This paper qualitatively evaluates the application of blockchain technology for three energy efficiency use cases. To achieve the Sustainable Development Agenda, energy efficiency improvements have to double by 2030. However, the adoption of energy efficiency interventions is slow due to several market barriers. Blockchain technology is a nascent technology with the potential to address these barriers or even fundamentally change energy system designs, by enabling transparent, decentralised, and tamper-resilient systems. Nevertheless, a blockchain application comes with trade-offs and needs to be considered on a case by case basis. In this paper, we examine the benefits and constraints of a blockchain application for three different approaches to achieving energy efficiency: (i) peer-to-peer (P2P) energy trading; (ii) White Certificate Scheme (WCS); and (iii) Energy Service Companies (ESCOs). For each of these cases, we apply a decision framework to assess blockchain feasibility and ou... [more]

Operating power systems with large amounts of renewables requires predicting future photovoltaic (PV) production with fine temporal and spatial resolution. State-of-the-art techniques combine numerical weather predictions with statistical post-processing, but their resolution is too coarse for applications such as local congestion management. In this paper we introduce computing methods for multi-site PV forecasting, which exploit the intuition that PV systems provide a dense network of simple weather stations. These methods rely entirely on production data and address the real-life challenges that come with them, such as noise and gaps. Our approach builds on graph signal processing for signal reconstruction and for forecasting with a linear, spatio-temporal autoregressive (ST-AR) model. It also introduces a data-driven clear-sky production estimation for normalization. The proposed framework was evaluated over one year on both 303 real PV systems under commercial monitoring across Sw... [more]

Smart grid (SG), an evolving concept in the modern power infrastructure, enables the two-way flow of electricity and data between the peers within the electricity system networks (ESN) and its clusters. The self-healing capabilities of SG allow the peers to become active partakers in ESN. In general, the SG is intended to replace the fossil fuel-rich conventional grid with the distributed energy resources (DER) and pools numerous existing and emerging know-hows like information and digital communications technologies together to manage countless operations. With this, the SG will able to “detect, react, and pro-act” to changes in usage and address multiple issues, thereby ensuring timely grid operations. However, the “detect, react, and pro-act” features in DER-based SG can only be accomplished at the fullest level with the use of technologies like Artificial Intelligence (AI), the Internet of Things (IoT), and the Blockchain (BC). The techniques associated with AI include fuzzy logic,... [more]

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Serious ice accretion will cause structural problems and ice flashover accidents, which result in outdoor insulator string operating problems in winter conditions. Previous investigations have revealed that the thicker and longer insulators are covered with ice, the icing degree becomes worse and icing accident probability increases. Therefore, an image processing method was proposed to extract the characteristics of the icicle length and Rg (ratio of the air gap length to the insulator length) of ice-covered insulators for monitoring the operation of iced outdoor insulator strings. The tests were conducted at the artificial climate room of CIGELE Laboratories recommended by IEEE Standard 1783/2009. The surface phenomena of the insulator during the ice accretion process were recorded by using a high-speed video camera. In the view of the ice in the background of the picture of fuzzy features and high image noise, a direct equalization algorithm is used to enhance the grayscale iced ima... [more]

Demand response (DR) can offer a wide range of advantages for electrical systems by facilitating the interaction and balance between supply and demand. However, DR always requires a central agent, giving rise to issues of security and trust. Besides this, differences in user response cost characteristics are not taken into consideration during incentive pricing, which would affect the equal participation of users in DR and increase the costs borne by the electricity retail company. In this paper, a blockchain-enabled DR scheme with an individualized incentive pricing mode is proposed. First, a blockchain-enabled DR framework is proposed to promote the secure implementation of DR. Next, a dual-incentive mechanism is designed to successfully implement the blockchain to DR, which consists of a profit-based and a contribution-based model. An individualized incentive pricing mode is adopted in the profit-based model to decrease the imbalance in response frequency of users and reduce the cos... [more]

The recursive discrete Fourier transformation (RDFT) method can be used for grid voltage phase-locking and harmonic current detection in a shunt active power filter (SAPF). However, in weak power grids such as microgrids, significant errors might occur in the amplitude and phase detection due to grid frequency deviation. In this study, to resolve this problem, a directly modified RDFT (DMRDFT) method is proposed for SAPF weak grid application. Through theoretical analysis, the errors of phase and amplitude detection were found to consist of fixed error and fluctuating error. The fixed error is only determined by frequency deviation, whereas the fluctuating error is also related to the recursive pointer and the initial phase. The DMRDFT algorithm can obtain the real grid frequency through the calculation of the phase angle difference for two consecutive periods. Then it can employ the grid frequency deviation and the recursive pointer value to directly correct the detection results gath... [more]

