Modeling and control strategy for energy storage system of micro-grid based on value stream analysis method

doi:10.19799/j.cnki.2095-4239.2020.0048

Abstract

Abstract:

Coordinated control among the energy sources, girds, loads, and storages is vital for the economic operation of a microgrid system, especially when the microgrid system includes energy storage systems. To improve the operation economy of such systems, a model library based on value stream analysis was developed on process simulation software. After calculating the flow and potential variables, the unit price variable was calculated according to the bidirectional flow characteristics of the energy storage system. To verify the reliability of the EnergySystem library in optimizing the control of a microgrid system, the control strategy of its energy storage system was analyzed. The result showed that a reasonable control strategy of the energy storage system must fully consider many boundary conditions, such as the time-of-use electric price, load demand, photovoltaic power generation, and energy-storage system parameters. After implementing a control strategy based on the value stream analysis, the peakvalley arbitrage was 1.8 times higher and the solar power loss was 50% lower than after implementing the strategy of the energy storage provider.

Key words: energy storage system, micro-grid, modelica, optimization control strategy, dynamic programming

CLC Number:

TM 73

LI Xiaoen, LU Ting, ZHAO Lulu, ZHOU You. Modeling and control strategy for energy storage system of micro-grid based on value stream analysis method[J]. Energy Storage Science and Technology, 2020, 9(3): 735-742.

Figures/Tables 14

Fig.1

Fig.2

Table 1

Commonly used carrier flow the corresponding unit price variables and value streams as well as the unit definition in EnergySystem"

载体依托的流变量 $f$	对应单价变量 $c$	载体的价值流 $f$
物质流量 $m ˙$ /kg·h^-1	￥/kg	￥/h
功率 $E ˙$ /kW	￥/(kW·h)	￥/h
热流量 $Q ˙$ /kW	￥/(kW·h)	￥/h

Table 1

Fig.3

Fig.4

Fig.5

Table 2

Fig.6

Fig.7

Fig.8

Fig.9

Fig.10

Table 3

c	—	单价变量
e	—	势变量
f	—	流变量
SOC	—	电池充放电状态
$p (k)$	—	环境变量
$u (k)$	—	控制变量
$x (k)$	—	状态变量
下角标
bat	—	储能蓄电池
cal	—	计算值
upstream	—	上游值

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时段	23:00—7:00	7:00—10:00	10:00—15:00(11:00—13:00^①)	15:00—18:00(16:00—17:00)	18:00—21:00	21:00—23:00
工作模式	充电	待机	放电	待机（放电）	放电	待机
持续时间	8 h	3 h	5 h（2 h）	3 h（1 h）	3 h	2 h
峰/平/谷	谷	平	峰（尖峰）	平（尖峰）	峰	平
电价/元.(kW.h)^-1	0.3648	0.8645	1.3902 （1.5195）	0.8645 （1.5195）	1.3902	0.8645

参量	储能供应商策略	基于价值流分析策略
日市电购电费用/元	697.6	567.5
日峰谷套利/元	123.7	233.0
日弃光量/kW·h	41.6	21.6

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