An Optimizing Heat Consumption System Based on BMS

The recent trend is to transform existing buildings into smart, green, or passive buildings by adopting sustainable technologies to achieve increased life comfort and production efficiency through reducing carbon emissions, energy consumption, and operating costs. Thus, existing buildings can be reh...

Full description

Saved in:
Bibliographic Details
Published in:Applied sciences 2022-04, Vol.12 (7), p.3271
Main Authors: Gaitan, Nicoleta Cristina, Ungurean, Ioan, Roman, Costica, Francu, Catalin
Format: Article
Language:English
Subjects:
Air conditioning
Alternative energy sources
Artificial intelligence
building management system
Building management systems
Cogeneration
Cold
Cold season
Control systems
Emissions
Energy consumption
energy efficiency
Energy management
Energy resources
Green buildings
Heat
Heating
HVAC
Internet of Things
Operating costs
Optimization
Rehabilitation
Sensors
smart building
smart system
Ventilation
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:The recent trend is to transform existing buildings into smart, green, or passive buildings by adopting sustainable technologies to achieve increased life comfort and production efficiency through reducing carbon emissions, energy consumption, and operating costs. Thus, existing buildings can be rehabilitated in order to have the lowest possible energy consumption. One of the highest demands on the energy consumption of buildings is the heating system used during the winter months. In this paper, we propose a management and control system for electrical and energy heating consumption, based on a BMS (building management system) that is used for the rehabilitation of the students’ dormitories on a university campus. This includes a cogeneration plant that can be controlled in order to produce electrical and heating energy, depending on the requirements needed to heat the building in the cold season. The system reduced the consumption of energy for heating by 13% and of electricity by 32%.
ISSN:2076-3417
2076-3417
DOI:10.3390/app12073271