking economy, environmental protection and quick responsiveness to dispatching commands into consideration at the same time. And take the minimal whole plants power-supply coal cost rate, the minimal pollutant emissions and the minimal load adjusting time as these three objective functions respectively. The four constraint conditions are unit power balance constraint, load bound constraint, ramping constraint and pollution discharge standards constraint. An improved particle swarm optimization algorithm is used to get the Pareto solution set. The optimal solution was obtained by using the method of multi-attribute decision making, through sequencing the solution set by comprehensive evaluation. A case study based on a power plant with 4×600MW units was carried out. The result shows that the method can solve the multi-objective optimal load distribution problem accurately and quickly, and get the good effect in energy conservation and emissions reduction.

Multi Objective Optimization of Cutting Process Based on Improved Particle Swarm Optimization Algorithm

2014 ◽  
Vol 800-801 ◽  
pp. 688-692
Author(s):  
Xue Liu ◽  
Cai Xu Yue ◽  
Ming Yang Wu ◽  
Yong Heng Yang ◽  
Guang Xu Ren ◽  
...  
Keyword(s):  
Particle Swarm Optimization ◽  
Cutting Force ◽  
Optimization Algorithm ◽  
Particle Swarm Optimization Algorithm ◽  
Cutting Temperature ◽  
Particle Swarm ◽  
Multi Objective Optimization ◽  
Swarm Optimization ◽  
Improved Particle Swarm Optimization ◽  
Multi Objective

With the rapid development of machinery industry, the processing parameters which affect on the quality of the products in machining and measuring index also appeared diversified, which makes the study of multi-objective optimization problem is very important. Among the many factors, cutting consumption plays a key role in many indicators, in effect, cutting force and cutting temperature on the quality and performance of products is the most prominent, so this paper takes PCBN tool cutting Cr12MoV steel as the experimental basis, the cutting parameters to optimize the parameters;the cutting force and cutting temperature as the index;with the aid of the BP neural network modeling of cutting force and cutting temperature, at the same time, this paper improved particle swarm optimization algorithm to achieve multiple objectives, provides multi objective optimization parameters more reliable for die steel production process.

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