Research on Distributed Grid Connected Capacity Optimization Method for Power System Pre Dispatch

2019 4th Asia Conference on Power and Electrical Engineering

能源学;电工学

Xu, Zhengqing^1 ; Yan, Faqi^2 ; Liu, Zhicheng^2 ; Xiao, Yanwei^3 ; Sun, Shu-Qin^4 ; Yang, Jing^4 ; Yan, Wen-Li^4

Beijing Kedong Electric Power Control System Co.Ltd, Beijing

100192, China^1

State Grid Huazhong Electric Power Control Subcenter, Wuhan

430077, China^2

State Grid Zhejiang Electric Power Co.Ltd, Hangzhou

310007, China^3

College of Instrumentation and Electrical Engineering Jilin University, Lab. of Geo-Exploration and the Instrumentation Ministry of Education of China, Changchun

130026, China^4

关键词: Adaptive weights;    Basic principles;    Distributed energies;    Economical efficiency;    Grid supply points;    Grid-connected capacities;    Particle swarm optimization algorithm;    Reconstruction networks;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/486/1/012057/pdf
DOI  :  10.1088/1757-899X/486/1/012057

来源: IOP

【 摘 要 】

The particle swarm optimization algorithm with adaptive weight and Newton-Raphson method are studied to connect the distributed energy to the grid in this paper. We will discuss the research status of the current stage of the project. The basic principles and processes of particle swarm optimization algorithm and Newton-Raphson method are expounded, and their improvement and combination are made (as well as their improvement and combination ) so that they can optimize reactive power for networks with distributed energy better. Then the improved algorithm is applied to the IEEE-14 and IEEE-30 models and the reconstruction results are analyzed. The network loss and reactive power of the reconstruction network are declined, the voltage quality is improved. The SIMULARTOR software is used to establish and calculate the power flow of original model and reconstruction model of IEEE-14 and IEEE-30 respectively. The economic factors with grid supply point and connected capacity are analyzed to obtain the best ratio of power system at the same time. Compared with the above results, the results are basically consistent, and the accuracy and reliability of the algorithm are verified. Finally, considering the economic factors of the system, adjusting the connected capacity of the distributed energy-wind power and photovoltaic, and obtaining the best access ratio (proportion), the economical efficiency of the system is improved, and it has referential value.