Day-ahead Optimal Joint Scheduling Model of Electric and Natural Gas Appliances for Home Integrated Energy Management

Home energy management systems (HEMSs) enable residential customers to efficiently participate in demand response programs in order to obtain optimal benefits. Traditional HEMSs only manage household electric appliances to reduce the electricity consumption cost while the optimal scheduling of natur...

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Bibliographic Details
Published in:IEEE access 2019-01, Vol.7, p.1-1
Main Authors: Li, Kangping, Zhang, Peng, Li, Gang, Wang, Fei, Mi, Zengqiang, Chen, Hongyu
Format: Article
Language:English
Subjects:
Batteries
Customers
Demand response
Dissatisfaction
Electric appliances
Electricity consumption
Energy costs
Energy management
Energy management systems
Gas appliances
Home appliances
Home energy management system
Household appliances
Households
Joint scheduling
Load modeling
Mathematical models
Natural gas
Optimal scheduling
Residential energy
Scheduling
Smart buildings
Water heating
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Summary:Home energy management systems (HEMSs) enable residential customers to efficiently participate in demand response programs in order to obtain optimal benefits. Traditional HEMSs only manage household electric appliances to reduce the electricity consumption cost while the optimal scheduling of natural gas appliances has been overlooked. Due to the increasing popularity of natural gas appliances in modern smart homes, the electricity consumption of residential customers connected to the natural gas network is significantly affected by the use of natural gas appliances. To consider the interaction between electric and natural gas appliances in households, a day-ahead optimal joint scheduling model of electric and natural gas appliances for HEMS is proposed. Firstly, all household appliances are classified into several categories and the mathematical model of each appliance is presented. Then, a day-ahead optimal joint scheduling model of both electric and natural gas appliances for HEMS is formulated, in which the objective function is to minimize the household's energy cost and the dissatisfaction level caused by the shifting, reduction and replacement of loads in response to the time varying prices. Case studies using realistic data indicate that the proposed model can save the total energy costs up to 3% for customers whilst ensuring their satisfaction levels.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2019.2941238