Global trends such as the growing share of renewable energy sources in the generation mix, electrification, e-mobility, and the increasing number of prosumers reshape the electricity value chain, and distribution systems are necessarily affected. These systems were planned, developed, and operated as a passive structure for decades with low level of observability. Due to the increasing number of system states, real time operation planning and flexibility services are the key in transition to an active grid management. In this pathway, distribution system state estimation (DSSE) has a great potential, but the real demonstration of this technique is in an early stage, especially on low-voltage level. This paper focuses on the gap between theory and practice and summarizes the limits of low-voltage DSSE implementation. The literature and the main findings follow the general structure of a state estimation process (meter placement, bad data detection, observability, etc.) giving a more essential and traceable overview structure. Moreover, the paper provides a comprehensive mapping of the possible use-cases state estimation and evaluates 27 different experimental sites to conclude on the practical applicability aspects.

Due to the enormous increase in the interconnection of electric vehicles (EVs) into utility power grids, more and more challenges are arising in modern power systems. To handle these challenges, many attempts have been proposed to achieve the satisfactory performance of EV charging/discharging, the improvement of utility power grids operation, and an adaptive coordination strategy for the EV-grid connection. Energy storage systems (ESSs) may play a vital role in this process by injecting/absorbing their energy into/from the grid, including EVs. This paper proposes an adaptive coordination method based on fuzzy logic control (FLC) for EVs and superconducting magnetic energy storage (SMES) to enhance the charge and discharge processes of EVs during off and on peak loading periods. FLC is utilized to organize the charging/discharging process for both EVs and SMES. The state of charge (SoC) of SMES and EVs is considered as the input for EVs' FLC besides the electricity price (EP) signal. To verify the effectiveness of the proposed coordination method, uncertain numbers of EVs, the rate of EP, and daily residential load profile are included in this study. The results demonstrate that the proposed coordination method can improve the performance of EV charging/discharging. Moreover, the cooperative operation with SMES and the reliability improvement of the utility power are preserved using the proposed coordination strategy.

The superior access to renewable sources in modern power systems increases the fluctuations in system voltage and power. Additionally, the central dilemmas in using renewable energy sources (RESs) are the intermittent nature of and dependence on wind speed and solar irradiance for wind and photovoltaic (PV) systems, respectively. Therefore, utilizing a vigorous and effective energy storage system (ESS) with RESs is crucial to overcoming such challenges and dilemmas. This paper describes the impacts of using a battery storage system (BSS) and superconducting magnetic energy storage (SMES) system on a DC bus microgrid-integrated hybrid solar–wind system. The proposed method employs a combination of BSS and SMES to improve the microgrid stability during different events, such as wind variation, shadow, wind turbine (WT) connection, and sudden PV outage events. Distinct control approaches are proposed to control the system’s different components in order to increase overall system stability and power exchange. Both the PV and wind systems are further equipped with unique maximum power point tracking (MPPT) controllers. Additionally, each of the ESSs is controlled using a proposed control method to supervise the interchange of the active power within the system and to keep the DC bus voltage constant during the different examined instabilities. Furthermore, to maintain the load voltage /frequency constant, the prime inverter is controlled using the proposed inverter control unit. The simulation results performed with Matlab/Simulink show that the hybrid BSS + SMES system successfully achieves the main targets, i.e., DC voltage, interchange power, and load voltage/frequency are improved and smoothed out. Moreover, a comparison among three case studies is presented, namely without using ESSs, using the BSS only, and once more using both BSS and SMES systems. The findings prove the efficacy of the proposed control method based on the hybrid BSS + SMES approach over BSS only in preserving the modern power system’s stability and reliability during the variable events.

This paper presents an effective solution to overcome the problem caused by intermittent energy sources that are connected to a balanced/unbalanced distribution system using a superconducting magnetic energy storage (SMES) system by mitigating the voltage and frequency fluctuations during wind gusts. The fuzzy logic control technique (FLC) is used with SMES to improve the voltage and frequency. A squirrel cage induction generator (SCIG) is applied as the wind energy generator. The IEEE 33-bus distribution system is used to validate the proposed method. Buses 18 33 are the weakest points in this system; thus, the wind and SMES systems are connected to the system at these buses. We used MATLAB/Simulink to simulate the performance of the IEEE 33-bus system (balanced/unbalanced) considering the SMES, wind system, and fuzzy logic control (FLC). The simulation results show the high performance of the proposed control method to alleviate the voltage and frequency fluctuation and achieve the power leveling strategy of the studied system.

In recent years, electric vehicles (EVs) have had a huge growth, which leads to decrease of the fuel consumption, emissions, and aid in keeping the clean environment but, this will have an effect on distribution systems operation if the plug-in vehicles are not managed. Therefore it is urgent to choose the ideal charging/discharging methods. This paper presents a comprehensive analysis of four scenarios for plug-in EVs to the distribution system. Firstly, base case, secondly, uncontrolled plug-in EVs charging, thirdly, controlled plug-in EVs charging, and fourthly controlled plug-in EVs charging/discharging. A fuzzy logic control (FLC) system is proposed to determine the charging/discharging priority level of each EV based on the associated state-of-charge (SOC) level of the battery and the electricity tariff. The fuzzy logic controller is used to control the EV charging/discharging process to achieve benefits for the electricity network and EVs owners, as well. The benefits for the electricity network are the improving voltage profile, potential shifting of charging to the off-peak period and discharging during the on-peak period to minimize the system loading. Benefits for EVs owners are the charging the EV at low cost and discharging at a high cost to motivate the EVs owners. A 400 V low voltage (LV) distribution network is selected as a case study in this paper to execute simulations. It is based on a real distribution network located in New Toshka city, Aswan, Egypt. MATLAB/SIMULINK is used to perform simulations and test the effectiveness of the proposed control method. The results demonstrate that the proposed controlled plug-in EVs charging/discharging method improves the distribution system performance more than other methods.