Miodrag Forcan

Wide-area voltage quality assessment represents one of the mandatory objectives for distribution system operators in the development of advanced distribution management systems supporting smart grid requirements. This paper introduces a zonal approach for wide-area temporary voltage quality evaluation in a distribution network. The concept of temporary voltage quality evaluation and assessment is recommended to incentivize active/online management of voltage quality issues. A decision support system based on simple deterministic rules is proposed for rating the voltage quality zones in a distribution network and making recommendations to the distribution system operator. Voltage RMS level, unbalance, and total harmonic distortion are considered voltage quality indices representing the inputs in the decision support system. Residential, commercial, and industrial load types are considered when setting the thresholds for voltage quality indices. The proposed zonal approach for the division of distribution networks in voltage quality zones is applied to the example of a typical European-type distribution network. The operation of a decision support system is tested using the developed distribution smart grid model. The following simulation case studies are conducted: loads with low power factors, manual voltage regulation at MV/LV transformers, unbalanced loads, integration of solar power plant, and nonlinear loads. The obtained simulation results reveal the benefits of the proposed voltage quality assessment approach. Cybersecurity challenges that may impact the proposed approach are addressed, including security vulnerabilities, data privacy, and resilience to cyber threats.

Wide area voltage quality assessment represents one of the mandatory objectives for distribution system operators in development of advanced distribution management systems supporting smart grid requirements. This paper introduces a zonal approach for wide area temporary voltage quality evaluation in distribution network. The concept of temporary voltage quality evaluation and assessment is recommended to incentivize active/online management of voltage quality issues. Decision support system based on the simple deterministic rules is proposed for rating the voltage quality zones in distribution network and making recommendations to distribution system operator. Voltage RMS level, unbalance, and total harmonic distortion are considered as voltage quality indices representing the inputs in decision support system. Residential, commercial, and industrial load types are considered in setting the thresholds for voltage quality indices. The proposed zonal approach for division of distribution network in voltage quality zones is applied to the example of a typical European-type distribution network. The operation of decision support system is tested using the developed distribution smart grid model. The following simulation case studies are conducted: loads with low power factors, manual voltage regulation at MV/LV transformers, unbalanced loads, integration of solar power plant, and nonlinear loads. The obtained simulation results reveal the benefits of the proposed voltage quality assessment approach.

Global warming and its negative effect on the environment pose a great threat to the future of mankind. In order to overcome these challenges, EU countries have set the target of becoming climate neutral by 2050, a path defined through the policies of the European Green Deal. The Republic of Serbia and Bosnia and Herzegovina also agreed upon the same goal through the endorsement of the Green Agenda for the Western Balkans. One of the means to achieve this goal is by increasing the share of renewable energy sources. In this paper, we analyze the feasibility, challenges, and potential issues of substituting conventional traffic light signalization with signalization based on renewable energy sources on a national scale. An ad hoc questionnaire was used to collect data from representatives of most of the municipalities in the Republic of Srpska entity in Bosnia and Herzegovina and representatives of the city of Novi Sad in Serbia. In the city of Novi Sad, personal interviews were also carried out to collect additional information. The results of this research show that the implementation of solar-powered traffic lights is economically and environmentally viable. These results will provide the basis for understanding the benefits and challenges in the case of the application of traffic light signalization based on renewable energy sources.

Fifth-Generation (5G) networks have a potential to accelerate power system transition to a flexible, softwarized, data-driven, and intelligent grid. With their evolving support for Machine Learning (ML)/Artificial Intelligence (AI) functions, 5G networks are expected to enable novel data-centric Smart Grid (SG) services. In this paper, we explore how data-driven SG services could be integrated with ML/AI-enabled 5G networks in a symbiotic relationship. We focus on the State Estimation (SE) function as a key element of the energy management system and focus on two main questions. Firstly, in a tutorial fashion, we present an overview on how distributed SE can be integrated with the elements of the 5G core network and radio access network architecture. Secondly, we present and compare two powerful distributed SE methods based on: i) graphical models and belief propagation, and ii) graph neural networks. We discuss their performance and capability to support a near real-time distributed SE via 5G network, taking into account communication delays.

The potential of the combined application of Cloud computing and the fifth generation of cellular network technology (5G) in Smart Grid (SG) could be revolutionary in terms of empowering the Advanced Metering Infrastructure (AMI). The model of a real-time 5G-based communication system for remote reading of Smart Meters' data is developed and presented in this paper. Online monitoring of power demand has been performed using the Cloud-based platform ThingSpeak. The proposed 5G communication model and online monitoring function have been tested and validated using a power demand variation scenario in a well-known IEEE 13 node network. The obtained results confirm the model accuracy and reveal the potential of AMI based on realtime data transmission between Smart meters (SM) and Cloud computing platform using a 5G communication network.