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In the development of electric, electronic, and information technologies in the medium and low voltage plants, designers reach out the moment of decision when it is necessary to choose equipment and systems that will be optimal for the set requirements. The smart grid concept in the power industry, especially at medium and low voltage, imposes the choice of equipment that will provide more data. The result of this development is the appearance of non-conventional instrument transformers and voltage sensors at medium and low voltage. Their dimensions, price, and functionality fit into these trends. Non-conventional instrument transformers (NCIT) and voltage sensors (VS) compete with conventional current transformers (CCT) and voltage transformers (VT). The paper discusses the specifics of replacing conventional with non-conventional instrument transformers and compares the measurement characteristics of both types, functionality, advantages, and disadvantages of both solutions

Fuzzy logic provides an appropriate way to incorporate an individual’s knowledge into expert systems using descriptive language expressions. A large number of commercially successful applications in power energy systems show that fuzzy logic can be used very successfully, especially during disturbances. During a disturbance, automation of system fault analysis and information processing becomes desirable and necessary, due to the large increase in data collected from the system. The paper analyzes the possibilities for implementing automated fault analysis systems based on digital fault recorders, digital protection relays, sequence of events recorders, intelligent alarm processors and lightning location systems. These systems are interconnected with Intelligent Electronic Devices, supervisory control and data acquisition systems, remote terminal units or protection devices which are combined with different intelligent electronic devices in the system. For large number of devices and data, fuzzy systems have proven to be effective in detecting and classifying power system failures.

Islanding problem of DG-s in distribution network (DN) comes with development and implementation of renewable energy sources (RES) as distributed generator (DG). This research introduces new hybrid method for islanding detection of DC/AC inverter based DG in low voltage (LV) DN. Proposed technique is combination of active and passive technique: frequency change at given moment and rate of change of RMS voltage. Proposed method heavily exploit sinusoidal function interpolation due to Fourier transformation when Gibbs phenomenon occurs. To prove its effectiveness several test conducted based on different active load conditions and multiple DGs. Simulation results shows precision with allowed impact on power quality according to standard EN 50160. Proposed method shows good results as in low power consumption regime thus in high power regime. Hybrid method gives non detection zone (NDZ) smaller than individual islanding detection hybrid methods of frequency and under voltage based by combining those techniques as active and passive

In this paper, a measurement device based on "Open Source" components of hardware and software will be presented. This device has been used to measure voltages and currents of a low-voltage (LV) networks, on which a virtually unlimited number of sensors can be added, and the device is assembled of components available on electronic components Internet. The used hardware for this project is based on Arduino UNO R3 motherboard and peripheral sensors needed for measurement of the mentioned data. The Arduino motherboard is not only the sole peace of hardware, but it can also act as a Wi- Fi router for the devices and the laptop used for data presentation and server side computations. The server is programmed in Java programming language and is open source. Main goal was to make smart meter by the “Do It Yourself” method spending as much less founds as it is possible, by keeping user friendly interface, data validity, accuracy of measurement and ease of use for final user. Data gathering is achieved in almost 1 ms which is excellent for custom made device. However, the measured values should be calculated to RMS values to be usable for energy analyzes and further processing of information.

The basic challenge of today’s energy system is to increase the flexibility of the network in the context of greater energy demands and the increasing presence of intermittent renewable energy sources. The answer is in advanced networks (Smart Grid) based on an active approach to the demands of end users who can contribute with their energy portfolio to increase system flexibility in real time. To meet the needs of end users and all other participants it is necessary to offer adequate energy services that will meet these needs at an economically acceptable price. Energy services are based on several basic Active Demand products. Successful modelling of energy services, with the implementation of various end user activation strategies, is key to starting an energy market where small and large users, producers and intermediaries will be able to meet their needs and benefit. Each of the services is modelled according to the needs of each participant, and as such, in accordance with the current situation and the available energy resources are offered on the market in real time. To start such a market process, a new participant, Aggregator, is being introduced, who arbitrates in the exchange of energy services at the local and regional energy market.

