In this paper the idea of functioning of Building Management Systems and Object Management Systems in intelligent buildings is presented. New functionalities of intelligent buildings resulting from the introduction of microgeneration are described. Low-Power Wide-Area Networks (LPWAN) are characterized and compared. The selected Long-Range (LoRaWAN) technology is tested for its use for communication with energy meters and monitoring the power supply network in intelligent buildings. In the paper a new system for reading and monitoring the network is proposed, consisting of hardware, communication, and application layers. A key element of the system is a specially developed converter, which has been designed and tested in a real urban environment. Using our solution in practice could allow to change the architecture of a measurement data acquisition system to much more flexible and efficient.

This paper focuses on the consumer preferences for the so-called “smart homes” (also known as “smart houses”) which represent a novel addition and a product of the on-going digitalization and the deployment of the Internet of Things (IoT). The major scientific contribution of our study is the empirical model build on the data from the online questionnaire conducted with randomly selected respondents (N = 523) from four European Union (EU) countries and Russia. Even though our results are subject to limitations (no Southern of Northern European countries are included in the scope of this research, which might have yielded different results due to the differences in wealth of citizens and climate in comparison to the Central and Eastern European countries or Germany), they demonstrate that the users included in our sample generally feel inclined to the smart homes technologies and perceive them as a plausible means for improving the safety and security of their lives. On the other hand,... [more]

This paper presents an open architecture for a sensor platform for the processing, collection, and image reconstruction from measurement data. This paper focuses on ultrasound tomography in block-wise-transform-reduction image reconstruction. The advantage of the presented solution, which is part of the project “Next-generation industrial tomography platform for process diagnostics and control”, is the ability to analyze spatial data and process it quickly. The developed solution includes industrial tomography, big data, smart sensors, computational intelligence algorithms, and cloud computing. Along with the measurement platform, we validate the methods that incorporate image compression into the reconstruction process, speeding up computation and simplifying the regularisation of solving the inverse tomography problem. The algorithm is based on discrete transformation. This method uses compression on each block of the image separately. According to the experiments, this solution is m... [more]

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... [more]

Power generation, distribution, transmission, and consumption face ongoing challenges such as smart grid management, control, and operation, resulting from high energy demand, the diversity of energy sources, and environmental or regulatory issues. This paper provides a comprehensive overview of blockchain-based solutions for smart grid management, control, and operations. We systematically summarize existing work on the use and implementation of blockchain technology in various smart grid domains. The paper compares related reviews and highlights the challenges in the management, control, and operation for a blockchain-based smart grid as well as future research directions in the five categories: collaboration among stakeholders; data analysis and data management; control of grid imbalances; decentralization of grid management and operations; and security and privacy. All these aspects have not been covered in previous reviews.

Datahubs step forth as convenient test beds for innovative solutions to create value from the energy data. There are numerous pilots and early trials for establishing energy Datahubs, especially in northern Europe. These are all centralised models, and the centralisation of data control and value creation can be regarded as contradictory to the decentralisation trend in the energy sector. This paper attempts to design the first decentralised energy Datahub ecosystem’s business ecosystem, with the name DenHub, using Blockchain technology. This model enables easy access to transparent and flexible energy data and new business models that will emerge upon its use. All data produced, distributed, used, and curated will help researchers and entrepreneurs study this field and propose new business models to make the energy ecosystem more efficient, clean, and inclusive. The paper also presents the differences between centralised and decentralised methods by underlining the advantages and disa... [more]

The paper’s main objective is to demonstrate the trading and flexibility of services amongst TSOs, DSOs, and Prosumers in a transparent, secure, and cost-effective manner using Blockchain-based TSO-DSO flexibility marketplace (EFLEX). The aim is to look for ways to help DSOs/TSOs be more flexible and more directly engaged in managing energy flows on the network. EFLEX will streamline the needs of both TSO and DSO on the same platform. Based on the paper’s proposed services, the pilot service demonstration will be carried out in Bulgaria and Romania, and the main focus will be on congestion management, TSO-DSO Coordination, and Marketplace. The proposed objective is achieved by using Blockchain-based smart contracts and distributed ledger technology.

