Title :
A Fuzzy Multi-objective Optimization Method Solving the Output of Energy Storage System
Author :
Yiyi Wang ; Mei Huang ; Caiping Zhang
Author_Institution :
Nat. Active Distrib. Network Technol. Res. Center (NANTEC), Beijing Jiaotong Univ., Beijing, China
Abstract :
The electricity consumption of a charging station is obviously fluctuant. An energy storage system is an effective device to improve the load variation of the charging station. In order to give full play to energy storage system, this paper proposes a charging and discharging control strategy of the storage system considering multi-objective including stabilizing load and economizing electric consumption, changing a bi-objective problem into a single objective problem with weights after fuzzy processing. This paper solves the problem based on Particle Swarm Optimization algorithm, and considers constraints including the demand of uninterruptible power supply and SOC at given time, which has greater practical significance. In this paper, the data of a practical integrated smart grid construction project is taken into considered. Finally, we verify the effectiveness and feasibility of the optimization strategy after simulation analysis.
Keywords :
electric vehicles; energy storage; fuzzy set theory; load regulation; particle swarm optimisation; power consumption; power system economics; power system stability; secondary cells; smart power grids; uninterruptible power supplies; SOC; biobjective problem; charging station; discharging control strategy; economic electric consumption; electricity consumption; energy storage system output; fuzzy multiobjective optimization method; fuzzy processing; integrated smart grid construction project; load variation; particle swarm optimization algorithm; simulation analysis; stabilizing load; uninterruptible power supply demand; Batteries; Charging stations; Economics; Electricity; Optimization; Power system stability; System-on-chip; charging scheduling; electric vehicles; energy storage system; multi-objective optimization; particle swarm optimization algorithm;
Conference_Titel :
Parallel Architectures, Algorithms and Programming (PAAP), 2014 Sixth International Symposium on
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-3844-5
DOI :
10.1109/PAAP.2014.48