In the electricity market, different pricing models can be applied to increase market competitiveness. Different electricity systems use different market structures. Uniform marginal pricing, zonal marginal pricing, and nodal marginal pricing methods are commonly used market structures. For markets wishing to move from a uniform pricing structure to a more competitive zonal pricing structure, the determination of price zones is critical for achieving a competitive market that generates accurate price signals. Three different pricing zone detection algorithms are analyzed in this paper including the k-means clustering and queen/rook spatially constraint clustering. Finally, the results of a case study for the Turkish electricity system are shared to compare each method.

In this paper, a device with swinging plate electrodes has been proposed to measure contact electrification of a liquid sample. The proposed structure is composed of two parallel metallic plates immersed in a dielectric liquid. One of the plates is swinging with a constant frequency in a range from 0.4 to 4 Hz. The paper investigates the dependence in time and frequency of electrode velocity and streaming electrification. The measured current occurs for a very low intermittent velocity of less than 10 mm/s. In this range, the electrification current is around 50 pA. For higher velocities of up to 150 mm/s, the current is at the level of 1200 pA. The time−frequency characteristic using short-time Fourier transform shows no temporal changes in the frequency spectrum. The dependence of electrification on shuttle speed was calculated and it can be approximated with a second order polynomial model with the determination coefficient higher than 0.9. The advantage of the sensor is the ability... [more]

For the next generation of manufacturing, the industrial internet of things (IoT) has been considered as a key technology that enables smart factories, in which sensors transfer measured data, actuators are controlled, and systems are connected wirelessly. In particular, the wireless sensor network (WSN) needs to operate with low cost, low power (energy), and narrow spectrum, which are the most technical challenges for industrial IoT networks. In general, a relay-assisted communication network has been known to overcome scarce energy problems, and a spectrum-sharing technique has been considered as a promising technique for the radio spectrum shortage problem. In this paper, we propose a phase steering based hybrid cooperative relaying (PSHCR) technique for the generic relay-assisted spectrum-shared WSN, which consists of a secondary transmitter, multiple secondary relays (SRs), a secondary access point, and multiple primary access points. Basically, SRs in the proposed PSHCR technique... [more]

Solar energy is the most promising renewable resource with an unbounded energy source, capable of meeting all human energy requirements. Solar Photovoltaic (SPV) is an effective approach to convert sunlight into electricity, and it has a promising future with consistently rising energy demand. In this work, we propose a smart solution of outdoor performance characterization of the SPV module utilizing a robust, lightweight, portable, and economical Outdoor Test Facility (OTF) with the Internet of Things (IoT) capability. This approach is focused on the capacitive load-based method, which offers improved accuracy and cost-effective data logging using Raspberry Pi and enables the OTF to sweep during the characterization of the SPV module automatically. A demonstration using an experimental setup is also provided in the paper to validate the proposed OTF. This paper further discusses the advantages of using the capacitive load approach over the resistive load approach. IoT’s inherent bene... [more]

This paper, for the first time, investigates the possibility of exploiting a nonlinear bistable snap-through buckling structure employing piezoelectric transducers, to implement an autonomous sensor of mechanical vibrations, with an embedded energy harvesting functionality. The device is operated in the presence of noisy vibrations superimposed on a subthreshold deterministic (sinusoidal) input signal. While the capability of the device to harvest a significant amount of energy has been demonstrated in previous works, here, we focus on the signal processing methodology aimed to extract from the sensor output the information about the noise level (in terms of the standard deviation) and the root mean square amplitude of the deterministic component. The developed methodology, supported by experimental evidence, removes the contribution to the overall piezoelectric output voltage ascribable to the deterministic component using a thresholding and windowing algorithm. The contribution to th... [more]

Current Peer-to-Peer (P2P) energy market models raise serious concerns regarding the confidentiality and integrity of energy consumption, trading and billing data. While Distributed Ledger Technology (DLT) systems (e.g., blockchain) have been proposed to enhance security, an attacker could damage other parts of the model, such as its infrastructure: an adversarial attacker could target the communication between entities by, e.g., eavesdropping or modifying data. The main goal of this paper is to propose a model for a decentralised P2P marketplace for trading energy, which addresses the problem of developing security and privacy-aware environments. Additionally, a Multi-Agent System (MAS) architecture is presented with a focus on security and sustainability. In order to propose a solution to DLT’s scalability issues (i.e., through transaction confirmation delays), off-chain state channels are considered for the energy negotiation and resolution processes. Additionally, a STRIDE (spoofin... [more]

