Design and advanced control strategies of a hybrid energy storage system for the grid integration of wind power generations. Issue 2 (1st March 2015)

• Record Type: Journal Article
• Authors: Wang, Shu; Tang, Yuejin; Shi, Jing; Gong, Kang; Liu, Yang; Ren, Li; Li, Jingdong
• Is Part Of: IET renewable power generation. Volume 9:Issue 2(2015)
• Page Start: 89
• Page End: 98
• Publication Date: 2015-03-01
• Subjects: wind power plants -- power generation control -- superconducting magnet energy storage -- DC‐AC power convertors -- fuzzy control -- genetic algorithms -- stability; hybrid energy storage system -- grid integration -- wind power generations -- advanced control strategies -- modern power system -- superconducting magnetic energy storage -- SMES dc chopper -- WPG -- complementary characteristics -- mathematical model -- dc‐ac converter -- battery buck‐boost converter -- system‐level control strategy -- power allocation -- fuzzy logic controller -- genetic algorithm -- controller designs -- stability -- MATLAB simulations -- HESS operation performance; Renewable energy sources -- Periodicals; 333.79405
• DOI: 10.1049/iet-rpg.2013.0340
• Languages: English
• ISSNs: 1752-1416

Abstract

Abstract : Energy storage (ES) has become increasingly important in modern power system, whereas no single type of ES element can satisfy all diverse demands simultaneously. This study proposes a hybrid energy storage system (HESS) based on superconducting magnetic energy storage (SMES) and battery because of their complementary characteristics for the grid integration of wind power generations (WPG). This study investigates the mathematical model and the topology of the proposed HESS, which is equipped with a grid‐side DC/AC converter, a battery buck/boost converter and a SMES DC chopper. The advanced control strategies comprised of device level and system level are designed. The control strategy for the converters which can be considered as device level is briefly discussed. The significant contribution of this study is proposing a novel system‐level control strategy for reasonable and effective power allocation between SMES and battery. According to the control objectives, a fuzzy logic controller optimised with genetic algorithm is adopted. The detailed controller designs are described, meanwhile system stability and HESS operation performance are evaluated. MATLAB simulations are presented to demonstrate the effectiveness of the proposed strategies.