Application of genetic algorithms and the cross-entropy method in practical home energy management systems

• Type: Article in International Scientific Journal
• Date: 2019

Authors

Abreu, C (Author) Other; Soares, I (Author) Other; Oliveira, L (Author) Other; Rua, D (Author) Other; Machado, P (Author) Other; Leonel Carvalho (Author) Other; João Peças Lopes (Author) FEUP

Journal

Title: IET Renewable Power Generation

Vol. 13

Pages: 1474-1483

ISSN: 1752-1416

Publisher: Wiley-Blackwell

Indexing

ISI Web of Knowledge - 5 Citations

Scopus - 4 Citations

Other information

Authenticus ID: P-00Q-QWQ

DOI: 10.1049/iet-rpg.2018.6022

Abstract (EN): Home energy management systems (HEMSs) are important platforms to allow consumers the use of flexibility in their consumption to optimise the total energy cost. The optimisation procedure embedded in these systems takes advantage of the nature of the existing loads and the generation equipment while complying with user preferences such as air temperature comfort configurations. The complexity in finding the best schedule for the appliances within an acceptable execution time for practical applications is leading not only to the development of different formulations for this optimisation problem, but also to the exploitation of non-deterministic optimisation methods as an alternative to traditional deterministic solvers. This study proposes the use of genetic algorithms (GAs) and the cross-entropy method (CEM) in low-power HEMS to solve a conventional mixed-integer linear programming formulation to optimise the total energy cost. Different scenarios for different countries are considered as well as different types of devices to assess the HEMS operation performance, namely, in terms of outputting fast and feasible schedules for the existing devices and systems. Simulation results in low-power HEMS show that GAs and the CEM can produce comparable solutions with the traditional deterministic solver requiring considerably less execution time.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 10