This paper describes a methodology and specifics for technical studies on fault-induced delayed voltage recovery (FIDVR) mitigation to ensure power system reliability. Optimal locations of the dynamic volts-ampere-reactive (VAR) sources are determined for addressing the FIDVR issues in the voltage stability analysis and assessment methodology. We propose a voltage stability analysis method for planning dynamic VAR sources for bettering electric power transmission systems under contingency conditions. A time-domain dynamic simulation is performed to assess short-term voltage stability. While conducting dynamic simulations, sensitivity analysis is performed to assess the need for dynamic VAR sources. This study focuses on a reactive power compensation strategy to determine system voltage recovery performance by optimal flexible alternating current transmission system (FACTS) placement in a metropolitan region. The objective of this study is to determine the optimal installation of dynamic VAR sources while satisfying the requirements of voltage stability margin and transient voltage dip under a set of criteria. New insights are presented on the effect of FACTS controls on the reactive power compensation, which supports voltage recovery. The main features of the proposed method are (i) the development based on a load model for FIDVR, (ii) the use of sensitivity analysis of the network to the variations of the IM load, (iii) the establishment of the control function and compensation strategy to maintain the voltage of system within criteria limits, and (iv) the use of the sensitivity analysis based on branch parameterization for unsolvable cases. Case studies on the Korean power system validated the performance of the proposed strategy, showing that it effectively installed FACTS under contingency scenarios.

Interest in DC microgrids is rapidly increasing along with the improvement of DC power technology because of its advantages. To support the integration process of DC microgrids with the existing AC utility grids, the form of hybrid AC/DC microgrids is considered for higher power conversion efficiency, lower component cost and better power quality. In the system, AC and DC portions are connected through interlink bidirectional AC/DC converters (IC) with a proper control system and power management. In the stand-alone operation mode of AC/DC hybrid microgrids, the control of power injection through the IC is crucial in order to maintain the system security. This paper mainly deals with a coordination control strategy of IC and a battery energy storage system (BESS) converter under stand-alone operation. A coordinated control strategy for the IC, which considers the state of charge (SOC) level of BESS and the load shedding scheme as the last resort, is proposed to obtain better power sharing between AC and DC subgrids. The scheme will be tested with a hybrid AC/DC microgrid, using the tool of the PSCAD/EMTDC software.

The target for South Korea's domestic energy consumption is to increase the proportion of the total energy consumption supplied by renewable energy to 11% by 2030. Increasing renewable energy generation has become a natural trend, thereby making it an essential factor to be considered in research for the development of a smart grid. The power system of Jeju Island is connected to the mainland (the Korean Peninsula) through HVDC #1, with another line, HVDC #2, presently under construction. The purpose of the first HVDC construction was essentially to supply a portion of the power supply to the Jeju area. However, if the construction of HVDC #2 is completed, the role of the Jeju HVDC system in the Jeju power system will be changed significantly. If flexibility through the operation of an HVDC system is increased, more wind farms can be built on Jeju Island. In addition, depending on the operation of HVDC #1 and #2, the stability of the Jeju power system will be changed greatly. In this paper, the operation of the HVDC lines and its impacts are analyzed.

This paper presents continuation-based quasi-steady-state (CQSS) analysis to approximate the long-term evolution by tracing successive equilibrium points. Applying the parameterized continuation technique to QSS simulation can provide good convergence when the system approaches the bifurcation points. Parameterization of the load exponents through continuation method makes it possible to simulate dynamic load recovery models in the system without numerical integration. The tap dynamics are also included in the CQSS analysis. The simulation results with the modified WECC 179-bus system are described in order to demonstrate the overall methodology.

This paper proposes an optimal Energy Storage System (ESS) scheduling algorithm Building Energy Management System (BEMS). In particular, the focus is placed on how to reduce the peak load using ESS and load forecast. To this end, first, an existing deep learning-based load forecast method is applied to a real building energy prediction and it is shown that the deep learning-based method leads to an accuracy-enhanced load forecast. Second, an optimization problem is formulated in order to devise an ESS scheduling. In the optimization problem, the objective function and constraints are defined such that the peak load is reduced; the cost for electricity is minimized; and the ESS’s lifetime is elongated considering the accuracy-enhanced load forecast, real-time electricity price, and the state-of-charge of the ESS. For the purpose of demonstrating the effectiveness of the proposed ESS scheduling method, it is implemented using a real building load power and temperature data. The simulation results show that the proposed method can reduce the peak load and results in smooth charging and discharging, which is important for the ESS lifetime.