The transformation of passive distribution systems to more active ones thanks to the increased penetration of distributed energy resources, such as dispersed generators, flexible demand, distributed storage, and electric vehicles, creates the necessity of an enhanced test system for distribution systems planning and operation studies. The value of the proposed test system, is that it provides an appropriate and comprehensive benchmark for future researches concerning distribution systems. The proposed test system is developed by modifying and updating the well-known 33 bus distribution system from Baran & Wu. It comprises both forms of balanced and unbalanced three-phase power systems, including new details on the integration of distributed and renewable generation units, reactive power compensation assets, reconfiguration infrastructures and appropriate datasets of load and renewable generation profiles for different case studies.

An Enhanced IEEE 33 Bus Benchmark Test System for Distribution System Studies

Faults in smart grid systems: Monitoring, detection and classification

A critical and comprehensive review on power quality disturbance detection and classification

Cloud-Fog-based approach for Smart Grid monitoring

The United Nations’ sustainable development goals have emphasized implementing sustainability to ensure environmental security for the future. Affordable energy, clean energy, and innovation in infrastructure are the relevant sustainable development goals that are applied to the energy sector. At present, digital technologies have a significant capability to realize the target of sustainability in energy. With this motivation, the study aims to discuss the significance of different digital technologies such as the Internet of Things (IoT), artificial intelligence (AI), edge computing, blockchain, and big data and their implementation in the different stages of energy such as generation, distribution, transmission, smart grid, and energy trading. The study also discusses the different architecture that has been implemented by previous studies for smart grid computing. Additionally, we addressed IoT-based microgrids, IoT services in electrical equipment, and blockchain-based energy trading. Finally, the article discusses the challenges and recommendations for the effective implementation of digital technologies in the energy sector for meeting sustainability. Big data for energy analytics, digital twins in smart grid modeling, virtual power plants with Metaverse, and green IoT are the major vital recommendations that are discussed in this study for future enhancement.

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Energy System 4.0: Digitalization of the Energy Sector with Inclination towards Sustainability

In order to enable voltage ride-through operation, fast and reliable voltage dips detection is necessary. It has been noticed by the analysis of a huge number of measurement results recorded in-field, in laboratory, and obtained by simulation that the voltage dips may be characterized by specific low-order voltage harmonics pattern, which appears at the beginning and at the end of the voltage dips. This feature is named harmonic footprint. This paper proposes a new method of voltage dips detection based on harmonic footprint as part of smart algorithm for detection and classification of power quality events. The aim is to achieve reliable smart voltage dips detection in 1 ms range. Several methods for harmonic estimation in real time were compared in order to choose the optimal one. The footprint is modeled by mathematical function and applied for voltage dips smart detection using recurrent neural network. The proposed method was tested for voltage dips detection analyzing signals from measurement in the real distribution grid (680 records), computer simulations using IEEE-13 bus test grid, and testing in the laboratory. The reliability (detection rate) and speed of voltage dips detection are tested and verified. Furthermore, the future research directions for presented method are outlined.

Smart Detection of Voltage Dips Using Voltage Harmonics Footprint

Grid condition information extraction is very important for converter control systems in order to perform special functionalities, especially grid support during low voltage ride through (LVRT). As a part of grid condition detection, the voltage sag detection provides information about the start of a fault and obtains indices that determine the behavior of the whole control system of the converter during a fault. Estimation of the magnitude of voltage sag (MoVS) is essential for obtaining proper grid support. This paper presents an algorithm for MoVS (as defined in IEEE Std 1564-2014) prediction. The existence of correlation between magnitudes of a set of low-order harmonics during the transient of voltage PQ events with MoVS is for the first time determined and statistically proved. Correlation is mathematically formulated and the prediction function is obtained on the basis of real grid measurements. Complete algorithm for magnitude prediction is explained, and its possible application in distributed generation control is prese-nted. It is shown that significant time gain is achieved, which may be used as an additional benefit in LVRT operation.

Magnitude of Voltage Sags Prediction Based on the Harmonic Footprint for Application in DG Control System

The paper presents an overview of the electric distribution test grids issued
 by different technical institutions. They are used for testing different
 scenarios in operation of a grid for research, benchmarking, comparison and
 other purposes. Their types, main characteristics, features as well as
 application possibilities are shown. Recently, these grids are modified with
 inclusion of distributed generation. An example of modification and
 application of the IEEE 13-bus for testing effects of faults in cases without
 and with a distributed generator connection to the grid is presented.

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A brief overview of the distribution test grids with a distributed generation inclusion case study

The paper describes voltage dips detection method in cases of grid-tie inverter systems. A newly developed harmonic estimation algorithm, Reduced FFT (RFFT), has been applied. The grid-tie inverter system has been modelled and simulated in the Matlab/SimPowerSystems environment. Laboratory experiment was carried out with dSPACE control hardware. The voltage dips were produced by grid emulator. For voltage dips detection the algorithm, which is able to monitor the 3rd harmonic is considered suitable in most of the cases. It is shown, both in simulation and experiments that the proposed method is reliable, successful and quick enough. It is much faster than existing ones, i.e. detection time is less than one half-period, so it is more convenient for grid-tie inverter protection purposes.

Voltage dips detection in a system with grid-tie inverter

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 and presents several clear advantages over existing solutions based on conventional blockchains. Therefore, the proposed approach represents a promising, robust solution to the smart grid decentralized power trading problem.

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Aleksandar M. Stanisavljevic

Papers

Smart Detection of Voltage Dips Using Voltage Harmonics Footprint

Magnitude of Voltage Sags Prediction Based on the Harmonic Footprint for Application in DG Control System

A brief overview of the distribution test grids with a distributed generation inclusion case study

Voltage dips detection in a system with grid-tie inverter

A Distributed Ledger-Based Automated Marketplace for the Decentralized Trading of Renewable Energy in Smart Grids