scholarly journals A QR code based framework for auto-configuration of IoT sensor networks in buildings

2021 ◽  
Vol 4 (S2) ◽  
Author(s):  
Simon Soele Madsen ◽  
Athila Quaresma Santos ◽  
Bo Nørregaard Jørgensen
Keyword(s):  
Sensor Networks ◽  
Energy Management ◽  
Cost Effective ◽  
Energy Management Systems ◽  
Building Energy Management ◽  
Communication Signal ◽  
Management Capabilities ◽  
Global Carbon

AbstractWorldwide buildings are responsible for about 40% of the overall consumption and contribute to an average of 30% percent of the global carbon emissions. Nevertheless, most current buildings lack efficient energy management systems because such solutions are very expensive, especially when necessary instrumentation needs to be installed after the building’s construction. As an alternative, we purpose the use of IoT sensor networks to retrofit existing medium and large-sized buildings to provide energy management capabilities in a cost-effective way. An IoT network auto-configuration platform for building energy management was developed. In order to efficiently manage metadata related to location and devices, a database using dynamic QR codes was created. Furthermore, we discuss the potential and shortcomings of different sensor-gateway pairing strategies that are applicable to an auto-configuring system. Lastly, we share our implementation of these concepts and demonstrate their use in a medium-sized building case study. The results show a trade-off between optimal configuration and total configuration time with a focus on the quality of the communication signal strength. The proposal provided the necessary automation for a cost-effective energy management system that can be deployed in both new constructions and existing buildings.

scholarly journals Evaluating the Economic and Environmental Impacts of Smart Management Systems for Cooling and Heating Systems in Building: Case study of Office Building in Tehran

2021 ◽  
Author(s):  
Gholamreza Heravi ◽  
Milad Rostami ◽  
Maryam Shekari
Keyword(s):  
Energy Consumption ◽  
Environmental Impacts ◽  
Energy Management ◽  
Building Energy ◽  
Office Building ◽  
Management Systems ◽  
Energy Management Systems ◽  
Building Energy Management ◽  
Operation Period

Considering the increasing rate of energy consumption and its environmental detrimental effects, as well as considering the use of non-renewable energy sources such as fossil fuels, energy management issues have become more important. Given the 40% share of the building industry's total energy consumption, as well as the 80% share of energy consumed during the operation period, attention to the areas of energy management and optimization during the operation period of the buildings can have a major impact on buildings’ energy performance. In this research, through identifying building energy management tools and studying previous studies and assessing the effects of building energy management systems, the economic and environmental impacts of using building energy management systems on the annual energy consumption in an office building in Tehran as a case study has been investigated. The results indicate a 32 percent reduction in energy consumption and a significant reduction in the release of the environmental pollutants in smart mode compared to the base mode. Moreover, considering the social costs associated with the emitted pollutants as well as the return period, it has been attempted to identify the factors contributing to the economic justification of using smart heating and cooling systems. According to the results, the use of smart energy management systems can be considered as an effective step in optimizing and managing energy consumption in the construction sector.

scholarly journals Energy Management Model for HVAC Control Supported by Reinforcement Learning

Energies ◽  
2021 ◽  
Vol 14 (24) ◽  
pp. 8210
Author(s):  
Pedro Macieira ◽  
Luis Gomes ◽  
Zita Vale
Keyword(s):  
Predictive Model ◽  
Energy Management ◽  
Decision Model ◽  
Cost Effective ◽  
Building Energy ◽  
Office Buildings ◽  
Energy Prices ◽  
Energy Management Systems ◽  
Building Energy Management ◽  
Current Energy

Heating, ventilating, and air conditioning (HVAC) units account for a significant consumption share in buildings, namely office buildings. Therefore, this paper addresses the possibility of having an intelligent and more cost-effective solution for the management of HVAC units in office buildings. The method applied in this paper divides the addressed problem into three steps: (i) the continuous acquisition of data provided by an open-source building energy management systems, (ii) the proposed learning and predictive model able to predict if users will be working in a given location, and (iii) the proposed decision model to manage the HVAC units according to the prediction of users, current environmental context, and current energy prices. The results show that the proposed predictive model was able to achieve a 93.8% accuracy and that the proposed decision tree enabled the maintenance of users’ comfort. The results demonstrate that the proposed solution is able to run in real-time in a real office building, making it a possible solution for smart buildings.

scholarly journals Cyber-Physical Systems Improving Building Energy Management: Digital Twin and Artificial Intelligence

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2338
Author(s):  
Sofia Agostinelli ◽  
Fabrizio Cumo ◽  
Giambattista Guidi ◽  
Claudio Tomazzoli
Keyword(s):  
Artificial Intelligence ◽  
Renewable Energy ◽  
Energy Management ◽  
Three Dimensional ◽  
Cost Effective ◽  
Automation System ◽  
Climate Conditions ◽  
Digital Twin ◽  
Building Energy Management ◽  
Computing Paradigm

The research explores the potential of digital-twin-based methods and approaches aimed at achieving an intelligent optimization and automation system for energy management of a residential district through the use of three-dimensional data model integrated with Internet of Things, artificial intelligence and machine learning. The case study is focused on Rinascimento III in Rome, an area consisting of 16 eight-floor buildings with 216 apartment units powered by 70% of self-renewable energy. The combined use of integrated dynamic analysis algorithms has allowed the evaluation of different scenarios of energy efficiency intervention aimed at achieving a virtuous energy management of the complex, keeping the actual internal comfort and climate conditions. Meanwhile, the objective is also to plan and deploy a cost-effective IT (information technology) infrastructure able to provide reliable data using edge-computing paradigm. Therefore, the developed methodology led to the evaluation of the effectiveness and efficiency of integrative systems for renewable energy production from solar energy necessary to raise the threshold of self-produced energy, meeting the nZEB (near zero energy buildings) requirements.

scholarly journals The effect of building energy management systems on battery aging

2018 ◽  
Vol 61 ◽  
pp. 00014
Author(s):  
Lluc Canals Casals ◽  
Lucía Igualada ◽  
Cristina Corchero
Keyword(s):  
Energy Management ◽  
Smart Cities ◽  
Lithium Ion ◽  
Power Generators ◽  
Electricity Grid ◽  
Energy Management Systems ◽  
Renewable Power ◽  
Building Energy Management ◽  
Electricity System ◽  
Electricity Bill

Smart buildings are a key element to walk towards smart cities and grids. Nonetheless, there are several degrees of intelligence. A first step is to incorporate commercial self-consumption solutions in buildings so they can manage the energy from local renewable power generators. A second step is to substitute this commercial solutions with an optimized Energy Management System (EMS) to reduce the electricity bill at the end of the month. Further. This EMS may contribute to stabilize and improve the quality and emissions of the electricity grid by offering some energy flexibility to the electricity system in favour of decentralization. This study compares the battery aging between buildings that count with an EMS to optimize the electricity bill under three scenarios in contrast to those that have a simple self-consumption kit. Lithium ion battery lifespan is estimated by means of an electric equivalent battery circuit model that runs on Matlab and simulates its behaviour through time. Moreover, this study evaluates the distribution of the battery costs regarding its use, observing that batteries controlled by simple self-consumption kits have longer lifespan because they are underused, ending up in higher calendar aging costs than the ones that are controlled by EMS.

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