78
[1鄄2]
[3鄄5]
DOI
:
10.13234/j.issn.2095鄄2805.2018.4.2 8
中图分类号
TM615
文献标志码
A
基于混合储能系统的风电跟踪目标出力
优化控制
1
1
2
2
1.
100192
2.
300380
摘 要 :
SOC
state of charge
NSGA鄄Ⅱ
Matlab
关键词:
Optimal Control of Wind Power Tracking Dispatching Plan
Based on Hybrid Energy Storage System
XIE Zhijia
1
, LI Jianlin
1
, CHENG Wei
2
, LIU Zhaoliang
2
(
1. State Key Laboratory of Operation and Control of Renewable Energy & Storage Systems, China Electric Power Research Institute
Ltd., Beijing 100192, China; 2. Tianjin Tuo Xin Li Shen Electric Vehicle Rental Co., Ltd., Tianjin 300380, China
)
Abstract
The inherent randomicity,volatility, and intermittency of wind power make s it difficult to track the
dispatching plan. Although the introduction of an energy storage system c a n improve the schedulability of wind farms, a
single鄄type of energy storage system is not suitabl e for applications due to its poor eco no mi c efficiency. Inthis paper,an
optimal control strategy for improving the capability of wi nd power tracking dispatching plan is proposed based on a
hybrid energy storage system. This strategycan be divided into two parts, i.e., coordinated control of internal energy in
the hybrid energy storage system and multi鄄objective opti ma l control;by using appropriate control methods in the st a te of
charge
SOC
of different energy storage systems, the optimal tracking c o nt rol can be realized. On one hand, the multi鄄ob鄄
jective optimization model takes t he extension of battery life into account; on the other hand, it fully takes advantage of
the characteristics of supercapacitors. The NSGA鄄Ⅱ method is used to solve this model, achievinga reasonable power
distribution between batteries and supercapacitors. Simulations are conducted on a MATLAB platform, and re sul t s verify
the effectivene ss of the proposed cont rol strategy.
Keywords: hybrid energy storage system; tracking dispatching plan; optimal control
电 源 学 报
Journal of Power Supply
Vol.16 No.4
Jul. 2018
16
4
2018
7
收稿日期:
2018鄄04鄄11
修回日期:
2018鄄07鄄15
基金 项 目:
2016GK1003
2017YFB0903 505
51777197
Project Supported by Major Science and Technology Project of
Hunan Province
2016GK1003
National Key R&D Program of
China
2017YFB0903 505
National Natural Science Foundation
of China
51777197