• CSCD核心库收录期刊
  • 中文核心期刊
  • 中国科技核心期刊

电力建设 ›› 2020, Vol. 41 ›› Issue (1): 71-79.doi: 10.3969/j.issn.1000-7229.2020.01.009

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混合储能系统的功率变换器电流预测控制方法

王上行1,贾学翠1,王立华2,闫士杰2,李相俊1   

  1. 1.新能源与储能运行控制国家重点实验室(中国电力科学研究院有限公司),北京市 100192;2. 东北大学信息科学与工程学院,沈阳市 110819
  • 出版日期:2020-01-01
  • 作者简介:王上行(1990),男,博士,工程师,主要研究方向为储能控制与应用、电网安全稳定分析; 贾学翠(1984),女,硕士,高级工程师,主要研究方向为储能控制与应用、储能建模与数据分析; 王立华(1995),男,硕士研究生,主要研究方向为电力电子与新能源发电、储能控制与应用; 闫士杰(1964),男,博士,副教授,主要研究方向为电力电子与新能源发电、储能控制与应用; 李相俊(1979),男,博士,教授级高级工程师,IET Fellow,主要研究方向为大规模储能技术、新能源与分布式发电、电力系统运行与控制。
  • 基金资助:
    国家电网公司科技项目(基于信息物理融合的超大规模电池储能电站智能协调控制与能量优化管理——超大规模电池储能电站仿真模型及其暂态变化特性研究)(DG71-18-009)

Current Predictive Control of Power Converter for Hybrid Energy Storage System

WANG Shangxing1,JIA Xuecui1,WANG Lihua2, YAN Shijie2,LI Xiangjun1   

  1. 1. State Key Laboratory of Control and Operation of Renewable Energy and Storage Systems (China Electric Power Research Institute), Beijing 100192, China;2. College of Information Science and Engineering, Northeastern University, Shenyang 110819, China)
  • Online:2020-01-01
  • Supported by:
    This work is supported by State Grid Corporation of China Research Program(No. DG71-18-009).

摘要: 针对随机性强和波动性大的新能源发电系统,为了平滑其出力,提出了一种混合储能系统的功率变换器电流预测控制方法。该方法首先分析了锂电池和超级电容充放电速度的互补特性,以及它们的功率变换器各种开关状态。然后基于模型预测控制建立了锂电池、超级电容器和双功率变换器预测模型。在此基础上,应用模型预测控制设计了混合储能控制系统。在考虑锂电池电流跟踪误差、超级电容器电流跟踪误差、超级电容器损耗和双功率变换器开关管导通数量的情况下,构建了多目标评价函数,并进行了最优开关模式求解。通过实时优化控制系统,输出最优开关模式,既实现了锂电池大电流充放电和跟踪低频变化功率,也实现了超级电容器小电流充放电和跟踪高频变化功率。因此,该方法实现了混合储能系统能量合理分配,延长了锂电池使用寿命,减少了开关动作,提高了系统整体效率。最后,通过仿真验证了所提方法的正确性。

关键词: 混合储能系统, 模型预测控制, 双功率变流器, 多目标优化, 最优开关模式

Abstract:  In order to smooth the power output of the new energy generation system with strong randomness and fluctuation, a current predictive control method of power converter for hybrid energy storage is proposed. Firstly, the complementary characteristics of charging and discharging speeds of lithium batteries and super-capacitors are analyzed, as well as the switching states of their power converters. Then, on the basis of model predictive control, the predictive models of lithium battery, super-capacitor and dual power converter are established. On this basis, a hybrid energy storage control system is designed by using model predictive control. Considering the current tracking errors of lithium batteries, super-capacitor current tracking errors, super-capacitor losses and the number of switches of dual power converter, a multi-objective evaluation function is constructed and the optimal switching mode is solved. After real-time optimization of the control system, the optimal switching mode is output. In this way, not only the high-current and low-frequency variable power tracking of lithium battery, but also the low-current and high-frequency variable power tracking of super-capacitor are realized. Therefore, the balanced energy distribution of hybrid energy storage system is realized. The service life of lithium battery is prolonged. The switching action is reduced, and the overall efficiency of the system is improved. Finally, the correctness of the proposed method is verified by simulation.

Key words:  hybrid energy storage system, model predictive control, dual power converter, multi-objective optimization, optimal switching mode

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