In recent years, people have witnessed numerous Internet of Things (IoT)-based attacks with the exponential increase in the number of IoT devices. Alongside this, the means to secure IoT-based applications are maturing slower than our budding dependence on them. Moreover, the vulnerabilities in an IoT system are exploited in chains to penetrate deep into the network and yield more adverse aftereffects. To mitigate these issues, this paper gives unique insights for handling the growing vulnerabilities in common IoT devices and proposes a threat architecture for IoT, addressing threats in the context of a three-layer IoT reference architecture. Furthermore, the vulnerabilities exploited at the several IoT attack surfaces and the challenges they exert are explored. Thereafter, the challenges in quantifying the IoT vulnerabilities with the existing framework are also analyzed. The study also covers a case study on the Intelligent Transportation System, covering road transport and traffic c... [more]

In developed nations, the advent of distributed ledger technology is emerging as a new instrument for improving the traditional system in developing nations. Indeed, adopting blockchain technology is a necessary condition for the coming future of organizations. The distributed ledger technology provides better transparency and visibility. This study investigated the features that may influence the behavioral intention of energy experts to implement the distributed ledger technology for the energy management of developing countries. The proposed model is based on the Technology Acceptance Model construct and the diffusion of the innovation construct. Based on a survey of 178 experts working in the energy sector, the proposed model was tested using structural equation modeling. The findings showed that perceived ease of use, perceived usefulness, attitude, and cost saving had a positive and significant impact during the blockchain technology adoption. However, innovativeness showed a pos... [more]

Finding an appropriate technique to detect an islanding issue is one of the major challenges associated with the design of a resilient grid-linked photovoltaic-based distributed power generation (PV-DPG) system. In general, the technique used for islanding detection must be able to sense the disruptions from the electric grid and quickly disconnect PV-DPG from the grid. The quick disconnection of PV-DPG mostly avoids power quality problems, damage to power assets, voltage stability issues, and frequency instability. In this paper, a new islanding detection technique that is based on tunable Q-factor wavelet transform (TQWT) and an artificial neural network (ANN) is proposed for PV-DPG. The proposed approach consists of two steps: in the first step, the vital detection parameters are computed by performing simulations considering all possible switching transients, islanding events, and faults from the grid side. Then, the decomposition of obtained signals is done using TQWT on different... [more]

This paper presents a new algorithm for the detection of ferroresonance oscillations in medium voltage (MV) power systems. The proposed method is based on an analysis of estimated flux resulting from the voltage in open delta voltage transformer (VT) connection. The testing results proved that the new solution is capable of identifying quickly and reliably ferroresonance oscillations and it does not maloperate during faults. In addition, this method is simple for hardware implementation. The developed solution has been thoroughly tested on simulation runs (from the MATLAB2019b/Simulink program), as well as recorded signals.

In this work, a new time-frequency tool based on minimum-norm spectral estimation is introduced for multiple fault detection in induction motors. Several diagnostic techniques are available to identify certain faults in induction machines; however, they generally give acceptable results only for machines operating under stationary conditions. Induction motors rarely operate under stationary conditions as they are constantly affected by load oscillations, speed waves, unbalanced voltages, and other external conditions. To overcome this issue, different time-frequency analysis techniques have been proposed for fault detection in induction motors under non-stationary regimes. However, most of them have low-resolution, low-accuracy or both. The proposed method employs the minimum-norm spectral estimation to provide high frequency resolution and accuracy in the time-frequency domain. This technique exploits the advantages of non-stationary conditions, where mechanical and electrical stresse... [more]

Power quality and stability have become the most important issues in power system operations, Micro Grids, and Smart Grids. Sensitive equipment can be seriously damaged when exposed to unstable power swing conditions. An unstable system may cause serious damage to Micro Grid System elements such as generators, transformers, transmission lines, and so forth. Therefore, out-of-step detection is essential for the safe operation of a Micro Grid system. In general, Equal Area Criterion (EAC) is a method for evaluating the stability of Smart Grid systems. However, EAC can be performed only if it is possible to analyze the active power and generator angle. This paper presents an analysis of the trajectory of complex power using a mathematical model. The variation of complex power is analyzed using a mathematical method, and then the relationship between complex power and EAC is presented, and a simulation performed. Later, in part II, a novel out-of-step detection algorithm based on part I wi... [more]

