In this study, an optimal reactive power (Volt/VAr) control of smart inverters for photovoltaic (PV) and battery energy storage systems (BESSs) to improve the PV hosting capacity (PVHC) of distribution networks is proposed. The primary objective of the proposed method is to improve the PVHC of a distribution network by determining the optimal oversize, dispatch, and control setting of the Volt/VAr functions of the smart inverters for both PVs and BESSs. Concurrently, the optimal locations of the PVs and BESSs are determined. The problem is formulated as a multi-objective mixed-integer nonlinear optimization to maximize the PVHC and minimize the voltage deviation simultaneously. A bio-inspired metaheuristic optimization method, i.e., the slime mould algorithm (SMA), is employed to solve the optimization problem. To assess the efficacy of the proposed PVHC improvement method, extensive simulations are conducted on an IEEE 33-node system using MATLAB software. The simulation results verify that the proposed method improves the PVHC of the distribution network compared to different cases and the default Volt/VAr control settings of the smart inverters. Furthermore, the SMA optimization method provides superior performance in finding the optimal PVHC of a distribution network compared to the conventional metaheuristic optimization methods.

The integration of distributed generators has changed the paradigm of modern power transmission systems. To cope with energy demands, electrical networks emphasize the efficient utilization of power transmission. Thus, high-voltage DC (HVDC) and hybrid (AC/DC) transmission systems are also getting attention owing to their high efficiency in addition to the widely adopted high-voltage AC (HVAC) systems. Most faults in the bulk of transmission lines are temporary or intermittent. Auto-reclosing schemes can be used to prevent these faults. However, conventional auto-reclosing schemes based on constant dead time cannot recognize the fault nature within the assigned duration. Consequently, the accuracy of power grids can be compromised. Therefore, adaptive auto-reclosing schemes are convenient for overcoming the issues caused by the rapid restoration of faulty power lines. This can enhance system reliability and avoid power failures and blackouts. This study is based on a systematic, detailed, and thorough research review of the existing auto-reclosing schemes in all three power transmission lines, i.e., AC, DC, and hybrid (AC/DC). Subsequently, a critical analysis has been performed to assess the pros and cons of each existing adaptive auto-reclosing scheme. Finally, future recommendations are presented to improve adaptive auto-reclosing schemes in each medium.

As a large number of distributed generations are connected to the distribution system, research on the hosting capacity is actively being conducted. In particular, various methods, such as smart inverter functionality, co-located energy storage systems (ESS), and the use of on-load tap changers (OLTC), have been proposed to improve the hosting capacity. In this paper, a method to improve the hosting capacity by utilizing a solid-state transformer (SST) and its unique control capability is proposed. Lastly, the proposed method is verified in the distribution system of the Republic of Korea using the OpenDSS program.

As the energy sector transitions toward decarbonization, the integration of variable renewable energy (VRE) sources presents challenges in grid reliability, operational flexibility, and cost optimization. This article explores the practical approaches and advanced optimization methods for look-ahead coordinated generation scheduling in grids with a high share of VREs. Using Republic of Korea as a case study, we discuss the implementation of real-time markets, renewable energy bidding systems, and bulk energy storage solutions to mitigate the intermittency of renewables and ensure secure power system operation. Emphasis is placed on the role of accurate forecasting, coordinated operation of dispatchable and nondispatchable resources, and the use of enabling technologies to achieve a sustainable and robust power grid. The findings offer actionable insights into addressing the technical and economic challenges of transitioning to a low-carbon energy system.