基于滚动优化的家庭能量管理系统分布式鲁棒优化

doi:10.1007/s11708-020-0665-4

Frontiers in Energy

2020, Vol. 14

Issue (2): 254-266 https://doi.org/10.1007/s11708-020-0665-4

本期目录

基于滚动优化的家庭能量管理系统分布式鲁棒优化

王继东, 陈伯煜, 李鹏, 车延博(

)

天津大学电气自动化与信息工程学院

Distributionally robust optimization of home energy management system based on receding horizon optimization

Jidong WANG, Boyu CHEN, Peng LI, Yanbo CHE(

)

Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China

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摘要:

本文提出一种基于滚动优化（RHO）的分布式鲁棒优化（DRO）方法，用以解决不确定环境下家庭能源管理系统（HEMS）中可调度负荷的优化调度问题。首先，考虑户外温度和热水需求为不确定性变量，建立HEMS的优化模型，并基于不确定性变量的概率分布歧义集，采用DRO方法将HEMS调度问题转化为混合整数线性规划（MILP）问题。结合RHO实时更新与不确定性变量相关的信息，以滚动优化的方式求解MILP。仿真结果表明，在不确定的环境下，调度结果具有较强的鲁棒性，几乎没有违反用户的热舒适性，同时满足了所有运行约束。此外，与鲁棒优化（RO）方法相比，本文提出的RHO-DRO方法具有更低的保守性，可以为用户节省更多的电费。

Abstract：

This paper investigates the scheduling strategy of schedulable load in home energy management system (HEMS) under uncertain environment by proposing a distributionally robust optimization (DRO) method based on receding horizon optimization (RHO-DRO). First, the optimization model of HEMS, which contains uncertain variable outdoor temperature and hot water demand, is established and the scheduling problem is developed into a mixed integer linear programming (MILP) by using the DRO method based on the ambiguity sets of the probability distribution of uncertain variables. Combined with RHO, the MILP is solved in a rolling fashion using the latest update data related to uncertain variables. The simulation results demonstrate that the scheduling results are robust under uncertain environment while satisfying all operating constraints with little violation of user thermal comfort. Furthermore, compared with the robust optimization (RO) method, the RHO-DRO method proposed in this paper has a lower conservation and can save more electricity for users.

Key words： distributionally robust optimization (DRO) home energy management system (HEMS) receding horizon optimization (RHO) uncertainties

收稿日期: 2019-06-06 出版日期: 2020-06-22

通讯作者: 车延博 E-mail: ybche@tju.edu.cn

Corresponding Author(s): Yanbo CHE

引用本文:

王继东, 陈伯煜, 李鹏, 车延博. 基于滚动优化的家庭能量管理系统分布式鲁棒优化[J]. Frontiers in Energy, 2020, 14(2): 254-266.
Jidong WANG, Boyu CHEN, Peng LI, Yanbo CHE. Distributionally robust optimization of home energy management system based on receding horizon optimization. Front. Energy, 2020, 14(2): 254-266.

链接本文:

https://academic.hep.com.cn/fie/CN/10.1007/s11708-020-0665-4
https://academic.hep.com.cn/fie/CN/Y2020/V14/I2/254

Fig.1

Fig.2

Fig.3

Fig.4

Fig.5

Name	$b$	$e$	Duration/h	Power/kW
WM	20:30	23:00	1	1
DS	12:30	14:30	1	1.5
EV	00:30	9:30	3	3
PP	15:00	20:00	1	3

Tab.1

C_p/(J·kg^?¹·°C^?¹)	M/L	γ_WH/°C	β_WH/(°C·kg^?¹)	P_WH,MAX/kW	$θ water min ?$ /°C	$θ water max$ /°C
4185	184	0.04	0.068	3	60	70

Tab.2

R/(°C·kW^?¹)	C/(kWh·°C^?¹)	P_{AC, max}/kW	$θ room min$ /°C	$θ room max$ /°C
18	0.525	1.8 20		24

Tab.3

$L θ, t m$ /°C	$U θ, t m$ /°C	$L d, t m$ /L	$U d, t m$ /L	E_θ/°C	E_d/L	σ_θ/°C²	σ_d/L²
$θ out, ? t f − 3$	$θ out, ? t f +3$	$0.7 d WH, ? t f$	$1 .3 d WH, ? t f$	$θ out, ? t f$	$d WH, ? t f$	1	$0.1 d WH, ? t f$

Tab.4

Fig.6

Fig.7

Fig.8

Tab.5

Fig.9

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