In recent years, machine learning applications have received increasing interest from power system researchers. The successful performance of these applications is dependent on the availability of extensive and diverse datasets for the training and validation of machine learning frameworks. However, power systems operate at quasi-steady-state conditions for most of the time, and the measurements corresponding to these states provide limited novel knowledge for the development of machine learning applications. In this paper, a data mining approach based on optimization techniques is proposed for filtering root-mean-square (RMS) voltage profiles and identifying unusual measurements within triggerless power quality datasets. Then, datasets with equal representation between event and non-event observations are created so that machine learning algorithms can extract useful insights from the rare but important event observations. The proposed framework is demonstrated and validated with both... [more]

The transit-time ultrasonic gas flowmeter plays a vital part in the measurement field with its unique advantages. In recent years, it has developed into a research hotspot in the field of gas flow measurement. However, while the ultrasonic signal propagates in gas, the amplitude fluctuation of the ultrasonic signal is produced under the condition of energy attenuation and unstable flow field. This leads to inaccurate transit time of ultrasonic signal that causes flow calculation errors. Aiming at this problem, a signal processing method is proposed in this paper for the transit-time ultrasonic gas flowmeter based on the peak ratio characteristic value sequence (PRCVS). Through the research on the mathematical model of ultrasonic signal, the ratio of the amplitude of adjacent peaks is defined as the peak ratio characteristic value (PRCV) of the peak. According to the corresponding relationship between the PRCV and the peak serial number, a set of reference PRCVS is established. By match... [more]

Electric arcing is a common problem in DC power systems. To overcome this problem, the electric arc detection algorithm has been developed as a faster alternative to existing algorithms. The following issues are addressed in this paper: The calculation of the proposed algorithm of incremental decomposition of the signal over time; the computational complexity of Fast Fourier Transform (FFT) and the incremental decomposition; the test bench used to measure electric arcs at given parameters; the analysis of measurements using FFT; and the analysis of measurements using incremental decomposition. The parameters are the DC voltage, electric load, and width of the gap between electrodes. The results showed that the proposed algorithm allows for a faster calculation—about seven times faster than FFT—and cheaper implementation in electric arc detection devices than FFT.

The conventional direct device discovery scheme which uses the random access protocol and encounters contentions or collisions is highly energy and time-consuming. To reduce the energy consumption of user equipments (UEs), this work proposes a two-phase hybrid device discovery mechanism for device-to-device (D2D) communications. In the first phase, the evolved packet core (EPC) or base station (BS) uses the location information of UEs to judge whether two UEs are able to establish a D2D link. In the second phase, UEs use Wi-Fi Direct to discover their target UEs. The BS directly assigns UEs’ states and allocates appropriate Wi-Fi channels to UEs. UEs no longer have to search or listen to all channels, thus reducing the discovery delay. The proposed mechanism saves cellular spectrum resources because it uses unlicensed bands for D2D discovery and communications. The performance of the proposed hybrid D2D discovery mechanism is also theoretically analyzed in this paper. Evaluation result... [more]

The Internet has been going through significant transformations and changing the world around us. We can also see the Internet to be used in many areas, for innumerable purposes, and, currently, it is even used by objects. This evolution leads to the Internet of Things (IoT) paradigm. This new concept can be defined as a system composed of storage resources, sensor devices, controllers, applications, and network infrastructure, in order to provide specific services to its users. Since IoT comprises heterogeneous components, the creation of these systems, the communication, and maintenance of their components became a complex task. In this paper, we present a dependability model to evaluate an IoT system. Amid different systems, we chose to assess availability in a smart building. The proposed models allow us to calculate estimations of other measures besides steady-state availability, such as reliability. Thus, it was possible to notice that there was no considerable gain of availabili... [more]

The Wireless Sensor Network (WSN) has seen rapid growth in the development of real-time applications due to its ease of management and cost-effective attributes. However, the balance between optimization of network lifetime and load distribution between sensor nodes is a critical matter for the development of energy-efficient routing solutions. Recently, many solutions have been proposed for constraint-based networks using the cloud paradigm. However, they achieve network scalability with the additional cost of routing overheads and network latency. Moreover, the sensors’ data is transmitted towards application users over the uncertain medium, which leads to compromised data security and its integrity. Therefore, this work proposes a light-weight secure and energy-efficient fog-based routing (SEFR) protocol to minimize data latency and increase energy management. It exploits the Quality of Service (QoS) factors and facilitates time-sensitive applications with network edges. Moreover, t... [more]

