A Multistage Home Energy Management System With Residential Photovoltaic Penetration

Advances in bilateral communication technology foster the improvement and development of home energy management system (HEMS). This paper proposes a new HEMS to optimally schedule home energy resources (HERs) in a high rooftop photovoltaic penetrated environment. The proposed HEMS includes three sta...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on industrial informatics 2019-01, Vol.15 (1), p.116-126
Main Authors: Luo, Fengji, Ranzi, Gianluca, Wan, Can, Xu, Zhao, Dong, Zhao Yang
Format: Article
Language:English
Subjects:
Air conditioners
Air conditioning
Atmospheric modeling
Buildings
Communications systems
Demand response
demand side management
Energy management
energy management system
Energy sources
Forecasting
Home appliances
Load modeling
Mathematical models
Photovoltaic systems
Power consumption
Predictive control
Predictive models
Residential energy
Scheduling
smart home
Thermal comfort
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Advances in bilateral communication technology foster the improvement and development of home energy management system (HEMS). This paper proposes a new HEMS to optimally schedule home energy resources (HERs) in a high rooftop photovoltaic penetrated environment. The proposed HEMS includes three stages: forecasting , day-ahead scheduling , and actual operation . In the forecasting stage, short-term forecasting is performed to generate day-ahead forecasted photovoltaic solar power and home load profiles; in the day-ahead scheduling stage, a peak-to-average ratio constrained coordinated HER scheduling model is proposed to minimize the one-day home operation cost; in the actual operation stage, a model predictive control based operational strategy is proposed to correct HER operations with the update of real-time information, so as to minimize the deviation of actual and day-ahead scheduled net-power consumption of the house. An adaptive thermal comfort model is applied in the proposed HEMS to provide decision support on the scheduling of the heating, ventilating, and air conditioning system of the house. The proposed approach is then validated based on Australian real datasets.
ISSN:1551-3203
1941-0050
DOI:10.1109/TII.2018.2871159