Edge computing is a distributed computing paradigm such that client data are processed at the periphery of the network, as close as possible to the originating source. Since the 21st century has come to be known as the century of data due to the rapid increase in the quantity of exchanged data worldwide (especially in smart city applications such as autonomous vehicles), collecting and processing such data from sensors and Internet of Things devices operating in real time from remote locations and inhospitable operating environments almost anywhere in the world is a relevant emerging need. Indeed, edge computing is reshaping information technology and business computing. In this respect, the paper is aimed at providing a comprehensive overview of what edge computing is as well as the most relevant edge use cases, tradeoffs, and implementation considerations. In particular, this review article is focused on highlighting (i) the most recent trends relative to edge computing emerging in t... [more]

Internet of Things (IoT) provides large-scale solutions for efficient resource monitoring and management. As such, the technology has been heavily integrated into domains such as manufacturing, healthcare, agriculture, and utilities, which led to the emergence of sustainable smart cities. The success of smart cities depends on the availability of data, as well as the quality of the data management infrastructure. IoT introduced numerous new software, hardware, and networking technologies designed for efficient and low-cost data transport, storage, and processing. However, proper selection and integration of the correct technologies is crucial to ensuring a positive return on investment for such systems. This paper presents a novel end-to-end infrastructure for solar energy analysis and prediction via edge-based analytics.

The current energy prices do not include the environmental, social, and economic short and long-term external effects. There is a gap in the literature on the decision-making model for the energy transition. True Cost Accounting (TCA) is an accounting management model supporting the decision-making process. This study investigates the challenges and explores how big data, AI, or blockchain could ease the TCA calculation and indirectly contribute to the transition towards more sustainable energy production. The research question addressed is: How can IT help TCA applications in the energy sector in Europe? The study uses qualitative interpretive methodology and is performed in the Netherlands, Germany, and Poland. The findings indicate the technical feasibilities of a big data infrastructure to cope with TCA challenges. The study contributes to the literature by identifying the challenges in TCA application for energy production, showing the readiness potential for big data, AI, and blo... [more]

Smart buildings provide opportunities for technological transformations in building environments to improve resource management, comfort, and efficiency of the systems present in these facilities. For this, Internet of Things (IoT) solutions contribute, with monitoring and remote control features, to automate these environments. However, these solutions can promote the disposal or replacement of outdated but still-needed legacy systems. Thus, a reference model that uses retrofit techniques to update pre-existing systems would be an alternative to enable smart building convergence. The lack of models that advocate this type of strategy provides an opportunity for the emergence of methods capable of filling this gap. Thus, this work presents a strategy for implementing monitoring, control, and communication resources to achieve smart building convergence in legacy building systems. This strategy consists of the use of retrofit techniques based on the adaptation of the SmartLVGrid metamod... [more]

Throughout time, European policies on climate and energy change have generated several transformations in the building sector. In this endeavour, digital technologies have played an essential role in energy efficiency through process optimisation. However, data integration and exchange between different solutions is still challenging to achieve. With the advancement of Internet of Things (IoT) based solutions, one of the latest innovations, new opportunities are envisioned. IoT solutions have been implemented in smart grids, intelligent buildings, smart cities, and other sectors in recent years. Following the guidelines of ISA/ANSI 95-Enterprise-Control System Integration, the edge computing apps and cloud platform are needed to solve data bottlenecks, data ingestion, data integration aspects, bringing at the same time new knowledge related to user comfort, energy management and accessibility. This research focuses on a case study that shows how the thermal comfort of a building can be... [more]

Quantum computing is a game-changing technology that affects modern cryptography and security systems including distributed energy resources (DERs) systems. Since the new quantum era is coming soon in 5−10 years, it is crucial to prepare and develop quantum-safe DER systems. This paper provides a comprehensive review of vulnerabilities caused by quantum computing attacks, potential defense strategies, and remaining challenges for DER networks. First, new security vulnerabilities and attack models of the cyber-physical DER systems caused by quantum computing attacks are explored. Moreover, this paper introduces potential quantum attack defense strategies including Quantum Key Distribution (QKD) and Post-Quantum Cryptography (PQC), which can be applied to DER networks and evaluates defense strategies. Finally, remaining research opportunities and challenges for next-generation quantum-safe DER are discussed.

