Energy Management Method for Microgrid Based on Real-time Corrected Double-loop Control of Energy Storage

被引：0
|
作者：
Jia K. [1 ]
Lin Y. [1 ]
Chen Y. [2 ]
Bi T. [1 ]
Liu B. [3 ]
机构：
[1] State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources (North China Electric Power University), Beijing
[2] State Grid Zhejiang Electric Power Research Institute, Hangzhou
[3] State Grid AC Project Construction Co. Ltd., Beijing
来源：
Jia, Ke (ke.jia@ncepu.edu.cn) | 2018年 / Automation of Electric Power Systems Press卷 / 42期
基金：
中国国家自然科学基金;
关键词：
Combined cooling; heating and power (CCHP); Micro-turbine; Real-time corrected control of energy storage; Renewable energy source (RES);
D O I：
10.7500/AEPS20170924003
中图分类号：
学科分类号：
摘要：
Utilization of the renewable energy source (RES) can address the environmental degradation and energy shortage problems. However, due to the different output characteristics of each energy source, how to efficiently use and allocate all kinds of energy is one of the major problems of current microgrid. An operation system combining the combined cooling, heating and power (CCHP) system and the energy storage system is designed. The output of micro-turbines and charging and discharging power of energy storage system are hierarchically controlled by the optimal algorithm. The output and load demand are regulated by the integrated coordination of photovoltaic, wind turbines and micro-turbines. It can solve the non-equivalent problem of the RES output and the load demand to realize the effective utilization of RES. In addition, a predicted data based real-time corrected power management algorithm is proposed to control the dispatch power of the energy storage system. The algorithm can reduce the disturbance resulted from the forecasting error and improve the flexibility of the energy management. Tested by the on-site measured data, this method shows the advantages in smoothing the load demand, especially in shaving the electric vehicles load demand compared with the conventional fixed threshold method and adaptive intelligence technique, and realizes the economic and optimal utilization of energy. © 2018 Automation of Electric Power Systems Press.
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页码：131 / 138
页数：7
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