Energy Management Based on Internet of Things

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Power Electronics".

Deadline for manuscript submissions: closed (29 February 2020) | Viewed by 26506

Special Issue Editors


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Department of Energy Technology, Aalborg University, Pontoppidanstræde 111, 9220 Aalborg Ø, Denmark
Interests: smart grids; energy modelling; energy management systems; demand response strategies; energy digitalisation; IoT energy applications

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Department of Energy Technology, Aalborg University, Pontoppidanstræde 111, 9220 Aalborg Ø, Denmark
Interests: microgrids; renewable energy; minigrids; distributed generation; islanded energy systems; distributed and hierarchical control; energy internet; IoT-based smart energy homes
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Department of Electronic Engineering, Technical University of Catalonia, Barcelona, Spain
Interests: microgrids; renewable energy systems; neuroscience-based artificial intelligence; digital twins; cybersecurity
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Special Issue Information

Dear Colleagues,

The integration of renewable energy sources (RES) at both network and household levels, as well as the pursuit of more sustainable energy consumption, has boosted the research of new energy management systems (EMS) that allow these elements to be coordinated in a reliable manner.

This task presents itself as a great challenge due to the uncertainty of the RES as well as the difficulty in predicting the behavior of the consumer elements. In this way, the implementation of any EMS, demand response (DR) strategies or another type of demand-side management (DSM) program requires the collection of a large amount of data, its subsequent processing, and the appropriate action on the resources to be managed.

In this context, the Internet of Things (IoT) emerges as the best solution to these challenges when considering the unforeseen massive data collection from sensors and actuators within current energy systems. What is more, it will unlock the potential of advance processing strategies based on cutting edge applications of artificial intelligence, big data or blockchain to name a few.

This Special Issue on “Energy Management Based on Internet of Things” is focused on state-of-the innovations in IoT-based infrastructures, communication and networking systems, control architectures, cyber-physical energy systems, and practical implementation of digital technologies in smart grid applications. Topics include but are not limited to:

  • IoT-drive solutions for EMS and DR;
  • Energy digitalization;
  • Smart Community, Smart Building, and Smart Home IoT solutions;
  • Blockchain-based P2P energy trading systems;
  • Data-driven management of energy systems.

Prof. Dr. Antonio Moreno-Munoz
Dr. Emilio José Palacios-García
Prof. Dr. Juan C. Vasquez
Prof. Dr. Josep M. Guerrero
Guest Editors

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Keywords

  • Smart grids
  • Energy management system
  • Demand response
  • Smart appliances
  • Smart buildings
  • Internet of Things
  • Grid digitalization
  • Big Data
  • Artificial Intelligence
  • Blockchain

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Published Papers (4 papers)

