Open IoT Infrastructures for In-Home Energy Management and Control

García, Emilio José; Arbab-Zavar, Babak; Vasquez, Juan C.; Guerrero, Josep M.

doi:10.1109/icce-berlin47944.2019.8966225

Cited by 5 publications

(5 citation statements)

References 5 publications

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“…The proposed testbed scenario considered a dynamic tariff system. Another energy management system (EMS) was proposed by authors in [ 19 ], where a system was implemented at the IoT Microgrid Laboratory at Aalborg University. The IoT-based EMS showed the feasibility of using IoT devices to regulate consumption.…”

Section: Related Workmentioning

confidence: 99%

“…Type Description [16] Review Comprehensive review for home energy management system with respect to concepts, architecture infrastructure, and challenges [17] Technical/Simulation Performance analysis among three different Cloud-IoT platforms services for Amazon web service, Microsoft Azure, and Google Cloud [18] Technical/Implementation IoT-based infrastructure on edge-fog-cloud architecture to monitor and control residential loads to support demand response [19] Technical/Implementation IoT-based infrastructure for EMS. The system has been tested in a pilothouse named IoT Microgrid Living Lab, Denmark [20] Technical/Implementation Energy monitoring platform to collect real-time electricity consumption data in a smart villa, Doha Qatar [21] Technical/Implementation Detailed building operation data (electricity consumption and indoor environment) of seven-story building in Bangkok, Thailand [22] Technical/Implementation Electrical energy dataset (52 months) from commercial and residential building at one minute sampling rate, India…”

Section: Ref Yearmentioning

confidence: 99%

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Design and Implementation of a Cloud-IoT-Based Home Energy Management System

Condon

Martínez

Eltamaly

et al. 2022

Sensors

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The advances in the Internet of Things (IoT) and cloud computing opened new opportunities for developing various smart grid applications and services. The rapidly increasing adoption of IoT devices has enabled the development of applications and solutions to manage energy consumption efficiently. This work presents the design and implementation of a home energy management system (HEMS), which allows collecting and storing energy consumption data from appliances and the main load of the home. Two scenarios are designed and implemented: a local HEMS isolated from the Internet and relies on its processing and storage duties using an edge device and a Cloud HEMS using AWS IoT Core to manage incoming data messages and provide data-driven services and applications. A testbed was carried out in a real house in the city of Valparaiso, Chile, over a one-year period, where four appliances were used to collect energy consumption using smart plugs, as well as collecting the main energy load of the house through a data logger acting as a smart meter. To the best of our knowledge, this is the first electrical energy dataset with a 10-second sampling rate from a real household in Valparaiso, Chile. Results show that both implementations perform the baseline tasks (collecting, storing, and controlling) for a HEMS. This work contributes by providing a detailed technical implementation of HEMS that enables researchers and engineers to develop and implement HEMS solutions to support different smart home applications.

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Section: Related Workmentioning

confidence: 99%

Section: Ref Yearmentioning

confidence: 99%

Design and Implementation of a Cloud-IoT-Based Home Energy Management System

Condon

Martínez

Eltamaly

et al. 2022

Sensors

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“…In this case, wide coverage is no longer required and ease of implementation and scalability are the important required characteristics that define the selected communication protocol. ZigBee is a very good candidate for smarthomes [14,15]. In line with the development of MG, their low level control structures became less communication dependent and more reliant on local measurements.…”

Section: Communication System For Residential Mg Managementmentioning

confidence: 99%

Reducing Detrimental Communication Failure Impacts in Microgrids by Using Deep Learning Techniques

Arbab-Zavar

Sharkh

García

et al. 2022

Sensors

Self Cite

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A Microgrid (MG), like any other smart and interoperable power system, requires device-to-device (D2D) communication structures in order to function effectively. This communication system, however, is not immune to intentional or unintentional failures. This paper discusses the effects of communication link failures on MG control and management and proposes solutions based on enhancing message content to mitigate their detritus impact. In order to achieve this goal, generation and consumption forecasting using deep learning (DL) methods at the next time steps is used. The architecture of an energy management system (EMS) and an energy storage system (ESS) that are able to operate in coordination is introduced and evaluated by simulation tests, which show promising results and illustrate the efficacy of the proposed methods. It is important to mention that, in this paper, three dissimilar topics namely MG control/management, DL-based forecasting, and D2D communication architectures are employed and this combination is proven to be capable of achieving the aforesaid objective.

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“…The main idea of this laboratory is to simulate an intelligent building environment with renewable energy access, intelligent energy management, measurement and control automation, things-based convergence, energy-based interoperability and energy digitalization, etc. The IoT-MGLab also serves as a demonstrator to show the viability of low voltage DC and AC systems for future households, which will enhance the energy efficiency, flexibility and reliability following the Danish smart grid strategy [32][33][34][35].…”

Section: Case Study-iot Microgrid Laboratory At Aalborg Universitymentioning

confidence: 99%

IoT-enabled Microgrid for Intelligent Energy-aware Buildings: A Novel Hierarchical Self-consumption Scheme with Renewables

Guerrero

et al. 2020

Electronics

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This paper presents a novel hierarchical Internet of Things (IoT)-based scheme for Microgrid-Enabled Intelligent Buildings to achieve energy digitalization and automation with a renewable energy self-consumption strategy. Firstly, a hierarchical structure of Microgrid-Enabled Intelligent Buildings is designed to establish a two-dimensional fusion layered architecture for the microgrid to interact with the composite loads of buildings. The building blocks and functions of each layer are defined specifically. Secondly, to achieve transparent information fusion and interactive cooperation between the supply-side and demand-side, a state transition mechanism driven by a combination of time and events is proposed to activate the real-time and mutual response of generation and loads dynamically. Thirdly, based on the above hierarchical fusion structure and data-driven state transition mechanism, a power balance control algorithm driven by a self-consumption strategy is further proposed to achieve the autonomous balance of supply and demand. Finally, the IoT Microgrid Laboratory at Aalborg University is introduced to show how to implement this novel hierarchical IoT-based scheme in a Microgrid-Enabled Intelligent Building, and the power consensus control method based on the state transition mechanism is verified to achieve a renewable energy self-consumption strategy.

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Open IoT Infrastructures for In-Home Energy Management and Control

Cited by 5 publications

References 5 publications

Design and Implementation of a Cloud-IoT-Based Home Energy Management System

Design and Implementation of a Cloud-IoT-Based Home Energy Management System

Reducing Detrimental Communication Failure Impacts in Microgrids by Using Deep Learning Techniques

IoT-enabled Microgrid for Intelligent Energy-aware Buildings: A Novel Hierarchical Self-consumption Scheme with Renewables

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