Optimal Output of Distributed Generation Based On Complex Power Increment

2017 International Conference on Environmental, Industrial and Energy Engineering

生态环境科学;工业技术;能源学

Wu, D.^1 ; Bao, H.^1

School of Electrical and Electronic Engineering, North China Electric Power University, Beijing

102206, China^1

关键词: Calculation speed;    Classical optimization;    Coupling parameters;    Distribution generation;    Impedance parameters;    Photovoltaic power generation;    Power Optimization;    Sensitivity methods;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/104/1/012005/pdf
DOI  :  10.1088/1755-1315/104/1/012005

来源: IOP

【 摘 要 】

In order to meet the growing demand for electricity and improve the cleanliness of power generation, new energy generation, represented by wind power generation, photovoltaic power generation, etc has been widely used. The new energy power generation access to distribution network in the form of distributed generation, consumed by local load. However, with the increase of the scale of distribution generation access to the network, the optimization of its power output is becoming more and more prominent, which needs further study. Classical optimization methods often use extended sensitivity method to obtain the relationship between different power generators, but ignore the coupling parameter between nodes makes the results are not accurate; heuristic algorithm also has defects such as slow calculation speed, uncertain outcomes. This article proposes a method called complex power increment, the essence of this method is the analysis of the power grid under steady power flow. After analyzing the results we can obtain the complex scaling function equation between the power supplies, the coefficient of the equation is based on the impedance parameter of the network, so the description of the relation of variables to the coefficients is more precise Thus, the method can accurately describe the power increment relationship, and can obtain the power optimization scheme more accurately and quickly than the extended sensitivity method and heuristic method.