The use of emerging technologies such as cloud computing, Internet of Things, and Big Data, is increasing as tools to assist the management of data and information related to energy systems grow. This allows for greater flexibility, scalability of solutions, optimization of energy use, and management of energy devices. In this sense, the objective of this research is to present the basic elements and requirements for the energy cloud and its management and discuss the main management challenges and opportunities for the development and diffusion of the energy cloud. This study was based on a systematic review carried out to identify the elements that compose the energy cloud and what is necessary for its management, and to list the challenges and opportunities that may be explored by researchers and practitioners. The results show that the layout for the energy cloud and its management can be structured in layers and management support blocks’ format. It was found that 70 basic element... [more]

Cybersecurity is a critical issue for Real-Time IoT applications since high performance and low latencies are required, along with security requirements to protect the large number of attack surfaces to which IoT devices are exposed. Elliptic Curve Cryptography (ECC) is largely adopted in an IoT context to provide security services such as key-exchange and digital signature. For Real-Time IoT applications, hardware acceleration for ECC-based algorithms can be mandatory to meet low-latency and low-power/energy requirements. In this paper, we propose a fast and configurable hardware accelerator for NIST P-256/-521 elliptic curves, developed in the context of the European Processor Initiative. The proposed architecture supports the most used cryptography schemes based on ECC such as Elliptic Curve Digital Signature Algorithm (ECDSA), Elliptic Curve Integrated Encryption Scheme (ECIES), Elliptic Curve Diffie-Hellman (ECDH) and Elliptic Curve Menezes-Qu-Vanstone (ECMQV). A modified version... [more]

One of the basic conditions for the successful implementation of energy demand-side management (EDM) in smart grids is the monitoring of different loads with an electrical load monitoring system. Energy and sustainability concerns present a multitude of issues that can be addressed using approaches of data mining and machine learning. However, resolving such problems due to the lack of publicly available datasets is cumbersome. In this study, we first designed an efficient energy disaggregation (ED) model and evaluated it on the basis of publicly available benchmark data from the Residential Energy Disaggregation Dataset (REDD), and then we aimed to advance ED research in smart grids using the Turkey Electrical Appliances Dataset (TEAD) containing household electricity usage data. In addition, the TEAD was evaluated using the proposed ED model tested with benchmark REDD data. The Internet of things (IoT) architecture with sensors and Node-Red software installations were established to... [more]

In this paper, the dynamic experimental identification of an inductive energy harvester for the conversion of vibration energy into electric power is presented. Recent advances and requirements in structural monitoring and vehicle diagnostic allow defining Autonomous Internet of Things (AIoT) systems that combine wireless sensor nodes with energy harvester devices properly designed considering the specific duty cycle. The proposed generator was based on an asymmetrical magnetic suspension and was addressed to structural monitoring applications on vehicles. The design of the interfaces of the electric, magnetic, and structural coupled systems forming the harvester are described including dynamic modeling and simulation. Finally, the results of laboratory tests were compared with the harvester dynamic response calculated through numerical simulations, and a good correspondence was obtained.

The role of distributor system operators is experiencing a gradual but relevant change to include enhanced ancillary and energy dispatch services needed to manage the increased power provided by intermittent distributed generations in medium voltage networks. In this context, the paper proposes the insertion, in strategic points of the network, of specific power electronic systems, denoted as active nodes, which permit the remote controllability of the active and reactive power flow. Such capabilities, as a further benefit, enable the distributor system operators to provide ancillary network services without requiring any procurement with distributed generation systems owners. In particular, the paper highlights the benefits of active nodes, demonstrating their capabilities in reducing the inverse power flow issues from medium to high voltage lines focusing on a network cluster including renewable energy resources. As a further novelty, this study has accounted for a real cluster opera... [more]

In the Industrial Internet of Things (IIoT), non-orthogonal multiple access (NOMA) has emerged as a viable multiple access method due to its superior efficiency. In this paper, a new power allocation technique for NOMA-enabled IIoT devices is presented with trade-offs between increasing energy efficiency and decreasing power consumption. We present a joint optimization of transmission rate and energy harvesting in simultaneous wireless information and power transfer (SWIPT) NOMA-enabled IIoT devices. With the power splitting (PS) approach, we examine how to improve overall transmission rate and harvested energy, simultaneously, while fulfilling the minimum rate and harvested energy needs of each IIoT device in a SWIPT-enabled NOMA system. An objective function is established by adding transmission rates obtained from information decoding and the transformed throughput from energy harvesting. The combination of management approaches with Industry 4.0 technology provides a viable strateg... [more]

