Energy management system for residential buildings based on fuzzy logic: design and implementation in smart‐meter. Issue 2 (26th February 2020)

• Record Type: Journal Article
• Authors: Chojecki, Adrian; Rodak, Michał; Ambroziak, Arkadiusz; Borkowski, Piotr
• Is Part Of: IET smart grid. Volume 3:Issue 2(2020)
• Page Start: 254
• Page End: 266
• Publication Date: 2020-02-26
• Subjects: energy conservation -- power engineering computing -- distributed power generation -- building management systems -- smart meters -- object‐oriented programming -- renewable energy sources -- energy consumption -- energy management systems -- smart power grids; maximum added value -- energy management system -- EMS -- smart metre -- fuzzy logic -- rule base -- energy management algorithm -- energy consumption -- residential buildings -- renewable energy source -- smart grid technologies -- smart metering systems -- modern buildings -- building management system -- energy efficiency; B8110B Power system management, operation and economics -- B8150 Power system measurement and metering -- C6110J Object‐oriented programming -- C7410B Power engineering computing -- B8120K Distributed power generation; Smart power grids -- Periodicals; Computer science -- Periodicals; Energy industries -- Periodicals; Broadcasting -- Periodicals; 333.79110285
• DOI: 10.1049/iet-stg.2019.0005
• Languages: English
• ISSNs: 2515-2947

Abstract

Abstract : Advances in distributed generation and increased contribution of renewable energy source (RES) require development of smart grid technologies. Smart metering systems, as a part of smart grid technologies, in cooperation with modern buildings equipped with building management system allows for improvement of energy efficiency. It is possible to partially cover the power demand of a building from the local RESs. However, in order to ensure maximum added value, energy management system (EMS) is essential. This article presents the project and practical implementation of an EMS implemented in smart‐meter. The designed system is based on an original algorithm using fuzzy logic. The rule base was created in FCL language and the implementation was carried out in C++ with the object‐oriented programming (OOP). For the efficiency rating indicator, peak‐to‐average ratio (PAR) was selected. This ratio depending on the daily load profile decreased within a range from 15 to 54%, and the average value was 30%. The proposed energy management algorithm helps to reduce energy consumption at peak demand by 34%, with the total reduction of energy consumption during the day of 7%. The described solution demonstrates a potential for real implementation and was tested in hardware.