This paper demonstrates the effectiveness of using anomaly detection in cyclic communication as a method aimed at protecting industrial installations from steganographic communication and a wide range of cyberattacks. The analysis was performed for a method based on deterministic finite automaton and the authors’ method using cycles. In this paper, we discuss the cycle detection algorithm and graph construction as well as demonstrate an anomaly detection method for cyberattack detection that utilizes stochastic elements, such as time-to-response and time-between-messages. We present a novel algorithm that combines finite automaton determinism modeling consecutive admissible messages with a time-domain model allowing for random deviations of regularity. The study was conducted for several test scenarios, including C&C steganographic channels generated using the Modbus TCP/IP protocol. Experimental results demonstrating the effectiveness of the algorithms are presented for both methods.... [more]

The Internet of Vehicles (IoV), where people, fleets of electric vehicles (EVs), utility, power grids, distributed renewable energy, and communications and computing infrastructures are connected, has emerged as the next big leap in smart grids and city sectors for a sustainable society. Meanwhile, decentralized and complex grid edge faces many challenges for planning, operation, and management of power systems. Therefore, providing a reliable communications infrastructure is vital. The fourth industrial revolution, that is, a cyber-physical system in conjunction with the Internet of Things (IoT) and coexistence of edge (fog) and cloud computing brings new ways of dealing with such challenges and helps maximize the benefits of power grids. From this perspective, as a use case of IoV, we present a cloud-based EV charging framework to tackle issues of high demand in charging stations during peak hours. A price incentive scheme and another scheme, electricity supply expansion, are present... [more]

The fourth industrial revolution taking place in the industrial sector is related to the increasing digitization and linkage of goods, products, value chains and business models. Industry 4.0 is based on the global connection of people, things and machines. By connecting devices and sensors to the internet, we are entering a new era of data analysis, connectivity and automation. This gives great opportunities for innovation and progress, previously unattainable in such a dimension. The term Internet of Things (IoT) has spread along with the vision of a world instrumented with intelligent inputs and outputs able to communicate with each other through internet data and technologies. IoT is being implemented in various areas of the modern economy, for example, healthcare, quality control, logistics, energy, agriculture and production. The Industrial Internet of Things (IIoT) blazes the trail to a better understanding of the manufacturing process, thus enabling efficient and sustainable pr... [more]

It is essential for the electricity sector to analyze and determine the distribution capacity throughput and apply new methods aimed at increasing the capacity of the transmission system. Consequently, the transition to modern electricity networks is two-sided, i.e., involving technological and social modifications. The demand response (DR) redistributes consumption away from peak times when grid load and costs are the highest. It incentivizes customers to use electricity when supply is high and inexpensive due to various market mechanisms. The present DR policy proposals stress the importance of fostering behavioral change through competitive pricing and customer participation in reducing carbon emissions and implementing smart energy solutions (including monitoring tools, such as smart meters and applications). The internet of things (IoT) has been applied to ensure adaptive monitoring of energy consumption and cost-effective and adequate demand-side management (DSM). The article is... [more]

Microgrids should be continuously monitored in order to maintain suitable voltages over time. Microgrids are mainly monitored remotely, and their measurement data transmitted through lossy communication networks are vulnerable to cyberattacks and packet loss. The current study leverages the idea of data fusion to address this problem. Hence, this paper investigates the effects of estimation fusion using various machine-learning (ML) regression methods as data fusion methods by aggregating the distributed Kalman filter (KF)-based state estimates of a linear smart microgrid in order to achieve more accurate and reliable state estimates. This unreliability in measurements is because they are received through a lossy communication network that incorporates packet loss and cyberattacks. In addition to ML regression methods, multi-layer perceptron (MLP) and dependent ordered weighted averaging (DOWA) operators are also employed for further comparisons. The results of simulation on the IEEE 4... [more]

The paper presents problems related to the processing of signals recorded with differential field probes E and H. The fundamental problem to which special attention has been paid is the result of the integration operation. Due to the presence of constant/slowly-varying components in the raw signal, there is a drift present in the outcome of integration. This line wander can be enormous. This is particularly evident if the integration is performed in a standard manner, uniformly over the entire recorded waveform. The paper contains the Authors’ proposition to segment the signal and perform the integration independently in each of the sub-regions. This approach is based on the assumption of a local mean value instead of its global character for the recorded waveform. Although this leads to more complex signal processing, it gives significantly better results as it is suppressing the deterioration drift in the integrated signal more than 400 times. The results are presented on laboratory... [more]