This paper presents an arc flash risk assessment procedure using different computer tools from different countries. Different computation methods according new requirements in NFPA 70E (2018), IEEE 1584 and DGUV I 203-077 standard. Three different software are used and compared incident energy (E I ) or full energy (W E ), arc flash boundary and the level of Personnel Protection Equipment (PPE). Arc flash risk assessment is today a mandatory part of each risk assessment for electrical workplaces and several recommendations exist in different countries. National OSHA rules in USA, EN 50110-1 in Europe and PPE Directive in Europe. A short circuit analysis is performed to calculate the values of arching currents and compute arc flash energy dissipated at busbars at HV and LV voltage busbars. Worst case scenario approach is used to examine what is highest level of Arc Thermal Performance Value (ATPV). There different software tools where used in computation: “EasyPower Arc Flash” (USA), BSD Arc Calculator (Germany) and RENblad 1710 (Norway). A practical sample case is presented and arc flash energy is computed and PPE recommended for high and low voltage busbars in one stone pit facility in Slovenia and biomass power plant in Croatia.

This paper presents a method for computation of arc flash incident energy in mixed alternating current (AC)/direct current (DC) systems with DC units such as strings, panel cabinets, inverters in Photovoltaic (PV) power plant, as well as on AC side behind the inverters connected to the distribution network. It also gives measures to reduce the risk and consequences of electrical arc flash that may occur due to live work or maintenance on DC and AC part of the PV power plant. By exploiting an advanced smart protection software for coordination of protective devices, this paper shows how we can reduce the risk of these harmful consequences for the personnel working in such power plants. An example case of a PV power plant with rated power of 300 kW is modelled with with its all components and existing protection settings. Then, the power of the electric arc flash will be evaluated using the suggested analytical-simulation-based method according to IEEE 1584 standard, followed by selection of proper protection devices settings for minimum arc power and risk for the staff.

In the last years, besides the implementation in the smart city applications, IoT has also found significant place in the agricultural and food production process. In the paper we present an innovative, power efficient and highly scalable IoT agricultural system. This system is based on LoRaWAN network for long range and low power consumption data transmission from the sensor nodes to the cloud services. Our system of cloud services is highly scalable and utilizes data stream for analytics purposes. In our case study we show some preliminary results for grape farm.

Energy is the most important resource in state-of-the-art Internet of Things solutions. There are a lot of concepts and techniques dedicated to save energy, mainly focused to reduce transmission, since the energy used for preprocessing (encoding) is incomparable smaller than energy used for broadcasting. If applications do not require real-time measurements, data compression is one solution to energy saving problem. The goal of this paper was to develop new coding scheme for delta compression, that can be used for efficient data compression of temporally correlated data, such as temperature measurements coming from different smart devices. We proved that our coding scheme can achieve up to 85% energy saving. Compared to other coding techniques, our scheme has greater compression ratio and lower memory requirements.

The paper presents an example of modeling high-voltage line with classical columns and pillars compacted with the same lines and testing out the model in the programming tool DIgSILENT with actual measured data for Single Line to Ground Fault with the use of ARs. The parameters of the classical and compacted 400 kV transmission line are entered into the model in the example of 400 kV line Tuzla 4 — Visegrad, and Single Line to Ground Fault was simulated and compared with the actual measured data. Afterwards, lines with classical columns and pillars compacted with the lines were compared and assessed if a readjustment of distance protection on the line is necessary. The SIEMENS numerical distance relay 7SA was used.

Efficient and reliable data dissemination is crucial to most of the vehicular network applications. However, the inherent vehicular network characteristics make data dissemination a challenging task. Typically, the existing algorithms generate too many redundant packets that saturate the network, thus causing frequent channel contention and packet collisions. To tackle these problems we propose an Efficient Encounter-based Event Dissemination Protocol. By exploiting the distance and the encountering probability of the vehicles to the event, the proposed protocol is capable of performing an efficient data dissemination in both urban and highway scenarios. An extensive set of simulation experiments was conducted to evaluate the performance of the proposed algorithms. Results showed that the proposed protocol outperforms the selected approaches in terms of retransmission packets and delivery ratio.