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Research

18 pages, 6896 KiB  
Article
IoT-enabled Microgrid for Intelligent Energy-aware Buildings: A Novel Hierarchical Self-consumption Scheme with Renewables
by Yanpeng Wu, Ying Wu, Josep M. Guerrero, Juan C. Vasquez, Emilio José Palacios-García and Yajuan Guan
Electronics 2020, 9(4), 550; https://doi.org/10.3390/electronics9040550 - 25 Mar 2020
Cited by 24 | Viewed by 5452
Abstract
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 [...] Read more.
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. Full article
(This article belongs to the Special Issue Energy Management Based on Internet of Things)
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15 pages, 3182 KiB  
Article
Demand and Storage Management in a Prosumer Nanogrid Based on Energy Forecasting
by Eva González-Romera, Enrique Romero-Cadaval, Joaquín Garrido-Zafra, Olivia Florencias-Oliveros, Mercedes Ruiz-Cortés, Antonio Moreno-Munoz and Juan-José González-de-la-Rosa
Electronics 2020, 9(2), 363; https://doi.org/10.3390/electronics9020363 - 21 Feb 2020
Cited by 7 | Viewed by 3340
Abstract
Energy efficiency and consumers’ role in the energy system are among the strategic research topics in power systems these days. Smart grids (SG) and, specifically, microgrids, are key tools for these purposes. This paper presents a three-stage strategy for energy management in a [...] Read more.
Energy efficiency and consumers’ role in the energy system are among the strategic research topics in power systems these days. Smart grids (SG) and, specifically, microgrids, are key tools for these purposes. This paper presents a three-stage strategy for energy management in a prosumer nanogrid. Firstly, energy monitoring is performed and time-space compression is applied as a tool for forecasting energy resources and power quality (PQ) indices; secondly, demand is managed, taking advantage of smart appliances (SA) to reduce the electricity bill; finally, energy storage systems (ESS) are also managed to better match the forecasted generation of each prosumer. Results show how these strategies can be coordinated to contribute to energy management in the prosumer nanogrid. A simulation test is included, which proves how effectively the prosumers’ power converters track the power setpoints obtained from the proposed strategy. Full article
(This article belongs to the Special Issue Energy Management Based on Internet of Things)
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17 pages, 1091 KiB  
Article
Experiments on a Real-Time Energy Management System for Islanded Prosumer Microgrids
by Carlos A. Macana, Hemanshu R. Pota, Quanyan Zhu, Josep M. Guerrero and Juan C. Vasquez
Electronics 2019, 8(9), 925; https://doi.org/10.3390/electronics8090925 - 23 Aug 2019
Cited by 5 | Viewed by 3845
Abstract
This paper presents an experimental demonstration of a novel real-time Energy Management System (EMS) for inverter-based microgrids to achieve optimal economic operation using a simple dynamic algorithm without offline optimization process requirements. The dynamic algorithm solves the economic dispatch problem offering an adequate [...] Read more.
This paper presents an experimental demonstration of a novel real-time Energy Management System (EMS) for inverter-based microgrids to achieve optimal economic operation using a simple dynamic algorithm without offline optimization process requirements. The dynamic algorithm solves the economic dispatch problem offering an adequate stability performance and an optimal power reference tracking under sudden load and generation changes. Convergence, optimality and frequency regulation properties of the real-time EMS are shown, and the effectiveness and compatibility with inner and primary controllers are validated in experiments, showing better performance on optimal power tracking and frequency regulation than conventional droop control power sharing techniques. Full article
(This article belongs to the Special Issue Energy Management Based on Internet of Things)
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27 pages, 8556 KiB  
Article
LoBEMS—IoT for Building and Energy Management Systems
by Bruno Mataloto, Joao C. Ferreira and Nuno Cruz
Electronics 2019, 8(7), 763; https://doi.org/10.3390/electronics8070763 - 8 Jul 2019
Cited by 68 | Viewed by 12417
Abstract
This work presents the efforts on optimizing energy consumption by deploying an energy management system using the current IoT component/system/platform integration trends through a layered architecture. LoBEMS (LoRa Building and Energy Management System), the proposed platform, was built with the mindset of proving [...] Read more.
This work presents the efforts on optimizing energy consumption by deploying an energy management system using the current IoT component/system/platform integration trends through a layered architecture. LoBEMS (LoRa Building and Energy Management System), the proposed platform, was built with the mindset of proving a common platform that would integrate multiple vendor locked-in systems together with custom sensor devices, providing critical data in order to improve overall building efficiency. The actions that led to the energy savings were implemented with a ruleset that would control the already installed air conditioning and lighting control systems. This approach was validated in a kindergarten school during a three-year period, resulting in a publicly available dataset that is useful for future and related research. The sensors that feed environmental data to the custom energy management system are composed by a set of battery operated sensors tied to a System on Chip with a LoRa communication interface. These sensors acquire environmental data such as temperature, humidity, luminosity, air quality but also motion. An already existing energy monitoring solution was also integrated. This flexible approach can easily be deployed to any building facility, including buildings with existing solutions, without requiring any remote automation facilities. The platform includes data visualization templates that create an overall dashboard, allowing management to identify actions that lead to savings using a set of pre-defined actions or even a manual mode if desired. The integration of the multiple systems (air-conditioning, lighting and energy monitoring) is a key differentiator of the proposed solution, especially when the top energy consumers for modern buildings are cooling and heating systems. As an outcome, the evaluation of the proposed platform resulted in a 20% energy saving based on these combined energy saving actions. Full article
(This article belongs to the Special Issue Energy Management Based on Internet of Things)
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