Research on two-stage optimization control method for energy storage systems based on multi service attribute utility evaluation

ABSTRACT

With the high proportion of new energy access and the increasing demand for load electricity, efficient and reasonable control of battery energy storage systems (BESS) in the power grid is the key to promoting new energy consumption, improving the quality and economy of power supply in the power grid. To solve the optimization control problem of BESS under multiple power service objectives, a two-stage optimization control method for BESS based on multi-service attribute utility evaluation has been proposed in this paper. Firstly, based on various power service demands and grid operation constraints, a multi-objective optimized scheduling model for BESS has been established; Then, to solve the complex coupling problem between multiple optimization objectives of BESS, a two-stage optimization structure has been designed that the changes of various service indicators under different optimization objectives have been recognized in the first stage, and the entropy weight method was used to weight each optimization objective in the second stage objectively; Finally, in the IEEE 33-bus simulation example, compared with the suboptimal result under each single-objective method, the relative error of the power line losses, the maximum voltage deviation, the curtailment of new energy and the economics of power grid of this algorithm has been reduced at least 2.31, 1.11, 2.90, and 1.05 times, respectively. Meanwhile, the performances of active power reserve and reactive power reserve are better than most single-objective optimizations.

KEYWORDS:

• Battery energy storage system
• energy storage optimization control
• multi-objective optimization
• multi-service attribute utility evaluation
• entropy weight method

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported in part by the Beijing Nova Program [Z211100002121081].

Notes on contributors

Suliang Ma

Suliang Ma got received his Ph.D. degree in electrical engineering from Beihang University, China, in 2020. He is currently an assistant research fellow of North China of University Technology. His research interests include control and optimization problems in large scale energy storage Systems, control theory and power generation technology in new energy.

Yiwen Wu

Yiwen Wu is a doctoral candidate at North China University of Technology. His research direction is power system energy storage optimization planning and control.

Yuan Jiang

Yuan Jiang received his Ph.D. degree in electrical engineering from Beihang University, Beijing, China, in 2016. He is currently an associate professor of University of Science and Technology Beijing. His research interests include the theory and application of vacuum arcs, electrical appliances detection and fault diagnosis, intelligent micro-grid and new energy technology.

Yaxin Li

Yaxin Li is a doctoral candidate form North China University of Technology. Her research direction is optimization of energy storage joint planning and configuration under high proportion of new energy electricity penetration.

Guanglin Sha

Guanglin Sha got received his Ph.D. degree in China University of Mining and Technology beijing, China, in 2017. He is working at China Electric Power Research Institute. His research interests include control theory and power generation technology in energy systems.