Tool condition monitoring (TCM) systems are key technologies for ensuring machining efficiency. Despite the large number of TCM solutions, these systems have not been implemented in industry, especially in small- and medium-sized enterprises (SMEs), mainly because of the need for invasive sensors, time-consuming deployment solutions and a lack of straightforward, scalable solutions from the laboratory. The implementation of TCM solutions for the new era of the Industry 4.0 is encouraging practitioners to look for systems based on IoT (Internet of Things) platforms with plug and play capabilities, minimum interruption time during setup and minimal experimental tests. In this paper, we propose a TCM system based on low-cost and non-invasive sensors that are plug and play devices, an IoT platform for fast deployment and a mobile app for receiving operator feedback. The system is based on a sensing node by Arduino Uno Wi-Fi that acts as an edge-computing node to extract a similarity index... [more]

High-impedance faults (HIFs) represent one of the biggest challenges in power distribution networks. An HIF occurs when an electrical conductor unintentionally comes into contact with a highly resistive medium, resulting in a fault current lower than 75 amperes in medium-voltage circuits. Under such condition, the fault current is relatively close in value to the normal drawn ampere from the load, resulting in a condition of blindness towards HIFs by conventional overcurrent relays. This paper intends to review the literature related to the HIF phenomenon including models and characteristics. In this work, detection, classification, and location methodologies are reviewed. In addition, diagnosis techniques are categorized, evaluated, and compared with one another. Finally, disadvantages of current approaches and a look ahead to the future of fault diagnosis are discussed.

In the study, an interrupting performance test on the 145 kV gas circuit breaker is performed according to three different gases: SF6, g3 (5% NovecTM4710 with 95% CO2), and CO2(70%)/O2(30%) gases. Thanks to research advancements, it is confirmed that CO2 and g3 (5% NovecTM 4710) gases, respectively, have 40% and 75% dielectric strength, compared to that of SF6 gas. The filling pressure and transient recovery voltage criteria of each gas were determined differently in order to compare the maximum interrupting performance of each gas. The pressure of SF6 gas was determined to be 5.5 bar, which is typically used in circuit breakers. The pressure of the other two gases was determined to be 8.0 bar (the maximum available pressure of the test circuit breaker) to find the maximum interrupting performance. Moreover, the rate-of-rise of transient recovery voltage of SF6 was determined as 10 kV/μs, which is the value at the state of maximum interrupting performance of the test circuit breaker wi... [more]

The paper is devoted to computer simulations of the distribution and time evolution of the temperature in a wooden house in summer. The goal of simulations was to assess the effect of covering walls inside the house with a PCM (phase change material) on its passive cooling, which prevents the undesired overheating of the house and provides the required thermal comfort for the occupants under warm summer days. Computer simulations were performed by the COMSOL Multiphysics software (COMSOL Inc., Stockholm, Sweden). A model of a house without the PCM coverage was compared with models of houses in which the PCM was located on all walls, except a floor, and on a wall opposite the window. Results of simulations proved that the wood wall thickness and PCMs location influence overheating the wooden house. Under studied conditions, the coverage of a wall opposite the window best eliminated extremes of the air temperature inside the house. The maximum temperature decrease was 3.9 °C (i.e., drop... [more]

Finding new sustainable energy sources or improving the efficiencies of the existing ones represents a very important research and development direction. The hybridization approach is one solution for increasing the efficiency of the existing energy sources. In the case of photovoltaic technology, the hybridization of the photovoltaic panels (PV) with thermoelectric generators (TEGs) has become a more interesting solution for the research community in the last decade. Thus, a comprehensive review of the characterization methods and instruments used in PV-TEG hybrid system study represents the objective of this work. PV and TEG equivalent circuits are presented. The instruments and software applications used for the measurements and simulations are presented and analyzed. The analysis of the literature reveals that there are many papers that offer partial or no information about the instruments used or about the measurement quality (accuracies, uncertainties, etc.). In hybrid system mod... [more]

With the tremendous increase of heterogeneous Internet of Things (IoT) devices and the different service requirements of these IoT applications, machine-type communication (MTC) has attracted considerable attention from both industry and academia. Owing to the prominent advantages of supporting pervasive connectivity and wide area coverage, the cellular network is advocated as the potential wireless solution to realize IoT deployment for MTC, and this creative network paradigm is called the cellular IoT (C-IoT). In this paper, we propose the three-layer structured C-IoT architecture for MTC and review the challenges for deploying green C-IoT. Then, effective strategies for realizing green C-IoT are presented, including the energy efficient and energy harvesting schemes. We put forward several strategies to make the C-IoT run in an energy-saving manner, such as efficient random access and barring mechanisms, self-adapting machine learning predictions, scheduling optimization, resource a... [more]

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]