We present a prototype of a decentralized power trading system based on the use of distributed ledger technology. This sort of efficient, decentralized marketplace is needed to empower prosumers and make them first-class members of a smart, decentralized power grid in order to drive further renewable energy adoption. Unlike the bulk of previous work in this field, we focus on private permissioned distributed ledgers rather than conventional blockchains. The proposed solution is entirely independent of cryptocurrency, with an explicit design capability of being adapted piecemeal without any fundamental changes to the present regulatory environment. To be economical, efficient, and scalable, our prototype is based on a lean, Corda-based private permissioned distributed ledger. It allows for instant, automatic bidding on and trading of ‘power promises’ and the robust implementation of short-term, small-scale liquid electrical power futures. We demonstrate that the prototype performs well... [more]

The increasing prevalence of renewable energy resources introduces a high variability that complicates the task of energy management in modern power grids. Among other technologies, batteries have proven effective in managing power imbalances in such grids. However, the high cost of large-scale batteries, coupled with their enormous space requirements, could deter their adoption by large consumers such as shared facility controllers. The aggregation of residential energy storage units offers shared facility controllers (SFCs) an alternative way to leverage storage; however, a secure scheme that promotes fairness and transparency in the selection and compensation of shared storage unit owners is needed. To this end, an Ethereum smart contract that makes residential storage capacities available to SFCs via a double auction mechanism is proposed. The contract is written with solidity and deployed in the browser-based Remix-integrated development environment. Scenario tests prove the effec... [more]

Lithium-ion battery devices are essential for energy storage and supply in distributed energy generation systems. Robust battery management systems (BMSs) must guarantee that batteries work within a safe range and avoid the damage caused by overcharge and overdischarge. The state-of-charge (SoC) of Li-ion batteries is difficult to observe after batteries are manufactured. The hysteresis phenomenon influences the existing battery modeling and SoC estimation accuracy. This research applies a terminal sliding mode observer (TSMO) algorithm based on a hysteresis resistor-capacitor (RC) equivalent circuit model to enable accurate SoC estimation. The proposed method is evaluated using two dynamic battery tests: the dynamic street test (DST) and the federal urban driving schedule (FUDS) test. The simulation results show that the proposed method achieved high estimation accuracy and fast response speed. Additionally, real-time battery information, including battery output voltage and SoC, was... [more]

This paper presents a comprehensive review of multi-port power electronics converters used for application in AC, DC, or hybrid distribution systems in an Internet of Energy scenario. In particular, multi-port solid-state transformer (SST) topologies have been addressed and classified according to their isolation capabilities and their conversion stages configurations. Non-conventional configurations have been considered. A comparison of the most relevant features and design specifications between popular topologies has been provided through a comprehensive and effective table. Potential benefits of SSTs in distribution applications have been highlighted even with reference to a network active nodes usage. This review also highlights standards and technical regulations in force for connecting SSTs to the electrical distribution system. Finally, two case studies of multi-port topologies have been presented and discussed. The first one is an isolated multi-port bidirectional dual active... [more]

The building sector is undergoing a deep transformation to contribute to meeting the climate neutrality goals set by policymakers worldwide. This process entails the transition towards smart energy-aware buildings that have lower consumptions and better efficiency performance. Digitalization is a key part of this process. A huge amount of data is currently generated by sensors, smart meters and a multitude of other devices and data sources, and this trend is expected to exponentially increase in the near future. Exploiting these data for different use cases spanning multiple application scenarios is of utmost importance to capture their full value and build smart and innovative building services. In this context, this paper presents a high-level architecture for big data management in the building domain which aims to foster data sharing, interoperability and the seamless integration of advanced services based on data-driven techniques. This work focuses on the functional description o... [more]

The development of tourist destinations has been determined by sustainable energy management and the advancement of traditional methods. The rate of development must adapt to technological innovations while also considering future generations. The present study aims to determine to what extent tourism personnel are aware of the skills, knowledge, and methods for sustainable energy management, and also to analyze the Internet of Things as a technological solution for sustainable energy management at tourism destinations in India with the help of the Servqual method. It is important to implement modern technologies such as internal things and develop a sustainable attitude toward tourism. Findings suggested that over each attribute of Servqual model, reliability, assurance, tangibles, empathy and responsiveness of IoT as sustainable energy management solutions at tourism destinations in India, tourism stakeholders have higher level of expectations (23.41, 19.86, 18.45, 23.60 and 24.73) a... [more]