Integrated Reactive Power Optimization Method for Active Distribution Networks Based on a Quantum Krill Herd Algorithm

Abstract

Aiming at the problem that the reactive power optimization of traditional distribution network can’t adapt to the active distribution network (ADN) of large-scale distributed power access, a comprehensive reactive power optimization method based on quantum krill herd algorithm for ADN is proposed. Firstly, a reactive power optimization model of ADN based on proportional coefficient is proposed by analyzing the characteristics of active control and active management. Secondly, the krill herd algorithm is easy to fall into local optimum when solving optimization problems. To overcome this shortcoming, a quantum krill swarm algorithm is proposed. The algorithm uses the probability amplitude of quantum bits to represent the information of particle position, uses quantum revolving gate to increase population diversity and generates new population through chaotic crossover, which improves the convergence accuracy of the algorithm. Finally, simulation experiments are carried out on the modified IEEE33 node and IEEE 69 node to verify the effectiveness of the proposed model and algorithm.

Keywords:

• ADN
• reactive power optimization
• active management strategy
• quantum krill herd algorithm

Additional information

Notes on contributors

Yuancheng Li

Yuancheng Li received the Ph.D. degree from University of Science and Technology of China, Hefei, China, in 2003. From 2004 to 2005, he was a postdoctoral research fellow in the Digital Media Lab, Beihang University, Beijing, China. Since 2005, he has been with the North China Electric Power University, where he is a professor and the Dean of the Institute of Smart Grid and Information Security. From 2009 to 2010, he was a postdoctoral research fellow in the Cyber Security Lab, college of information science and technology of Pennsylvania State University, Pennsylvania, USA. He has hosted and participated in several research projects for the National Natural Science Foundation of China, National 863 Plan projects. He is the author of more than 70 articles, and more than 10 inventions. His research interests include power grid security, information security, cloud computing, big data security, and cloud security.

Rongyan Yang

Rongyan Yang master degree candidate in North China Electric Power University, Beijing, China. Her research interest is power grid security and information security.

Xiaoyu Zhao

Xiaoyu Zhao master degree candidate in North China Electric Power University, Beijing, China. Her research interests include active distribution network and reactive power optimization intelligent algorithm.