An Active Power Allocation Method for Wind-solar-batteries Hybrid Power System

Abstract

In this article, an active power allocation method based on multi-objective optimization technique for wind-solar-batteries hybrid system (WSBHPS) is proposed. The problem of active power allocation of WSBHPS is formulated as following multi-objectives: minimizing of error between the output power of WSBHPS and desired power from the grid, minimizing start/stop switch number of power generation units, and maximizing the utilization of the regulation ability of wind turbines. The short-term power prediction of wind and solar power is utilized to quantify the available output power of each generation component, which is taken as constraint conditions of optimization problem with state of charge (SOC) of the batteries. The pattern-search algorithm is utilized to solve the multi-objective optimization problems. The proposed method is illustrated by implementing it to the active power allocation of a WSBHPS in simulation. The simulation results demonstrate that the proposed method has better active power output performance and less fluctuating rate compared with conventional average method. This method not only could maintain the SOC of batteries in an appropriate range, but also could reduce the on-or-off switching number of wind turbines and PV modules.

Keywords:

• wind-solar-batteries hybrid power system
• multi-objective optimization
• pattern search algorithm
• active power allocation
• power prediction
• state of charge (SOC) of the batteries
• maximum power point track
• running condition
• regulation ability of wind turbine
• start/stop switch number of power generation units

Additional information

Notes on contributors

Jianxiao Zou

Jianxiao Zou received the B.Sc., M.Sc., and Ph.D. degrees from the School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, China, in 2000, 2003, and 2009, respectively. He was a visiting scholar in U.C. Berkeley January 2010 to January 2011. Presently, he is a professor at he School of Automation Engineering, University of Electronic Science and Technology of China. His research is focused on the control techniques in the renewable power systems and the intelligent information processing.

Jun Shu

Jun Shu received the B.Sc. degree from the School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, China, in 2012. His main research interest is the power system optimization in the context of renewable energy.

Zhenzhen Zhang

Zhenzhen Zhang received the Ph.D. degree from the School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, China, in 2013. She was a research engineer in in National University of Singapore, Singapore, from October 2010 to July 2011. She is a lecturer at College of Electrical and Information Engineering, Southwest University for Nationalities. Her research is focused on intelligent control for renewable energy generation system.

Wuqiao Luo

Wuqiao Luo received the B.S. degree in 2008 from School of Electronics Engineering and Computer Science, Peking University, Beijing. She is currently working toward the Ph.D. degree in School of Automation Engineering, University of Electronic Science and Technology of China. Her main research interest is intelligent systems for power system optimization and control.