The paper analyzes ways on how to establish and sustain an active participation of consumers in the modern Smart Grid Architecture based on the Active Demand Approach by proposing the conceptual framework that supports it. The planning and implementation of the power system is a very demanding task, requiring that the electrical energy production and consumption are always equal. In order to efficiently manage such system, and its safety, an appropriate level of flexibility must be present. Today, the generators acting on the production side are the main flexibility enablers, and there is a very low level of flexibility available on the consumer side. From the technical point of view, it is necessary to establish a smart infrastructure that will be networked by the data transmission chain, in order to provide timely, accurate and highly secure transfer of required data. In this paper, we present the demand response approach and the respective solution on how to achieve the sufficient level of the consumer flexibility in such proposed model implementation. With addressing different technical aspects and IoT (Internet of Things) the envisaged integration is elaborated by taking into account the important requirements of its IT infrastructure, by analyzing the robustness, reliability and safety issues of the proposed system.

This article presents results of high voltage (HV) 400 kV circuit breakers (CB) testing in high induction environment. The most common case of new HV circuit breakers installation is replacement of old circuit breakers in existing power plants or substations. After installation and before energization of any HV equipment it is needed to test and assure the functionality. A circuit breaker, as an important and complex element, needs to be tested according to IEC 62271-100 standard on the site. The test procedure was carried out using direct current (DC) on the terminals of CB. Recorded signal was an error duo to impact of strong voltage induction in the conditions of CB testing. This paper proposes the new method for assessment of mechanical parameters of HV circuit breakers.

OTLM (Overhead Transmission Line Monitoring) is a system solution for monitoring and rating of existing and new overhead lines (OHL) based on real-time monitoring of conductor temperature, sag, load, and weather conditions in order to ensure save maximum utilization of transmission line ampacity. Successful development and more than 10 years' of experience in using the OTLM system on transmission networks in several countries all over the world has initiated some system upgrades to ensure even more crucial information on OHL behaviour. The existing functionality of conductor temperature measurements (used for static rating-STR) was initially combined with a weather station measurement that enables the determination of dynamic rating (DTR). With additional inclination (sag/tension) measurements, we developed the OTLM-SAG application. With this additional feature we are able to determine the sag on critical spans. This additional information is especially useful in case of OHL crossings over roads, railroads, other overhead lines, etc. Additionally, measured data like angle (sag) is implemented to the software application to detect ice overloads or fallen trees. The mathematical relationship between the conductor's tensile force and sag is crucial for the calculation of the conductor's expansion (tension) and final length over a constant span distance. The reliability of ice thickness calculations mainly depends on the accuracy of conductor temperature and angle/sag measurements. The OTLM-ICE application enables the operator of the transmission network to monitor sag and clearance changes on a conductor, subjected to ice overloads. The operator can optimize and determine the suitable ampacity of transmission lines in order to prevent the damage in early phases of ice-rain.

Photovoltaic systems as part of larger distribution systems for the production of electricity have non-linear current-voltage characteristics. These characteristics depend on the temperature of the solar cells and insolation of panels. The method for the search of the maximum power or MPPT is widely known, and there are many offered algorithm solutions. The aim of this paper is to present ANFIS (Adaptive Neural Fuzzy System Inference) as a method of computer intelligence in the search function of maximum power or maximum utilization of the PV system, without prior knowledge of the system. MPPT ANFIS will be located between the PV panels and devices for voltage regulation. Inputs used to go inside the fuzzy regulators and outputs of the fuzzy regulators are going into power changing device. The advantage of this method is the low cost of implementation because it uses embedded computer systems and does not require additional sensors for measuring temperature and insolation. It is very easy to upgrade in the case of increasing the knowledge base used in FIS membership function. Everything is simulated by MATLAB/Simulink software on the one-phase IBC system.