A Multi-Objective Model for Home Energy Management System Self-Scheduling using the Epsilon-Constraint Method

• Type: Article in International Conference Proceedings Book
• Date: 2020

Authors

Mohammad Javadi (Author) Other; Mohamed Lotfi (Author) Other; Gerardo J. Osório (Author) Other; Abdelrahman Ashraf (Author) Other; Ali Esmaeel Nezhad (Author) Other; Matthew Gough (Author) Other; João P. S. Catalão (Author) FEUP

Conference proceedings International

Title: 2020 IEEE 14th International Conference on Compatibility, Power Electronics and Power Engineering (CPE-POWERENG)

Pages: 175-180

Indexing

ISI Web of Knowledge - 33 Citations

Scopus - 39 Citations

INSPEC

Other information

Authenticus ID: P-00S-QXM

DOI: 10.1109/cpe-powereng48600.2020.9161526

Abstract (EN): Self-scheduling of Home Energy Management Systems (HEMS) is one of the most interesting problems for active end-users to reduce their electricity bills. The electricity bill reduction by adopting Demand Response Programs (DRP) considering the flexibility of the end-users is addressed in this paper. The problem is addressed as a multi-objective optimization problem. The first objective function is the minimization of the daily bill, while the second objective aims to minimize the Discomfort Index (DI) regarding shifting the home appliances plugging-in time. The Time-of-Use (ToU) tariff is adopted in this paper and therefore, the end-users can benefit from shifting their flexible loads from peak hours to the off-peak hours and this reduces their bills, accordingly. In this case, the end-users have to change their energy consumption which imposes a level of discomfort on the end-users. Therefore, a two-stage model is proposed in this paper to deal with the mentioned objective functions. The proposed model is represented as standard mixed-integer linear programming (MILP) and for solving this problem the epsilon-constraint method is adopted in this study. The obtained Pareto front from the epsilon-constraint multi-objective framework is fed to the fuzzy satisfying method for final plan selection. These results show that by providing the Pareto set of optimal solutions to the user, they are more informed and can make decisions that better suit their preferences. © 2020 IEEE.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 6