Blockchain technology has emerging areas of deployment in diverse sectors and use cases. In this study, several potential application areas of blockchain with promising benefits have been identified in the natural gas industry. There is no single solution that can address different challenges and meet disparate requirements. Therefore, it is important to understand the needs of the natural gas industry and propose appropriate blockchain solutions. Moreover, in the literature, there is a lack of detailed case studies involving industrial experts from the natural gas sector. Expert opinion can be useful for prioritizing the most needed or expected blockchain application areas among several options. By considering privacy, authentication, speed, security, energy consumption, and costs, suitable blockchain types and consensus mechanisms can be determined. This study presents one of the first detailed case studies for tailored applications of blockchain in the natural gas industry. Through... [more]

Energy is at the center of human society and drives the technologies and overall human well-being. Today, artificial intelligence (AI) technologies are widely used for system modeling, prediction, control, and optimization in the energy sector. The internet of things (IoT) is the core of the third wave of the information industry revolution and AI. In the energy sector, tens of billions of IoT appliances are linked to the Internet, and these appliances generate massive amounts of data every day. Extracting useful information from the massive amount of data will be a very meaningful thing. Complex event processing (CEP) is a stream-based technique that can extract beneficial information from real-time data through pre-establishing pattern rules. The formulation of pattern rules requires strong domain expertise. Therefore, at present, the pattern rules of CEP still need to be manually formulated by domain experts. However, in the face of complex, massive amounts of IoT data, manually set... [more]

Electric vehicles (EVs) are becoming popular due to their efficiency, eco-friendliness, and the increasing cost of fossil fuel. EVs support a variety of apps because they house powerful processors and allow for increased connectivity. This makes them an attractive target of stealthy cryptomining malware. Recent incidents demonstrate that both the EV and its communication model are vulnerable to cryptojacking attacks. The goal of this research is to explore the extent to which cryptojacking impacts EVs in terms of recharging and cost. We assert that while cryptojacking provides a financial advantage to attackers, it can severely degrade efficiency and cause battery loss. In this paper we present a simulation model for connected EVs, the cryptomining software, and the road infrastructure. A novel framework is proposed that incorporates these models and allows an objective quantification of the extent of this economic damage and the advantage to the attacker. Our results indicate that bat... [more]

Increasing waste generation has become a significant issue over the globe due to the rapid increase in urbanization and industrialization. In the literature, many issues that have a direct impact on the increase of waste and the improper disposal of waste have been investigated. Most of the existing work in the literature has focused on providing a cost-efficient solution for the monitoring of garbage collection system using the Internet of Things (IoT). Though an IoT-based solution provides the real-time monitoring of a garbage collection system, it is limited to control the spreading of overspill and bad odor blowout gasses. The poor and inadequate disposal of waste produces toxic gases, and radiation in the environment has adverse effects on human health, the greenhouse system, and global warming. While considering the importance of air pollutants, it is imperative to monitor and forecast the concentration of air pollutants in addition to the management of the waste. In this paper,... [more]

With regard to the best electro-chemical efficiency of an active direct methanol fuel cell (DMFC), the stacks and their balance of plant (BOP) are complex to build and operate. The yield of making the large-scale stacks is difficult to improve. Therefore, a portable power station made of multiple simpler planar type stack modules with only appropriate semi-active BOPs was developed. A planar stack and its miniature BOP components are integrated into a semi-active DMFC stack module for easy production, assembly, and operation. An improved energy management system is designed to control multiple DMFC stack modules in parallel to enhance its power-generation capacity and stability so that the portability, environmental tolerance, and long-term durability become comparable to that of the active systems. A prototype of the power station was tested for 3600 h in an actual outdoor environment through winter and summer. Its performance and maintenance events are analyzed to validate its stabil... [more]

IoT-based applications operate in a client−server architecture, which requires a specific communication protocol. This protocol is used to establish the client−server communication model, allowing all clients of the system to perform specific tasks through internet communications. Many data communication protocols for the Internet of Things are used by IoT platforms, including message queuing telemetry transport (MQTT), advanced message queuing protocol (AMQP), MQTT for sensor networks (MQTT-SN), data distribution service (DDS), constrained application protocol (CoAP), and simple object access protocol (SOAP). These protocols only support single-topic messaging. Thus, in this work, an IoT message protocol that supports multi-topic messaging is proposed. This protocol will add a simple “brain” for IoT platforms in order to realize an intelligent IoT architecture. Moreover, it will enhance the traffic throughput by reducing the overheads of messages and the delay of multi-topic messaging... [more]